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Liu et al. (2025) Unrevealing site-dependent relationship between solar-induced chlorophyll fluorescence and gross primary productivity using the terrestrial ecosystem carbon cycle simulator
This study developed TECs-SIF, a terrestrial biosphere model integrating a radiative transfer module, to simultaneously simulate canopy solar-induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP) and investigate their relationship across forest ecosystems. The model accurately simulates SIF and GPP across various temporal scales, revealing that the SIF-GPP relationship is site-dependent and influenced by canopy structure and leaf traits.
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Liu et al. (2025) Strong Contributions of Abnormal Vortex Street-Like System in the Tibetan Plateau’s Wake to Record-Breaking Strong Rainfall over Southern China in April 2024
This study investigates the unprecedented heavy rainfall in southern China in April 2024, revealing that an abnormally strong Tibetan Plateau vortex street-like system (TPVSL), driven by an extreme north-south temperature gradient linked to a preceding El Niño, provided a favorable background for approximately 78% of the precipitation.
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Zhao et al. (2025) Regional Variations in Drivers of Extreme Reference Evapotranspiration Across the Contiguous United States
This study investigates the regional contributions of meteorological drivers to extreme reference evapotranspiration across the Contiguous United States (CONUS), revealing distinct spatial patterns where different atmospheric variables dominate extreme events.
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Heyblom et al. (2025) Global Moisture Cycling Rate an Important Control on Regional-Mean Precipitation under Warming
This study proposes an updated framework explaining regional precipitation change under climate forcing through three additive drivers, finding that the global moisture cycling rate robustly accounts for key spatial patterns like "wet-get-wetter, dry-get-drier" across various Earth system models.
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Tiwari et al. (2025) Underestimation of Historical Terrestrial Water Storage Droughts in Global Water Models
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Abbasizadeh et al. (2025) Can causal discovery lead to a more robust prediction model for runoff signatures?
This study investigates whether incorporating causal relationships between catchment attributes, climate indices, and runoff signatures can lead to more robust and interpretable prediction models. The findings indicate that models trained on causally identified parent variables, particularly Bayesian Networks and Generalized Additive Models, demonstrate enhanced robustness and parsimony across diverse environments compared to models using all available predictors.
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Harrison et al. (2025) Will landscape responses reduce glacier sensitivity to climate change in High Mountain Asia?
This paper proposes an alternative "Paraglacial Transition Model" for glacier evolution in High Mountain Asia (HMA), where increasing rock debris cover transforms glaciers into rock glaciers and other ice debris landforms, potentially prolonging ice persistence and reducing their sensitivity to climate warming, in contrast to conventional models predicting significant ice loss.
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Nie et al. (2025) Divergent Impacts of Precipitation Regimes on Autumn Phenology in the Northern Hemisphere Mid‐ to High‐Latitudes
This study investigated the impacts of total precipitation and precipitation frequency on the end of the vegetation growing season (EOS) across the mid- to high-latitudes of the Northern Hemisphere. It found that both increased total precipitation and decreased precipitation frequency delayed EOS, and developed an improved process-based autumn phenology model by incorporating precipitation frequency.
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He et al. (2025) Response of Mixed‐Phase Cloud Microphysics to Aerosol Perturbations at the Contrasting Sites of Limassol, Cyprus, and Punta Arenas, Chile
This study investigates the microphysical response of mixed-phase clouds to contrasting aerosol conditions at Limassol, Cyprus (dust-influenced) and Punta Arenas, Chile (continental/marine), finding that ice crystal number concentrations directly correlate with the availability and type of ice-nucleating particles.
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Eccles et al. (2025) High-resolution downscaled CMIP6 drought projections for Australia
This study investigates the impacts of climate change on meteorological droughts across Australia using a high-resolution ensemble of downscaled CMIP6 climate models under three Shared Socioeconomic Pathway (SSP) scenarios. It projects consistent increases in drought frequency, duration, spatial extent, and percent time in drought, particularly for southern Australia and when considering evapotranspiration, indicating a significant shift towards more extreme climatic conditions under higher emissions.
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Suriano et al. (2025) Temporal trends and large-scale atmospheric and oceanic forcings of central U.S. snowfall producing weather systems, 1948–2021
This study investigates the temporal trends and large-scale atmospheric and oceanic forcings of snowfall-producing weather systems in the central U.S. from 1948 to 2021, revealing significant changes in synoptic weather type frequencies, inherent meteorological characteristics, and their links to teleconnection indices.
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Fallah et al. (2025) The Impact of CO 2 ‐Driven Vegetation Changes on the Future of Flash Drought in the Northern Hemisphere
## Identification - **Journal:** Journal of Geophysical Research Atmospheres - **Year:** 2025...
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Getirana et al. (2025) Inconsistencies in GRACE‐Based Groundwater Storage Estimation—A Call for a Proper Use of Land Surface Models
This comment critically examines the common practice of estimating groundwater storage anomalies by subtracting land surface model components from GRACE terrestrial water storage, highlighting implicit assumptions and structural challenges due to model simplifications. It advocates for careful interpretation and more sophisticated methods in hydrological analyses.
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Sharma et al. (2025) Comparative Analysis of Machine Learning Methods for Imputing Missing Daily Rainfall Data in Complex Himalayan Terrain
This study evaluated seven machine learning methods for imputing missing daily rainfall data across different elevations and agro-climatic zones in Himachal Pradesh, India, finding that Multilayer Perceptron (MLP) consistently demonstrated the highest accuracy and lowest estimation errors.
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Campos et al. (2025) Regional Aspects of Observed Temperature and Precipitation Trends in the Western Mediterranean: Insights From a Timescale Decomposition Analysis
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Gebresellase et al. (2025) Projected impacts of climate and land use changes on streamflow extremes in the upper awash Basin, Ethiopia
This study investigated the projected impacts of climate and land use/land cover (LULC) changes on streamflow extremes in the Upper Awash Basin, Ethiopia. It found that climate change is the dominant driver, significantly increasing high-flow extremes and decreasing low-flow extremes, while LULC changes had statistically non-significant effects.
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Wang et al. (2025) Gross primary productivity is more sensitive to droughts than to heatwaves in China
This study investigated the response of Gross Primary Productivity (GPP) to droughts and heatwaves across different climate zones and vegetation types in China from 1950 to 2020 using the SEIB-DGVM model, revealing that GPP is generally more sensitive to droughts than to heatwaves, with significant spatial variations influenced by precipitation gradients.
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Eltahir et al. (2025) A Theory on Regional Impacts of Global Warming
This paper proposes a theory explaining how relatively uniform global warming can lead to significantly diverse regional impacts by considering how local background temperatures interact nonlinearly with temperature thresholds governing natural phenomena.
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Kruskopf et al. (2025) ClimateServ: An open source earth observation climate data access tool
This paper introduces ClimateSERV, an open-source web application and API developed by the SERVIR program, designed to lower barriers for users to visualize, analyze, and download curated Earth observation climate data for water and food security applications. It details the system's architecture, performance, and usage, including a case study demonstrating its utility in drought monitoring in Southeast Asia.
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Lorente-Ramos et al. (2025) Accurate calibration of hydrological models with evolutionary computation multi-method ensembles
This study introduces the Dynamic Probabilistic Coral Reefs Optimization algorithm with Substrate Layer (DPCRO-SL) to enhance hydrological model calibration. Applied to the *abcd* model in two Spanish river basins, DPCRO-SL consistently outperformed the benchmark SCE-UA algorithm, demonstrating superior accuracy and reliability, particularly in test scenarios reflecting future projections.
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Barbaux et al. (2025) Integrating non-stationarity and uncertainty in design life levels based on climatological time series
This study develops a novel method to infer design life levels for extreme events under non-stationary climate conditions, integrating both non-stationarity and uncertainty. It introduces the Predictive Equivalent Reliability (PER) level, a single, interpretable indicator that accounts for stochastic and estimation uncertainties, demonstrating its utility for robust risk assessment in a changing climate.
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Liu et al. (2025) Corrigendum to “Quantifying the effects of irrigation schedule on groundwater level variability using a linked APSIM-MODFLOW model framework” [Agric. Water Manag. 316, 2025, 109610]
This study aimed to quantify the effects of various irrigation schedules on groundwater level variability by employing a linked crop simulation and hydrological modeling framework.
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Guo et al. (2025) Incorporation alfalfa with annual forage enhances even water use and maintains forage yield resilience in a semiarid region
This study investigated whether intercropping alfalfa with annual forage crops could improve soil water distribution and maintain forage yield resilience in a semiarid region. Findings show that intercropping significantly enhanced soil water content, water productivity, and overall yield advantage, particularly with alfalfa-maize combinations, offering a feasible solution for efficient water management.
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Ishikawa et al. (2025) Evaluation of a Width‐Based Satellite Discharge Algorithm for Detecting Longitudinal Flow Changes in a Human‐Regulated Continental River Basin
This study investigated the capabilities and limitations of estimating spatially continuous river discharge using satellite-observed river width and the AMHG-based algorithm (BAM) along the Yellow River. It found that the method can reproduce spatial discharge patterns, with improved accuracy using irrigation-corrected prior discharge, but faces significant challenges in levee-confined reaches.
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Feng et al. (2025) Disentangling atmospheric, hydrological, and coupling uncertainties in compound flood modeling within a coupled Earth system model
This study leverages the Energy Exascale Earth System Model (E3SM) with multi-component coupling to disentangle atmospheric, hydrological, and coupling uncertainties in compound riverine and coastal flood modeling. It demonstrates the critical role of two-way river-ocean coupling and antecedent soil moisture conditions in amplifying flood impacts, advocating for a broader definition of compound flooding.
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Kupzig et al. (2025) A controlled model experiment for the global hydrological model WaterGAP3: Understanding recent and new advances in the model structure
This study conducts a controlled model experiment on the global hydrological model WaterGAP3 to evaluate if increased model complexity in river routing, reservoir algorithms, and snow on wetlands leads to better process representation. It finds that volume-dependent river routing generally worsens performance, while reservoir algorithms and snow on wetlands show benefits but require further development.
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Yu et al. (2025) A Novel Quality Control Framework for Long‐Term Hourly Sunshine Duration Data in China
This study develops a systematic four-step quality control framework to enhance the reliability of historical hourly sunshine duration data across China from 1951 to 2023, effectively identifying and flagging significant data errors linked to historical digitization limitations and improving data quality for solar energy and climate studies.
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Prakash et al. (2025) An integrated assessment of hydro-meteorological extremes and water scarcity in a mountainous river catchment under climate change
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Quispe (2025) Modélisation intégrée du bilan hydrique du lac Titicaca : un cadre pour identifier les facteurs de variabilité et atténuer les risques de sécheresses et d’inondations
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Naeem et al. (2025) Simulating and predicting lake dynamics by fusing HBV modeling, machine learning approach and remote sensing data
This study comprehensively analyzes historical (1990-2023) and projected (up to 2060) hydrological dynamics and land use changes in the Hongjiannao Lake Basin by integrating HBV modeling, Random Forest, CA-Markov, and remote sensing, revealing significant lake area fluctuations and predicting future increases despite ongoing pressures.
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Yu et al. (2025) Cross-scale soil moisture content monitoring of winter wheat by integrating UAV and sentinel-1/2 data
This study developed an innovative framework integrating ground, UAV, and satellite data to accurately estimate and map soil moisture content (SMC) in winter wheat fields across scales, demonstrating significantly improved accuracy compared to traditional ground-satellite models.
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Qing et al. (2025) Delayed formation of Arctic snow cover in response to wildland fires in a warming climate
This study reveals that from 1982 to 2018, Arctic wildland fires significantly increased, causing a substantial delay in snow cover formation primarily due to fire-induced albedo reduction and temperature increases. Projections under a high-emissions scenario indicate a 2.6-fold increase in burned area and an 18-day decrease in annual mean snow cover duration by 2100.
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Hasan et al. (2025) Satellite data and physics-constrained machine learning for estimating effective precipitation in the Western United States and application for monitoring groundwater irrigation
This study developed a physics-constrained machine learning framework to accurately estimate effective precipitation for irrigated croplands in the Western United States at a spatial resolution of approximately 2 kilometers and a monthly temporal scale from 2000 to 2020. The framework's effective precipitation estimates were successfully integrated into a water balance model to monitor groundwater irrigation, showing good skill with an R² of 0.78 and a PBIAS of –15 % when compared to in-situ pumping records.
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Yu et al. (2025) Irrigated agriculture expansion drives groundwater storage decline in Black Soil Region of Northeast China
This study analyzed the spatiotemporal distribution and drivers of groundwater storage changes in the Black Soil Region of Northeast China using high-resolution GRACE data and a random forest model. It revealed a significant overall decline in groundwater storage, primarily driven by the expansion of irrigated agriculture, particularly in long-term trends.
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Beyá-Marshall et al. (2025) Water stress thresholds for walnuts: Stem water potential baselines to maximize yield and water productivity
This study established cultivar-specific midday stem water potential (Ψₓ) baselines and detrimental thresholds for 'Chandler' and 'Serr' walnuts, demonstrating that optimizing irrigation based on these baselines can improve water productivity by 20–25% while sustaining high yields under water-limited conditions.
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Zhang et al. (2025) Global optimization of a water-constrained two-leaf light use efficiency model through multi-biome FLUXNET observations
This study developed and globally optimized a water-constrained two-leaf light use efficiency (WTL-LUE) model using multi-biome FLUXNET observations to improve terrestrial gross primary productivity (GPP) estimation, particularly under water stress. The optimized WTL-LUE model significantly enhanced GPP simulation accuracy and stability across various ecosystems compared to existing LUE and machine learning models.
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Farokhzadeh et al. (2025) Drought Characteristics and Risks in Iran: A Four‐Dimensional Copula‐Based Approach Under Future Climate Scenario
This study investigated historical (1966–2019) and future (2020–2050) drought dynamics in Iran under the SSP2-4.5 scenario using SPI and copula models, revealing a general reduction in drought severity, duration, and magnitude but an increased likelihood of more frequent, less severe droughts and a moderate increase in severe drought probability for longer return periods.
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Folland et al. (2025) A Review of 25 Annual Forecasts of Global Mean Surface Temperature Including the Record Warm Years 2023 and 2024
This study evaluates the skill of real-time global mean surface temperature forecasts issued annually for 2000–2025, finding high skill in capturing interannual variability for 2000–2024, though the extreme 2023 warming was missed, while 2024's record warmth was better predicted, especially by dynamical models.
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Fu et al. (2025) Remote sensing-based monitoring of compound drought-waterlogging stress in groundwater-sensitive agroecosystems in arid regions
This study developed a remote sensing-based framework to monitor groundwater-driven compound drought-waterlogging stress in arid Groundwater-Sensitive Agroecosystems (GWSA) in Northwest China. By downscaling root-zone soil moisture data to 30 m resolution and employing novel indices, the research revealed significant spatial heterogeneity in stress patterns and identified groundwater level, precipitation, and temperature (via snowmelt) as key drivers, offering critical insights for agricultural resilience.
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Asmus et al. (2025) The Role of Horizontal Resolution in Modeling Irrigation Effects With a Coupled Regional Climate Model System Up To Convection‐Permitting Scale
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Chebbo (2025) Intégration de l’identité et de la diversité fonctionnelle dans un modèle de surface terrestre : une étude de la productivité et de la stabilité d’un écosystème dans un contexte de changement climatique
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Wang et al. (2025) Impacts of irrigation on hot extreme in the Yangtze River Basin using observed analysis and model simulation
This study investigates the impact of irrigation on hot extremes in the Yangtze River Basin using observational analysis and WRF model simulations, revealing that irrigation reduces extreme high temperatures by an average of 0.3 °C, with a maximum decrease of 1.4 °C, and identifies a threshold for cooling benefits at an irrigated area fraction of 0.3.
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Yang et al. (2025) Propagation dynamics of meteorological, agricultural, and vegetation droughts in China
This study quantified the propagation mechanisms of meteorological, agricultural, and vegetation droughts across China, revealing distinct propagation times and seasonal variations influenced by climate and vegetation types. The findings provide a scientific foundation for enhanced drought monitoring and early warning systems.
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Keel et al. (2025) Representing the Teleconnection Between the Jet Stream and Extreme Cold Air Outbreaks Over North America
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Gao et al. (2025) The exposure threat of wet heat extremes is substantially increasing to the 65+ elderly population in Asia
This study analyzes past trends (2001-2020) and projects future exposure (2030-2100) to wet heatwaves across Asia, particularly focusing on the elderly population. It finds a significant increase in wet heatwave days and projected exposure, with population growth contributing more than climate change to the heightened exposure.
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Devanand et al. (2025) The influence of lateral flow on land surface fluxes in southeast Australia varies with model resolution
Lateral flow significantly increases evapotranspiration near major river channels in high-resolution (1 and 4 km) land surface simulations in southeast Australia, consistent with observations. This inclusion reveals resolution-dependent spatial patterns, such as drier ridges at 1 km, which are crucial for improved drought and water availability modeling.
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Castillo et al. (2025) Evaluation of Monin‐Obukhov Similarity Theory Wind Profiles in Convective Storm Environments and Cold Pools at the ARM Southern Great Plains Atmospheric Observatory
This study evaluates the performance of Monin-Obukhov similarity theory (MOST) in fair-weather and convective storm environments using observational data, finding that MOST accurately predicts wind profiles in fair weather but systematically overestimates wind shear in cold pools following convective storms.
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Tang et al. (2025) Radiative–Convective Equilibrium over an Idealized Land Surface with Fixed Soil Moisture
This study uses theory and simulations to understand radiative-convective equilibrium (RCE) over idealized land surfaces with fixed soil moisture, a crucial step for land climate modeling. It finds that potential evapotranspiration primarily scales with surface net radiation, implying only modest increases in global mean aridity with warming, contrary to some prior predictions.
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Suri et al. (2025) Optimal Rain Gauge Network: A Data‐Driven Design for Enhanced Precision in Rainfall Measurements Over Northwest Himalayas
## Identification - **Journal:** International Journal of Climatology - **Year:** 2025...
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Zhang et al. (2025) Land use and economic development influenced the hotspots of groundwater storage gains and losses in mainland China in the past 20 years
This study identifies groundwater storage change hotspots across mainland China over the past two decades using GRACE/GRACE-FO satellite data. It reveals that land use and economic factors are the primary drivers of these changes, with their influence varying geographically.
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Schmidt et al. (2025) Analysis of the Meso‐Scale Climate of the Galápagos Archipelago by Dynamical Downscaling of Reanalysis Data
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Zeng et al. (2025) The Spatial Patterns and Trends of Sensible and Latent Heat Fluxes in the Northern Drought‐Prone Belt of China
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Hui et al. (2025) Refine Extreme Hot Day Predictions With the Sea Surface Temperature Tendency
This study investigates the underlying mechanisms influencing extreme hot days over Western North America (WEHDs) and aims to improve their seasonal prediction, revealing that two independent sea surface temperature (SST) precursor signals enable robust and enhanced prediction using a physics-informed convolutional neural network.
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Shi et al. (2025) Improving runoff simulation in cold alpine regions based on VIC-glacier by combining LSTM error correction technology
This study developed and optimized a coupled Variable Infiltration Capacity-Glacier (VIC-glacier) model for the upper Hotan River Basin, demonstrating that integrating Long Short-Term Memory (LSTM) error correction significantly enhances runoff simulation accuracy in cold alpine regions.
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Mondal et al. (2025) Hot Drought of Summer 2023 in Southwestern North America
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Struglia et al. (2025) Impact of spatial resolution on multi-scenario WRF-ARW simulations driven by the CMIP6 MPI-ESM1-2-HR global model: a focus on precipitation distribution over Italy
This study dynamically downscales CMIP6 global climate projections over Italy and the Mediterranean to 5 km resolution, demonstrating the added value of high resolution for precipitation, and projects a general warming, mean precipitation reduction over the Mediterranean, and a strong increase in extreme precipitation intensity over the Italian Peninsula by 2100, especially under SSP5-8.5.
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Bruno et al. (2025) Imprints of increases in evapotranspiration on decreases in streamflow during dry periods, a large-sample analysis in Germany
This study quantifies the impact of increased evapotranspiration on decreased summer low flows and altered precipitation-streamflow relationships during dry periods in 363 small German catchments from 1970 to 2019, finding that increased evapotranspiration is a significant driver, particularly in more arid regions.
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Jesse et al. (2025) Sub-shelf melt pattern and ice sheet mass loss governed by meltwater flow below ice shelves
This study presents a novel coupled ice sheet–sub-shelf melt model (IMAU-ICE/LADDIE) to resolve 2D horizontal meltwater flow and compares its impact on Antarctic ice sheet evolution against traditional melt parameterizations. The findings reveal that resolving 2D meltwater flow introduces critical feedbacks, particularly along shear margins, leading to distinct transient volume loss and sensitivity to ocean warming not captured by simpler parameterizations.
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Mazzolini et al. (2025) Spatio-temporal snow data assimilation with the ICESat-2 laser altimeter
This study presents a novel spatio-temporal data assimilation framework to integrate sparse ICESat-2 laser altimeter snow depth profiles with Sentinel-2 fractional snow-covered area (fSCA) observations into a snow model. It demonstrates that jointly assimilating both data types significantly improves the accuracy and spatial distribution of simulated snow depth, particularly during the accumulation season, compared to using fSCA alone.
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Chalmers et al. (2025) Defining the Agricultural Wet Season in Africa Using Soil Moisture From the Soil Moisture Active‐Passive Satellite
This study estimates root-zone soil moisture across Africa using SMAP satellite data from 2016 to 2023 to redefine the wet season, finding that soil moisture timing correlates more strongly with vegetation timing than precipitation in African croplands and better captures early season rainfall events.
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Hannaford et al. (2025) Have river flow droughts become more severe? A review of the evidence from the UK – a data-rich, temperate environment
This extended review assesses whether river flow droughts in the UK have become more severe, synthesizing existing literature and conducting new analyses. The study finds little compelling evidence of worsening hydrological droughts in the UK, a finding that appears to contradict near-future climate projections and common assumptions about human impacts.
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Laan et al. (2025) Decadal re-forecasts of glacier climatic mass balance
This study presents the first application of decadal re-forecasts to simulate global glacier climatic mass balance, bridging the gap between seasonal forecasts and long-term projections. It demonstrates that forcing the Open Global Glacier Model (OGGM) with decadal re-forecasts generally outperforms persistence forecasts and historical General Circulation Model (GCM) simulations for multi-annual glacier mass balance, offering moderate improvements for near-term predictions.
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Thakur et al. (2025) Unveiling the impact of potential evapotranspiration method selection on trends in hydrological cycle components across Europe
This study evaluates the impact of selecting different potential evapotranspiration (PET) methods on trends in actual evapotranspiration (AET), runoff (Q), and total water storage (TWS) across 553 European catchments. It finds that annual and seasonal trends are variably sensitive to the PET method choice, depending on the hydrological component and catchment type, underscoring the importance of careful method selection for robust hydrological assessments.
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Bellat et al. (2025) Soil information and soil property maps for the Kurdistan region, Dohuk governorate (Iraq)
This study provides the first detailed, high-resolution (30 m) soil property and depth maps for the Dohuk governorate, Kurdistan Region of Iraq, outperforming global models and offering crucial data for local land management in a data-poor, arid/semi-arid environment.
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Kulkarni et al. (2025) Global assessment of socio-economic drought events at the subnational scale: a comparative analysis of combined versus single drought indicators
This study globally assesses socio-economic drought events at the subnational scale by comparing a novel combined drought indicator (CDI) with single-parameter indices, finding that CDI significantly outperforms individual indices in identifying GDIS-documented socio-economic drought impacts.
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Li et al. (2025) Generative Downscaling and Bias Correction of Multivariable Earth System Model Simulations
This study introduces a multivariate generative downscaling model (MVGDM) to simultaneously downscale global climate simulations from 100 km to 25 km resolution and correct inherent biases, significantly improving the simulation of key climate variables, phenomena like ENSO and IOD, and climate extremes.
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Kraulich et al. (2025) The impact of aerosol forcing on the statistical attribution of heatwaves
This study demonstrates that the standard statistical method for attributing heatwaves, which relies solely on global mean temperature, produces significant biases in regions with strong aerosol trends. Incorporating regional aerosol optical depth as an additional covariate in the Generalized Extreme Value distribution model substantially reduces these biases and improves heatwave return period estimates.
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Deleuze (2025) Nonlinear internal gravity wave modes and settling particles in stratified fluids : two pathways to mixing
This study experimentally investigates energy transfer and diapycnal mixing in stratified fluids, focusing on internal gravity waves and particle sedimentation. It reveals complex non-linear wave dynamics, including resonant triadic instability and a feedback loop between wave evolution and background stratification, alongside quantifying mixing induced by sedimenting particle clouds.
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Zhang et al. (2025) Applicability of a Sine–Random Forest Hybrid Method for meteorological and energy variables
This study proposes a Sine-Random Forest Hybrid Method to reduce bias and enhance the accuracy of meteorological and energy variables in reanalysis datasets, demonstrating its effectiveness in improving agreement with measured data and capturing diurnal patterns.
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Quang et al. (2025) Future Intensity‐Duration‐Frequency Curves of Extreme Precipitation in the Midwest United States From Convection‐Permitting Modeling
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Strijker et al. (2025) The dynamics of peak head responses at Dutch canal dikes and the impact of climate change
This study investigated the dynamics of peak hydraulic heads in Dutch canal dikes at a national scale using non-linear time series models calibrated on extensive observation data. It found that climate change will significantly alter the frequency of extreme peak heads, with projections indicating occurrences between 3 times less and 8 times more frequently by 2100, depending on the climate scenario and dike characteristics.
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Cooper et al. (2025) Greenland ice sheet runoff reduced by meltwater refreezing in bare ice
This study combines field measurements and numerical modeling to demonstrate that extensive meltwater retention and refreezing occur in bare glacier ice, significantly reducing runoff from the Greenland Ice Sheet's ablation zone. This overlooked process explains why current climate models overestimate runoff by 9–15% in southwest Greenland, impacting sea-level rise projections.
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Yang et al. (2025) Improving Weeks 1–2 Temperature Forecasts in the Sierra Nevada Region Using Analog Ensemble Postprocessing with Implications for Better Prediction of Snowmelt, Water Storage, and Streamflow
This study applies analog ensemble (AnEn) postprocessing to improve subseasonal 2-meter temperature (T2m) forecasts in the Sierra Nevada during the spring snowmelt season, demonstrating significant accuracy enhancements, particularly at higher elevations, compared to dynamical benchmarks and basic bias correction methods.
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Verjans et al. (2025) The Greenland Ice Sheet Large Ensemble (GrISLENS): simulating the future of Greenland under climate variability
This study introduces GrISLENS, the first large-ensemble ice sheet model resolving individual glaciers and calibrated to observations, to quantify the impact of internal climate variability on Greenland Ice Sheet evolution. It finds that internal climate variability significantly contributes to ice sheet mass change uncertainty on decadal timescales, but its relative importance diminishes on longer timescales compared to anthropogenic forcing.
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Peng et al. (2025) Spatiotemporal Reconstruction of Annual Glacier Mass Balance in Central Asia (2000–2020) Using Machine Learning
This study reconstructs annual glacier-wide mass balance for glaciers in the Tien Shan and Pamir from 2000 to 2020 using machine learning, revealing an average mass loss of -0.39 meters water equivalent per year with significant spatiotemporal variability and accelerated loss for smaller glaciers.
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Parisouj et al. (2025) Hourly streamflow forecasting across diverse climate zones on Oʻahu Island, Hawaiʻi
This study proposes a novel hybrid Honey Badger Algorithm-optimized Multilayer Perceptron (HBA–MLP) model for hourly streamflow forecasting across diverse climate zones on Oʻahu Island, Hawaiʻi, demonstrating exceptional performance in arid and semi-arid zones while identifying challenges in subhumid regions.
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Su et al. (2025) Space-time deep hybrid boosting learning for investigating day-night hourly seamless air temperature distribution from FY-4A over China
This study developed a Space-Time Deep Hybrid Boosting (ST-DHB) model to generate day-night hourly seamless 0.04-degree air temperature (Ta) distributions across China from Fengyun-4A data, achieving high accuracy (R² > 0.94, RMSE < 2.6 °C) and outperforming existing methods. The resulting Ta data reveals significant geographical, seasonal, and diurnal disparities in heatwave exposure, particularly in urban and farmland areas.
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Elenius et al. (2025) Where can rewetting of forested peatland reduce extreme flows? Model experiment on the hydrology of Sweden
This study used a national hydrological model to investigate the impact of rewetting drained forested peatlands in Sweden on extreme water flows. It found that rewetting has a negligible effect on extreme flows in larger catchments (≥10 km²), but can significantly alter local runoff and groundwater levels in small streams draining only peatlands, with effects depending on pre-rewetting conditions and tree cover reduction.
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Zhou et al. (2025) Neglecting land–atmosphere feedbacks overestimates climate-driven increases in evapotranspiration
This study develops a theoretical framework to disentangle land-atmosphere interactions, achieving consistent evapotranspiration (ET) projections between offline and coupled models. It reveals that neglecting these feedbacks leads to a 25–39% overestimation of climate-driven global ET increases and a 77–121% exaggeration of negative land surface contributions, causing significant discrepancies in hydrological projections.
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Idhirij et al. (2025) Water management innovations for adapting to climate water stress: new evidence from the American Southwest
This study developed and applied a basin-scale hydroeconomic optimization model to evaluate the economic outcomes of different water shortage sharing institutions in a drought-prone watershed of the American Southwest. The findings indicate that market-based water trading institutions significantly outperform proportional allocation in minimizing income losses and reallocating water to higher-value uses during periods of water scarcity.
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Liberty-Levi et al. (2025) The Role of Ocean Processes in Future Northern Hemisphere Midlatitude Winter Precipitation Changes
This study quantifies the relative roles of dynamic and thermodynamic ocean processes in the projected intensification of Northern Hemisphere midlatitude winter net precipitation, finding that thermodynamic processes dominate over land and the Pacific, while dynamic processes are key over the Atlantic.
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Yang et al. (2025) Characteristics, prediction model and driving mechanism of multidimensional daily scale propagation from meteorological to agricultural drought in Guangxi, China
This study investigated the daily propagation characteristics, developed a prediction model, and elucidated the driving mechanisms of meteorological drought to agricultural drought in Guangxi, China, revealing distinct seasonality, time-lag effects (average 10.4 days), and scaling effects, primarily driven by precipitation and potential evapotranspiration.
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Varotsos et al. (2025) CLIMADAT-GRid: a high-resolution daily gridded precipitation and temperature dataset for Greece
This study introduces CLIMADAT-GRid, the first publicly available high-resolution (1 km × 1 km) daily gridded dataset for air temperature and precipitation across Greece for 1981–2019, demonstrating superior spatial performance and closer agreement with observational data compared to global products like CHELSA-W5E5.
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Qi et al. (2025) Global Increase of Tropical Cyclone Precipitation Rate Toward Coasts
This study investigates the global coastward trends of tropical cyclone (TC)-induced precipitation changes over the past four decades, revealing a statistically significant landward migration of TC lifetime maximum precipitation intensities and faster growth in coastal areas linked to a warming-humidifying environment.
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Xia et al. (2025) Quantification of Critical Thresholds in Soil Moisture and the Leaf Area Index Regulating Aeolian Dust Events: A Sensitivity Analysis of the Response of Aeolian Dust Events to Wind Velocity Variations
This study develops an empirical methodology using long-term satellite observations to assess the global sensitivity of aeolian dust events to wind velocity variations. It quantifies this sensitivity and identifies critical soil moisture and leaf area index thresholds that constrain dust emissions, projecting future changes in constrained dust events under various climate scenarios.
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Hu et al. (2025) Investigating Aerosol Hygroscopicity in the Subcloud Transition Zone and at the Surface in the Southern Great Plains
This study investigates the hygroscopicity and optical properties of aerosols in the subcloud transition zone (SCTZ) and at ground level in the Southern Great Plains, revealing distinct seasonal variations driven by aerosol composition at the surface and cloud fragmentation effects within the SCTZ.
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Yue et al. (2025) Watershed sediment cascades across multiple timescales: Causal relationships with hydroclimate and underlying surface attributes
This study investigated watershed sediment dynamics and their causal relationships with hydroclimate and underlying surface factors across multiple timescales (event to decadal) in seven subtropical watersheds, revealing a shift in dominant controls from hydroclimate to surface properties at longer timescales.
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Gambini et al. (2025) Uncertainty Quantification and Spatial Biases Assessment in Precipitation Forecasts: A Methodology for Real-Time Flood Forecasting Applications
This study proposes a methodology to assess and account for spatial biases in high-resolution convective rainfall forecasts to improve flood predictions in small watersheds. It identifies a systematic 20 km northeastward displacement error in the MOLOCH model's forecasts for northern Italy and suggests using a derived displacement probability density function to generate rainfall ensembles for hydrological uncertainty quantification.
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Wang et al. (2025) Flood inundation mapping with CYGNSS over CONUS: a two-step machine-learning-based framework
This study developed a two-step machine learning framework using CYGNSS bistatic reflectance observations and ancillary data to retrieve daily fractional flood inundation at a 3-kilometer resolution across the contiguous United States, demonstrating comparable performance to SAR-based flood maps and other inundation products.
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Tao et al. (2025) Permafrost vulnerability to climate change: understanding thaw dynamics and climate feedback of permafrost degradation
This editorial synthesizes findings from 35 interdisciplinary studies to advance understanding of permafrost degradation dynamics and their cascading impacts, highlighting the critical importance of integrative, cross-disciplinary approaches.
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Karbi et al. (2025) Seasonally Asymmetric Projected Changes in Austral Atmospheric Waves
This study investigates the seasonally asymmetric response of Southern Hemisphere mid-latitude atmospheric waves to anthropogenic emissions, finding that scale-dependent changes (large-scale intensification in winter, small-scale weakening in summer) drive these differences, primarily due to seasonal variations in upper-level warming patterns.
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Chevuru et al. (2025) Relevance of feedbacks between water availability and crop systems using a coupled hydrological–crop growth model
This study quantifies the fine-grained spatiotemporal feedback between crop systems and hydrology using a coupled hydrological-crop growth model. It finds that two-way coupling, incorporating dynamic feedback of crop phenology, significantly improves performance for rainfed crops compared to one-way coupling, highlighting its necessity for capturing interannual climate variability impacts on food production.
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Persch et al. (2025) A Critical Role for North Pacific Meridional Mode in the ENSO Response to Orbital Precession
This study investigates how orbital precession influences El Niño–Southern Oscillation (ENSO) variability through the Pacific meridional mode (PMM) using climate model simulations. It finds that precession strongly modulates PMM variability, its effectiveness in triggering El Niño events, and ENSO diversity, primarily driven by changes in surface wind fields affecting the wind–evaporation–sea surface temperature (WES) feedback.
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Lin et al. (2025) Linking High‐Amplitude Quasi‐Stationary Waves With Concurrent Humid‐Heat Extremes in a Warming World
This study investigates how high-amplitude quasi-stationary waves (QSWs), linked to concurrent humid-heat extremes in the Northern Hemisphere midlatitudes, respond to climate warming. Using a large ensemble climate model, the research finds that the climatological-mean amplitude of wavenumbers 3 and 7 QSWs increases in late summer with warming, leading to more frequent high-amplitude events and consequently increased regional frequencies of humid-heat extremes.
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Zeng et al. (2025) Identification of Precipitating Marine Low‐Altitude Water Clouds by CALIPSO: Observations and Detections
This study uses CALIOP measurements to investigate microphysical and optical property changes in marine boundary layer clouds at cloud top during precipitation formation. It finds distinct lidar signatures that enable effective discrimination between precipitating and non-precipitating clouds, offering new insights into cloud life cycles and enhancing global light precipitation detection.
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Wilke et al. (2025) Hail events in Germany: rare or frequent natural hazards?
This study investigates hail characteristics across Germany using crowdsourced observations and C-band weather radar data to assess hail frequency, spatial distribution, and size variations. It reveals a north-south gradient in hail occurrence, with June being the peak month, and highlights the challenges and biases in human observations versus radar-derived estimates.
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Song et al. (2025) Physically Interpretable Emulation of a Moist Convecting Atmosphere With a Recurrent Neural Network
This study develops a recurrent neural network (RNN) for data-driven convective parameterization, combining linear and nonlinear components to predict temperature, moisture, and precipitation time series. The model demonstrates stable and realistic long-term emulation performance, revealing physically interpretable properties of convectively coupled gravity waves.
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Diop et al. (2025) Climate change impacts on floods in West Africa: new insight from two large-scale hydrological models
This study provides a large-scale analysis of flood frequency and magnitudes across West Africa using two hydrological models driven by CMIP6 climate models, projecting consistent increases in flood frequency and magnitude under future climate change scenarios.
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Lee et al. (2025) Multi-centennial climate change in a warming world beyond 2100
A new 10-member ensemble simulation with the state-of-the-art Earth system model was employed to study the long-term climate response to sustained greenhouse warming through to the year 2500. The findings show that the projected changes in the forced mean state and internal variability during 2101–2500 differ substantially from the 21st-century projections, emphasizing the importance of multi-century perspectives for understanding future climate change and informing effective mitigation strategies.
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Tsigaridis et al. (2025) ROCKE-3D 2.0: an updated general circulation model for simulating the climates of rocky planets
This paper presents ROCKE-3D version 2.0, an updated generalized three-dimensional general circulation model (GCM) designed for simulating the climates of rocky planets in both the Solar System and exoplanetary contexts. It details new physics, expanded configurations, and quantifies how different component choices affect model results, demonstrating its enhanced capabilities for diverse planetary conditions.
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Guo et al. (2025) Enhanced MODIS-derived ice physical properties within the Common Land Model (CoLM) revealing bare-ice–snow albedo feedback over Greenland
This study integrates an enhanced radiative transfer model (SNICAR-ADv4) and MODIS-derived bare-ice properties into the Common Land Model (CoLM) to investigate the impact of bare-ice metamorphism on the Greenland Ice Sheet's ablation zone. The research reveals a significant bare-ice–snow albedo feedback, where bare-ice darkening due to metamorphism reduces albedo, increases surface temperature, and accelerates snowmelt, further exposing bare ice and intensifying melt.
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Wood et al. (2025) Comparison of high-resolution climate reanalysis datasets for hydro-climatic impact studies
This study comprehensively evaluates four high-resolution climate reanalysis datasets (ERA5, ERA5-Land, CERRA, CHELSA-v2.1) against gridded observations over complex terrain in Switzerland for hydro-climatic impact studies. It concludes that CERRA generally offers the most reliable representation of precipitation, temperature, and snowfall metrics, including their variability and extreme events, making it highly suitable for a broad range of hydrological analyses, particularly in regions where snow processes and daily to inter-annual precipitation variability are crucial.
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Menapace et al. (2025) Sensors prioritisation for hydrological forecasting based on interpretable machine learning
This study proposes an interpretable machine learning framework to prioritise hydrological sensors, aiming to enhance short-term predictions. The research demonstrates that identifying and maintaining critical sensors significantly improves forecasting accuracy and reliability, offering a data-driven approach to optimise monitoring system maintenance.
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Yu et al. (2025) A nudging-based data assimilation method coupled with bidirectional gated neural networks for error correction
This study develops a novel nudging-based data assimilation method that integrates Bidirectional Gated Recurrent Units (BiGRU) with the Ensemble Kalman Filter (EnKF) to enhance accuracy and stability in error correction. Numerical experiments using the Lorenz-96 model demonstrate its improved resilience to noise interference and greater robustness with sparse observations.
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Lim et al. (2025) Remote Forcing and Prediction of the June 2023 Texas Heat Wave
This study identifies the remote forcings of the June 2023 Texas heat wave, attributing it to a Rossby wave generated by tropical Pacific heating and extratropical Pacific vorticity transients, and demonstrates its predictability up to three weeks ahead using NASA models.
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Ghosh et al. (2025) Quantifying rainfall-induced climate risk in rainfed agriculture: A volatility-based time series study from semi-arid India
This study develops a volatility-in-mean time series framework to quantify rainfall-induced climate risk on rice yield forecasts in semi-arid Maharashtra, India, finding that GARCH-type models, particularly eGARCH and gjrGARCH with log-differenced rainfall measures, significantly improve forecast accuracy and robustness.
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Yin et al. (2025) Characteristics and Attribution of Winter Extreme Cold Indices in China
This study analyzes winter extreme cold indices in China from 1961 to 2023, finding a general weakening trend driven by anthropogenic forcing and modulated by the Arctic Oscillation.
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Guan et al. (2025) The ability of a stochastic regional weather generator to reproduce heavy-precipitation events across scales
This study assesses a non-stationary regional weather generator's (nsRWG) ability to reproduce heavy-precipitation event (HPE) extremity across spatial and temporal scales in Germany, finding it largely excels in replicating observed extremity patterns and potential influential areas, making it suitable for flood risk assessment.
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Papić (2025) Spatial and Temporal Dynamics of Drought in Bosnia and Herzegovina During the Period 1956–2023
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Ndiaye et al. (2025) Hydrological variability of large rivers in West Africa: gap-filling with Earth observations and daily rainfall-runoff modelling
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Deman et al. (2025) Future changes in runoff over western and central Europe: disentangling the hydrological behavior of CMIP6 models
This study characterizes future runoff changes over western and central Europe using a large ensemble of CMIP6 models under a high-end emissions scenario, identifying diverse hydrological responses grouped into clusters. It disentangles inter-model uncertainties, highlighting the roles of large-scale circulation and the physiological effect of CO2, while finding the soil moisture-precipitation feedback important for the ensemble mean but not the inter-model spread.
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Zhou et al. (2025) Influence of Eurasian Spring Snowmelt on May and June Minimum Temperature Variability Over Northeastern China
This study examines the impact of Eurasian spring snowmelt (SSD) on intraseasonal extreme minimum temperature ($T_{min}$) variability in northeastern China during May and June, finding that decreased Siberian SSD enhances both warm and cold night extremes.
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Günaçtı et al. (2025) Assessment of a Survivability Index for Drought Management in River Basins
This paper introduces a novel Survivability from Droughts Index (SDI) to assess drought management capacity in river basins, integrating WEF Nexus and sustainability pillars. The index was applied to the Gediz River Basin, Türkiye, demonstrating its ability to validate historical drought impacts and guide actions for improved drought survivability.
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Min et al. (2025) A Diachronic Assessment of Advances in Seasonal Forecasting: Evolution of the APCC Multi‐Model Ensemble Prediction System Over the Last Two Decades
This study provides a diachronic assessment of the APCC Multi-Model Ensemble (MME) system since 2005, demonstrating a 34% increase in global forecast skill.
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Lu et al. (2025) Role of Soil Moisture Gradients in Favoring Mesoscale Convective Systems in East China
This study demonstrates that mature mesoscale convective systems (MCSs) in East China preferentially propagate toward the drier side of strong soil moisture gradients.
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Dietz et al. (2025) Impact of climate change on snow cover in the Pyrenees, Alps, and Andes Mountains, derived from 40 years of Landsat data
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Guthrie et al. (2025) Deep Root Loss and Regeneration in the Anthropocene Drive Continental‐Scale Changes in Deep Soil Structure
This study investigates how land-use changes and vegetation recovery influence root abundance and soil structure in deep subsurface horizons (>30 cm) across four soil orders. The authors find that root dynamics drive structural transformations, with less-developed soils being more susceptible to these changes.
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Yang et al. (2025) Climate Change and Population Aging Exacerbate Flood Risk to the Elderly in European Regions
This study evaluates the flood risk to the elderly population in Europe by integrating climate projections and socioeconomic pathways into a hydraulic modeling framework, revealing significant increases in exposure within Central Europe.
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Lorenzo‐Lacruz et al. (2025) Losing Water by Storing It: The Oversighted Side of Intensive Water Regulation and Damming
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Saunders et al. (2025) Sensitivity to Data Choice for Index‐Based Flood Insurance
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Xiang et al. (2025) ADAF: An Artificial Intelligence Data Assimilation Framework for Weather Forecasting
The study introduces an AI-based data assimilation framework (ADAF) to generate high-quality kilometer-scale analysis fields, significantly reducing computational costs while improving short-term weather forecasts.
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Liu et al. (2025) Spatiotemporal Flood Prediction From Single Frame Input With a Post‐Processing Method
The study introduces a "single frame prediction" framework using a U-Net architecture and physics-based post-processing to predict spatiotemporal flood maps based on boundary conditions and the previous time step's state.
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Duan et al. (2025) The Impact of Soil Preconditioning on the Evolution of Heatwaves Under Constrained Circulation: A Case Study of the 2021 Pacific Northwest Heatwave
This study utilizes CESM2 ensemble simulations to evaluate the role of initial soil moisture and land-atmosphere interactions in the June 2021 Pacific Northwest heatwave, finding that while circulation is the primary driver, soil moisture state significantly modulates the event's intensity and duration.
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Memari et al. (2025) Quantifying the Impact of Groundwater on Ice Formation in the Great Lakes
This study investigates the impact of subsurface groundwater flux on ice formation and thermal stratification in Lakes Michigan and Huron, finding that moderate groundwater inputs generally promote thicker and longer-lasting ice by enhancing water column stability.
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Zhang et al. (2025) Drip Irrigation in Dryland Agriculture Controls Soil Water‐Filled Pore Space and Reduces Greenhouse Gas Emissions: A Meta‐Analysis
This meta-analysis quantifies the impact of drip irrigation (DI) on greenhouse gas emissions in dryland agriculture, concluding that DI reduces global warming potential primarily by decreasing soil moisture.
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Su et al. (2025) Widening Urban–Rural Precipitation Differences in China: Regionally Varied Intensification Since 2000
This study analyzes the impact of urbanization on precipitation patterns across 37 Chinese cities from 1980 to 2022, finding that urbanization generally increases total and extreme precipitation while reducing the overall number of wet days.
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Bertoli et al. (2025) Revisiting Machine Learning Approaches for Short‐ and Longwave Radiation Inference in Weather and Climate Models
This study evaluates several machine learning (ML) architectures as parameterizations for radiative transfer within the ICON weather and climate model on GPUs, finding that a physics-informed BiLSTM model achieves stability and performance comparable to classical physics-based schemes.
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Randriatsara et al. (2025) Historical changes in drought characteristics and their impact on vegetation cover over Madagascar
This study analyzes historical drought characteristics (1981–2022) and their impact on vegetation cover (2000–2022) across Madagascar using the Standardized Precipitation Index (SPI) and Normalized Difference Vegetation Index (NDVI). It finds that drought events have intensified and become more consecutive, particularly in southern Madagascar, leading to severe vegetation losses.
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Huo et al. (2025) Incremental Analysis Updates in a Convective‐Scale Ensemble Kalman Filter Using Minute‐by‐Minute Phased Array Radar Observations
This study evaluates the integration of the Incremental Analysis Update (IAU) method with the Ensemble Kalman Filter (EnKF) to mitigate physical imbalances in rapid-update data assimilation for convective precipitation. The results indicate that this combination improves forecast skill and ensemble diversity by refining the development of convective structures.
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Bahrunani Punjabi (2025) GPR B-scan analysis with machine learning algorithms
The study develops a noninvasive robotic system using Ground-Penetrating Radar (GPR) and the YOLO computer vision algorithm to detect subsurface objects, specifically tree roots, for improved agricultural water management.
