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Liu et al. (2025) Transformer-based soil moisture simulation for understanding future drying trend globally
This study introduces TSMSNet, a Transformer-based deep learning model designed to simulate global soil moisture (SM) from 2016 to 2099 under various climate scenarios. The research identifies a significant global drying trend that intensifies with higher greenhouse gas emission pathways, particularly affecting habitable regions and agricultural lands.
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Zhou et al. (2025) Bayesian-factorial analysis for unveiling multi-factor interactive effect on water demand in Central Asia
This study develops an integrated Bayesian support vector machine-based two-step factorial analysis (BSVM-TFA) method to reveal the individual and interactive effects of human activities on water demand, applying it to Central Asia to project future water demand and identify key influencing factors.
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Qi et al. (2025) MODIS-Landsat fusion reveals two-decade 8-day lake dynamics with critical intra-annual regime shifts
The study reconstructs 8-day resolution dynamics for lakes and reservoirs in southern China from 2001 to 2020 using MODIS-Landsat data fusion. It reveals that high-frequency intra-annual variations are critical for accurate carbon budget estimates, often offsetting or equaling the impact of long-term interannual trends.
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Weng et al. (2025) Evolution and impact of rainfall infiltration in global alpine water towers
This study develops a temperature-mediated infiltration model to quantify rainfall infiltration across 78 global Water Tower Units (WTUs) from 1980 to 2023. The findings reveal that climate warming and freeze-thaw cycles are significantly altering infiltration characteristics, threatening the stability of downstream water supplies and ecological buffering.
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Wang et al. (2025) Estimating soil moisture at farm scale with high spatial resolution: integrating remote sensing data, and machine learning
This study develops a machine learning-based downscaling framework that integrates evapotranspiration and groundwater depth to estimate surface soil moisture at a 30 m resolution from 9 km coarse data. The approach significantly improves soil moisture monitoring in complex agricultural environments by accounting for both upper and lower boundary conditions.
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Claros et al. (2025) Moisture Sources of Precipitation Using Convection‐Permitting Simulations: A Study Over South America
This study compares precipitation moisture sources over the Amazon Basin using convection-permitting (CPM) and non-CPM WRF simulations, revealing significant differences. It then introduces a revised, computationally efficient 2L-DRM model that accurately replicates CPM moisture source estimates, enabling broader climatological analyses across South America.
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Jain et al. (2025) Deriving hydrological inferences from a machine learning model to understand the physical drivers of flow duration curves
This study utilizes Random Forest regression and SHapley Additive exPlanations (SHAP) to predict Flow Duration Curves (FDCs) across 991 watersheds in the contiguous United States. The research demonstrates that while climate attributes primarily determine the scale of FDCs, the baseflow index and geological features are the critical drivers of FDC shape and low-flow regimes.
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Tan (2025) The Climatic Impacts of a Satellite‐Based Parameterization of the Wegener‐Bergeron‐Findeisen Process for Large‐Scale Models
This study develops and implements a satellite-based, temperature-dependent parameterization for the Wegener-Bergeron-Findeisen (WBF) process in CAM5.3, which significantly improves the simulation of ice mass and effective radius in mixed-phase clouds compared to satellite observations.
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Waldowski et al. (2025) Data Assimilation in Integrated Subsurface Flow Models—Making Optimal Use of Cross‐Compartmental Interactions
This study investigates the risks and benefits of cross-compartmental data assimilation (DA) in integrated subsurface flow models, revealing that while single-compartment DA has trade-offs, multivariate assimilation of both soil moisture and groundwater tables yields the most robust predictions for root zone soil moisture.
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Khan et al. (2025) Remote sensing-based cropping pattern identification and its impact on groundwater use in canal command areas of an irrigated agriculture region in Pakistan
This study integrates Sentinel-2 satellite imagery and Random Forest algorithms to map seasonal cropping patterns across eight Canal Command Areas in Pakistan's Bari Doab from 2018 to 2023. The findings quantify a rising dependency on groundwater for irrigation, driven by water-intensive crops and urbanization, leading to significant regional aquifer depletion.
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Wang et al. (2025) Diverging Impacts of Snow Fraction and Soil Drainage on Seasonal and Annual Water Balances Across Snow‐Influenced Catchments
This study investigates how climate and soil drainage nonlinearity control seasonal and annual water balances across 230 snow-influenced catchments in the contiguous United States. It reveals that climate dictates both regional hydrological differences and the factors driving within-region variations, with the impacts of snow fraction and soil drainage nonlinearity diverging based on prevailing water and energy balance regimes.
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Karimzadeh et al. (2025) Climate change has increased global evaporative demand except in South Asia
Climate change has increased global evaporative demand, but this study reveals a significant decline in South Asia due to widespread irrigation, which has increased local moisture, cloud cover, and reduced solar radiation. These contrasting trends highlight how human water use can locally reshape the climate's influence on the water cycle.
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Qin et al. (2025) The effect of deficit irrigation combining with transparent/black film and straw mulching on wheat-maize cropping system in the North China Plain
This study investigated the effects of deficit irrigation combined with various mulching materials on winter wheat-summer maize rotation in the North China Plain. It found that transparent film mulching under deficit irrigation significantly increased annual yield, water productivity, and economic profit, while deficit irrigation alone negatively impacted wheat but not subsequent maize.
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Yang et al. (2025) Watershed boundary extraction from digital elevation models using RBM-SegNet
This study developed RBM-SegNet, a deep learning framework, to overcome limitations in traditional watershed boundary extraction from Digital Elevation Models (DEMs), demonstrating superior accuracy compared to existing methods.
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Yan et al. (2025) Biophysical feedback from earlier leaf-out enhances nonerosive precipitation in China
This study investigates the impact of earlier vegetation leaf-out on precipitation intensity and water erosion in China using remote sensing, reanalysis data, and a coupled land-atmosphere model. It finds that advanced phenology enhances nonerosive precipitation, particularly in semi-humid temperate regions, while reducing erosive precipitation in sparsely vegetated areas and during summer/autumn, driven by biophysical feedbacks that redistribute atmospheric moisture and energy.
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Vries et al. (2025) Precipitation disaster hotspots depend on historical climate variability
This study investigates how historical climate variability and climate change interact to shape the probability of future record-breaking precipitation events and identifies global disaster hotspots where high risk combines with potentially low societal preparedness. It reveals that regions with low historical precipitation records are currently most vulnerable, while those with high records face the steepest increase in risk due to climate change, exposing over a billion people to high record-breaking probabilities by 2100.
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Dong et al. (2025) Integrating prior information for improving 3D model-driven GAI estimation with application to wheat crops
This study investigated the integration of prior information (soil background, leaf optical properties, and canopy structure) into radiative transfer models to enhance Green Area Index (GAI) estimation for wheat crops. It demonstrated that stage-specific GAI retrieval with detailed prior information significantly improves accuracy compared to standard model inversion approaches.
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Chen et al. (2025) Asymmetric East‐West Changes in Mountain Fog Driven by Urbanization and Climate Warming
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Chucuya et al. (2025) Reconstructing aquifer dynamics with machine learning: Linking irrigation expansion to groundwater decline in a data-scarce hyper-arid region
This study utilizes machine learning (BPNN) to reconstruct fragmented groundwater records in the hyper-arid Caplina aquifer, revealing a 0.6 m/yr water table decline driven by a 400% expansion of irrigated agriculture over three decades. The research highlights the critical role of seawater intrusion in maintaining stable water levels near the coast while severely degrading water quality.
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Liu et al. (2025) Characterizing Shallow Cumulus and Its Drivers Over the Tibetan Plateau
This study investigates the macrophysical characteristics and environmental controls of shallow cumulus (ShCu) over the Tibetan Plateau (TP) using 15 years of satellite observations and reanalysis data. It reveals a distinct ShCu regime primarily controlled by near-surface relative humidity, with lower cloud bases compared to surrounding regions, offering insights for improved cloud parameterization.
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Chen et al. (2025) Baseflow index dynamics and its non-monotonic drivers from a spatiotemporal heterogeneity perspective
This study analyzed the spatiotemporal dynamics and non-monotonic drivers of the Baseflow Index (BFI) in 60 Taiwanese catchments from 1960 to 2022, revealing significant non-stationarity and identifying the simple daily intensity index (SDII) as the most dominant driver.
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Cheng et al. (2025) The 3D Evolution of Spatiotemporally Contiguous Summer Heatwaves in China: Tracks and Underlying Mechanism Associated With Compound Typhoons and High‐Pressure Systems
This study introduces a 3D perspective to track the evolution of regional summer heatwaves (HWs) in China from 1979 to 2022, revealing that the interactions between inland high-pressure systems and typhoon tracks critically modulate HW intensity, duration, and affected area.
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Li et al. (2025) Spatiotemporal fog origins in a foggy desert through integrating isotope and satellite observations
This study establishes a new framework integrating isotope and satellite observations to identify the spatiotemporal origins of fog in the Namib Desert, revealing an increasing trend of locally generated fog over time at Gobabeb and distinct spatial patterns across the central Namib Desert.
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Jiang et al. (2025) Nonlinear impacts of urban size and vegetation cover on global surface urban heat: Insights from 6022 cities
This study globally assesses surface urban heat island (SUHI) across 6022 cities to reveal nonlinear impacts of urban size and vegetation cover, finding distinct SUHI intensification patterns and compounded thermal stress in Global South cities.
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Sugita et al. (2025) Ship's Motion and Eddy Correlation Measurements of Surface Fluxes on the Small Research Ship NIES ' 94 in Lake Kasumigaura, Japan
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Tunca et al. (2025) Integration of UAV images and ensemble learning for root zone soil moisture estimation in sorghum
This study developed and evaluated a methodology to estimate root-zone soil moisture in sorghum using high-resolution unmanned aerial vehicle (UAV) multispectral and thermal imagery combined with machine learning. An ensemble model integrating XGBoost, Light Gradient Boosting Machine, and K-Nearest Neighbors achieved the highest accuracy (R² = 0.85, RMSE = 11.124 mm/90 cm, MAE = 8.775 mm/90 cm) for field-scale monitoring.
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Akor et al. (2025) Impact of Cloud Microphysics Schemes and Boundary Conditions on Modeled Snowpack in the Central Idaho Rocky Mountains, USA
This study investigates how the choice of cloud microphysics parameterization and lateral boundary conditions in the Weather Research and Forecasting (WRF) model impacts hydrometeorological forcings and snow conditions in mountainous regions, revealing significant variability in precipitation, radiation, and snow metrics due to these configuration choices.
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Guillou (2025) Approche machine learning pour le suivi des changements de l'occupation / utilisation du sol des zones humides littorales de Bretagne
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Xin et al. (2025) A flexible, differentiable framework for neural-enhanced hydrological modeling: Design, implementation, and applications with HydroModels.jl
This paper introduces HydroModels.jl, a flexible and differentiable Julia-based framework designed to overcome challenges in integrating deep learning with hydrological models by supporting automatic differentiation and symbolic programming for hybrid modeling applications.
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Zhou et al. (2025) Impacts of Subseasonal Silk Road Pattern on Extreme Heat Events in Eurasia
This study investigates the subseasonal Silk Road Pattern (SRP) and its significant impact on the occurrence and development of individual extreme heat events in Eurasia, revealing its quasi-biweekly oscillation and its synergistic effect with the British Baikal Corridor Pattern (BBC) on 2 m temperature anomalies.
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Athira et al. (2025) Multi-model ensemble improves evapotranspiration estimation over India
This study develops and evaluates multi-model ensemble techniques for improving evapotranspiration (ET) estimation over India at both in-situ and 1 km spatial scales, demonstrating that machine learning-based ensembles significantly enhance accuracy compared to individual models and simpler ensemble methods.
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Nayak et al. (2025) Evaluating Physical Climate Model Emulators for Global Warming Projections
This study develops a framework to systematically evaluate the robustness of physical climate model emulators against global climate model (GCM) large ensembles, revealing that while emulators can match GCM warming projections, they often do so for incorrect physical reasons due to compensating biases.
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Lemus‐Canovas et al. (2025) More intense heatwaves under drier conditions: a compound event analysis in the Adige River basin (Eastern Italian Alps)
This study analyzes a severe compound drought and heatwave (CDHW) event in the Adige River basin (Eastern Italian Alps) in May 2022, revealing that similar events are now significantly hotter (by 1–4 °C) and drier (with pronounced precipitation deficits) due to climate change, exacerbating water stress and shifting streamflow seasonality. It also highlights the inability of many regional climate models (EURO-CORDEX) to accurately reproduce these observed changes in both magnitude and sign.
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Weynants et al. (2025) Dheed: an ERA5 based global database of compound dry and hot extreme events from 1950 to 2023
This study introduces Dheed, a novel global database of compound dry and hot (CDH) extreme events from 1950 to 2023, derived from ERA5 reanalysis data, and confirms a significant increase in the frequency and spatial extent of these events over recent decades.
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Ávila-Díaz et al. (2025) Projections of Atmospheric Moisture Transport Over South America in a Changing Climate
This study projects future atmospheric moisture transport over South America using CMIP6 models and ERA5 data, revealing significant basin-level variations in Vertically Integrated Moisture Flux (VIMF) and its convergence (VIMFC) under different SSP scenarios, with implications for regional precipitation regimes and water resource management.
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Dangare et al. (2025) Estimating transpiration dynamics of a low-density litchi orchard using crop coefficients derived from a variable leaf conductance model, canopy cover, and tree height in Northeastern South Africa
This study improved the estimation of litchi orchard transpiration in semi-arid South Africa by modifying the Allen and Pereira (A&P) crop coefficient approach to incorporate a variable leaf resistance model and a litchi-specific typical leaf resistance, achieving significantly higher accuracy compared to the original fixed-value method.
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Li et al. (2025) A hybrid framework for sub-seasonal to seasonal streamflow prediction: integrating numerical and statistical models
This study develops a hybrid framework integrating a distributed hydrological model (DRIVE) with a probabilistic statistical model (BJP) to enhance sub-seasonal to seasonal (S2S) streamflow prediction, demonstrating improved forecast skill for flood events in the complex Pearl River Basin.
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Esch et al. (2025) Modelling runoff in a glacierized catchment: the role of forcing product and spatial model resolution
This study assesses the reliability of glacio-hydrological simulations in a 39.4 km² glacierized catchment in Switzerland, investigating the impact of varying meteorological forcing products and spatial model resolutions. It finds that precipitation forcing has the largest effect on model results, and resolutions coarser than 1000 meters fail to capture essential glaciological and topographic details, affecting the accuracy of small and medium-sized glaciers.
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Chang et al. (2025) Resolution Dependence of Tropical Poleward Energy Transport in Aquaplanet GCMs
This study benchmarks the resolution dependence of tropical poleward energy transport in two aquaplanet atmospheric general circulation models without convective parameterizations, finding that mean meridional circulation transport increases while transient eddy transport decreases with higher resolution, primarily due to changes in gross moist stability and explicit deep convection.
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Huang et al. (2025) Urban heat forecasting in small cities: evaluation of a high-resolution operational numerical weather prediction model
This study evaluates the performance of the High-Resolution Rapid Refresh (HRRR) model in forecasting urban heat dynamics, including temperature, humidity, nocturnal cooling, and urban heat advection (UHA), in a small, semi-arid city (Lubbock, Texas). Findings reveal systematic biases in HRRR forecasts and limitations in its urban representation, highlighting the need for improved urban parameterizations in numerical weather prediction models for small to mid-sized cities.
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Zongjie et al. (2025) Increased rainfall alters soil moisture dynamics in alpine meadows
This study investigated the impact of increased precipitation on soil moisture dynamics and water sources in alpine meadows on the Qinghai-Tibet Plateau, revealing that enhanced rainfall significantly reorders the vertical sequence and timing of soil water sources, shifting recharge towards supra-permafrost water.
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Papalexiou et al. (2025) Machine unlearning: bias correction in neural network downscaled storms
This study evaluates four machine learning models for downscaling precipitation using synthetic benchmark storms, demonstrating that combining machine learning with post-processing bias correction ("machine unlearning") is crucial for reliable outputs, especially for Wasserstein Generative Adversarial Networks (WGANs). It finds that raw neural network outputs struggle to reproduce key statistical properties and wet/dry boundaries, necessitating systematic bias correction for operational use.
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Rapella (2025) Modélisation et évaluation de la solution agrivoltaïque au nexus climat-eau-énergie-alimentation dans le contexte du changement climatique dans la région euro-méditerranéenne
This study integrates a photovoltaic module into the ORCHIDEE land surface model to assess the regional impact of agrivoltaics across the Euro-Mediterranean. The findings reveal that agrivoltaics significantly improve crop yields and resource efficiency in arid southern regions like the Iberian Peninsula, while providing limited or negative impacts in wetter northern regions like the Netherlands.
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Wang et al. (2025) Machine learning-based inversion and sensitivity analysis of soil moisture in Hemerocallis cultivation
This study developed a machine learning framework integrating TSM640 sensor data, multi-source remote sensing (Sentinel-1/2), and meteorological datasets to analyze soil moisture (SM) dynamics across soil layers and their impact on Hemerocallis yield. The framework successfully estimated SM (BPNN R² = 0.64) and predicted yield (RF R² = 0.63), identifying bolting and squaring as critical moisture-sensitive growth stages for optimizing irrigation.
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Yin et al. (2025) The Preliminary Assimilation and Impacts of FY‐4B Geostationary Interferometric Infrared Sounder (GIIRS) Cloud‐Cleared Radiances
This study evaluates the impact of assimilating Cloud-Cleared Radiances (CCRs) from the Fengyun-4B Geostationary Interferometric Infrared Sounder (GIIRS) on Numerical Weather Prediction (NWP). It finds that CCRs significantly increase assimilated observations and provide modest positive contributions to analysis and forecast fields, particularly for typhoon events.
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Idowu et al. (2025) Open problems in uncertainty quantification for flood modelling: A systematic review
This systematic review identifies eight critical open problems in uncertainty quantification for flood modelling, highlighting a system-level mismatch between flood complexity and current fragmented modelling practices, and advocating for seamless, end-to-end probabilistic pipelines.
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Solanki et al. (2025) River drought forcing of the Harappan metamorphosis
This study integrates high-resolution paleoclimate archives with palaeohydrological reconstructions from transient climate simulations to identify severe and persistent river droughts, lasting from decades to centuries, that affected the Indus basin between approximately 4400 and 3400 years before present, contributing to the Harappan metamorphosis.
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Tagliabue et al. (2025) Appraising retrieval schemes from spaceborne hyperspectral imagery for mapping leaf and canopy traits in forest ecosystems
This study investigated and compared machine learning regression algorithms (MLRA) and hybrid approaches for retrieving forest traits from PRISMA hyperspectral imagery. It demonstrated that hybrid models accurately quantify key leaf and canopy traits, including Leaf Chlorophyll Content (LCC), Leaf Nitrogen Content (LNC), Leaf Water Content (LWC), Leaf Mass per Area (LMA), and Leaf Area Index (LAI), in forest ecosystems, even under drought conditions.
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Callahan et al. (2025) Author Correction: Increasing risk of mass human heat mortality if historical weather patterns recur
This paper quantifies the increasing risk of mass human heat mortality under recurring historical weather patterns, demonstrating high predictive accuracy through statistical modeling. This specific document is an author correction updating key statistical values to ensure accuracy.
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Cui et al. (2025) Energy flux, evapotranspiration, and crop coefficients of drip-irrigated kiwifruit and citrus orchards in Southwest China
This study investigated energy flux, evapotranspiration (ET), and crop coefficients (Kc, Kcb) in drip-irrigated kiwifruit and citrus orchards in Southwest China using eddy covariance and sap flow measurements, providing locally calibrated coefficients and insights into their biophysical regulation for improved irrigation management.
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Schmidt et al. (2025) Effectiveness of Irrigation Tanks for Enhancing Groundwater Recharge
This study evaluates the effectiveness of traditional Indian irrigation tanks in facilitating groundwater recharge using numerical modeling and satellite data, confirming their significant contribution, especially in cascade systems, and identifying key influencing factors for optimizing their dual function.
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Zeng et al. (2025) A Neural Network Parametrization of Volumetric Cloud Fraction Profiles Using Satellite Observations and MERRA‐2 Reanalysis Meteorological Data
This study develops a deep machine learning (DML) physical parameterization for volumetric cloud fraction (VCF) using satellite lidar-radar measurements and reanalysis data. The DML model, particularly an LSTM network, effectively captures cloud physical processes, outperforming MERRA-2 reanalysis in representing various cloud types and improving VCF histograms across different spatial and temporal scales.
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Woldemeskel et al. (2025) Assessment of JULES Land Surface Model Coupled With CaMa ‐Flood for an Operational Streamflow Forecasting Across Australia
This study implemented the Catchment-based Macro-scale Floodplain (CaMa-Flood) model across Australia and evaluated its performance when coupled with various land surface models (JULES, AWRA-L) and reanalysis datasets (BARRA-R2, ERA5-Land) for operational streamflow forecasting. It found that offline JULES and AWRA-L performed well but with regional biases, while reanalysis products largely underestimated runoff, and all models struggled in ephemeral catchments.
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Jayasuriya et al. (2025) The HYDRUS model for soil and water management: A brief review of capabilities, trends, and future directions
This paper provides a comprehensive review of the HYDRUS software suite, utilizing a bibliometric analysis of 3154 articles (1993–2024) to quantify its evolution, identify key applications, and synthesize persistent challenges and future research directions in vadose zone modeling.
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Nelli et al. (2025) Drivers and Trends of Summertime Convection Over the Southeastern Arabian Peninsula
This study examines summertime convection in the southeastern Arabian Peninsula using observations, reanalysis, and climate projections, revealing a significant increase in convective events driven by regional warming and boundary layer instability, with projections indicating a continued positive trend.
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Dowdy et al. (2025) Compound weather systems of cyclones, fronts and thunderstorms in global reanalysis
This study globally examines the climatology and long-term trends of compound weather systems (cyclones, fronts, thunderstorms) using environmental diagnostics applied to global reanalysis data from 1979 to 2020, revealing distinct spatial patterns and increasing thunderstorm-related systems in certain regions.
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Schüller et al. (2025) Quantifying coupling errors in atmosphere-ocean-sea ice models: A study of iterative and non-iterative approaches in the EC-Earth AOSCM
This study quantifies numerical coupling errors in atmosphere-ocean-sea ice models using iterative Schwarz waveform relaxation (SWR) methods, revealing that standard non-iterative coupling introduces substantial errors in atmospheric and sea ice surface temperatures, often due to discontinuous physics parameterizations.
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Song et al. (2025) Downstream Amplification of Rossby Waves in Summertime Heavy Precipitation Events Over the Korean Peninsula
This study investigates long-lasting summertime heavy precipitation events (HPEs) over South Korea linked to quasi-stationary atmospheric rivers (QSARs), finding that westward-moving Pacific QSARs lead to HPEs preceded by downstream amplification of finite-amplitude local wave activity (LWA), suggesting LWA's utility for forecasting.
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Venäläinen et al. (2025) Updated monthly and new daily bias correction for assimilation-based passive microwave SWE retrieval
This study updates and expands the bias correction for assimilation-based passive microwave Snow Water Equivalent (SWE) retrieval, introducing a new daily bias-corrected Snow CCI v3.1 product. The updated methodology, utilizing expanded snow course data, significantly improves Northern Hemisphere climatological snow mass estimates, bringing them into consistency with reanalysis products, especially for high SWE values and previously problematic months.
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Dong et al. (2025) Warm and wet anomalies persist across the pan-Arctic after carbon dioxide removal
This study investigates Pan-Arctic climate responses to carbon dioxide removal (CDR) using CMIP6 models, revealing significant hysteresis and a persistent warming of approximately 1.5 °C and increased precipitation of about 0.1 mm d⁻¹ even after carbon dioxide concentrations return to pre-industrial levels.
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Hwang et al. (2025) Large‐Scale Moisture Sources and Delivery Pathways Contributing to Winter Floods in the US
This study updates previous research on US winter flood hydroclimatology by identifying large-scale moisture delivery pathways and quantifying source contributions across the Conterminous United States (CONUS). It finds that oceanic sources dominate coastal floods, while land is a key contributor to Midwest floods, influenced by moisture dynamics over mountain ranges.
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Otryakhin et al. (2025) Comparison of simulations from a state-of-the-art dynamic global vegetation model (LPJ-GUESS) driven by low- and high-resolution climate data
This study explores the differences in vegetation outcomes from the dynamic global vegetation model LPJ-GUESS when driven by high- (0.05°) versus low-resolution (0.5°) climate data across Europe. It reveals significant systematic discrepancies, particularly in mountainous regions where high-resolution simulations show substantially smaller carbon pools (e.g., total carbon 37 %–39 % smaller), and quantifies the impact of under-represented orographic climate variability and shoreline features on regional predictions.
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Zhao et al. (2025) A Hybrid Modeling Approach for Improved Simulation of Thermal‐Hydrological Dynamics in Active Layer on the Qinghai‐Tibet Plateau
This study presents a novel hybrid modeling approach combining the SHAW model with random forest-corrected Noah LSM simulations to accurately model active layer dynamics on the Qinghai-Tibet Plateau, significantly outperforming existing models in simulating soil temperature and moisture.
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Detre et al. (2025) Sentinel‐1 SAR Estimates of Snowmelt Onset Coincide With SNOTEL Soil Moisture Pulses Across the Western United States
This study investigated snowpack conditions around Sentinel-1 SAR-derived snowmelt runoff onset and evaluated these estimates against SNOTEL soil moisture pulses, finding that SAR-derived onset corresponds to increasing liquid water content but can differ temporally from in-situ melt signals due to local climatological conditions.
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Escudier (2025) Study of filter and predictor error in gaussian pairwise Markov models
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Ling et al. (2025) Global warming weakens Maritime Continent barrier effect on MJO propagation
This study projects that the probability of Madden-Julian Oscillation (MJO) events successfully propagating through the Maritime Continent will increase by 29.3% by the late 21st century under global warming, driven by a zonal asymmetry in moistening associated with the expanding Indo-Pacific warm pool.
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Meydani et al. (2025) Scenario-driven Decision Support System for assessing water balance to support agricultural and ecosystem sustainability
This study proposes a novel scenario-driven decision support system (DSS) that integrates hydrological modeling and multi-objective optimization to evaluate complex water allocation strategies in arid regions. Applied to Iran's Lake Urmia basin, the DSS identified optimal strategies capable of increasing environmental water supply by 31% while simultaneously boosting agricultural profit by 26%.
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Yang et al. (2025) Modulation of Warm‐Season Heavy Precipitation Microphysics by Synoptic Patterns in the Yangtze‐Huaihe River Basin: Insights From GPM‐DPR and Principal Component Classification
This study investigates the microphysical characteristics of warm-season heavy precipitation in the Yangtze–Huaihe River Basin across six identified synoptic patterns, revealing that while warm-rain processes generally dominate, monsoon-related patterns lead to high concentrations of small-to-medium raindrops, whereas convective patterns enhance ice-phase processes producing larger, less concentrated raindrops.
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Shah et al. (2025) Global patterns of reservoir fullness and fluctuations during droughts
This study assesses the storage conditions and fluctuations of 6634 global reservoirs during major river basin-scale droughts from 1999 to 2018, revealing significant regional, functional, and socio-economic disparities in reservoir resilience and a strong link to large-scale climate variability.
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Weng et al. (2025) Spatially coherent changes in Chinese annual flood peaks revealed by a consensus-based machine learning framework for regionalization
This study develops a consensus-based machine learning framework to identify homogeneous flood regions across China, revealing predominant trends of decreasing annual flood peak magnitudes and delayed occurrences in most regions, primarily driven by climate factors.
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Tügel et al. (2025) Extreme precipitation and flooding in Berlin under climate change and effects of selected grey and blue-green measures
This study quantifies the projected increase in extreme precipitation in Berlin under climate change (RCP8.5) and its impact on urban flooding, demonstrating that a 46 % increase in 1 h 100-year rainfall leads to a 51 % increase in maximum water depth. It further assesses the effectiveness of grey infrastructure, infiltration, and retention roofs in mitigating these impacts, highlighting the non-linear relationship between rainfall and flooding and the need for combined adaptation strategies.
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Chen et al. (2025) Spatiotemporal patterns of coexisting plant water uptake in ecologically vulnerable areas along the southeast margin of the Qinghai-Tibet Plateau
This study investigated plant water uptake patterns and the influence of belowground and aboveground stresses, including human activities like tunneling, across an elevation gradient in the Qinghai-Tibet Plateau. It revealed varied water uptake strategies among plant growth forms and highlighted the impact of tunneling on hydrological changes and plant water sources.
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Liu et al. (2025) Rapid Shrinking of the Warming Hole Over the United States in ERA5 and SPEAR
This study reveals that the U.S. "warming hole," a summer cooling anomaly, has significantly shrunk and weakened in recent decades, with accelerated contraction during 2021–2024, driven by changes in atmospheric circulation and precipitation. It projects the warming hole's disappearance around 2050 under strong external forcing, emphasizing the role of both external forcing and internal variability.
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Sakar et al. (2025) A physics-informed neural network workflow for forward and inverse modeling of unsaturated flow and root water uptake from hydrogeophysical data
This study introduces a Physics-Informed Neural Network (PINN) to infer the spatiotemporal dynamics of root water uptake (RWU) directly from hydrogeophysical data. The PINN successfully reconstructs high-resolution soil saturation fields and predicts unknown RWU distributions, with significant accuracy improvements when constrained by total daily transpiration.
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Boschat et al. (2025) Covariability in Large-Scale Climate Modes: Implications for Australian Precipitation Variability
This study applies principal component analysis to investigate the covariability of El Niño–Southern Oscillation (ENSO), Indian Ocean dipole (IOD), and Southern Annular Mode (SAM), quantifying their individual and collective impact on Australian seasonal precipitation, finding they explain up to 40%–45% of precipitation variance in parts of eastern Australia during spring.
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Shi et al. (2025) An Accelerated Discrete Ordinate Method (ADOM) Developed for Scalar Radiative Transfer by Merging Adjacent Clear‐Sky Atmospheric Layers: Forward and Jacobians Derivation
This study proposes an Accelerated Discrete Ordinate Method (ADOM) to significantly improve the computational efficiency of multi-layer radiative transfer simulations by applying the Discrete Ordinate Method only in scattering layers and merging adjacent clear-sky layers. ADOM maintains high accuracy, is applicable from visible to microwave spectra, and includes tangent linear and adjoint modules for accurate Jacobian computation in satellite radiance assimilation.
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Alford et al. (2025) Dual‐Polarization Phased Array Radar Observations of Quasi‐Linear Convective System Tornadic Mesovortices
This study utilized a dual-polarization phased array radar to investigate three tornadic mesovortices within a Quasi-Linear Convective System, revealing pre-tornadogenesis downdrafts, enhanced gust front convergence, and associated dual-polarization signatures indicative of evaporation and precipitation.
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Yang et al. (2025) Impact of Localized High Temperatures on Extreme Rainfall: Insights From the July 2023 Heavy Rainfall Event in the Beijing–Tianjin–Hebei Region Over the Taihang Mountains
This study demonstrates how antecedent high temperatures intensified moisture transport and convective activity, leading to a 22.2% increase in total rainfall during an extreme event in the Beijing–Tianjin–Hebei region, providing a new mechanism for such events.
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Naud et al. (2025) A Map of Dominant Cloud‐Controlling Factors for Cloud Fraction and Total Liquid Water Path can Identify Marine Low‐Level Cloud Types
This study analyzes daily Moderate Resolution Imaging Spectroradiometer (MODIS) cloud fraction and multi-sensor total liquid water path (TLWP) over open oceans for a 5-year period to identify dominant cloud-controlling factors (DCCF). It presents the first global map of DCCF for TLWP and shows that pairing DCCF for cloud fraction and TLWP reveals known low-level cloud type regimes, aiding in understanding cloud feedbacks.
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Zhou et al. (2025) Remote sensing meta modal representation for missing modality land cover mapping: From EarthMiss dataset to MetaRS method
This paper introduces EarthMiss, a high-resolution multimodal dataset for land cover mapping with missing modalities, and proposes MetaRS, a meta-modal learning framework that disentangles features to significantly improve performance in such challenging scenarios.
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Young et al. (2025) Tracking vegetation phenology across diverse biomes using Version 3.0 of the PhenoCam Dataset
This paper introduces PhenoCam Dataset Version 3.0, a significantly expanded and updated dataset for tracking vegetation phenology across diverse biomes, which now includes a camera-derived Normalized Difference Vegetation Index (cameraNDVI) and simplified data products. It demonstrates that while cameraNDVI offers a complementary measure of canopy structure, the Green Chromatic Coordinate (GCC) generally provides a less noisy signal for phenological tracking.
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Unknown (2025) No Title
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Lehr et al. (2025) Technical note: An illustrative introduction to the domain dependence of spatial principal component patterns
This technical note introduces the concept of Domain Dependence (DD) in S-mode Principal Component Analysis (PCA) to the hydrological community, demonstrating how spatial PC patterns can be determined by the spatial extent and arrangement of data rather than hydrological functioning, and provides methods to detect and diminish this effect.
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Pikeroen (2025) Modèles simplifiés de climat ˸ approche thermodynamique et approche dynamique
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Zheng et al. (2025) Deconstructing the Effects of Climate and Phenology on Hydrological Processes: A Case Study From an Inland Basin in Central Asia
This study quantified the individual contributions of temperature, precipitation, and phenological shifts to evapotranspiration and streamflow in the Kashi Basin, Central Asia, using an eco-hydrological model. It found that phenological changes, particularly a longer growing season, had impacts on hydrological processes comparable to those of temperature and precipitation changes, emphasizing their critical role under warming conditions.
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Seager et al. (2025) Mediterranean Drying by a Positive North Atlantic Oscillation Trend over the Last 65 Years Is an Extreme Outlier in the CMIP6 Multimodel Ensemble
The study investigates the causes of observed Mediterranean cool season precipitation decline since the 1950s, finding it to be dynamically driven by a positive North Atlantic Oscillation trend, which current CMIP6 climate models largely fail to reproduce, suggesting either extreme natural variability or a missing forced response.
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Zhang et al. (2025) Development of UI-WRF-Chem (v1.0) for the MAIA satellite mission: case demonstration
This paper presents the development of the Unified Inputs (of initial and boundary conditions) for WRF-Chem (UI-WRF-Chem) framework to support the Multi-Angle Imager for Aerosols (MAIA) satellite mission. Major updates include improving dust size distribution in chemical boundary conditions, updating land surface properties using recent satellite data, and enhancing the representation of soil NOₓ emissions, with subsequent model improvements demonstrated over several MAIA target areas.
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Unknown (2025) Mesoscale moisture convergence drives stronger rainfall extremes
High-resolution global climate simulations reveal that mesoscale moisture convergence, rather than thermodynamic effects alone, is the primary driver of projected extreme rainfall intensification under warming, significantly improving the robustness of future rainfall projections.
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Rombeek et al. (2025) Torrential rainfall in Valencia, Spain, recorded by personal weather stations preceding and during the 29 October 2024 floods
This study quantifies the spatial and temporal structure of the torrential rainfall event in Valencia, Spain, on 29 October 2024, using high-density personal weather station (PWS) data. It demonstrates the significant potential of PWSs for real-time rainfall monitoring and flood early warning systems, complementing traditional rain gauge networks.
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Nystrom et al. (2025) A Hybrid Four‐Dimensional Variational Data Assimilation System for the Model for Prediction Across Scales (MPAS‐Atmosphere): Leveraging the Joint Effort for Data Assimilation Integration (JEDI)
This study presents and evaluates a global Four-Dimensional Ensemble Variational (4DEnVar) data assimilation system for the Atmospheric component of the Model for Prediction Across Scales (MPAS-A) using the Joint Effort for Data assimilation Integration (JEDI), demonstrating improved meteorological and precipitation forecasts, especially with Hybrid-4DEnVar and all-sky assimilation.
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Razavi-Termeh et al. (2025) Spatially explicit and interpretable GeoAI models for understanding factors controlling groundwater availability
This study develops an advanced GeoAI approach, optimizing the CatBoost algorithm with the Fruit Fly Optimization Algorithm (FOA) and using SHAP for interpretability, to accurately predict groundwater-prone areas in semi-arid regions. The model significantly improves prediction accuracy and identifies key environmental factors influencing groundwater availability.
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Marrocu et al. (2025) Integrating deficit irrigation, crop modelling and Water–Energy–Food nexus to enhance durum wheat resilience in Mediterranean climate conditions
This study evaluates the impact of deficit irrigation on durum wheat yield and quality in southern Sardinia over two cropping seasons and two soil types, integrating agronomic monitoring, remote sensing, and crop modeling within a Water–Energy–Food (WEF) nexus framework. It found that moderate deficit irrigation (50% of plant water requirement) significantly improved grain yield and was comparable to full irrigation in efficiency, offering a sustainable strategy for food security in drought-prone Mediterranean regions.
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Giannakopoulos et al. (2025) Examining the Characteristics and Evolution of Wintertime Temperature Whiplash Events in the U.S. Southern Plains
This study defines and characterizes rapid extreme temperature swings, termed "temperature whiplashes," in the U.S. southern plains during winter, identifying specific atmospheric and stratospheric precursors that offer opportunities for improved subseasonal to seasonal predictions.
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Finlon et al. (2025) Influence of Cloud Microphysical Properties on Airborne Lidar Measurements: Results From the IMPACTS Field Campaign
This study utilized airborne lidar and in-situ measurements during the IMPACTS campaign to characterize ice and supercooled liquid water clouds. It established distinct lidar signatures (backscatter, color ratio, depolarization) for ice-dominated regions compared to supercooled liquid water, linking them to particle size and morphology.
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La et al. (2025) Cloud‐Top Entrainment Instability in Marine Stratocumulus Clouds: Observational Evidence From Collocated Microphysical, Turbulence, and Radiation Measurements
This study uses helicopter-borne observations to investigate the mechanisms governing the descent of entrainment-affected parcels in marine stratocumulus clouds (MSC), focusing on the relative roles of cloud-top entrainment instability (CTEI) and longwave radiative cooling (RC). It finds that sufficiently strong CTEI can dominate RC in driving the descent of diluted parcels, clarifying how CTEI, RC, and entrainment interfacial layer (EIL) thickness jointly shape MSC structure.
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Chu et al. (2025) Evaluation of Tropical Cyclone Characteristics in the SPEAR Large Ensemble Simulations
This study evaluates tropical cyclone (TC) activity in the SPEAR model, finding that it generally captures key TC characteristics and their modulation by natural climate variability, despite exhibiting regional biases in track density, landfall frequency, and precipitation.
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Tang et al. (2025) Baseline temperature variability shapes the geographical distribution of future hot extremes under anthropogenic warming
This study identifies baseline temperature variability as a key factor shaping the global distribution of future hot extremes under anthropogenic warming, demonstrating that over 80% of the global increase in hot extremes is anticorrelated with this variability, a relationship anchored by persistent land-atmosphere coupling over century timescales.
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Liu et al. (2025) A Nonstationary Probabilistic Approach for Probable Maximum Precipitation Estimation Based on Global Climate Model Large Ensembles
This study proposes a novel approach integrating a stochastic rainfall generator (StormLab) with a nonstationary generalized extreme value (GEV) model to estimate probable maximum precipitation (PMP) and probable maximum flood (PMF) under varying climate conditions. The approach projects significant increases in PMP (15%–25%) and PMF (35%–36%) by 2100 in the upper Red River basin, highlighting the impact of climate change on extreme events.
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Qian et al. (2025) Optimized decadal prediction of summer precipitation over eastern China
This study evaluates and optimizes decadal prediction skills of summer precipitation over eastern China using CMIP6 DCPP models and machine learning, identifying North Atlantic Subtropical and Subpolar Gyre sea surface temperatures as key predictability sources that significantly enhance forecast accuracy.
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Chua et al. (2025) Impact of Future Methane Emission Trajectories on Atmospheric Composition and Climate in a Future Hydrogen Economy
This study uses an atmospheric chemistry-climate model to investigate the interactions between hypothetical future hydrogen (H2) and methane (CH4) emission trajectories, finding that H2's climate impact is largely independent of background CH4 levels, and that CH4 mitigation is crucial to maximize the climate and air quality benefits of a future H2 economy.
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Wu et al. (2025) Multi-spatial scale assessment and multi-dataset fusion of global terrestrial evapotranspiration datasets
This study comprehensively evaluates 30 global terrestrial evapotranspiration (ET) datasets across multiple spatial scales and fuses them using a Bayesian model averaging (BMA) method to create a new, robust, and long-term ET dataset (BMA-ET) for 1980–2020, demonstrating improved accuracy and capturing a global increasing ET trend.
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Lynne et al. (2025) Climatology, trends, and variability of cold-season northern hemisphere extratropical cyclone characteristics during 1950–2023 in ERA5
This study analyzes the climatology, trends, and variability of cold-season Northern Hemisphere extratropical cyclones (ETCs) from 1950 to 2023 using an impact-based tracking algorithm on ERA5 reanalysis data, revealing significant regional shifts and intensity changes in storm tracks, particularly a westward shift in the North Pacific and a poleward shift and strengthening in the North Atlantic.
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Li et al. (2025) NRT-GSF: A novel near-real-time ground-satellite fusion algorithm to retrieve daily green area index at field scale
This study developed the Near-Real-Time Ground-Satellite Fusion (NRT-GSF) algorithm, integrating Sentinel-2 imagery with IoTA system data to generate daily 10-meter Green Area Index (GAI) products for precision agriculture. The algorithm demonstrated enhanced spatiotemporal completeness and accuracy, offering a robust solution for near-real-time, high-resolution crop GAI mapping.
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Michalezyk et al. (2025) Evaluation and Attribution of a Warm Winter Bias over Arctic Sea Ice in a Climate Model
This study evaluates near-surface air temperature biases in the IPSL-CM6A-LR climate model over Arctic sea ice, revealing a persistent winter warm bias ranging from +0.4 °C to +3.1 °C, primarily attributed to excessive poleward atmospheric heat transport and underestimated summertime sea ice cover in the coupled configuration.
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Abdeyazdan et al. (2025) Projection of non-stationary compound droughts considering internal variability of a climate model over Iran
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Ren et al. (2025) Differential seasonal patterns and driving mechanisms of evapotranspiration components in a subtropical monsoon forest
This study quantified and partitioned evapotranspiration (ET) components (canopy rainfall interception evaporation (Ei), transpiration (Et), and soil evaporation (Es)) and their driving mechanisms in a subtropical monsoon forest over two years. It found that Et (46.2%) and Ei (43.9%) were the major components, with distinct seasonal patterns and drivers (precipitation characteristics for Ei, energy factors for Et, and a mix for Es), highlighting the significant role of Ei in wet-hot subtropical regions.
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Wang et al. (2025) Hydrothermal integration and synergy regulate carbon exchange in forest ecosystems of eastern China
This study investigated the influence of hydrothermal integration and synergy on carbon exchange across 16 forest ecosystems in eastern China, developing novel indices (TP and D) that more effectively explain the variability in gross primary productivity, ecosystem respiration, and net ecosystem productivity, with soil water content and atmospheric hydrothermal synergy identified as primary drivers.
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Muzammal et al. (2025) Exploring the Links Between Variations in Snow Cover Area and Climatic Variables Across the Upper Indus Basin Under a Changing Climate
This study developed an ARIMA model to predict daily Snow Cover Area (SCA) in the Upper Indus Basin (UIB) using MODIS satellite data and correlated these predictions with future climate scenarios (SSP1-2.6, SSP5-8.5), revealing a significant decline in SCA, particularly under higher emission scenarios, with notable regional variations.
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Chen et al. (2025) Summer Surface Rainfall Deviations From Convective Cold‐Cloud Shields Over China
This study defines a novel index to quantify the spatial discrepancy between surface rainfall and cold-cloud shields in convective systems, finding that larger deviations are more prevalent in southern China and exhibit distinct spatial patterns linked to cloud tilting and wind shear.
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Srivastava et al. (2025) Introducing Glaciohydrological Model Calibration Using Sentinel‐1 SAR Wet Snow Maps in the Himalaya‐Karakoram
This study introduces and validates a satellite-based calibration method for the SPHY glaciohydrological model using Sentinel-1 SAR wet snow maps and geodetic mass balance in the data-sparse Himalaya-Karakoram region, demonstrating its robustness for improving runoff estimates and understanding glaciohydrology.
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Wang et al. (2025) More Frequent and Intense Tropical Cyclone‐Heat Wave Compound Extremes Over the Coastal Regions of China in a Warmer Climate
This study projects future changes in tropical cyclone and heat wave (TC-HW) compound extreme events over the southeastern coast of China (SECC) using high-resolution CMIP6 simulations. It finds that TC-HW events are projected to become significantly more frequent and stronger under high-emission scenarios, primarily driven by enhanced heat wave activity.
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Li et al. (2025) Wind Shaped Winter Snow Mass Balance at High Altitude: Insights From an Integrated Snow Observation System
This study develops an integrated observation system and a Gaussian kernel-based probabilistic classification method to quantify wind-driven snow events in the northeastern Tibetan Plateau, revealing that wind-driven processes account for 68.5% of snow mass changes and amplify sublimation above 8 m/s wind speeds.
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Yang et al. (2025) Aerosol emission reductions cause post-2011 rapid warming in the northwestern Pacific
This study identifies anthropogenic aerosol emission reductions as the primary driver of the anomalously rapid warming observed in the northwestern Pacific since 2011, attributing this warming to increased surface shortwave radiation resulting from decreased cloud cover. The research reveals a five-year lag in ocean warming, governed by a threshold-triggered nonlinear aerosol-cloud interaction.
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Huang et al. (2025) Increasing Variability in Tropical Cyclone Lifetime Maximum Intensity Over the South China Sea
This study investigates Lifetime Maximum Intensity (LMI) trends in the South China Sea (SCS) since the 1980s, revealing a significant increase in LMI amplitude driven by opposing trends in local and migratory tropical cyclones, attributed to shifts in genesis, track, and environmental conditions.
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Lee et al. (2025) Introducing NLCD-Imp: A QGIS plugin to better replicate urban characteristics in land use/cover maps for SWAT
This study developed NLCD-Imp, a QGIS plugin, to enhance National Land Cover Database (NLCD) maps with detailed urban characteristics for improved hydrological modeling. Applying NLCD-Imp to the Soil and Water Assessment Tool (SWAT) revealed increased surface runoff, reduced evapotranspiration, and a two-to fourfold increase in simulated nutrient loads in highly impervious urban areas, with a 2 % imperviousness threshold balancing model accuracy and complexity.
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Portmann et al. (2025) ClimLoco1.0: CLimate variable confidence Interval of Multivariate Linear Observational COnstraint
This paper introduces ClimLoco1.0, a new statistical model that rigorously describes the confidence interval of a projected climate variable obtained using multivariate linear observational constraints, explicitly accounting for observational noise and estimator quality. It demonstrates that observational constraints correct the best guess and reduce uncertainty, with observational noise weakening this effect, and highlights the underestimation of uncertainty in existing methods that neglect estimator quality.
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Gjerde et al. (2025) Seasonal drainage-system evolution beneath the Greenland Ice Sheet inferred from transient speed-up events
This study investigates the seasonal evolution of subglacial drainage beneath the western Greenland Ice Sheet by analyzing transient ice speed-up events using a Global Positioning System (GPS) array. It reveals that late-season melt events produce larger, more uniform velocity responses with less uplift compared to early-season lake drainages, suggesting a shift to a pervasive, cavity-dominated subglacial system with closed channels.
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Scinocca et al. (2025) Runtime bias correction of regional climate model driving data and its continental-scale impacts
This study introduces and evaluates an Empirical Runtime Bias Correction (ERBC) method for Earth System Model (ESM) driving data, demonstrating its effectiveness in significantly reducing global model biases in regional climate model (RCM) downscaling products and inducing statistically significant changes in climate-change circulation responses.
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Dasari et al. (2025) A regionalization based machine learning framework for bias correction and downscaling of ESACCI soil moisture in data limited region: A case study over India
This study developed a regionalization-based machine learning framework for bias correction and downscaling of ESACCI soil moisture data in data-limited regions like India, demonstrating significant bias reduction (over 90%) and effective downscaling with high containment ratios (over 89%).
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Lefebvre (2025) Retrieval of satellite-based microphysical and dynamical properties of deep convection ˸ preparation of the C²OMODO mission
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Lin et al. (2025) Cloud4D
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Li et al. (2025) PhysWRNet: A physics-guided deep learning framework for flood inundation mapping with SAR and hydrodynamic simulations
This paper introduces PhysWRNet, a physics-guided deep learning framework that integrates Sentinel-1 SAR data and HEC-RAS flood probability maps to significantly improve flood inundation mapping accuracy and reduce errors compared to conventional deep learning methods. The framework achieves an overall accuracy of 90.2% and enhances boundary accuracy by 68.3%.
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Ayar et al. (2025) Ensemble random forest for tropical cyclone tracking
This study develops and evaluates an Ensemble Random Forest (ERF) approach for tracking tropical cyclones (TCs) using a limited set of aggregated atmospheric variables. The ERF method demonstrates good performance in detecting TCs over the Eastern North Pacific and North Atlantic basins, achieving similar detection rates but significantly lower false alarm rates compared to a physics-based tracker.
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Han et al. (2025) Climate science data can be compressed efficiently by dual-stage extreme compression with a variational auto-encoder transformer
This paper introduces Aeolus, a deep learning framework utilizing Variational Auto-Encoder Transformer (VAEFormer) modules, to achieve extreme compression of large-scale atmospheric datasets. It successfully compresses the 400-terabyte ERA5 reanalysis dataset by a factor of 470x into a 0.85-terabyte dataset (CRA5) while maintaining high numerical accuracy and preserving critical climate patterns for scientific analysis and forecasting.
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Neethu et al. (2025) A model-based assessment of the regional safe aerosol boundary for the South Asian monsoon region
This study uses idealized climate model simulations to rigorously confirm proposed planetary boundary values for regional aerosol optical depth (AOD) in South Asia. It finds that an AOD of 0.25 can cause drought conditions (>10% precipitation reduction) in India, and an AOD of 0.5 reduces Indian summer monsoon precipitation by 19%.
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Sodemann (2025) The Lagrangian moisture source and transport diagnostic WaterSip V3.2
This paper introduces WaterSip V3.2, a diagnostic software tool that identifies evaporation sources and transport pathways of precipitation or water vapour based on Lagrangian model output. It provides a comprehensive reference for the method's foundations, technical setup, and interpretation, illustrated with a case study, to facilitate its wider application and inter-comparison with other moisture source diagnostics.
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Yang et al. (2025) Extreme multi-source forcings reshape three-dimensional circulation to drive the record-breaking Early-Autumn 2024 heat event over the Yangtze River Basin
This study investigates the record-breaking early-autumn 2024 heat event over the Yangtze River Basin, revealing it was driven by a synergistic combination of remote warm North Atlantic Sea Surface Temperature anomalies and intense South China Sea convection, which reshaped three-dimensional atmospheric circulation.
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Lindersson et al. (2025) SHEDIS-Temperature: linking temperature-related disaster impacts to subnational data on meteorology and human exposure
This paper introduces SHEDIS-Temperature, an open-access dataset linking temperature-related disaster impacts from EM-DAT with subnational meteorological and population exposure data to enable comprehensive analysis of disaster drivers and outcomes. It reveals that more populated subnational areas tend to experience higher temperatures, highlighting critical risk hotspots.
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Belaid et al. (2025) Hemispherical imaging of canopy light interception: A ceptometer alternative for precision irrigation in orchards and vineyards
This study introduces a cost-effective hemispherical imaging method for rapidly and reliably assessing the diurnal pattern and daily fraction of Intercepted Photosynthetically Active Radiation (fIPAR) in orchards and vineyards. The proposed method, utilizing either still or action cameras, demonstrated high agreement with traditional ceptometer measurements (R² between 0.88–0.92) and offers a practical, scalable, and labor-efficient alternative for precision irrigation.
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Li et al. (2025) A Novel Fusion Method of Optical and Wide-Swath Interferometric Radar Altimeter Images for Enhanced Water Detection
This paper introduces a novel fusion method that combines optical and wide-swath interferometric radar altimeter images to enhance the detection of water bodies.
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Kim et al. (2025) Improved Maritime Continent MJO Simulation in the KMA GloSea6 through Enhanced Thermodynamic Processes
This study evaluates the Madden–Julian oscillation (MJO) simulation and prediction skill in the Korea Meteorological Administration’s Global Seasonal Forecast System, version 6 (GloSea6), comparing it with its predecessor, GloSea5. GloSea6 demonstrates enhanced MJO propagation across the Maritime Continent (MC) due to improved thermodynamic processes and background state, leading to better prediction skill in that region.
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Zolghadr‐Asli et al. (2025) Evaluating the potential of desalinated irrigation in water-stressed regions through optimized planting dates and irrigation strategies
This study evaluates the potential of desalinated irrigation in water-stressed regions by optimizing planting dates and irrigation strategies for tomato production in Chile's Atacama region. It demonstrates that adjusting planting dates combined with optimal deficit irrigation significantly improves water productivity and profit margins, potentially offsetting the costs of desalinated water, especially when leveraging economies of scale.
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Park et al. (2025) Climate change paradox: worsening droughts amidst increasing average precipitation across South Korea
This study reveals a climate change paradox in South Korea, demonstrating that droughts have worsened in frequency and intensity over the past century despite an overall increase in average precipitation, driven by enhanced meteorological variability and temperature-driven evapotranspiration, with strong implications for water resources.
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Yang et al. (2025) Lakes are experiencing more severe heatwaves than the atmosphere
This study globally compares lake and atmospheric heatwaves from 2000-2022, revealing that lake heatwaves are more severe, with longer durations and shorter reoccurrence periods, primarily driven by reduced wind speed.
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Debrie et al. (2025) Hourly precipitation fields at 1 km resolution over Belgium from 1940 to 2016 based on the analog technique
This study develops and validates a high-resolution (1000 m, hourly) gridded precipitation dataset for Belgium from 1940 to 2016 using an analog technique, demonstrating that a median-based ensemble of 25 analogs provides optimal performance for precipitation estimation. The resulting dataset is publicly available for various hydrological and climate applications.
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Somogyvári et al. (2025) Regional-scale groundwater analysis with dimensionality reduction
This paper proposes a novel methodology using dimensionality reduction on the misfits between modeled and observed groundwater levels to analyze regional-scale climate effects on groundwater changes. The approach successfully identifies regions with distinct climate-groundwater relations and vulnerabilities in the Berlin-Brandenburg area, demonstrating that linear models can capture monthly groundwater dynamics even under significant anthropogenic influence.
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Yang et al. (2025) Seasonal drought during the soybean growth period and agricultural water stress in southern China eased in the context of global warming
This study investigated soybean water requirements and seasonal drought characteristics in the middle reaches of the Yangtze River Basin from 1961 to 2021. It revealed a decreasing trend in both drought severity and soybean water requirements amidst global warming, with net radiation and vapor pressure deficit identified as dominant drivers.
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Zou et al. (2025) Nitrogen limitation reduces CO₂ emissions from land use change primarily by decreasing CO₂ and climate interactions
This study quantifies the impact of nitrogen (N) limitation on direct and indirect CO₂ emissions from land-use change using the CABLE model, revealing that N limitation significantly reduces total emissions primarily by weakening interactions between land-use change and atmospheric CO₂ and climate.
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Han et al. (2025) Regional dynamics in the irrigation requirement of maize and wheat crops in relation to changes in the climate and cultivated area in the Shandong’s Yellow River Basin
This study analyzed the spatiotemporal variations and driving factors of irrigation water requirement (IWR) for maize and wheat in Shandong’s Yellow River Basin from 2003 to 2023. It revealed that a "warm-dry" climate trend combined with cultivated area expansion significantly increased IWR, with cultivated area being the dominant driver.
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Rotenberg et al. (2025) Evapotranspiration saturation amplifies climate sensitivity of terrestrial water yield
This study reveals that ecosystem evapotranspiration (ET) saturates at approximately 480 mm per year globally, which significantly amplifies the sensitivity of terrestrial water yield (WY) to precipitation variability, increasing climate change risks for ecosystems and society.
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Xiao-meng et al. (2025) Regional Changes in Precipitation Concentration, Seasonality and Intermittency in China
This study assesses regional changes in precipitation concentration, seasonality, and intermittency across five climatic zones in mainland China from 1961 to 2020, linking these changes to large-scale atmospheric circulations. It reveals varying trends, including increased seasonality in some zones and reduced winter drought risk across all zones, providing insights for disaster mitigation.
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Lu et al. (2025) A lake water level prediction method based on data augmentation and Physics-Informed Neural Networks with imbalanced data
This study proposes a novel Physics-Informed Neural Network (PINN) framework that integrates data augmentation and physically guided hyper-parameter selection to accurately predict lake water levels, specifically addressing challenges posed by imbalanced extreme event data and high computational costs. The framework demonstrates superior accuracy and efficiency compared to traditional models, achieving an RMSE of 0.021 m and requiring significantly less computational time.
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Yu et al. (2025) Impacts of the mega cascade reservoirs on riverine hydrothermal regimes based on deep learning
This study investigates the impacts of four mega cascade reservoirs on the Lower Jinsha River's downstream hydrological and water temperature regimes using an LSTM-based hydro-thermal model, revealing significant alterations in flow, temperature, and their coupling, with implications for ecological risks.
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Bokros et al. (2025) Homogenisation of Wind Data for the Period 1997–2023 in Hungary and Analysis of Different Methods Used for Deriving Daily Wind Data
This research homogenised automatic 10-minute wind speed measurements (1997–2023) from 40 Hungarian meteorological stations and compared them with simulated three-times-daily observations to quantify differences and enable integration with pre-1997 data for long-term climatological analyses.
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Smith et al. (2025) Strongly Heterogeneous Surface‐Water Warming Trends in High Mountain Asia
This study examines long-term (1994–2023) and high-resolution (30 m) changes in water-surface temperature across High Mountain Asia, revealing a significant increase in temperatures, particularly in snow-covered regions, with an acceleration in the last decade and surface water warming faster than land.
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Wu et al. (2025) Response of Tropical Cyclone‐Related Precipitation During Boreal Summer Season Over East Asia to Pseudo‐Global‐Warming Climates
This study systematically investigates the evolution of tropical cyclone (TC)-related precipitation across East Asia during boreal summer under a global warming scenario, revealing a substantial 125.6% increase in total TC precipitation due to TC intensification, altered steering flows, and enhanced atmospheric moisture content.
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Wang et al. (2025) Upper bound of pre-fill volume in cascade reservoirs considering forecast rainfall and its uncertainty
This study developed a risk-controlled framework to determine the upper bound of pre-fill volume (UBFV) for cascade reservoirs, explicitly linking forecast uncertainty to flood risk through probabilistic constraints to enhance floodwater utilization without increasing flood risk. It quantified UBFV for reservoir clusters and analyzed the impact of forecast uncertainty across spatial rainfall distribution, forecast lead time, and allowable flood high water level.
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Li et al. (2025) Integrating GNSS 3D deformation and GRACE/GRACE-FO gravity observations for terrestrial water storage changes and drought monitoring in Southwest China
This study pioneers the integration of GNSS 3D deformation with GRACE/GRACE-FO observations using three fusion methods to derive daily and monthly terrestrial water storage (TWS) changes in Southwest China, significantly improving TWS accuracy and enabling detailed drought monitoring.
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Wang et al. (2025) Interpretable deep learning hybrid streamflow prediction modeling based on multi-source data fusion
This study introduces CICLAR, an enhanced interpretable deep learning hybrid model, for accurate daily streamflow and extreme flood prediction by fusing multi-source data and optimizing neural network hyperparameters. The CICLAR model significantly outperforms benchmark models, demonstrating improved accuracy in both general streamflow and extreme flood forecasting.
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Sohrabi et al. (2025) Establishing coastal water level magnitude-duration-frequency curves for infrastructure design
This study introduces a framework for developing water level Magnitude-Duration-Frequency (MDF) curves using global tide gauge data to address the overlooked duration aspect of extreme sea level events. It finds that the average water level difference between 1-hour and 24-hour durations for similar return periods is 0.8 meters, with differences up to 3.63 meters for a 100-year event, and highlights the impact of event selection methods on these curves.
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Tang et al. (2025) Long‐Term Large‐Scale Atmospheric Forcing Data From Three‐Dimensional Constrained Variational Analysis for the ARM SGP Site
This study introduces VARANAL3D, a 15-year three-dimensional large-scale forcing data set, demonstrating that its incorporated spatial variability significantly improves the representation of clouds and precipitation in single column model simulations compared to domain-mean forcing.
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Guzzon et al. (2025) Improving extreme precipitation forecasts in Catalonia (NE Iberian Peninsula) using analog methods: A comparison with the GFS model
This study evaluates novel analog-based methods (AMs) to enhance 24-hour extreme precipitation forecasts in Catalonia, aiming to support flood risk management. The findings demonstrate that AMs integrating Seasonal Standardization and the Perfect Prognosis framework significantly improve forecasts compared to the operational Global Forecast System (GFS), particularly in reproducing the intensity and spatial distribution of extreme events.
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Rodrigo et al. (2025) Mechanisms of the QBO Influence on the Tropical Troposphere: Climatological SST Conditions
This study isolates the tropospheric impact of the Quasi-Biennial Oscillation (QBO) using an atmosphere-only experiment, revealing its seasonal modulation of deep tropical convection, Walker and Hadley circulations, particularly over the Indo-Pacific region, primarily driven by changes in static stability.
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Ma et al. (2025) Severe 2023/2024 Winter Subseasonal Weather Extremes Over Eastern China: Two Pathways of ENSO Impacts
The study attributes the 2023/2024 winter cold extremes, heavy snowfall, and freezing rain in eastern China to two distinct pathways of El Niño's influence, modulated by enhanced atmospheric intraseasonal oscillation. These pathways involve El Niño's impact on the North Atlantic jet stream and the western North Pacific anticyclone, reinforcing cold-air circulation and enhancing moisture transport, respectively.
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Onishi et al. (2025) How the hydrothermal regime differs between artificially planted coniferous and secondary deciduous forests
This study compared the hydrothermal regimes of paired coniferous and deciduous forest catchments using observational data and a two-heat source mixing model, revealing that deciduous catchments exhibit a larger groundwater contribution and a smaller seasonal stream temperature amplitude compared to coniferous catchments.
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Kabtih et al. (2025) Risk of successive hot-pluvial extremes on crop yield loss over global breadbasket regions
This study investigates the risk of successive hot-pluvial extremes (SHPEs) on crop yield loss in global breadbasket regions, revealing an increasing trend in SHPE occurrences from 1979 to 2024 and a significant association with synchronized low yields for maize, rice, soybean, and wheat. Using machine learning models, the research quantifies yield sensitivity and predicts yield responses to these compound extreme events.
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Yang et al. (2025) Agroforestry buffers drought stress by enhancing hydrological redistribution in dryland apple orchards
This study investigated the hydrological benefits of apple tree–oil crop (ATOC) intercropping systems under varying drought severities on China’s Loess Plateau, combining a four-year rainfall exclusion experiment with MAESPA modeling. It found that agroforestry enhances water-use efficiency and buffers moderate drought stress by promoting deeper water uptake and optimizing water partitioning, but its buffering capacity is overwhelmed under severe drought.
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Melón-Nava (2025) Patterns of snow cover distribution in the Cantabrian Mountains (NW Spain)
The study evaluates the performance of the ISBA land surface model and the mHM hydrological model across metropolitan France to improve the national hydrometeorological reanalysis. It demonstrates that while mHM excels in river discharge simulation due to its multiscale parameterization, ISBA provides a more comprehensive representation of surface energy fluxes.
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Valk et al. (2025) Evaporation measurements using commercial microwave links as scintillometers
This study proposes and evaluates a novel, opportunistic method to estimate evaporation using commercial microwave links (CMLs) as scintillometers. It demonstrates the feasibility of using CMLs to estimate 30 min latent heat fluxes and daily evaporation, with the energy-balance method showing promising performance, though highly dependent on the quality of net radiation estimates.
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Zhou et al. (2025) FoScenes: A high-fidelity, large-scale 3D forest plant area density product derived from open-access airborne lidar data
This study develops LS-PVlad, a novel workflow for large-scale 3D forest reconstruction from airborne lidar data, and introduces FoScenes, a high-fidelity plant area density product comprising 40 seamless scenes from 28 diverse forest sites, validated against field measurements and satellite products.
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Zhang et al. (2025) Characterizing cold surge induced storm surge in the northern East China Sea: A 60-year hindcast reveals paradoxical trends in surge heights and return levels
This study conducted a 60-year hindcast of 780 cold surge-induced storm events in the northern East China Sea, revealing a paradoxical trend of declining storm surge frequency and magnitude but increasing return levels due to shifts in the surge height distribution.
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Chen et al. (2025) Spatiotemporal propagation dynamics of multiple droughts in Central Asia: A three-dimensional perspective
This study employed a three-dimensional framework integrated with extreme gradient boosting and SHAP to systematically investigate the spatiotemporal dynamics, propagation characteristics, and dominant drivers of meteorological, hydrological, and agricultural droughts in Central Asia. The findings provide a scientific basis for developing early warning systems for drought-induced disaster chains in arid and semi-arid regions.
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Cui et al. (2025) Optimizing deficit mulched drip irrigation improves grain crop yield and water productivity in global cropland
This global meta-analysis of 1071 field observations reveals that optimizing deficit mulched drip irrigation (DMDI) can reduce grain crop yield reduction risk and significantly increase water productivity by 8.5% compared to full mulched drip irrigation, with specific management practices and environmental conditions identified as key drivers for improved performance.
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Li et al. (2025) Possible increase of tropical cyclone genesis frequency over the Northwest Pacific induced by the Tambora eruption in 1815
This study investigates the impact of the 1815 Tambora and 1991 Pinatubo tropical volcanic eruptions on tropical cyclone (TC) activity in the western North Pacific (WNP). Using high-resolution simulations and reanalysis data, the authors find that both eruptions significantly increased WNP TC genesis frequency and track density, primarily driven by dynamic factors like equatorial westerly wind anomalies despite general global cooling.
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Bourbour et al. (2025) Pre-harvest forecasting of rainfed wheat yield in Iran using multi-source remote sensing and machine learning
This study developed and compared machine learning models integrating multi-source remote sensing and meteorological data to forecast rainfed wheat yield across 22 Iranian provinces from 2001 to 2021. The XGBoost algorithm achieved superior accuracy (R²=0.64, MAE=0.25 t/ha) two months pre-harvest, outperforming Random Forest and Support Vector Regression.
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Lin et al. (2025) The impact of polar lows on the underlying ocean varies significantly by location
This study assesses the global impact of Polar Lows (PLs) on the underlying ocean using sensitivity experiments, revealing that their effects vary significantly by region depending on PL frequency and ocean structure, with PL-associated wind and precipitation often having distinct and opposing influences.
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July-Wormit (2025) Amélioration de la prévision du givrage par eau liquide surfondue
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Kuma et al. (2025) Ship‐Based Lidar Evaluation of Southern Ocean Low Clouds in the Storm‐Resolving General Circulation Model ICON and the ERA5 and MERRA‐2 Reanalyses
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Xue et al. (2025) Climate–human interactions influence widespread peatland subsidence and soil carbon stock vulnerability in China
This study provides the first national-scale assessment of peatland subsidence across China by integrating satellite radar observations with advanced modeling. It reveals widespread subsidence, particularly in hotspots like the Zoigê Plateau, driven by a combination of climate variability, drought, peat depth, and human pressures, projecting that over 65% of China's peatland carbon stock will be vulnerable under future high-emission scenarios.
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McErlich et al. (2025) Description and evaluation of airborne microplastics in the United Kingdom Earth System Model (UKESM1.1) using GLOMAP-mode
This study describes the integration and evaluation of airborne microplastics into the United Kingdom Earth System Model (UKESM1.1) using its GLOMAP aerosol scheme. The model simulates global transport and deposition, revealing that smaller, hydrophilic microplastics have longer atmospheric lifetimes and can reach remote regions and the lower stratosphere, though their current contribution to total aerosol burden is minor.
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Chen et al. (2025) Lateral groundwater-river exchanges estimation via actively heated fiber optics based thermal response test
This study introduces a novel data assimilation framework combining Actively Heated Fiber Optics Based Thermal Response Testing (ATRT) with Normal Score Ensemble Smoother with Multiple Data Assimilation (NS-ES-MDA) to accurately quantify lateral groundwater-surface water exchange fluxes by characterizing non-Gaussian hydraulic conductivity fields. The framework effectively resolves aquifer heterogeneity and localizes flux variations, showing enhanced accuracy under rapid flow reversal conditions.
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Nagashree et al. (2025) Evaluating sectoral water use and precipitation variability on blue water scarcity under historical and future climate conditions in the Mahi River Basin
This study quantifies the blue water scarcity index (WSIbw) in the Mahi River Basin, India, by integrating sectoral water withdrawals and precipitation variability under historical and future climate conditions. It finds that agriculture is the primary driver of scarcity, and future dry years are projected to intensify water stress by over 60% in some upper-basin districts.
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Liu et al. (2025) Global warming intensifies extreme day-to-day temperature changes in mid–low latitudes
Global warming is intensifying extreme day-to-day temperature changes (DTDTs) in mid-low latitudes, a distinct and largely ignored extreme weather event, posing substantial risks to human health and ecosystems, with climate models projecting further amplification by 2100.
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Hossan et al. (2025) Evaluation of wet snow dielectric mixing models for L-band radiometric measurement of liquid water content in Greenland's percolation zone
This study compares ten microwave dielectric mixing models for estimating liquid water amount (LWA) in wet snow and firn in Greenland's percolation zone using L-band radiometry, finding substantial differences in model performance and LWA retrievals, with power law-based empirical models generally performing better against surface energy and mass balance models.
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Cheng et al. (2025) Decadal Climatology and Trends in Oceanic Precipitation from Multiple Satellite and Reanalysis Datasets
This study examines climatologies and trends in global oceanic precipitation using 27 satellite and reanalysis datasets from 2001 to 2020. It finds that latest-version satellite products generally show an upward ocean-mean trend and better align with the "wet gets wetter, dry gets drier" hypothesis compared to reanalysis datasets, which often suggest declining trends.
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Westen et al. (2025) Changing European hydroclimate under a collapsed AMOC in the Community Earth System Model
This study investigates the impact of Atlantic Meridional Overturning Circulation (AMOC) collapse, combined with climate change scenarios, on the European hydroclimate using the Community Earth System Model (CESM). It finds that AMOC collapse exacerbates projected drying trends and drought extremes across Europe, primarily through reduced precipitation and increased potential evapotranspiration under higher radiative forcing.
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He et al. (2025) Stratospheric aerosol injection does not cause stronger Asian monsoon drying than greenhouse gas mitigation
This study investigates the impact of Stratospheric Aerosol Injection (SAI) on Asian Monsoon (ASM) rainfall, finding that equatorial SAI causes no additional drying compared to greenhouse gas (GHG) mitigation for the same global mean surface temperature (GMST) cooling, and suggests that well-designed SAI strategies can minimize monsoon failure risk.
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Clement et al. (2025) A Signal-to-Noise Problem in Model Simulation of Decadal Climate Modes
This study investigates the influence of external radiative forcing on three major regional decadal climate modes (AMV, NAO, PDO) using large ensembles of over 50 climate models. It finds that radiative forcing is an important component of their observed behavior, but climate models significantly underestimate the amplitude of this forced signal, leading to an erroneous "signal-to-noise problem" that obscures predictable trends.
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Peng et al. (2025) Ocean-driven shifts in circulation regime frequency modulate South China rainfall
This study reveals that the interannual variability of South China's rainy-season precipitation is primarily driven by shifts in the frequency of daily atmospheric circulation regimes, rather than changes in rainfall intensity. These regime frequency shifts are modulated by remote sea surface temperature (SST) anomalies in the Indian, Pacific, and Atlantic Oceans, which trigger large-scale atmospheric responses over the western North Pacific.
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Chakraborty et al. (2025) The mirage of the silver bullet: Exploring the limitations of high-resolution data in flood model validation
This study explores the limitations of high-resolution data in flood model validation, demonstrating that while beneficial, it does not resolve all discrepancies, which often stem from a complex interplay of observed data limitations, model uncertainties, and structural differences between datasets.
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Qiu et al. (2025) Large contribution of antecedent climate to ecosystem productivity anomalies during extreme events
This study quantifies the significant contribution of antecedent climate conditions to ecosystem productivity anomalies during extreme events using an interpretable machine-learning framework, revealing that memory effects, particularly from precipitation, temperature, and vapour pressure deficit, substantially influence ecosystem responses, especially in semi-arid regions.
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Pfeifer et al. (2025) Efficient ice multiplication from freezing raindrop fragmentation
This study quantifies secondary ice production (SIP) from freezing raindrop fragmentation (DFF) during a refreezing rain event using combined in situ and remote sensing observations, estimating 1.2 to 6.1 secondary ice crystals produced per drop, with drops of 5.0 x 10^-4 m to 1.0 x 10^-3 m diameter being most prone to breakup.
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Silber-Coats et al. (2025) Beyond scarcity: Science-based solutions for water and agriculture in the Western United States
This editorial synthesizes 14 research contributions focusing on science-based demand management strategies for sustainable agriculture in the water-scarce Western United States, demonstrating that agricultural productivity, environmental sustainability, and economic resilience are mutually compatible goals.
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Morgan et al. (2025) Co-regulation of water use and canopy temperature in desert trees
This study assessed how desert trees co-regulate water use and canopy temperature under varying hydroclimatic stress using UAV-based remote sensing, finding species-specific water-use strategies but similar thermal responses, with a decoupling of water and temperature regulation under hot, wet conditions.
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Bartsch et al. (2025) Soil laboratory and satellite spectral data filtering: A Spectral Quality Protocol (SQuaP)
This study introduces the Spectral Quality Protocol (SQuaP) to filter laboratory and satellite soil spectral data, significantly improving the reliability and predictive performance of soil property models for clay and soil organic carbon.
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Li et al. (2025) Societal and environmental interconnections: future directions for flood inundation models
This review synthesizes the evolution of flood inundation models from 1970 to 2023, highlighting the transition toward large-scale simulations and identifying eight interdisciplinary frontiers for future research.
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Cenobio-Cruz et al. (2025) Uncertainty propagation from gridded precipitation datasets to streamflow simulations: application to the Reno River basin (Italy)
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Talbot et al. (2025) Enhancing physically based and distributed hydrological model calibration through internal state variable constraints
This study evaluates the impact of incorporating groundwater recharge constraints into the calibration of the physically-based Water Balance Simulation Model (WaSiM). It finds that while streamflow-only calibration yields higher Kling-Gupta Efficiency, adding groundwater recharge constraints improves the representation of internal hydrological processes and seasonal runoff patterns.
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Cai et al. (2025) Impacts of Local and Remote Sub‐Grid Terrain Solar Radiative Effect on the Meiyu Rainfall Forecast in the Yangtze‐Huaihe River Basin, China
This study systematically explores the relative impacts of local (Yangtze-Huaihe River Basin) and remote (Tibetan Plateau) sub-grid terrain solar radiative effects (STSRE) on Meiyu rainfall forecasts in East Asia. It finds that local STSRE significantly improves forecast skill more than remote STSRE, primarily by reducing the overestimation of rainfall.
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Wang et al. (2025) Spatiotemporal correction of decision variables using XGBoost for multi-objective intelligent scheduling rule extraction model in reservoir-lake flood control systems
This study introduces a Spatiotemporal Correction using XGBoost (SC-XGB) technique to extract intelligent multi-objective scheduling rules for reservoir-lake flood control systems, addressing challenges in reducing spatiotemporal errors and improving Pareto frontier simulation quality. The SC-XGB model demonstrates enhanced accuracy and generalization in the Chaohu Basin, significantly improving outflow prediction, reducing water balance errors, and decreasing relative hypervolume error compared to the standard XGB model.
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Li et al. (2025) Atmospheric dryness effects on canopy chlorophyll fluorescence and Gross Primary Production (GPP) in a deciduous forest during heat waves
This study investigated how atmospheric dryness during heat waves affects Sun-Induced chlorophyll Fluorescence (SIF), LED-induced chlorophyll fluorescence (FyieldLIF), and Gross Primary Production (GPP) in a temperate deciduous forest. It found that FyieldLIF provided a more robust and physiologically sensitive proxy for GPP and photosynthetic capacity (Amax) under high atmospheric dryness conditions compared to SIF, particularly at daily temporal scales.
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Zhou et al. (2025) Nonstationary groundwater level responses to coupled human–natural drivers in the Baiyangdian Watershed
This study develops an integrated framework to quantify direct and indirect effects of coupled human-natural drivers on groundwater level (GWL) variations in the Baiyangdian Basin, revealing a transition in GWL driving mechanisms from natural-anthropogenic synergy to human activity dominance and hydrological regulation over different periods.
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García‐García et al. (2025) Intercomparison of Earth Observation products for hyper-resolution hydrological modelling over Europe
This study comprehensively evaluated high-resolution Earth Observation (EO) products for precipitation, snow cover area, surface soil moisture, and evapotranspiration over Europe against observational references. It identified specific merged precipitation, MODIS/Sentinel-2 snow, and NSIDC SMAP soil moisture products as best performing for hyper-resolution hydrological modeling, while evapotranspiration products showed similar overall performance.
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Xie et al. (2025) The impact of compound droughts and heatwaves on ecosystem carbon-water dynamics in Eurasia
This study investigated the spatiotemporal patterns of compound droughts and heatwaves (CDHW) in Eurasia from 1984 to 2018 and their impacts on ecosystem carbon-water dynamics (Net Ecosystem Carbon Exchange and water fluxes) across different land cover types. It found an increasing CDHW frequency and a general negative impact on carbon uptake and water fluxes, with grasslands being most affected in terms of carbon uptake.
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Jalilvand et al. (2025) Characterization of irrigation timing using thermal satellite observations, a data-driven approach
This study presents a data-driven framework using thermal satellite observations and change point detection to estimate irrigation timing and individual events. By comparing cropland land surface temperature (LST) with nearby natural vegetation, the method accurately identifies irrigation schedules in diverse agricultural regions.
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Prange et al. (2025) Elucidating the loose tie between precipitation and streamflow sensitivities to warming across the contiguous United States
This study uses a moderately high-resolution global climate model in a counter-factual warming scenario to elucidate the hydrological processes driving regional streamflow sensitivities to warming across the contiguous United States. It finds that while the West Coast and eastern US experience increased high-flows driven by atmospheric rivers, the mountainous western US sees dwindling streamflows due to snow loss fueling evapotranspiration at double the rate of precipitation changes.
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Robelin et al. (2025) RECHARGE, a model of potential recharge of aquifers applied to mainland France
The study introduces the RECHARGE model, a simplified soil water balance approach designed to estimate potential groundwater recharge across mainland France by correlating effective precipitation with a cartographic infiltration index (IDPR). The model provides a robust, large-scale estimation of renewable groundwater resources, validated against observed river flows and the physically-based SURFEX model.
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Wang et al. (2025) Recent south-central Andes water crisis driven by Antarctic amplification is unprecedented over the last eight centuries
This study reconstructs 827 years of Negro River streamflow in northern Patagonia using tree-ring records, revealing an unprecedented decline in recent decades. This decline is primarily driven by Antarctic amplification, which exacerbates temperature rise and disrupts circulation patterns, intensifying regional aridity.
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Sanda et al. (2025) Assessing the adequacy of three-component hydrograph separation for runoff partitioning in a small forest catchment
This study assessed the adequacy of three-component hydrograph separation for runoff partitioning in a small forest catchment, focusing on the magnitude and persistence of tracer-based uncertainties throughout rainfall-runoff events. It revealed that significant and sometimes physically implausible uncertainty can persist when end-member tracer signatures are similar, emphasizing the need for comprehensive uncertainty evaluation across full event hydrographs.
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Yaseen et al. (2025) Quantitative assessment of best management practices for soil and water conservation: A case study from the Tarquinia plain
This study utilized the Soil and Water Assessment Tool (SWAT) to quantitatively evaluate individual and combined Best Management Practices (BMPs) in the Tarquinia plain, Italy, demonstrating that combined BMPs significantly reduce river sediment load by up to 33.9 %, total nitrogen by 27 %, and total phosphorus by 27.5 %.
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Bongiovanni et al. (2025) Mapping soil water properties using soil samples and satellite images in the irrigated area of Biota (Spain)
This study developed and assessed quantitative and qualitative Total Available Water (TAW) maps for a shallow, stony irrigated area in Spain using Sentinel-2 imagery and field data. The quantitative maps, derived from multi-temporal satellite data, provided finer spatial detail and correlated with crop yield, offering enhanced value for irrigation management compared to traditional qualitative approaches.
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Liang et al. (2025) Quantifying anthropogenic drivers of water storage decline to support sustainable water management in a coal-mining semi-arid region
This study quantifies the anthropogenic drivers of terrestrial and groundwater storage decline in China's Mu Us Sandyland from 2003 to 2020 using a water balance framework, finding that ecological restoration and irrigation are the primary drivers, with coal mining also significant in energy-intensive areas, and proposes spatially differentiated management strategies for future sustainability.
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Arifin et al. (2025) Plausibility Criteria for GRACE‐Derived Groundwater Storage Changes From Aquifers Globally
This paper introduces a framework to evaluate the physical plausibility of groundwater storage change (ΔGWS) estimates derived from GRACE satellite data across 37 large global aquifer systems. The study demonstrates that excluding implausible estimates significantly improves the correlation of ΔGWS with total water storage and in situ observations, enhancing the reliability of groundwater monitoring.
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Singh et al. (2025) Agricultural catchments exhibit enhanced climate and drought resilience compared to forested catchments in Peninsular India
This study assesses the drought and climate resilience of 116 catchments across 14 basins in Peninsular India, revealing that agricultural catchments with higher crop fraction and irrigation exhibit greater resilience compared to forested catchments, challenging traditional hypotheses.
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Liu et al. (2025) Enhanced evapotranspiration prediction by incorporating plant stomatal-hydraulic co-regulation into hydrological model
This study enhances hydrological predictions by integrating a plant stomatal-hydraulic co-regulation scheme into the SWAT model. The modified model significantly improves the simulation of runoff, soil moisture, and evapotranspiration, particularly during drought conditions, by accurately representing vegetation transpiration dynamics.
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Li et al. (2025) Quantification of water uptake by winter wheat roots under different dripline burial depths using hydrogen and oxygen stable isotopes
This two-year field study investigated the optimal dripline burial depth for winter wheat under drip irrigation in the Guanzhong Plain using stable isotopes. It found that a 20 cm subsurface dripline depth significantly enhanced root water uptake efficiency and water use efficiency by optimizing root-zone water availability and promoting dynamic water uptake shifts.
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Lubis et al. (2025) Projected changes in cross-equatorial northerly surges and their hydrological impacts in the near future
This study projects a significant increase in the regional hydrological impacts of cross-equatorial northerly surges (CENS) on extreme precipitation in Southeast Asia and northwestern Australia by 2030–2050, despite no change in CENS characteristics. This intensification is attributed to enhanced moistening efficiency and moist static instability in a warmer, more humid environment, leading to more intense CENS convection.
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Teng et al. (2025) Incorporating heat and water stress into BIOME-BGC to simulate the impact of extreme climate events on subtropical coniferous forest NEP
This study enhances the BIOME-BGC model by incorporating dynamic heat and water stress mechanisms to better simulate the impact of extreme climate events on subtropical coniferous forest Net Ecosystem Productivity (NEP). The improved model demonstrates significantly higher accuracy in NEP simulation and reveals an increasing NEP trend from 1981 to 2019, with drought identified as the strongest negative driver.
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Abolafia‐Rosenzweig et al. (2025) Snow Cover Plays a Non‐Dominant Role in WRF/Noah‐MP Simulated Surface Air Temperature Cold Biases Over the Western U.S.
This study evaluates whether snow cover errors are the primary cause of persistent 2-meter air temperature cold biases in WRF/Noah-MP simulations across the western U.S. during snow seasons, concluding that while snow cover errors contribute modestly, they are not the main driver.
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Ji et al. (2025) Tracking seasonal variability in plant traits from spaceborne PRISMA and NEON AOP across forest types and ecoregions
This study developed a multi-stage framework leveraging PRISMA spaceborne and NEON AOP hyperspectral data to investigate the seasonal dynamics of four key plant traits across diverse U.S. forest types, demonstrating PRISMA's capability to reliably track these traits and identifying their environmental drivers.
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Wahiduzzaman et al. (2025) Modelling of typhoon activities over the Western North Pacific using a generalised additive model and deep Q-learning model
This study developed a statistical and deep Q-learning model framework, incorporating kernel density estimation and a generalized additive model (GAM), to predict typhoon genesis and trajectories over the Western North Pacific, demonstrating significant competency (73-76%) in replicating observed landfall trajectories.
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Shen et al. (2025) Soil moisture retrieval under different land cover conditions based on Sentinel-1 SAR
This study systematically evaluates the performance of optical and radar-derived Vegetation Indices (VIs) in the WCM-Oh coupling model for soil moisture retrieval across five land cover types using Sentinel-1 SAR, proposing a new radar-based VI (SVIdp) and demonstrating improved accuracy in vegetated areas.
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García‐Pereira et al. (2025) Permafrost sensitivity to soil hydro-thermodynamics in historical and scenario simulations with the MPI-ESM
This work shows that changing the hydrological state of permafrost produces differences of up to 3 °C in the annual ground temperature, 1–2 m in the active layer thickness, and 5 million km² in the permafrost extent. Including a deeper vertical thermal scheme reduces the extent decline by more than 2 million km² in the highest radiative emission scenario, demonstrated for the first time in fully-coupled Earth System Model experiments.
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Yang et al. (2025) Synergistic effects of precipitation and phase changes intensify future rain-on-snow events in the Tianshan and Pamir regions, Central Asia
This study utilized WRF dynamically downscaled simulations driven by bias-corrected CMIP6 data to investigate future rain-on-snow (ROS) events in the Tianshan and Pamir regions. It projects significant increases in ROS frequency and intensity by mid-century under warming climate scenarios, leading to intensified flood potential and altered regional hydrological regimes.
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Τολίκα et al. (2025) Can we predict the extreme? Assessing the skill of seasonal forecasts in capturing the 2024 European heatwave
This study analyzed the pronounced summer 2024 warming and heatwaves in Eastern Europe, finding average maximum temperature anomalies exceeding 3.3 °C. It evaluated seasonal forecasting systems (GCFS, SEAS5, Météo-France), which successfully predicted regional warming and large-scale circulation patterns, but showed limitations in accurately forecasting the precise timing and location of heatwaves and midlatitude blocking events.
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Huang et al. (2025) Differential sensitivities of three types of compound drought and heatwave events to human-induced climate change across the globe
This study quantifies the differential influences of human-induced climate change on three types of compound drought and heatwave (CDHW) events (precipitation-based, runoff-based, and soil-moisture-based) using CMIP6 simulations, revealing greenhouse gas forcing as the dominant driver of global CDHW intensification, particularly for soil-moisture-based events, and projecting significant future severity growth and population exposure under high-emission pathways.
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Jeong et al. (2025) An integrated watershed modeling approach using soil and water assessment tool and graph convolutional long short-term memory
This study proposes an integrated watershed modeling approach combining the process-based Soil and Water Assessment Tool (SWAT) with the graph-based Graph Convolutional Long Short-Term Memory (GCLSTM) model to simulate streamflow and Total phosphorus (TP) load. The integrated approach significantly improved simulation accuracy compared to calibrated SWAT, demonstrating the GCLSTM's ability to capture complex spatiotemporal dependencies and aggregate upstream signals.
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Díaz et al. (2025) Water balance analysis in Iowa using satellite-based evapotranspiration, precipitation, and streamflow data
This study analyzes Iowa's water balance from 2000 to 2023 using satellite-based evapotranspiration, gridded precipitation, and streamflow data, identifying areas of groundwater-dependent evapotranspiration, validating the Budyko framework for runoff estimation, and quantifying that historical land cover change from native prairie to cropland increased annual runoff by 23%.
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Feng et al. (2025) A high-resolution (0.05°) global seamless continuity record (2002–2023) of near-surface soil freeze-thaw states via passive microwave and optical satellite data
This study developed a novel downscaling method integrating passive microwave and optical satellite data to create a global, high-resolution (0.05°), daily seamless record of near-surface soil freeze-thaw states from 2002 to 2023, which achieved an overall accuracy of 83.78% comparable to coarse-resolution products but with enhanced spatial detail.
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Lynne et al. (2025) Connections of cold-season northern hemisphere extratropical cyclone characteristics to common climate modes during 1950–2023
This study investigates the connections between six cold-season Northern Hemisphere extratropical cyclone (ETC) characteristics and five common climate modes (PNA, ENSO, IPO, NAO, and decadal NAO) from 1950 to 2023, revealing similarities and key differences in their influences across interannual and decadal timescales through correlative and composite analyses.
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Wang et al. (2025) Water balance of three plantations in hilly areas of South China
This study assessed the water balance of three plantations (exotic *Acacia mangium*, native *Schima wallichii*, and native *Cunninghamia lanceolata*) in hilly South China to inform tree species selection for vegetation restoration. It found that native *S. wallichii* exhibited hydrological advantages, while exotic *A. mangium* was more water-limited in dry seasons and native conifer *C. lanceolata* posed risks due to high surface runoff and inefficient water use.
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Liu et al. (2025) Projecting compound flood hazards induced by tropical cyclones in Southeast China using MRI-AGCM3-2-S climate model
This study developed an integrated framework to project tropical cyclone-induced compound flood hazards in 60 cities across Southeast China, finding that over half of these cities are projected to experience more severe flooding under future climate scenarios.
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Sezen et al. (2025) A multi-hybrid model approach optimizing discharge forecasts in karst catchment under climate change
This study developed a novel multiple hybrid hydrological model (TUW-CemaNeige GR5J-SR-GP) to enhance daily rainfall-runoff simulations in the complex karst Ljubljanica River catchment, demonstrating significant improvements in simulating extreme flows under both observed and future climate change scenarios.
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Devi et al. (2025) A framework for the evaluation of flood inundation predictions over extensive benchmark databases
This paper introduces FIMeval, an open-source framework for automated, large-scale Flood Inundation Mapping (FIM) evaluation, integrating pixel-based and impact-based assessments. It demonstrates FIMeval's utility across diverse flood scenarios and benchmark datasets, highlighting the sensitivity of evaluation outcomes to flood extent delineation methods.
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Chaudhary et al. (2025) A comprehensive water balance approach for improved assimilation of evapotranspiration estimates derived from soil moisture
This study develops and evaluates a Comprehensive Water Balance (CWB) model, coupled with an ensemble Kalman filter, to improve daily evapotranspiration (ET) estimation by explicitly accounting for ET-driven percolation, demonstrating superior performance over a Simple Water Balance (SWB) model, especially in coarse-textured soils.
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Yang et al. (2025) Balancing yield and water productivity in wheat: A meta-analysis of irrigation, soil, and climate interactions
This meta-analysis quantified the interactive effects of irrigation, climate, soil, and fertilizer management on wheat yield, yield components, grain protein content, and water productivity across China, revealing that irrigation significantly increased yield and water productivity, with optimal strategies varying based on environmental and management conditions.
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Liu et al. (2025) Agricultural rapid-onset droughts in southern China’s grain-producing regions: Spatiotemporal evolution and potential drought-crop risks
This study investigated the spatiotemporal evolution and seasonal characteristics of agricultural rapid-onset droughts and their coupling with critical crop growth stages across southern China's major grain-producing regions from 1950 to 2022. It revealed significant spatial heterogeneity in drought characteristics and identified critical crop-drought coupling risks during specific phenological windows, emphasizing the need for phenology-aligned drought management.
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Li et al. (2025) Multi-source data fusion for estimating potato transpiration under water stress using machine learning models
This study developed a multi-source data fusion framework to estimate daily cumulative potato transpiration under varying water stress by integrating image-derived canopy indices (Crop Water Stress Index and Relative Leaf Area Index) with meteorological measurements, demonstrating that this integration significantly enhances model performance and that optimal model choice depends on environmental stability.
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Li et al. (2025) Estimating soil water content of cotton fields using UAV-based multi-source remote sensing data fusion
This study aimed to improve soil water content (SWC) estimation in cotton fields by fusing UAV-based multi-source remote sensing and meteorological data with machine learning. It found that the CatBoost model, integrating multidimensional indices, achieved superior SWC estimation accuracy (R² = 0.762 ± 0.026) and robustness across different growth stages and irrigation levels.
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Chagas et al. (2025) Coupling hydrological modelling and remote sensing for soil moisture assessment in an experimental Brazilian semi-arid catchment
## Identification - **Journal:** Hydrological Sciences Journal - **Year:** 2025...
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Li et al. (2025) Magnitude and impacts of non-rainfall water inputs and nocturnal evapotranspiration on temperate grassland ecosystems
This study investigated the spatial variability and environmental drivers of non-rainfall water (NRW) inputs and nocturnal evapotranspiration (ETnight) across nine temperate grasslands, revealing that while NRW inputs were low and did not benefit early morning CO2 exchange, increasing ETnight losses pose additional challenges for grasslands in the future.
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Zhu et al. (2025) Giant Cloud Condensation Nuclei Facilitate Drizzle Formation in Stratocumulus—Insights From a Combined Observation‐Modeling Framework
This study investigates the hypothesis that Giant Cloud Condensation Nuclei (GCCN) initiate drizzle drops to trigger warm rain formation. It finds that GCCN efficiently generate drizzle drops and broad droplet size distributions, which accelerate collision-coalescence, with model simulations matching radar observations.
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Lache et al. (2025) Performance of controlled drainage in tile-drained agricultural fields: An exploratory scenario analysis with the soil-plant model SWAP
This study used the SWAP model to conduct an in silico scenario analysis comparing regular drainage (RD) with manual controlled drainage (MCD) and climate-adaptive drainage (CAD) over 30 years in maize cultivation across different soil textures and management practices. It found that MCD significantly increases groundwater recharge (28-45%) and reduces drainage flux (17-25%) compared to RD, with minimal and soil-dependent effects on maize transpiration, while CAD offered fewer benefits than MCD.
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Guo et al. (2025) A new precipitation index for summer precipitation in eastern China
This study develops a novel Precipitation Index (PI) for summer precipitation in eastern China, specifically designed to capture the coordinated variability between North and South China. The PI demonstrates superior performance over existing indices in representing synchronous precipitation anomalies and reveals the underlying atmospheric dynamic and thermodynamic mechanisms driving this coherence.
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Préaux et al. (2025) On the proper use of screen-level temperature measurements in weather forecasting models over mountains
This study investigates how structural inhomogeneities in mountain observational networks, particularly varied sensor height, affect near-surface air temperature representation and assimilation in the Arome-France numerical weather prediction system. It reveals that neglecting sensor height differences significantly degrades model evaluation and assimilation performance, especially at night in high-altitude regions.
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Jia et al. (2025) Ocean Wave Slope Effects on Global Air‐Sea Turbulent Heat Flux
This study introduces a geometric correction to standard ocean surface turbulent heat flux algorithms to account for the enhanced surface area due to ocean wave slopes. It finds that the effective air-sea interface is enhanced by approximately 2% on average, leading to mean corrections of 0.29 W/m² for sensible heat flux and 2.34 W/m² for latent heat flux, with statistically significant increasing trends over recent decades.
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Goodling et al. (2025) Technical note: A low-cost approach to monitoring relative streamflow dynamics in small headwater streams using time lapse imagery and a deep learning model
This paper introduces a low-cost, non-contact method for monitoring relative streamflow dynamics in small headwater streams using time-lapse imagery and a deep learning model (SRE) trained on human-annotated image pairs. The method successfully characterized relative streamflow dynamics, with modeled hydrographs closely matching observed ones (median Kendall’s Tau of 0.75 during the annotation period).
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Steyaert et al. (2025) Data derived reservoir operations simulated in a global hydrologic model
This study develops a workflow to implement data-derived reservoir operations in global hydrologic models using satellite altimetry and machine learning. It demonstrates that this approach significantly improves the accuracy of simulated global reservoir storage compared to generic operations, which tend to overestimate storage and water availability, while having modest impacts on downstream streamflow.
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Franze et al. (2025) Braided Rivers From SWOT: Water Surface Dynamics Over the Multi‐Channel Brahmaputra River
This study presents a method to integrate high-resolution SWOT pixel cloud data with Sentinel-2 imagery to generate dynamic river centerlines, significantly improving estimates of surface water dynamics in braided rivers compared to the standard SWOT RiverSP product.
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Salazar-Martínez et al. (2025) Influence of vineyard row orientation on evapotranspiration estimates from a satellite-based two-source energy balance model
This study quantified the influence of vineyard row orientation (Southwest-Northeast vs. Northwest-Southeast) on evapotranspiration (ET) using a satellite-based Two-Source Energy Balance (TSEB) model. It found that Southwest-Northeast oriented vineyard blocks consistently exhibited higher ET rates (average 1.32 mm day⁻¹) during the growing season compared to Northwest-Southeast blocks, a difference primarily driven by variations in land surface temperature and albedo related to canopy radiation interception and shadowing.
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Xie et al. (2025) Changing Northern Hemisphere weather linked to warming amplification in High Mountain Asia
Amplified warming in High Mountain Asia (HMA) has significantly altered Northern Hemisphere synoptic temperature variability (STV) from 1940–2022, enhancing summer STV in Canada and Russia while reducing winter STV in Eastern Europe and the Nordic Seas. These changes are primarily driven by modified high-frequency temperature advection through hemispheric teleconnections.
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Amiri et al. (2025) Modeling root water uptake of landscape groundcovers with HYDRUS-1D and particle swarm optimization
This study coupled HYDRUS-1D with Particle Swarm Optimization (PSO) to calibrate root water uptake (RWU) parameters for four groundcover species, demonstrating that simultaneous optimization of RWU and soil hydraulic parameters significantly enhances the accuracy of soil water content (SWC) simulations compared to a two-step approach.
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Gontara et al. (2025) Multivariate hydrological risk under heterogeneous conditions
This study proposes a framework for estimating multivariate quantile curves (MQCs) by directly integrating change-points (CPs) using mixture models for marginal distributions and copulas. It demonstrates that marginal CPs displace the curve, while dependence CPs alter its shape, with combined effects amplifying the impact on hydrological risk assessment.
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Madaula et al. (2025) Hypersaline recharge in Mediterranean coastal aquifers: The role of aquifer–lagoon connectivity
This study investigates seasonal salinity variations in the shallow aquifer of the La Pletera salt marsh using time-lapse electrical resistivity tomography (ERT) and continuous monitoring. It reveals that hypersaline lagoons are a primary source of aquifer salinization, particularly after rainfall events, often exceeding the influence of seawater intrusion.
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Zhang et al. (2025) Analysis of Monsoon Characteristics in China Based on Precipitable Water Vapor Derived From GNSS and ERA5 Over 2016–2020
This study characterized the Asian Summer Monsoon (ASM) over China by retrieving precipitable water vapor (PWV) grid products from GNSS data and ERA5 reanalysis for 2016-2020. It found the average monsoon onset from late May to mid-June and retreat in September, advancing unevenly from southeast to northwest across China.
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Henz et al. (2025) Alps-wide high-resolution 3D modelling reconstruction of glacier geometry and climatic conditions for the Little Ice Age
This study presents the first Alps-wide, three-dimensional, model-derived reconstruction of glacier surfaces during the Little Ice Age (LIA) at 50 m resolution, using the Instructed Glacier Model (IGM) to match empirically mapped LIA glacier extents. It reveals a total ice volume of 283 ± 42 km³ and regional/local patterns of equilibrium line altitudes (ELAs) influenced by climatic and topographic factors.
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Chen et al. (2025) Emerging Patterns of Changes in Intra‐Annual Variability of Streamflow
This study presents the first large-scale analysis of spatial patterns in long-term trends of intra-annual streamflow variability from 1970 to 2022 across 12,311 streamflow stations. It found that approximately 23% of stations exhibit significant trends, with increasing variability dominating in tropical regions due to declining low flows, and decreasing variability prevailing in cold regions due to rising low flows, indicating widespread non-precipitation-led flow regime changes.
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Zhang et al. (2025) Unraveling threshold effects and feature contributions in hydrological-soil-vegetation response to Budyko parameters: A data-driven perspective
This study investigated the threshold effects and feature contributions of hydrological, soil, and vegetation elements on watershed ecohydrological processes in a sandy region using a data-driven approach. It identified critical thresholds for key ecohydrological variables within the Budyko framework, providing a quantitative basis for ecosystem restoration.
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Gao et al. (2025) Quantifying controls on rapid and delayed runoff response in double-peak hydrographs using ensemble rainfall-runoff analysis (ERRA)
This study quantifies the controls of precipitation intensity and antecedent wetness on double-peak runoff generation in the Weierbach catchment using Ensemble Rainfall-Runoff Analysis (ERRA), demonstrating distinct thresholds for the rapid near-surface and delayed groundwater-mediated runoff components.
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Perin et al. (2025) Assessing the cumulative impact of on-farm reservoirs on modeled surface hydrology
This study developed a novel framework integrating remote sensing data with a hydrological model (SWAT+) to assess the cumulative spatial and temporal impacts of on-farm reservoirs (OFRs) on surface hydrology in eastern Arkansas, finding significant reductions in annual flow (14%–24%) and peak flow (43%–60%).
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Rosso et al. (2025) Drought hazard assessment across Sweden's diverse hydro-climatic regimes
This study assesses meteorological, agricultural, and hydrological drought hazard across Sweden using multiple standardized indicators and hydrological model simulations. It reveals distinct regional drought patterns, with central-eastern and south-eastern Sweden experiencing increasing dry conditions, while northern and western Sweden show wetting trends.
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Zhou et al. (2025) Future exposure to moist heat extremes linked to soil dryness
This study investigates the global impact of soil moisture on moist heat stress using CMIP6 models, revealing that soil moisture dynamics significantly amplify moist heat extremes and increase global population exposure to wet-hot conditions, particularly in mid-latitudes, with regional variations in coupling strength.
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Ma et al. (2025) Soil oxygen dynamics: a key mediator of tile drainage impacts on coupled hydrological, biogeochemical, and crop systems
This study used the ecosys model to quantify the integrated impacts of tile drainage on hydrology, biogeochemistry, and crop growth, revealing that soil oxygen dynamics mediate these interactions. It found that tile drainage enhances soil oxygenation, alleviating crop oxygen stress and promoting root growth, which increases crop yield by approximately 6% and improves resilience to climate change.
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Biget et al. (2025) Brief communication: Sharp precipitation gradient on the southern edge of the Tibetan Plateau during cold season
This study documents a sharp, order-of-magnitude precipitation gradient over a 10 km distance at the southern edge of the Tibetan Plateau during the cold season, using novel in-situ lake water pressure measurements, automatic weather station data, and atmospheric models. It reveals that precipitation totals can vary by a factor of ten over a short distance, marking the transition between the Great Himalayas and the Tibetan Plateau.
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Chen et al. (2025) Radiative Response to Large Decline in Anthropogenic Emissions From China Between 2008 and 2016 Is Modified by Simultaneous Biomass Burning Emission Changes
This study quantifies the instantaneous radiative forcing (IRF) from changes in anthropogenic and biomass burning aerosol emissions over 2008–2016 using the UK Earth System Model, revealing significant regional and global IRF shifts due to Chinese anthropogenic emission reductions and a notable role for biomass burning, particularly in the Arctic.
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Gong et al. (2025) Spatiotemporal Variability of Vegetation Productivity Responses to Meteorological Factors in China's Drylands Over Two Decades
This study developed a machine learning model to attribute gross primary productivity (GPP) trends in China's drylands from 2001 to 2020 to meteorological factors, revealing that declining solar radiation caused a GPP decrease largely offset by increased precipitation, with minor temperature effects due to seasonal compensations, leading to a slight overall GPP decline.
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Yin et al. (2025) Widespread weakening of soil-atmosphere thermal coupling and its response to climate warming on the Qinghai-Tibetan plateau
This study quantifies the spatiotemporal dynamics of soil-atmosphere thermal coupling (β) at 0.1 m depth on the Qinghai-Tibetan Plateau (QTP) from 1980 to 2020, revealing a widespread weakening of coupling, particularly in seasonal frost zones, driven by a complex interplay of atmospheric warming and soil moisture changes.
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Jong et al. (2025) A computationally efficient method to model similar and alternate stratospheric aerosol injection experiments using prescribed aerosols in a lower-complexity version of the same model: a case study using CESM(CAM) and CESM(WACCM)
This study develops a computationally efficient method using pattern-scaling to prescribe stratospheric aerosol injection (SAI) forcing in lower-complexity climate models (CESM(CAM)) based on data from full-complexity models (CESM(WACCM)). The method successfully replicates tropospheric climate responses to SAI across various scenarios and model configurations, significantly reducing computational costs.
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Tian et al. (2025) Global Patterns of Increasing Interannual Variability of Surface Air Temperature throughout the Holocene
This study examines the interannual variability of surface air temperature throughout the Holocene using new transient simulations, revealing a global increase in variability since 11.5 ka primarily driven by orbital forcing and energy balance changes, with regional influences from ice sheet retreat and ocean-atmosphere interactions.
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You et al. (2025) Growth in agricultural water demand aggravates water supply-demand risk in arid Northwest China: more a result of anthropogenic activities than climate change
This study quantifies water supply-demand risks in the arid Tailan River Basin under 24 climate-land change scenarios, revealing that continuous agricultural expansion and the resulting surge in irrigation demand are the primary drivers of increasing water scarcity and risk, rather than climate change.
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Aviv et al. (2025) The Relation between Jet Meandering and Storm Intensity in an Idealized Aquaplanet GCM
This study uses an idealized moist global circulation model to investigate the quantitative link between eddy-driven jet meandering and storm development under climate change. It demonstrates that Arctic amplification leads to a flattening of the mid-atmospheric meridional temperature gradient, which increases jet meandering, and that these greater meanders are associated with the development of more intense storms.
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Ayala et al. (2025) Less water from glaciers during future megadroughts in the Southern Andes
This study assesses the hydrological response of Southern Andes glaciers to the current Chilean megadrought (2010-2019) and projected end-of-century megadroughts using glacio-hydrological simulations. It finds that while glaciers buffered water supply during the current drought by losing 10% of their volume, their buffering capacity will significantly decline in future megadroughts due to massive ice loss, leading to substantial reductions in glacier runoff.
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Li et al. (2025) A new approach for joint assimilation of cosmic-ray neutron soil moisture and groundwater level data into an integrated terrestrial model
This study developed a novel weakly coupled multivariate data assimilation framework to jointly assimilate cosmic-ray neutron soil moisture and groundwater level data into an integrated terrestrial model (TSMP). The new approach significantly improved the accuracy of both soil moisture and groundwater level predictions, outperforming single-variable assimilation and conventional fully coupled methods.
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Zhang et al. (2025) Contrasting Effect of Spring Snowmelt on Early Summer Surface Air Temperature Over Western and Central Tibetan Plateau
This study investigates the causes of interannual variability in early summer surface air temperature (SAT) over the Tibetan Plateau (TP), revealing an opposite effect of spring snowmelt on local SAT in western versus central TP due to distinct snow-atmosphere coupling mechanisms.
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Deng (2025) Nonlinear influence of coexisting CO 2 and anthropogenic aerosols on East Asian summer precipitation through a mid-high-latitude pathway
This study investigates the nonlinear effects of coexisting increased carbon dioxide (CO₂) and anthropogenic aerosols (AAs) on summer precipitation over East Asia, revealing that their combined forcing leads to a nonlinear increase in North China precipitation, driven by remote nonlinear climate responses originating from the Arctic and North Atlantic via Rossby wave propagation.
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Cao et al. (2025) Increasing Frequency of Very Severe Cyclonic Storms Over the Northern Indian Ocean Driven by Anthropogenic Greenhouse Gas Forcing
This study identifies a significant increasing trend in the frequency of very severe cyclonic storms over the northern Indian Ocean since 1979, attributing this trend primarily to greenhouse gas emissions, with anthropogenic aerosols having a dampening effect.
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Chang et al. (2025) Future extreme precipitation amplified by intensified mesoscale moisture convergence
This study uses high-resolution climate simulations to demonstrate that future daily extreme precipitation over land could increase by approximately 41% by 2100, primarily due to intensified mesoscale moisture convergence, a dynamic contribution underestimated by low-resolution models.
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Zhang et al. (2025) Unraveling the anisotropic pattern of track uncertainty in tropical cyclones
This study quantifies the global pattern of tropical cyclone track uncertainty, revealing a strong latitudinal variation in the dominant direction of uncertainty (along-track vs. cross-track) and its correlation with translation speed.
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Wiuff (2025) Probability of Climate Records and Their Likely Magnitudes Given Climate Data with an Idealized Linear Trend
This study develops a simple stochastic model, incorporating a linear trend and a normal stochastic component, to analyze historical climate data and estimate the probabilities and magnitudes of climate extremes. It finds that these probabilities and magnitudes depend on the time scale (ratio of standard deviation to trend slope) and the number of observational years, stabilizing when the observational period exceeds approximately twice the time scale, and suggests climate change is accelerating based on a global temperature case study.
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Wang et al. (2025) Acceleration of diverging runoff trends on the Third Pole
This study quantifies long-term (1960-2016) divergent runoff trends in the Third Pole's major rivers, revealing significant increases in westerlies-dominated rivers and insignificant declines in monsoon-dominated rivers, with these contrasting changes remarkably accelerating post-1997 due to atmospheric circulation shifts and cryospheric melt.
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Zhang et al. (2025) A strong stratospheric harbinger for cold extremes: Weak polar vortex transition from displacement to split pattern
This study introduces a novel clustering method to identify "mixed-type" weak stratospheric polar vortex (WSPV) events, characterized by a transition from displaced to split patterns. These mixed-type events are found to induce more persistent and stronger negative Arctic Oscillation-like surface signatures, leading to robust cold anomalies over northern Eurasia and the central U.S. 10–39 days after onset, driven by synergistic tropospheric planetary wavenumbers 1 and 2.
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Chen et al. (2025) El Niño-like warming underestimated in a warmer climate due to ENSO rectification effect
This study reveals that traditional climate models underestimate El Niño-like warming in a warmer climate by 14.5% ± 11.9% due to a weakening El Niño–Southern Oscillation (ENSO) asymmetry-related rectification effect. By employing a normalized mean state framework, the research clarifies how ENSO nonlinearity shapes tropical Pacific warming patterns and provides an improved basis for climate projections.
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Xu et al. (2025) Objectivization of an expert assessment framework for drought monitoring
The study develops a Comprehensive Drought Monitoring Model (CDMM) that objectivizes the expert-based U.S. Drought Monitor (USDM) framework using the Random Forest algorithm. The model successfully reproduces USDM drought categories and demonstrates high transferability by effectively capturing regional drought dynamics across China.
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Ahmed et al. (2025) Drought Dynamics From Meteorological Stress to Agricultural Impacts Using Physically‐Based Remote Sensing Indices in the Horn of Africa
This study analyzed drought propagation, its impacts on vegetation and crop productivity, and recovery dynamics in the Horn of Africa (HOA) from 2000 to 2022 using a novel integrated framework of remote sensing indices. It identified eastern and southeastern HOA as severe drought hotspots with significant agricultural losses and prolonged recovery times, offering recommendations for mitigation.
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Wang et al. (2025) Moist orographic gravity wave drag parameterization reduces the bias of summer rainfall over the Tibetan Plateau
This study revises the orographic gravity wave drag (OGWD) parameterization in the Weather Research and Forecasting (WRF) model by incorporating moisture effects. Seasonal simulations demonstrate that this modification significantly reduces the persistent wet biases in summer precipitation over the southeastern Tibetan Plateau by altering monsoon circulation and water vapor transport.
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Dehghani et al. (2025) Classifying Drought Severity in Northern Iran Using Machine Learning and Integrated Climate Indices
This study assessed the effectiveness of machine learning models (Random Forest, AdaBoost, Decision Tree, Transformer) for drought classification in the northern Iranian provinces, finding that Random Forest consistently outperformed other models across all regions.
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Huang et al. (2025) Simulating precipitation-induced karst-stream interactions using a coupled Darcy–Brinkman–Stokes model
This study developed a coupled Darcy–Brinkman–Stokes model to simulate precipitation-induced karst-stream interactions, integrating water-air two-phase flow and variably saturated conditions. It found that rainfall intensity is the dominant driver, leading to complex multi-media interactions and shifting discharge contributions, with groundwater stored in porous media significantly influencing subsequent stream levels.
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Zhang et al. (2025) Impact of Spring Soil Moisture Over the Eastern Iranian Plateau on Interannual Variability of Persistent Spring‐Summer Dryness/Wetness in Yunnan, China
This study investigates the first leading mode of spring-summer dryness/wetness in Yunnan, China, revealing an in-phase variation driven by spring soil moisture anomalies over the Eastern Iranian Plateau through a series of atmospheric teleconnections that lead to consistent dry conditions in Yunnan.
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Tang et al. (2025) Reversed tropical-Arctic teleconnection under climate change
This study reveals a reversal in the interannual relationship between winter El Niño-Southern Oscillation (ENSO) and subsequent spring Arctic surface air temperature (SAT) in recent decades, attributing this shift to changes in high-latitude atmospheric circulation and Rossby wave propagation patterns modulated by climate-change induced alterations in the westerly jet.
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Sjursen et al. (2025) Machine learning improves seasonal mass balance prediction for unmonitored glaciers
This study introduces the Mass Balance Machine (MBM), an XGBoost-based machine learning model, to accurately predict seasonal and annual glacier mass balance on unmonitored glaciers in Norway. MBM significantly outperforms traditional temperature-index models in seasonal mass balance predictions, demonstrating the potential of machine learning to generalize from sparse in situ data.
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Ungermann et al. (2025) JuWavelet – continuous wavelet transform and S transform for wave analysis
This paper describes JuWavelet, an open-source Python package that implements 1-D, 2-D, and 3-D continuous wavelet transforms (CWT) using the Morlet wavelet and the S transform, providing a comprehensive tool for analyzing and reconstructing localized wave-like phenomena in geosciences.
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Weng et al. (2025) Seychelles Dome Simulated in the CMIP6 Models
This study evaluates the ability of CMIP6 models to reproduce key characteristics of the Seychelles Dome (SD), finding that while the multimodel ensemble mean captures its semiannual oscillation and ENSO relationship, individual models exhibit discrepancies linked to biases in the Intertropical Convergence Zone (ITCZ) and ENSO-driven atmospheric teleconnections, despite overall improvements over previous CMIP phases.
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Zhu et al. (2025) Drought identification using standardized evaporative fraction: Perspective from surface energy partitioning
This study introduces the Standardized Evaporative Fraction (SEF) as a new drought index, derived from surface energy partitioning, to better incorporate land-atmosphere interactions in drought identification. The SEF is shown to be effective globally from 1960–2022, demonstrating good consistency with existing indices and revealing increasing drought trends in several global hotspots.
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Dorthe et al. (2025) The thermal future of a regulated river: spatiotemporal dynamics of stream temperature under climate change in a peri-Alpine catchment
This study investigates the future thermal regime of a peri-Alpine regulated river under climate change using a high-resolution process-based model. Projections indicate mean annual water temperatures may rise by up to 4 °C by 2080–2090 under RCP 8.5, with river regulation introducing distinct spatial and seasonal warming patterns, particularly in autumn and winter due to reservoir thermal inertia.
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Yiou et al. (2025) Using artificial intelligence to identify CMIP6 models from daily SLP maps
This study employs a neural network to classify CMIP6 climate models from single daily sea-level pressure (SLP) maps over the North Atlantic, revealing high model identifiability in summer and enabling the identification of model families and the assessment of climate change impacts on SLP patterns.
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Boardman et al. (2025) Improving model calibrations in a changing world: controlling for nonstationarity after mega disturbance reduces hydrological uncertainty
This study demonstrates how equifinality in hydrological models leads to significant uncertainty in predicting post-disturbance streamflow changes after a megafire. It introduces a novel metamodel framework that controls for non-stationary model error (bias shift) to drastically reduce this uncertainty, providing more robust estimates of hydrological responses to environmental disturbances.
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Lesiv et al. (2025) A global reference data set for land cover mapping at 10 m resolution
This paper presents a unique global reference land cover dataset for 2015, featuring over 16.5 million 10 m resolution records across 12 land cover classes, collected through expert visual interpretation to support high-resolution land cover mapping.
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Duchemin et al. (2025) Data-driven estimation of the hydrologic response using generalized additive models
This paper introduces GAMCR, a novel data-driven approach employing Generalized Additive Models (GAM) to estimate time-dependent Catchment Responses (CR) from rainfall-runoff data. GAMCR successfully estimates hydrologic response functions, showing consistency with an alternative data-driven approach (ERRA) and physical catchment properties across synthetic and six diverse Swiss basins.
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Caicedo et al. (2025) Enhanced Boundary Layer Height Detection Using Ceilometer, Surface Meteorology, and Radiation Products With a Random Forest Ensemble Method
This study develops and evaluates a Random Forest (RF) model for estimating planetary boundary layer height (PBLH) using diverse atmospheric measurements, demonstrating its superior accuracy and robustness compared to traditional methods, particularly during daytime and transition periods.
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Xu et al. (2025) Joint estimation of global daily 1 km surface radiation budget components from MODIS observations (2000−2023) using conservation-constrained deep neural networks
This study developed conservation-constrained deep neural network models to jointly estimate global daily surface radiation budget (SRB) components at 1 km resolution from MODIS observations (2000–2023). The method significantly improves the accuracy and conservation of SRB component retrievals compared to existing products, facilitating a better understanding of their coordinated variation.
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Peleg et al. (2025) Hotter summers, heavier showers: Global warming and its impact on Swiss short-duration rainfall extremes
This study quantifies future changes in Swiss sub-daily extreme rainfall using the physically-based TENAX model and Klima CH2025 climate projections. It finds that a 3 °C global warming could increase 10-minute rainfall return levels by up to 40% and hourly extremes by approximately 20%, with greater intensification in high-altitude regions despite an overall reduction in summer rainfall event frequency.
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Comeau et al. (2025) From mild to extreme heatwaves: Examining trends in North America
This study quantifies the intensity and duration trends of North American heatwaves from 1940 to 2019, introducing a novel severity metric to differentiate between mild, moderate, and extreme events. It finds that while heatwave temperatures have increased due to climate warming, the temperature anomalies relative to a changing threshold have remained largely stable, with higher severity heatwaves exhibiting more spatially coherent trends influenced by changes in both the mean and standard deviation of the temperature distribution.
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Liu et al. (2025) High-resolution soil salinity mapping and driving factor analysis at regional scale using multi-source remote sensing data
This study mapped high-resolution soil salinity and analyzed driving factors across 15 oasis irrigation districts in southern Xinjiang, evaluating five machine learning models with diverse predictor sets and identifying quantile random forest as the best performer, with wind-related variables being crucial.
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Boettcher et al. (2025) Strategies for Statistical‐Dynamical Downscaling to Urban Climate Using Global Data
This study evaluates different statistical-dynamical downscaling strategies for urban climate modeling, comparing nested domain and non-uniform grid approaches using the METRAS model for Hamburg, Germany. It finds that the non-uniform grid method is more computationally efficient while achieving similar or slightly better performance, particularly for summer climate, suggesting its utility for very local scale downscaling.
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Shi et al. (2025) Spatial heterogeneity of agricultural drought drivers in irrigation district: A causal inference framework bridging covariation and structural equation modeling
This study developed a novel causal framework combining causal covariation and Structural Equation Modeling (SEM) to analyze the spatially heterogeneous drivers of agricultural drought in China's Hetao Irrigation District, revealing that temperature-related factors consistently dominate drought severity while other factors exhibit significant spatial variability influenced by elevation and drainage density.
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Jia et al. (2025) Sensitivity of thermal evapotranspiration models to surface and atmospheric drivers across ecosystems and aridity
This study investigates the sensitivity of thermal-based evapotranspiration (ET) models to surface and atmospheric drivers across diverse ecosystems and aridity levels. It reveals a global transition in the dominant ET driver from soil dryness in water-limited regimes to downward solar radiation in energy-limited regimes, and quantifies the differential impacts of soil dryness and vapor pressure deficit on ET partitioning under drought conditions.
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Fagan et al. (2025) Upper Troposphere Lower Stratosphere Composition Change in Tropical Cyclones: Assessments From 17 Years of Satellite Observations
This study investigates the impact of tropical cyclones (TCs) on upper troposphere and lower stratosphere (UTLS) ozone and water vapor composition using 17 years of satellite observations, revealing that composition changes are highly sensitive to TC intensity, distance from the center, and environmental wind shear.
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Cheng et al. (2025) Quantifying Global Climate Change Impacts on Daily Record‐Breaking Temperature Events in China Over the Past Six Decades
This study statistically analyzes record-breaking daily surface air temperature extremes across China from 1960 to 2023, revealing that summer high-temperature records occur more frequently than predicted while winter low-temperature records occur less frequently. It quantifies that climate-driven trends account for 10%–30% of these events, providing a reference for attributing changes in record-breaking events under non-stationary climate conditions.
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Wang et al. (2025) Projected decline in glacier runoff contribution during drought periods across the Qinghai-Tibetan Plateau
This study developed a new glacier-hydrology coupled model to quantify the evolving regulatory function of Qinghai-Tibetan Plateau glaciers under climate change, particularly during drought periods. It projects a significant decline (25–38 %) in glacier runoff contributions during future droughts by the late 21st century, weakening their buffering role for regional water security.
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Guan et al. (2025) Anthropogenic enhancement of subsurface soil moisture droughts
This study introduces a Lagrangian four-dimensional tracking framework to identify "deep droughts" (more extensive moisture deficits in deep than surface soils) and reveals their increasing duration and intensity globally over the past four decades due to anthropogenic climate change, with projections for further exacerbation under higher-emission scenarios.
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Zhou et al. (2025) A novel Hankel spectrum analysis filtering for reducing North-South stripes in GRACE gravity solutions
This study introduces the Hankel Spectrum Analysis Filtering (HSAF) framework to effectively reduce North-South striping noise in GRACE-derived terrestrial water storage anomalies. HSAF significantly improves the accuracy of water storage estimates by preserving hydrological signals and outperforming conventional filters across global and basin scales.
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Kang et al. (2025) Estimating Tropical Upper‐Level Cloud Feedback Based on Radiative‐Convective Equilibrium Framework
This study investigates tropical upper-level cloud (TUC) feedback to sea surface temperature (SST) warming using a radiative–convective equilibrium (RCE) model. It finds that the TUC feedback parameter is more negative when constrained by observations compared to CMIP6 models, suggesting that climate models may underestimate this crucial negative feedback.
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Legasa et al. (2025) Strengths and Limitations of Statistical and Dynamical Downscaling for the Representation of Compound Dry and Hot Events Over Spain
This study evaluates the performance of statistical and dynamical downscaling approaches in reproducing compound dry-hot events over Spain and the Balearic Islands. It finds that while both approaches perform well for individual variables, their performance declines for compound extremes, with neither consistently outperforming the other, highlighting the need for more advanced model development.
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Sun et al. (2025) All-sky AMSU-A radiance data assimilation using the gain-form of Local Ensemble Transform Kalman filter within MPAS-JEDI-2.1.0: implementation, tuning, and evaluation
This study implements and evaluates the Gain-form of Local Ensemble Transform Kalman Filter (LGETKF) within the MPAS-JEDI system for global all-sky Advanced Microwave Sounding Unit-A (AMSU-A) radiance assimilation. It demonstrates that an optimized LGETKF configuration significantly improves forecasts of moisture, wind, clouds, and precipitation, particularly in tropical regions, for up to 7 days.
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Wang et al. (2025) Hidden deep soil moisture droughts
Anthropogenic climate change exacerbates global soil moisture droughts, which are now revealed to also occur in deeper layers, and are projected to become longer lasting and more severe in a warming climate.
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Jiménez et al. (2025) Automatic optical depth parametrization in radiative transfer model RTTOV v13 via LASSO-induced sparsity
This study introduces a novel methodology for automatic and sparse parametrization of atmospheric optical depths within the Radiative Transfer for TOVS (RTTOV) version 13 model, utilizing statistical thresholds and LASSO regression. The approach significantly reduces computational costs and parameter counts while maintaining accuracy, making it highly efficient for satellite data assimilation.
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Leger et al. (2025) The Greenland-Ice-Sheet evolution over the last 24 000 years: insights from model simulations evaluated against ice-extent markers
This study simulates the Greenland Ice Sheet's evolution over the last 24,000 years using an ensemble of 100 high-resolution ice-sheet models, quantitatively evaluating them against empirical ice-margin extent data. The findings reveal the dynamics, drivers, and spatial heterogeneities of the ice sheet's past evolution, indicating a larger Last Glacial Maximum extent and faster deglacial mass loss than previously estimated, while highlighting persistent regional model-data misfits.
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Wu et al. (2025) Cascading effects of cross-year droughts on flow-sediment dynamics across distinct drought types
This study investigates the cascading effects of cross-year meteorological and hydrological droughts on flow-sediment dynamics in seven Loess Plateau tributaries. It reveals that hydrological droughts induce significantly greater reductions in sediment transport rates and larger post-drought surges compared to meteorological droughts, with afforestation further reducing sediment supply efficiency.
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Deser et al. (2025) Northern Hemisphere Wintertime Teleconnections from the 2023–24 El Niño Offset by Background SST Trends
> ⚠️ **Warning:** This summary was generated from the **abstract only**, as the full text was not available. ...
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Lehmann et al. (2025) Soil and tree stem xylem water isotope data from two pan-European sampling campaigns
This paper presents a pan-European dataset of stable hydrogen (δ2H) and oxygen (δ18O) isotope ratios in soil and tree stem xylem water from 40 forest sites, collected during spring and summer 2023, revealing spatial and seasonal variations in isotopic signatures and species-specific differences in water uptake.
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Tripathy et al. (2025) Lagged Soil Moisture Controls on the Persistence of Drought and Heatwaves in the United States
## Identification - **Journal:** Geophysical Research Letters - **Year:** 2025...
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Portmann (2025) Développement de nouveaux algorithmes d’apprentissage statistique pour coupler projections climatiques et observations passées en vue de réduire les incertitudes du changement climatique à venir
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Yuan et al. (2025) Detectable ship tracks account for just 5% of aerosol indirect forcing from ship emissions
This study reconciles a long-standing discrepancy in estimates of aerosol indirect forcing from ship emissions (AIF-ship), revealing that visible ship tracks account for less than 5% of the total forcing, with the majority stemming from diffused, undetected aerosol plumes.
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Islam et al. (2025) Variations of urban water balances considering subsurface sewer fluxes: a hydrologic modeling study
This study developed an integrated hydrologic model to evaluate how sewer-mediated subsurface fluxes respond to variations in environmental and structural factors in urban water balances. Findings reveal that sewer-mediated fluxes are primarily sensitive to water table depth and pipe defect size, while natural fluxes (surface runoff, evapotranspiration) are more sensitive to native soil and trench backfill types; backfilling trenches with native soils reduces sewer fluxes and enhances natural outflows.
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Fan et al. (2025) An Improved Neural Network‐Based Scale‐Adaptive Cloud Fraction Scheme: Incorporation of Atmospheric Stability
This study enhances a neural network-based cloud fraction scheme for general circulation models by incorporating atmospheric stability and predicting cloud volume fraction. The improved scheme significantly boosts prediction accuracy and scale adaptability for cloud area fraction, especially for low-level clouds, and effectively predicts cloud volume fraction.
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Gong et al. (2025) Spatiotemporal dynamics and influencing factors of precipitation and soil water use efficiency on the Chinese Loess Plateau
This study investigated the spatiotemporal dynamics and driving mechanisms of precipitation use efficiency (PUE) and soil water use efficiency (SWUE) on the Chinese Loess Plateau from 2001 to 2023 using an improved two-leaf model, finding that both efficiencies increased, primarily influenced by human activities, precipitation, and soil moisture.
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Li et al. (2025) Human influence on the unprecedented 2022 extreme dragon boat water event in South China: Insights from historical and projected perspectives
This study quantifies the influence of human-induced climate change on the unprecedented 2022 extreme dragon boat water event in South China and projects the future likelihood of similar events. It finds that anthropogenic forcing increased the event's probability by approximately 64%, with future projections indicating up to an 11-fold increase by the end of the 21st century under high-emission scenarios.
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Zheng et al. (2025) Corrigendum to “Coupling differentiable tau-omega model with Kolmogorov–Arnold network for soil moisture estimation over the Tibetan Plateau” [J. Hydrol. 662(Part B) (2025) 133940]
This corrigendum rectifies an error in the author affiliation order for the original article titled "Coupling differentiable tau-omega model with Kolmogorov–Arnold network for soil moisture estimation over the Tibetan Plateau."
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Gauch et al. (2025) How to deal w___ missing input data
This paper addresses the critical challenge of missing input data in operational deep learning hydrologic models by introducing and comparing three strategies: input replacing, masked mean, and attention. The study concludes that the masked mean approach generally performs best across various missing data scenarios, offering a robust solution for real-world applications.
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Gauvrit (2025) Applications de la Wavelet Scattering Transform à la caractérisation multi-échelle de signaux turbulents : de l'astrophysique à la couche limite atmosphérique marine
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Zhou et al. (2025) MSFlood-Net: A physically informed deep learning model integrating multi-source data for flood inundation mapping
This study introduces MSFlood-Net, an enhanced U-Net-based deep learning model that integrates multi-source remote sensing and topographic data with physical information for accurate flood inundation mapping. The model achieves 97.187 % accuracy and a 96.756 % F1 score, demonstrating superior robustness in complex environments compared to baseline models.
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Mouassom et al. (2025) Hydrodynamics of rainfall peaks in homogeneous regions clustered using the K-means algorithm in Central Africa
This study identifies three homogeneous rainfall subregions in Central Africa using K-means clustering on 1984–2023 daily reanalysis data, revealing distinct rainfall peak patterns and their underlying hydrodynamic and thermodynamic mechanisms.
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Makwana et al. (2025) Spatially Inhomogeneous Phase Change, and Its Effect on Cloud Turbulence
This study demonstrates that small-scale turbulence in clouds is significantly enhanced by inertial droplets, a phenomenon driven by a mismatch in time scales between vortex evacuation and condensation, which generates baroclinic torque and could accelerate raindrop growth.
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Swinbourne et al. (2025) Trade-off between water-saving and cooling objectives: restricting irrigation increases the number of hot days
This paper investigates the trade-off between urban cooling and water conservation by simulating various irrigation scenarios in Melbourne, Australia, finding that increased irrigation significantly reduces heat stress, with quantifiable benefits for reducing heat stress days and mean air temperature.
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Dong et al. (2025) ENSO Influence on Subsequent Early‐Summer North American Atmospheric Circulation: Role of Land‐Atmosphere Interaction
This study identifies an ocean-land-atmosphere relay mechanism where El Niño-induced sea surface temperature anomalies enhance moisture transport into North America, leading to land temperature anomalies that feedback on the atmosphere, weakening the westerly jet and extending ENSO's influence into early summer.
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Jääskeläinen et al. (2025) High-resolution soil moisture mapping in northern boreal forests using SMAP data and downscaling techniques
This study develops a machine-learning-based downscaling model to estimate soil moisture at 1 km and 250 m spatial resolutions across northern boreal forests. By integrating SMAP satellite data with vegetation and weather parameters, the model improves soil moisture prediction accuracy over forested sites compared to original coarse-resolution products.
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Shi et al. (2025) Amplified Global Seasonality in Water Availability over Land in Recent Decades
This study quantified global seasonal precipitation minus evapotranspiration (P-E) shifts from 2000 to 2020 using observational data, revealing a significant increase in seasonal P-E range driven primarily by a global decrease in minimum P-E values, largely attributed to increased evapotranspiration.
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Veness et al. (2025) User priorities for hydrological monitoring infrastructures supporting research and innovation
This study identifies end-user priorities for the UK’s new GBP 38 million Floods and Droughts Research Infrastructure (FDRI), revealing that value is maximized when infrastructures move beyond simple data provision to actively enable decentralized data collection and foster collaborative research communities.
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Gohil et al. (2025) Global Simulations Suggest Biomass Burning Aerosol Emissions From Grassland Fires Could Be Important Ice Nucleating Particles
This study investigates the global importance of biomass burning aerosols (BBA) as immersion-mode ice nucleating particles (INP) using a global aerosol-climate model. It finds that BBA can be a more significant INP source than mineral dust and marine INP in specific atmospheric regions and seasons, particularly over the Southern Hemisphere during June-September.
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Fair et al. (2025) Review article: using spaceborne lidar for snow depth retrievals: recent findings and utility for hydrologic applications
This review synthesizes the current status of spaceborne lidar for snow depth retrieval, focusing on the ICESat-2 mission, and evaluates its utility for hydrologic applications. It concludes that while ICESat-2 can achieve centimeter-level accuracy under ideal conditions, challenges persist in complex terrain and with current temporal revisit limitations, necessitating integration with hydrologic models and improved snow-off digital elevation models.
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Wang et al. (2025) Decadal Responses of Global Land Monsoon to Two Surface Thermal Modes in the Last Millennium
This study investigates the influence of global mean surface temperature (GMST) and tropical Pacific temperature gradient (TPTG) on global land monsoon variability over the last millennium (950–1850). It finds that cool-GMST primarily suppresses summer precipitation thermodynamically, while weak-TPTG drives a summer interhemispheric dipole dynamically, with compound conditions largely showing a linear superposition of these distinct effects.
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Patil et al. (2025) Investigating firn structure and density in the accumulation area of the Grosser Aletschgletscher using ground-penetrating radar
This study investigates firn structure, density, and accumulation history in the Grosser Aletschgletscher using ground-penetrating radar (GPR) and glaciological methods, demonstrating the potential to enhance glacier mass balance estimations by providing spatially distributed firn properties and accumulation records over the past 10-14 years.
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Wu et al. (2025) Thermodynamic and Dynamic Effects of Parametric Uncertainties on the Simulated Interannual‐To‐Interdecadal Variability of Summertime Precipitation Over China
This study quantifies uncertainties in simulated precipitation variability over China, attributing them primarily to the thermodynamic component, though the dynamic component's uncertainty is comparable, especially interannually. It identifies convective precipitation evaporation as a major source of interannual uncertainty, demonstrating its complex role in enhancing large-scale precipitation despite local suppression.
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Fang et al. (2025) IMPMCT: a dataset of Integrated Multi-source Polar Mesoscale Cyclone Tracks in the Nordic Seas
The Integrated Multi-source Polar Mesoscale Cyclone Tracks (IMPMCT) dataset provides a comprehensive 24-year (2001–2024) record of wintertime Polar Mesoscale Cyclone (PMC) tracks in the Nordic Seas, integrating ERA5 reanalysis, AVHRR infrared imagery, and scatterometer wind data. This dataset, containing 1110 tracks, 16 001 cloud features, and 4472 wind records, aims to advance the understanding of PMC genesis and intensification mechanisms.
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Luo et al. (2025) Coupling strategies for precipitation nowcasting in China
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Biella et al. (2025) The 2022 drought needs to be a turning point for European drought risk management
This study analyzes the 2022 European drought by linking climate indices with a continent-wide survey of 481 water managers to evaluate sectoral impacts and management effectiveness. The findings reveal that while drought risk is perceived to be increasing across Europe, current management remains largely reactive and fragmented, prompting a call for a legally binding European Drought Directive.
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Phogat et al. (2025) Regional dynamics in evapotranspiration components, crop coefficients, and water productivity of vineyards
This study estimated water balance components, crop coefficients, and water productivity for Shiraz vineyards across 48 locations in Barossa, South Australia, over three seasons using the FAO-56 dual crop coefficient approach, revealing significant spatial and temporal variability in these parameters and highlighting the need for site-specific irrigation management.
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He et al. (2025) Benchmarking and evaluating the NASA Land Information System (version 7.5.2) coupled with the refactored Noah-MP land surface model (version 5.0)
This study integrates the refactored Noah-MP version 5.0 land surface model with the NASA Land Information System (LIS) version 7.5.2 to enhance interoperability and evaluates its global and regional performance against the previous LIS/Noah-MPv4.0.1 for key land surface variables. The results show that LIS/Noah-MPv5.0 generally performs similarly or better than its predecessor, with slight degradations in simulated surface soil moisture and snow water equivalent.
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Carletti et al. (2025) Multitemporal analysis of Sentinel-1 backscatter during snowmelt using high-resolution field measurements and radiative transfer modelling
This study presents a unique high-resolution dataset of wet-snow properties to validate Sentinel-1 backscatter links to snowmelt stages and investigate scattering mechanisms using a radiative transfer model, revealing the dominant influences of liquid water content and surface roughness.
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Hierro (2025) Observational Evidence of Vertical Drying Over Deforested Amazonia From GPS ‐ RO Data
This study investigates the impact of deforestation on the vertical humidity structure in Amazonia, revealing significant drying, particularly in the lower troposphere, in highly deforested regions, which intensifies during the dry season.
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López-Martí et al. (2025) Can data-driven weather models accurately forecast atmospheric rivers?
This study assesses the performance of leading data-driven weather models (GraphCast, Pangu-Weather) against a physics-based model (IFS-HRES) in forecasting integrated vapour transport (IVT) and atmospheric rivers (ARs). While data-driven models show comparable IVT skill, they struggle with higher IVT quantiles and geometrically stricter AR detection, suggesting physics-based models may retain advantages for complex derived features.
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Samuel et al. (2025) Assessment of Historical and Future Mean and Extreme Precipitation Over Sub‐Saharan Africa Using NEX ‐ GDDP ‐ CMIP6 : Part II —Future Changes
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Thiam (2025) Paramétrisation du soulèvement de poussières au Sahel par les poches froides
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Qin et al. (2025) Sensitivity Differences Between 118 GHz and 183 GHz Radiance in All‐Sky Assimilation With Hydrometeor Control Variables and the Impact on a Typhoon Structure Forecast
This study investigates the comparative impacts of separate and joint assimilation of 118 GHz and 183 GHz Microwave Humidity Sounder-II (MWHS-II) channels on hydrometeor analysis and forecasting of Typhoon Lekima (2019). Joint assimilation significantly improves the representation of temperature, humidity, and hydrometeor distribution, enhancing typhoon intensity forecasting and understanding of its structure.
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Matthews et al. (2025) Error-correction across gauged and ungauged locations: A data assimilation-inspired approach to post-processing river discharge forecasts
This study presents a novel data-assimilation-inspired post-processing method to error-correct river discharge ensemble forecasts across both gauged and ungauged locations. The method successfully improves the skill of the ensemble mean and maintains spatial and temporal consistency in the corrected forecasts.
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Werapitiya et al. (2025) Extratropical Cloud Feedback Constrained by Cloud Sources and Sinks in Cyclones
This study constrains Southern Ocean liquid water path (LWP) response and shortwave cloud feedback (SW FB) in global climate models using observational data and a perturbed parameter ensemble, finding that observations suggest a more positive SW FB and do not reject high climate sensitivity models.
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Huang et al. (2025) Seasonal and Spatial Variations of Vertical Profile Heating (VPH) Latent Heat Over Northern East Asia Based on GPM Observations
This study quantifies the three-dimensional structure of latent heating (LH) from precipitation over northern East Asia using GPM observations, documenting its seasonal, meridional, and land-sea contrasts. It reveals that summer precipitation exhibits stronger and higher LH, with a poleward decrease in LH heights and coastal amplification, providing a crucial midlatitude LH climatology.
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Sarah et al. (2025) Earth observations for climate adaptation: tracking progress towards the Global Goal on Adaptation through satellite-derived indicators
This Perspective paper explores how space-based Earth Observation (EO) data can support tracking progress towards the Paris Agreement's Global Goal on Adaptation (GGA), focusing on agriculture, biodiversity, extreme events, and health. It highlights EO's strengths and challenges, offering recommendations for integrating EO into the development of standardized, operational adaptation indicators.
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Patil et al. (2025) Over 100 global climate sensitive rivers are experiencing large and severe changes in streamflow volume and timing
This study analyzed streamflow volume and timing changes in 812 climate-sensitive rivers globally from 1950 to 2022, finding increasing streamflow and earlier timing in over half of the sites, largely driven by precipitation changes, with significant implications for river health and water management.
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J et al. (2025) Can discharge be used to inversely correct precipitation?
This study investigates the feasibility of using observed streamflow to inversely correct catchment-average precipitation from reanalysis products using LSTM networks. It demonstrates that discharge significantly improves precipitation estimates, especially for high-magnitude events, and enhances subsequent hydrological forward modeling of streamflow and soil moisture.
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Pardo et al. (2025) Dynamics of Downdrafts Around a Growing Convective Cloud: A Numerical Study
This study investigates the dynamics of cloud-edge downdrafts in growing isolated cumuli, revealing that the most intense downdrafts are predominantly driven by dynamic pressure accelerations rather than buoyancy, and are stronger than predicted by simple vortex models.
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Bauer et al. (2025) An Analytical Model for the Influence of Soil Moisture on Temperature Extremes in the Midlatitudes
This paper develops a theoretical framework and analytical models to demonstrate that low soil moisture nonlinearly controls the frequency of midlatitude temperature extremes by slowly altering the land surface climate state, rather than directly modifying atmospheric variability.
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Coquereau et al. (2025) Increase in ENSO Frequency and Intensity Under 20th and 21st Century Warming: Insights From CMIP6 Large Ensembles
This study analyzes CMIP6 large-ensemble simulations to demonstrate that anthropogenic warming increases El Niño-Southern Oscillation (ENSO) frequency and strengthens its intensity, primarily driven by a shift towards Eastern Pacific El Niño and an overall increase in both EP and CP variability.
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Hunt et al. (2025) Wetter, Weaker, and More Frequent Monsoon Low Pressure Systems in CMIP6 Future Scenarios
This study synthesizes future characteristics of South Asian monsoon low pressure systems (LPSs) using CMIP6 models, projecting that LPSs will become more frequent and deliver increased precipitation per event despite dynamic weakening, leading to an expanded risk of extreme rainfall and flooding deeper into the Indian subcontinent.
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Wang et al. (2025) Subsurface constraints amplify vegetation stress during extreme heat and drought in a Mediterranean forest
This study investigated how subsurface conditions interact with climate stress to influence forest vulnerability and die-off at landscape scales. It revealed that vegetation die-off in the Jarrah Forest during the 2023–2024 summer resulted from the interplay of heat, water stress, and subsurface factors, with shallow soils and limited subsurface water predisposing vulnerability.
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Xu et al. (2025) Elevating predictive reliability: time-varying parameter bayesian deep learning techniques for flood probability forecasting
This study introduces a Fourier-based Time-Varying Parameter Bayesian Long Short-Term Memory (F-TV-BLSTM) model, integrating FourCastNet precipitation forecasts, to enhance multi-step-ahead probabilistic flood forecasting reliability in non-stationary environments. Applied to the Yalong River Basin, the model demonstrates superior performance in accuracy and dependability, particularly for extreme flood events, by dynamically adjusting parameters.
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Lee et al. (2025) Enhancement of hydrologic model optimization with single-step reinforcement learning
This study proposes a single-step Reinforcement Learning (PPO-1) approach for efficient calibration of hydrological models with static parameters. It demonstrates that PPO-1 achieves better or comparable calibration accuracy with significantly reduced computational resources compared to traditional methods.
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Pang et al. (2025) A skillful self-evolving deep-learning framework for pluvial flood process forecasting in urban areas
This paper presents a self-evolving deep-learning framework, based on two autoregressive convolutional neural networks, for real-time pluvial flood process forecasting. The framework accurately predicts flood depth and velocity fields with significantly reduced computational time compared to conventional hydrodynamic models and improved accuracy over existing end-to-end surrogate models.
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Pacheco‐Labrador et al. (2025) BOSSE v1.0: the Biodiversity Observing System Simulation Experiment
This paper introduces BOSSE v1.0, a novel Observing System Simulation Experiment (OSSE) designed to simulate synthetic landscapes featuring diverse vegetation, associated remote sensing signals, and ecosystem functions. BOSSE aims to address the critical lack of consistent global ground diversity measurements, enabling the benchmarking and development of remote sensing methodologies for estimating plant functional diversity (PFD) and biodiversity-ecosystem function (BEF) relationships.
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Köcher et al. (2025) The spatial distribution of convective precipitation – an evaluation of cloud microphysics schemes with polarimetric radar observations
This study statistically evaluates five cloud microphysics schemes in the WRF model for simulating convective precipitation events over a 30-day dataset, revealing that the choice of scheme significantly impacts the distribution of precipitation into convective and stratiform regions and their microphysical properties, mainly due to differences in simulated rain drop size distributions.
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Wang et al. (2025) The effect of rainfall variability on Nitrogen dynamics in a small agricultural catchment
This study investigates the effect of inter-annual and intra-annual rainfall variability on nitrogen (N) dynamics and water quality in a small agricultural catchment in central Germany using a coupled hydrological and N transport model driven by a stochastic rainfall generator. It finds that higher annual precipitation enhances N transformation and transport, while lower annual precipitation promotes N retention, with vegetation health critically influencing N dynamics during extreme droughts and rewetting periods.
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Xiao et al. (2025) Research status of winter irrigation based on bibliometric analysis
This bibliometric analysis reviews 61 articles on winter irrigation from the Web of Science (2000–2024) to map research trends, hotspots, and key challenges, highlighting the increasing focus on soil water-salt dynamics and the need for integrated, region-specific strategies.
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Elhaddad et al. (2025) Nile basin flow regimes under 21st century climate variability
This study assesses future flood risk in the Nile Basin's downstream countries using a calibrated, climate-driven SWAT+ model forced by bias-corrected CMIP6 models under SSP2-4.5 and SSP5-8.5 scenarios, projecting a significant increase in 100-year peak discharges (63% to 85%) and more frequent extreme floods by the 21st century.
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Chadwick et al. (2025) Processes Controlling the South American Monsoon Response to Climate Change
Future projections consistently show early South American monsoon drying, primarily driven by sea surface temperature (SST) changes (uniform warming and patterned changes), with Atlantic SST gradients explaining over half of the intermodel uncertainty in November.
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Zhang et al. (2025) First Global Retrievals of Solar Induced Chlorophyll Fluorescence From the SIFIS Instrument Onboard the Chinese Goumang Satellite
This paper introduces and validates the Solar-Induced Chlorophyll Fluorescence Imaging Spectrometer (SIFIS) on the Goumang satellite, demonstrating its capability to provide high-resolution SIF data (370 m × 800 m) with high accuracy, enabling fine-scale monitoring of terrestrial photosynthesis.
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Wu et al. (2025) Assessing the real impact of inter-provincial grain trade on water and land resources within China via a modified framework
This study developed a modified framework to assess the real impact of inter-provincial grain trade on water and land resources in China by incorporating irrigation's yield-enhancing effects. It found that existing frameworks significantly underestimate virtual blue water and arable land flows, leading to erroneous trade evaluations and policy guidance.
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Polonik et al. (2025) Emulation of the Climate Response to Greenhouse Gas and Aerosol Emissions From High‐ and Low‐Income Nations
This study uses a large ensemble climate model to identify spatiotemporal temperature changes due to greenhouse gases and aerosols from different economic regions, revealing that non-OECD aerosol emissions could mask over 20% of greenhouse gas-induced warming for a significant global population by 2050.
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Peven et al. (2025) Climate controls on seasonal groundwater–stream connectivity in snow-dominated semi-arid headwaters
This study investigates how groundwater-stream connectivity in snow-dominated semi-arid headwaters responds to climate variability, particularly the 2021 extreme drought, using diel air–water temperature amplitude ratios. It found that groundwater connectivity can increase or remain stable during drought, buffering thermal extremes in some streams.
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Kallush et al. (2025) Flash flood dynamics in arid areas at the Sub-Basin Scale: The Ze’elim Basin, Israel
This study quantitatively evaluates rainfall-runoff relationships at the sub-basin scale in the hyper-arid Ze’elim Basin, Israel, finding that rainfall depth reliably predicts runoff depth, and peak discharge correlates more strongly with rain-core coverage (spatial extent of intense rainfall) than with point-maximum rainfall intensity.
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Yang et al. (2025) Assessment of monthly vegetation response and ecosystem risks to drought-flood abrupt alternation using an integrated framework
This study investigates the distinct monthly vegetation response and ecosystem risks to drought-flood abrupt alternation (DFAA) modes (drought-to-flood and flood-to-drought) in the Hai River Basin, revealing a novel seasonal reversal in vegetation vulnerability and ecosystem risk patterns.
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Gomes et al. (2025) A coupled Darcy–Richards framework for hydrological modeling of permeable pavements, green roofs, and bioretention systems
This study introduces a physics-based, open-source framework that couples a one-dimensional Richards equation solver with a conceptual rainfall–runoff model to simulate the long-term hydrological performance of Low-Impact Development (LID) practices. The framework demonstrates high accuracy against established models and field data, providing critical insights into runoff retention, evaporation efficiency, and flow duration patterns of LIDs across various climate conditions over decades.
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Disasa et al. (2025) Comprehensive review of drought characteristics and intensification under climate change: implications for agriculture and water resources
This review synthesizes the intensification of drought characteristics across meteorological, hydrological, and agricultural sectors under climate change. It highlights how global warming alters drought frequency and severity, leading to significant risks for water resources and crop yields.
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Wessinger et al. (2025) An Unexpected Peak in Daytime Convection Initiation Weakens Diurnal Amplitude of Tropical Oceanic Precipitation and Cloud Cover
This study investigates the diurnal cycle of deep convective system (DCS) initiation and subsequent rainfall over tropical oceans to address deficiencies in Earth system models. It identifies two peaks of DCS initiation—an overnight peak and an unexpected late morning peak—and demonstrates that daytime-initiated DCSs significantly contribute to afternoon rain and cloud cover, suggesting that Earth system models may underestimate these daytime initiations.
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Kaur et al. (2025) Estimation of soil hydraulic parameters for fine-textured soils using HYDRUS-1D coupled with PEST
This study utilized HYDRUS-1D coupled with PEST to estimate van Genuchten-Mualem soil hydraulic parameters for a fine-textured soil in Manitoba over four growing seasons, revealing the non-uniqueness of solutions and identifying stable parameter ranges through sequential calibrations.
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Ming et al. (2025) Environmental and Boundary Layer Characteristics Associated With Intensity Change of Tropical Cyclones Under High Fullness
This study investigates why high-fullness tropical cyclones (TCs) sometimes weaken, comparing the structural and environmental conditions of intensifying and weakening TCs using GPS dropsonde data to improve intensity change prediction.
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Liu et al. (2025) A combined spatial interpolation method of co-Kriging with inverse distance weighting and random forest for soil water and salt in arid oasis
This study developed a combined spatial interpolation method integrating Co-Kriging (CK), Inverse Distance Weighting (IDW), and Random Forest (RF) to accurately characterize soil water and salt distribution in arid oasis regions. The novel combined method significantly improved prediction accuracy for both soil water content and total salt content compared to traditional methods, establishing a transferable framework for multi-method integration.
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Zhou et al. (2025) Snow effects on altimeter waveforms over sea ice in the Weddell Sea — Part I: Radar waveform decomposition
This study analyzes Ku-band CryoSat-2 and Ka-band KAREN altimeter waveforms over the Weddell Sea to decompose scattering contributions from snow surface, snow volume, and ice surface. It finds that snow-volume scattering significantly contributes to Ku-band returns, often as much as or more than the snow-ice interface, while Ka-band is dominated by surface/near-surface snow scattering.
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Schmidt et al. (2025) Datasets and protocols for including anomalous freshwater from melting ice sheets in climate simulations
This paper presents comprehensive data products and recommendations for incorporating anomalous freshwater fluxes from the Greenland and Antarctic ice sheets into climate model simulations, particularly for CMIP7, to improve the representation of ocean temperature, sea ice, and regional sea level trends.
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Sebastian et al. (2025) Incorporating varying vegetation characteristics driven by Hydrometeorology in the land surface modeling by variable Infiltration Capacity model
This study demonstrates the critical role of dynamic vegetation in hydrological modeling, particularly for evapotranspiration in India, by integrating a machine learning model (LSTM) to simulate vegetation variability within the Variable Infiltration Capacity (VIC) model, revealing an 18% increase in annual evapotranspiration compared to static vegetation approaches.
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Wang et al. (2025) Improvement of the hillslope-storage Boussinesq model by incorporating rainfall infiltration effects
This study develops a novel coupled hillslope-storage Boussinesq (hsB) and Green-Ampt (GA) infiltration model to improve the simulation of hillslope hydrological responses by incorporating rainfall infiltration, demonstrating superior performance over the conventional hsB model. The new model enables continuous simulation from rainfall onset through post-event drainage, capturing complex hydrodynamic features across various soil types and rainfall intensities.
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Gaiolini et al. (2025) Salt migration and export via subsurface irrigation in a saline reclaimed landscape of the Po River lowland (Italy)
This study investigates the causes and quantifies the sources of dissolved salts in a saline reclaimed landscape of the Po River lowland, Italy, focusing on the impact of subsurface irrigation via tile drains. It reveals that sub-irrigation significantly accelerates salinization and salt export, with peaty lenses and decomposing halophytes acting as major salt sources, leading to high surface water salinity.
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Cerato et al. (2025) Summer Drought Predictability in the Euro-Mediterranean Region in Seasonal Forecasts
This study evaluates the ability of state-of-the-art seasonal forecast systems to predict summer drought in Europe, finding that the Standardized Precipitation Evapotranspiration Index (SPEI-3) offers more spatially coherent and higher forecast skill than the Standardized Precipitation Index (SPI-3), particularly in southern Europe. The multimodel ensemble (MME) provides the most robust solution for early summer drought detection, demonstrating widespread significant skill up to a 1-month lead time.
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Paramanik et al. (2025) Automated and continuous estimation of FAPAR from distributed wireless PAR sensor networks
This study evaluates the performance of two-flux (2f) and four-flux (4f) FAPAR measurement systems and digital hemispherical photography (DHP) across multiple vegetation types and temporal scales using automated wireless PAR sensor networks. It reveals strong agreement between 2f- and 4f-FAPAR (R² > 0.99, RMSE ≤ 0.04), suggesting that 2f systems are a reliable and cost-effective alternative, and underscores the importance of daily integrated FAPAR for long-term ecosystem monitoring.
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Zhang et al. (2025) Rainfall monitoring based on commercial microwave links in Jiangyin, China: Long-term performance analysis over 3 years
This study analyzes 3 years of data from 48 commercial microwave links (CMLs) in Jiangyin, China, to calibrate and validate CML-based rainfall inversion algorithms, demonstrating their effectiveness, particularly for summer, high-intensity, and convective rainfall.
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Anderson et al. (2025) What is a drought-to-flood transition? Pitfalls and recommendations for defining consecutive hydrological extreme events
This study assesses the suitability and differences of various threshold-level methods for defining drought-to-flood transitions using eight case study catchments, revealing that methodological choices significantly alter detected event characteristics and often fail to capture historically impactful transitions.
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Wu et al. (2025) Perspective on the shifting interannual variability of recent summer temperature modes in eastern China: Roles of Arctic sea-ice, Arctic Oscillation and Pakistan precipitation
This study reveals a fundamental reorganization of interannual summer temperature variability in eastern China, characterized by an enhancing south-north uniform warming (SNUW) mode and a disappearing south-north meridional dipole (SNMD) mode. These shifts are driven by increasing Pakistan convective precipitation and Arctic Oscillation variability for SNUW, and reduced Barents-Kara sea-ice variability for SNMD, with implications for future extreme heat events.
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Wei et al. (2025) A time-varying weighted merging method for integrating multisource precipitation data considering error variations
This study developed a Time-varying Weighted (TVW) merging method to integrate multi-source precipitation data, demonstrating its superior performance over parent datasets and state-of-the-art products in mainland China, even with reduced station density.
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Montpetit et al. (2025) Snow Water Equivalent from airborne Ku-band data: the Trail Valley Creek 2018/19 snow experiment
This study develops and validates a snow water equivalent (SWE) retrieval algorithm for a proposed Ku-band synthetic aperture radar (SAR) satellite mission by combining a priori snow conditions from a land surface model (SVS-2) with a Markov Chain Monte Carlo (MCMC) Bayesian model coupled with the Snow Microwave Radiative Transfer (SMRT) model, achieving a root-mean-square error (RMSE) of 15.8 mm (16.4 %) for SWE retrieval.
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Guo et al. (2025) Modeling soil water–heat–salt transport and cotton growth under high salinity and seasonal freezing conditions in Northern Xinjiang, China
This study developed a coupled water–heat–salt transport and crop growth model (SWHS-C) to simulate annual cycles in salinized, seasonal frozen agricultural regions, revealing that salt stress primarily limits cotton transpiration and groundwater dynamics drive soil salinity evolution.
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Ono et al. (2025) Estimating Maximum Precipitation for an Extreme Rainfall Event in Japan Using Lower-Level Shifts of Atmospheric Initial and Boundary Conditions
This study investigates the sensitivity of maximum precipitation (MP) estimates to different atmospheric initial and boundary condition (AIBC) shifting methods using a high-resolution weather model. It finds that a novel lower-level shift (LLS) method, focusing on lower-tropospheric moisture, significantly increases estimated 6-hour precipitation by 65% compared to traditional all-layer shifts (ALS), which showed only slight increases.
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Anoop et al. (2025) Atmospheric aridity perturbs critical soil moisture thresholds of plant water stress over Indian biomes
This study quantifies critical soil moisture thresholds (θcrit) for Indian biomes using satellite data and two independent methodologies, revealing that atmospheric aridity (VPD) significantly perturbs θcrit, leading to seasonal and hydrological forcing-driven variations. The covariance-based method (Cov(GPP-VPD)-SM) is found to be more sensitive for assessing these dynamics.
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Zhang et al. (2025) Coupled surface water-groundwater-crop model considering the impact of irrigation using different calibration targets
This study developed a coupled VIC-EPIC-HYDRUS (VEH) model to improve the simulation accuracy of hydrological processes on agricultural land, considering irrigation impacts, and demonstrated its superior performance through multi-objective parameter optimization and validation.
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Puche (2025) Vers une modélisation hydrologique flexible et opérationnelle pour la simulation des débits : optimisation et comparaison des approches à base physique et de Deep Learning
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Hu et al. (2025) A novel framework for accurately quantifying wetland depression water storage capacity with coarse-resolution terrain data
This study developed a novel framework, WetlandSCB, to accurately quantify wetland depression water storage capacity (WDWSC) using coarse-resolution terrain data and multi-source remote sensing, overcoming limitations of high-resolution data scarcity and biases in global Digital Elevation Models (DEMs). The framework achieved WDWSC estimation with less than 10% relative error compared to field measurements, demonstrating its applicability for large-scale wetland water storage assessment.
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Wang et al. (2025) The Emerging Precipitation Dipole Regime during the Tropical Asian Summer Monsoon Termination Phase
This study investigates the mechanisms behind the amplified east-west precipitation dipole observed during the delayed tropical Asian summer monsoon withdrawal since 2005/06. It reveals that multiscale interactions between intraseasonal (Madden–Julian oscillation) and low-frequency (negative Interdecadal Pacific Oscillation and southern Indian Ocean warming) processes drive this dipole, leading to increased extreme rainfall risks in the east and precipitation deficits in the west.
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Karmokar (2025) Do morphometry and unit hydrograph consistently reflect the flood generation potential? Insights from the analysis of the Himalayan watersheds
This study investigates the consistency between morphometric parameters and unit hydrographs in assessing the flood generation potential of 30 Himalayan watersheds. It finds that a plot of Melton’s ruggedness number (MRn) versus log first order stream magnitude (F1m) provides 100% accuracy in categorizing watersheds by relative peak magnitude, showing 85% agreement with the CWC Synthetic Unit Hydrograph (SUH) model.
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Bonassies et al. (2025) A comprehensive study of Surface Water and Ocean Topography (SWOT) Pixel Cloud data for flood extent extraction
This study comprehensively evaluates the capabilities and limitations of the Surface Water and Ocean Topography (SWOT) satellite's Ka-band Radar Interferometer (KaRIn) Pixel Cloud products for flood extent extraction across four major flood events, comparing its performance against Sentinel-1/2 data and its built-in classification. It demonstrates SWOT's potential for detecting floods in vegetated and urban areas while identifying sensitivities to high soil moisture and incidence angle.
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Gou et al. (2025) Climate‐Dependent Mechanisms Accelerate Flash Droughts in Drylands and Humid Regions
This study globally assesses flash drought onset speed using satellite-based evaporative stress and machine learning interpretation to identify dominant hydrometeorological factors, revealing that while humid regions experience more frequent events, drylands intensify more rapidly due to climate-dependent energy and water constraints.
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Wu et al. (2025) Automated drone-borne GPR mapping of root-zone soil moisture for precision irrigation
This study demonstrates the potential of drone-borne Ground-Penetrating Radar (GPR) to map spatial and temporal root-zone soil moisture dynamics across an agricultural field over an entire growing season. Using the gprSense® system with full-wave inversion, the research achieved precise and automated time-lapse soil moisture mapping, showing strong agreement with conventional methods and providing actionable insights for precision irrigation.
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Ballinger et al. (2025) Importance of beginning industrial-era climate simulations in the eighteenth century
This study investigates early industrial climate changes (1750-1850) using Earth system model simulations, demonstrating that initializing simulations in 1750, rather than 1850, leads to more representative historical climate simulations with lasting effects into the 20th century due to better capture of early human influence and volcanic activity.
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Lee et al. (2025) Influence of Baroclinic Eddies on the Hadley Cell Edge
This study refines the theoretical understanding of Hadley Cell (HC) extent by incorporating baroclinic eddy heat and momentum fluxes into the energy flux balance, demonstrating that these eddies significantly shift the HC edge.
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Yao et al. (2025) Irrigation-induced land water depletion aggravated by climate change
This study uses seven Earth System Models to analyze the effects of historical irrigation expansion on global water fluxes and resources. It reveals that irrigation expansion significantly decreases the net water influx from the atmosphere to land, thereby exacerbating existing drying trends caused by climate change and leading to substantial terrestrial water storage depletion.
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Thual et al. (2025) A fresh perspective on ENSO nonlinearity: the ENSO pattern continuum metric
This study introduces a "pattern continuum" metric, based on Warm Pool Edge Position (WPEP) quantiles, to synthesize and understand the spatial diversity, asymmetry, and nonlinearity of El Niño-Southern Oscillation (ENSO) sea surface temperature (SST) patterns. It demonstrates that ENSO's complex features can be effectively approximated by a simple "shifted-mean" framework, where a fixed SST structure shifts zonally, providing a novel interpretation for the quadratic relationship between SST principal components.
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Qi et al. (2025) Retrieving fine-scale leaf and soil spectral properties from canopy reflectance with differentiable 3D radiative transfer
This study introduces 3D-Diff, a novel differentiable three-dimensional (3D) radiative transfer approach, to accurately retrieve fine-scale leaf and soil spectral properties from canopy reflectance using remote sensing imagery and known 3D canopy structures, demonstrating robust performance in both virtual and real-world validations.
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Wagner et al. (2025) The fully-automatic Sentinel-1 Global Flood Monitoring service: Scientific challenges and future directions
The Global Flood Monitoring (GFM) service, launched in 2021 as part of the Copernicus Emergency Management Service (CEMS), provides fully-automatic, near-real-time global flood maps using Sentinel-1 SAR imagery. This paper presents a comprehensive analysis of GFM's scientific achievements and challenges, demonstrating its rapid delivery and good accuracy for larger-scale floods while identifying limitations in coverage and detection in specific environments.
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Robinson et al. (2025) The hydrological archetypes of wetlands
This study investigated the hydrological regimes of 43 Ramsar wetlands in Sweden using Sentinel-1 SAR imagery and a deep learning model (DeepAqua) to predict surface water extent. It identified five distinct hydrological archetypes, revealing how wetland water dynamics relate to their ecosystem services and providing a novel classification method.
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Min et al. (2025) Hydrological drought prediction and its influencing features analysis based on a machine learning model
This study develops an interpretable machine learning framework using XGBoost and SHAP to predict hydrological drought in the Huaihe River Basin, China, achieving 79.9% overall accuracy and identifying the Standard Precipitation Index (SPI) as the most influential feature.
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McAdam et al. (2025) Feature selection for data-driven seasonal forecasts of European heatwaves
This study develops an inexpensive, purely data-driven machine learning approach for seasonal forecasting of European summer heatwaves, demonstrating skill comparable to, and in some regions outperforming, state-of-the-art dynamical multi-model products, while also identifying key predictors and their optimal time-lags.
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Zheng et al. (2025) Modeling, prediction, and retrieval of surface soil moisture from InSAR closure phase
This study presents a discretized, multi-layer soil moisture model that links soil moisture variability to single-look SAR measurements and their closure phase. It introduces a scalable algorithm for retrieving a relative InSAR Soil Moisture Index, demonstrating its potential for large-scale soil moisture monitoring through validation against in situ and satellite data.
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Bastviken et al. (2025) Future methane emissions from lakes and reservoirs
This study presents data-driven, globally gridded modeling to project future methane emissions from lakes and reservoirs under various IPCC climate change scenarios. It predicts a 24–91% increase in total lake and reservoir CH4 emissions by 2080–2099, primarily driven by changes in temperature and seasonality, with area and nutrient load also contributing significantly to reservoir emissions.
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Sandoval et al. (2025) Towards water resilience: A multi-stage calibration framework for large-scale integrated surface–subsurface hydrological models
This study presents a multi-stage calibration framework for large-scale, high-fidelity integrated surface water–groundwater models using sensitivity analysis and Gaussian Process Regression surrogates. The approach resulted in the first robustly calibrated integrated model of the Po River District (87,000 km²), effectively capturing complex 3D subsurface dynamics and river discharge.
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Khan et al. (2025) Deep learning approach for vertical soil moisture profile estimation using hydrometeorological data
This study presents the evaluation of the eartH2Observe Tier-1 dataset, a global ensemble of ten hydrological and land surface models forced by a consistent atmospheric dataset. The research demonstrates that the ensemble mean generally provides a more reliable estimation of global water fluxes and storage than any individual model.
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Zheng et al. (2025) Impact of Drought‐Flood Abrupt Alternation on Vegetation Productivity in Karst and Non‐Karst Regions of Southern China
This study identifies drought-flood abrupt alternation (DFAA) events using the Standardised Soil Moisture Index (SSMI) and quantifies their impact on vegetation productivity in southern China, revealing that flood-to-drought events intensify stress and slow vegetation recovery, particularly in vulnerable karst regions.
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Shi et al. (2025) Towards an easy-to-use algorithm to estimate longwave cloud radiative forcing: algorithm development and preliminary evaluation
This study develops a lightweight algorithm to estimate surface longwave cloud radiative forcing (LWCRF) using only five readily available parameters, achieving a theoretical root-mean-square error (RMSE) of 5.47 W/m² and an RMSE of 12.03 W/m² against global satellite data.
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Li et al. (2025) The Joint Occurrence Probability of Compound Drought and Heatwaves: A Copula‐Based Multivariate Analysis of Duration and Severity in China
This study develops a two-dimensional joint function integrating duration and severity to assess the comprehensive risk of Compound Drought and Heatwave (CDHW) events in China. It reveals that the impacts of duration and severity on CDHW joint occurrence probability vary significantly across different regions of China, with severity often having a greater influence on extreme events.
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Ho et al. (2025) The impact of climate change on dam overtopping floods in Australia
This study projects changes in the exceedance probabilities of dam overtopping floods for 18 large Australian dams under various global warming scenarios. It finds that under 4 °C of global warming, the probability of overtopping floods increases by 2.4–17 times compared to historical conditions, primarily driven by increases in rainfall depth.
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Farag et al. (2025) Enhancing Water Use Efficiency in Subsurface Drip Irrigated Citrus Trees Using Wrapped Drip Irrigation Lines and Soil Covers
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Wen et al. (2025) Terrain-Driven Variability of Raindrop Size Distribution and Rainfall Kinetic Energy in Shaanxi, China, and Implications for Microphysics Estimation
This study investigated the spatial variability of raindrop size distribution (DSD) across terrain gradients in Shaanxi Province, China, using six years of disdrometer observations. It revealed a pronounced south-north DSD gradient, with larger raindrops and higher kinetic energy in the semiarid Loess Plateau compared to the humid Qinling–Daba Mountains, amplifying soil erosion risks, and developed robust Dm-based estimators for key microphysical quantities.
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Shen et al. (2025) Unravelling the future role of internal variability in South Asian near-surface wind speed
This study quantifies the role of internal variability, specifically the Interdecadal Pacific Oscillation (IPO), in modulating near-surface wind speed (NSWS) projections over South Asia, finding that accounting for IPO reduces projection uncertainty by 8% in the near future and 15% in the far future.
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Bushra et al. (2025) CAMELS-NZ: hydrometeorological time series and landscape attributes for New Zealand
This paper introduces CAMELS-NZ, the first large-sample catchment hydrology dataset for New Zealand, providing hourly hydrometeorological time series and comprehensive landscape attributes for 369 catchments from 1972 to 2024. The dataset fills a critical gap in global hydrology by representing a Pacific Island environment with complex hydrological processes, supporting diverse research applications.
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Baste et al. (2025) Unveiling the limits of deep learning models in hydrological extrapolation tasks
This study investigates the extrapolation capabilities of stand-alone Long Short-Term Memory (LSTM) networks in hydrological rainfall-runoff modeling under extreme, synthetic precipitation events, revealing their inability to predict discharge beyond a calculated theoretical limit and exhibiting physically unrealistic concave runoff responses, in contrast to a more robust hybrid model.
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Wang et al. (2025) A UAV-based method for root zone soil moisture modeling of different farmland scale with grain and economic crops
This study developed an integrated UAV-based remote sensing and Remote Sensing-based Water Balance Assessment Tool (RWBAT) model to accurately estimate root zone soil moisture (RZSM) for four crop types in the Loess Plateau, demonstrating high simulation accuracy, especially at deeper soil depths.
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Bazlen et al. (2025) Hydrograph Spread Increases as Snow Declines Across the Western U.S.
This study investigates the previously unexamined influence of changing snow characteristics on the spread of streamflow distribution throughout the water year. It finds that lower peak snow water equivalent (SWE) is significantly associated with wider streamflow distributions across the western United States.
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Wen et al. (2025) Exploring causal pathways among soil moisture, climate and ocean–atmosphere teleconnection patterns over the drought-prone Greater Horn of Africa
This study employs a data-driven causal graph discovery algorithm (PCMCI+) to uncover causal relationships among ocean-atmosphere teleconnection patterns (ENSO, IOD), precipitation, temperature, and soil moisture over the drought-prone Greater Horn of Africa (GHOA) from 1980 to 2022, revealing that IOD generally exerts stronger causal effects on soil moisture, primarily mediated through precipitation.
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Reddy et al. (2025) Exploring the Influence of Sea Surface Temperature Extremes on Precipitation Extremes Across India's Climate Zones: A Complex Network Approach
This study investigates the multiscale impact of Sea Surface Temperature (SST) extremes on precipitation extremes across India's climate regions from 1981 to 2020, revealing that proximal oceanic regions drive short-term precipitation extremes while remote SST influences dominate longer-term extremes through atmospheric teleconnections.
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Zhang et al. (2025) Underestimated future flash drought risks in major grain-producing areas over China
This study assesses historical and future flash drought risks in major Chinese croplands by integrating crop phenology into the analysis framework. It reveals that a significant proportion of historical flash droughts occurred during critical crop growth phases, and future projections substantially underestimate risks if crop phenology is overlooked, particularly in northern regions.
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Rhee et al. (2025) Topographic Setting Drives the Imprint of the Madden–Julian Oscillation ( MJO ) on Tree Growth in the Northern Sierra Nevada
This study investigates whether conifer tree growth in the northern Sierra Nevada, United States, can serve as a proxy for Madden–Julian Oscillation (MJO) variability. It provides the first documented evidence that *Pinus jeffreyi* tree-ring chronologies exhibit significant correlations with MJO indices, offering a novel tool for reconstructing past MJO dynamics.
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Santos et al. (2025) Spatial and Temporal Patterns of Rainfall Anomalies and Their Relationship With Global Climate Indices in Rio Grande do Norte, Brazil
This study analyzed rainfall variability in Rio Grande do Norte, Brazil, using the Rainfall Anomaly Index (RAI) and its relationship with global climate indices (1963–2023). It identified homogeneous rainfall regions and found that teleconnections like AMO, TNA, and Niño indices directly influence rainfall, while LOTI and Solar Flux show an inverse relationship.
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Wu et al. (2025) Global patterns and drivers of canopy storage capacity in different biomes
This study compiled global canopy storage capacity (S) observations from 162 publications and used a boosted regression tree model to identify its biotic and climatic drivers. It revealed that global S ranges from 0.08 mm to 8.9 mm, with a median of 0.93 mm, and that biotic factors are the primary predictors of S variation.
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Ahamed et al. (2025) Identifying Baseflow Source Areas Using Remotely Sensed and Ground‐Based Hydrologic Data and Models
This study developed a data-driven approach using satellite and ground-based data to assess the spatial influence of rainfall and snowmelt on baseflow in California's Sierra Nevada. It revealed that snowmelt occurring in the 3000–3700 m elevation range is the most significant driver of baseflow, rather than areas with the highest annual rainfall or snowmelt rates.
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Fu et al. (2025) Intensifying Hydroclimate Whiplash From a 3D Perspective
This study investigates the spatiotemporal evolution of contiguous hydroclimate whiplash (HCW) extremes globally from 1982 to 2015 using a 3D scanning approach, revealing a significant underestimation of HCW frequency and affected areas by traditional pixel-level analyses.
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Peng et al. (2025) Beyond the Mean: Cold and Warm Tail Temperature Trends Reveal Asymmetric Controls on Snowpack Changes in the Northern Hemisphere
This study introduces a distributional diagnostic framework to decompose winter temperature trends into median, cold-tail, and warm-tail components across the Northern Hemisphere. It finds that mean and median winter temperature trends diverge significantly, and these asymmetric distributional changes, particularly tail behavior, are crucial for explaining March snow water equivalent trends, outperforming mean trends alone.
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Shi et al. (2025) Runoff Response to Climate and Landscape Changes Under Variable Fraction of Snowfall in Precipitation
This study modified the snow-involved Budyko equation to quantify runoff elasticity to various factors in 552 US catchments, revealing that ignoring snowfall overestimates runoff sensitivity to precipitation and landscape, and that declining snow ratios due to warming will increase runoff sensitivity.
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Anand et al. (2025) Balancing Productivity and Climate Impact: A Framework to Assess Climate‐Smart Irrigation
## Identification - **Journal:** Earth s Future - **Year:** 2025...
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Gao et al. (2025) Dynamics and Drivers of Suprapermafrost Groundwater on the Qinghai–Tibet Plateau Under Climate Change
This study investigated the seasonal dynamics, drivers, and future projections of suprapermafrost groundwater (SPG) in alpine meadow and alpine wet meadow ecosystems on the Qinghai–Tibet Plateau. It found that SPG fluctuations are primarily driven by thaw depth and rainfall infiltration, with climate warming projected to significantly deepen SPG tables by the 2090s.
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Liang et al. (2025) Is There Sufficient Information to Reliably Estimate Return Periods for Very Rare Heat Extremes in Event Attribution?
This study evaluates methods for estimating return periods of hot extremes in event attribution, finding that multi-year block maxima improve accuracy for very rare events compared to annual maxima, which tend to overestimate return periods in the far right tail.
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Miazza et al. (2025) Limits to the Estimation of Old Streamwater in Catchments Using Environmental Tracers
This paper introduces a framework to systematically assess the "critical age" in water transit time distributions (TTDs), which defines the maximum water age reliably identifiable by tracers. It demonstrates that the critical age is often significantly lower than previously assumed, typically below 1 year for stable isotopes and rarely exceeding 5–6 years for tritium in streamflow dominated by younger waters.
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Fiorese et al. (2025) Understanding the influence of Malta litho‐structural features on the dynamics of nitrate transport in the vadose zone
This study evaluates and compares the performance of the ISBA land surface model and the mHM hydrological model in simulating river discharge across 560 basins in France. The results demonstrate that mHM significantly outperforms ISBA in discharge simulation accuracy, while ISBA provides a more comprehensive representation of surface energy balance.
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Vernier et al. (2025) A Soil–Plant–Atmosphere Continuum model coupled to CFD to simulate plant energy and water exchanges in heterogeneous microclimates
This study developed and validated a Soil–Plant–Atmosphere Continuum (SPAC) model coupled with Computational Fluid Dynamics (CFD) to simulate plant energy and water exchanges in heterogeneous microclimates. The coupled model accurately assesses energy exchanges with a relative error less than 20% and successfully predicts soil water content evolution over several days, demonstrating its utility for agrivoltaic, agroforestry, and urban environments.
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Zhang et al. (2025) A generalized Complementary Principle (GCP) Model With Atmospheric Stability Correction for Estimating Sub‐Daily Evaporation
This study tested the validity of the Generalized Complementary Principle (GCP) for estimating land surface evaporation at sub-daily timescales, finding it to be accurate when combined with Monin-Obukhov similarity theory and atmospheric stability corrections.
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Barrientos et al. (2025) Dynamic Water Storage Response During Meteorological Droughts in South‐Central Chile
This study investigates the spatiotemporal patterns of dynamic water storage during 13 extreme drought events across 43 watersheds in south-central Chile (1980–2020), revealing its rapid response to precipitation and decline during dry periods, with lower storage maxima linked to drier conditions and specific catchment characteristics.
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Gupta et al. (2025) Finetuning AI Foundation Models to Develop Subgrid‐Scale Parameterizations: A Case Study on Atmospheric Gravity Waves
This study introduces a novel approach to developing machine learning parameterizations for small-scale climate processes by fine-tuning a pre-trained AI foundation model, demonstrating its superior performance in capturing atmospheric gravity wave effects for coarse-resolution climate models.
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Ye et al. (2025) Quadratic Response and Adaption of Vegetation Growth to Hydrological Drought in Heterogeneous Lake Floodplain Wetlands
This study investigated the response of wetland vegetation growth to hydrological drought in China's Poyang Lake floodplain from 2000 to 2023, revealing a quadratic relationship between vegetation growth (EVI) and hydrological drought (SIAI) with significant time-lag and cumulative effects.
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Yi et al. (2025) Flood changes and generating mechanisms in the Upper Rhine Basin under a warming climate
This study simulates runoff in the Upper Rhine Basin (URB) using the SPHY model to analyze flood characteristics and their underlying mechanisms from 1960 to 2019. It finds a general trend of increasing flood peaks and prolonged durations, primarily driven by rising temperatures altering hydroclimatology and enhancing snowmelt-driven runoff, especially for snowmelt-dominated events.
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Manteaux et al. (2025) Evaluation of SWAT‐RIVE's Ability to Represent the Hydrobiogeochemical Dynamics in the Vienne Watershed
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Patidar et al. (2025) Integrating Field Observations, Remote Sensing and Modelling for the Assessment of Bhilangana Lake, Central Himalaya, India
This study investigates the evolution of Bhilangana Lake and associated glacier changes in the Himalaya from 1968 to 2025, revealing significant lake expansion driven by rising temperatures and quantifying the high risk of a Glacial Lake Outburst Flood (GLOF) with substantial downstream impacts.
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Yan et al. (2025) Observational Evidences in the Effects of Large‐Scale Reforestation on Precipitation
This study statistically tests the effects of large-scale reforestation on downwind precipitation using observational data from China's Loess Plateau. It reveals a significantly positive relationship between increased vegetation cover (LAI) and regional precipitation during the growing season, providing observational evidence for this effect.
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Bernard et al. (2025) Process‐Level Evaluation of the Land‐Atmosphere Interactions Within CNRM‐CM6‐1 Single‐Column Model Configuration
## Identification - **Journal:** Journal of Advances in Modeling Earth Systems - **Year:** 2025...
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Li et al. (2025) Modeling Land Subsidence Under Future Water Stress: The Influence of Groundwater Exploitation, Climate Change, and Inter‐Basin Water Diversion
This study develops a coupled groundwater flow and land subsidence model to explore the co-evolution of groundwater levels and land subsidence in a key city along China's South-to-North Water Diversion route under future scenarios. It finds that future changes in groundwater levels and subsidence are primarily driven by water demand and diversion strategies, with climate change having a minor effect, and demonstrates that optimized water management can lead to significant subsidence recovery.
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Lee et al. (2025) Future variability in groundwater-surface water interactions: Implications for streamflow and its components using SWAT-MODFLOW 6 and CMIP 6 projections
This study investigates the future variability of groundwater-surface water interactions and their implications for streamflow and its components under climate change using integrated hydrological and climate models. Projections indicate an increase in average streamflow, a decrease in the baseflow index due to intensified surface runoff, and a higher probability of flooding under the SSP 5–8.5 scenario.
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Lee et al. (2025) Large‐Scale Drought Forecasting in the U.S. Southern Plains Through a Hybrid Cluster‐Based Wavelet‐Machine Learning Approach
This study developed a novel hybrid clustering-based machine learning approach, combining Discrete Wavelet Transform (DWT) and Multilayer Perceptrons (MLPs), to forecast the gridded Standardized Precipitation-Evapotranspiration Index (SPEI) across the U.S. Southern Plains, demonstrating effective capture of drought spatial variability for early warning systems.
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McEachran et al. (2025) Knowledge‐Guided Machine Learning for Operational Flood Forecasting
This study introduces a Factorized Hierarchical Neural Network (FHNN), a knowledge-guided machine learning framework for operational hydrologic forecasting at the catchment scale. The FHNN demonstrates superior streamflow prediction performance compared to expert human forecasters after the initial 12–18 hours, laying groundwork for AI-human collaboration in river forecasting.
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Wang et al. (2025) Seasonal divergence in the sensitivity of carbon and water fluxes to climate variability in terrestrial ecosystems
This study quantifies the seasonal sensitivity of daily carbon and water fluxes (GPP, RE, NEP, ET) to hydroclimate factors across diverse biomes globally using eddy covariance observations and Earth System Models (ESMs). It reveals significant seasonal variations in these sensitivities, identifying dominant climate drivers for different fluxes in different seasons and an increasing water limitation for summer GPP.
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Muñoz‐Vega et al. (2025) Influence of Hydraulic Conductivity Conceptualization and Unsaturated Flow Parameters for an Integrated Hydrological Model
This study investigates the sensitivity of integrated hydrologic model outputs to subsurface parameters, particularly hydraulic conductivity and van Genuchten parameters, in a headwater catchment. It finds that these parameters significantly influence streamflow, baseflow, peak flows, and soil moisture dynamics, especially during dry periods, providing crucial insights for model calibration.
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Aguayo et al. (2025) Hybrid Glacio‐Hydrological Modeling Reveals Contrasting Runoff Changes in Western Patagonia Over the 21st Century
This study develops a novel hybrid modeling framework combining LSTM neural networks with ice-dynamical glacier modeling (OGGM) to simulate historical glacio-hydrology and project climate change impacts on freshwater resources across 2,236 catchments in Western Patagonia. The framework outperforms other models and projects significant runoff reductions in northern Western Patagonia, while southern glacierized basins are projected to experience runoff increases under a high-emission scenario.
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Lin et al. (2025) Quantifying the Lifespan of 3D Flood Structures: Unlocking the Potential of Flood Detention Areas for Enhanced Flood Control in China
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Zhang et al. (2025) Thermodynamic and dynamic features of summer extreme heat events in the southwestern region of the Mongolian Plateau
This study investigates the thermodynamic and dynamic mechanisms of summer extreme heat waves in the southwestern Mongolian Plateau using JRA-55 reanalysis data, revealing a unique vertically tilted anticyclonic anomaly structure with dual-stratified wave activity peaks and distinct layer-specific heating pathways compared to Eastern China.
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Saavedra et al. (2025) From Soil Moisture Spatial Patterns to Catchment Nitrate Dynamics Using Explainable AI
This study developed a multi-branch Deep Learning framework, leveraging high-resolution satellite soil moisture data, to predict daily nitrate concentrations in streams across eight US catchments. The model successfully represents nitrate dynamics, demonstrating that spatial patterns of soil moisture are significant predictors and identifying near-stream hotspots as critical areas for nitrate export.
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Wu et al. (2025) Graph Fourier Deep Learning for Spatiotemporal and Hydrogeological Interpretation of Groundwater Levels in the Yellow River Basin
This study proposes a novel Graph Fourier Network (GFN) model that integrates hydrogeological prior information for regional groundwater level prediction. The GFN model significantly outperforms baseline models, achieving high accuracy and enhanced extrapolation capability for lead times up to 25 days, effectively capturing the complex dynamics of groundwater systems.
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Raghuvanshi et al. (2025) Complex network reveals propagation and moisture dynamics of Indian monsoon precipitation extremes
This study applies a complex network framework with nonlinear synchronization metrics to analyze the spatiotemporal organization, propagation, and drivers of extreme precipitation events (EPEs) during the Indian Summer Monsoon. It reveals distinct spatial communities influenced by synoptic systems and orography, identifying vertically integrated moisture convergence as the dominant driver of widespread EPEs, with the east coast and Bay of Bengal as major moisture sources and central and western India as primary sink zones.
