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Andria et al. (2025) Thermodynamic Versus Large‐Scale Controls on Extreme Precipitation: Temporal Scale Dependence and Clausius‐Clapeyron Scaling Redefined
This study introduces a framework using the Metastatistical Extreme Value Distribution to precisely define precipitation extremes and investigate their dependence on local thermodynamics and large-scale atmospheric circulation across different temporal scales. It finds that hourly precipitation extremes are primarily controlled by thermodynamics, with rarer events intensifying more sharply, while daily extremes are predominantly influenced by large-scale circulation, challenging conventional Clausius-Clapeyron scaling assumptions.
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Küçükoğlu et al. (2025) Global evolution of inland water levels: drying-speed analysis using ICESat-2 ATL13
This study analyzed global inland water level dynamics for over one million lakes and reservoirs from 2018-2025 using ICESat-2 ATL13 data, revealing that more than half of monitored bodies experienced decreasing water levels and demonstrating the capability of satellite altimetry for near-term global-scale monitoring.
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Zhang et al. (2025) Multi-stage flood utilization framework to support ecological flow protection and groundwater recovery mechanisms
This study introduces a multi-stage flood utilization framework that integrates ecological flow protection with groundwater recharge to address water scarcity. The framework significantly improves downstream ecological flow protection by eliminating flow interruptions and enhances groundwater recovery in water-scarce regions.
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Lee et al. (2025) Development of an automated hyperspectral system to monitor hyperspectral reflectance and sun-induced chlorophyll fluorescence with directional and hemispheric view geometries simultaneously
This study develops and evaluates an automated hyperspectral system (enhanced RotaPrism) for simultaneous monitoring of hyperspectral reflectance and sun-induced chlorophyll fluorescence (SIF) using both directional (conical) and hemispherical view geometries. It demonstrates the system's reliability and reveals significant, seasonally variable differences in spectral reflectance and SIF between these viewing geometries across rice paddy and mixed forest ecosystems.
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Zhang et al. (2025) Significant Shifts in Continental Precipitation Sources in the 21st Century
## Identification - **Journal:** Water Resources Research - **Year:** 2025...
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Zhang et al. (2025) Future Meiyu Precipitation Change and Atmospheric River Impacts Across East Asia: Regional Disparities and Risks
This study projects future changes in East Asian Meiyu precipitation and its coupling with atmospheric rivers (ARs) under CMIP6 SSP245 and SSP585 scenarios, finding significant increases in both mean/extreme rainfall and AR intensity, primarily driven by thermodynamic moistening, with notable regional variations.
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He et al. (2025) Hydrological response to land use change under low carbon-optimal economic scenario
This study developed a framework integrating land-use simulation (CA Markov) and hydrological modeling (SWAT) with spatiotemporal regression (GTWR) to assess hydrological responses to land-use change under a low-carbon, economic-optimal scenario in the Dongjiang River Basin. It found that by 2035, land-use changes, primarily farmland conversion to forest, grassland, and construction, lead to increased surface runoff and evapotranspiration, decreased soil percolation and groundwater recharge, with significant spatiotemporal heterogeneity and implications for drought and flooding risks.
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Feng et al. (2025) A Novel Method for Reservoir Outflow Simulation Based on Spearman Rank Correlation Between Satellite‐Derived Water Elevations and Model‐Simulated Reservoir Storage
This study proposes a novel calibration scheme for Reservoir Outflow Models (ROMs) utilizing Spearman rank correlation between satellite-derived surface water elevations and ROM-simulated storage to accurately reconstruct historical reservoir outflows, demonstrating comparable performance to gauged data calibration and superior data efficiency compared to hybrid methods.
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Sanchez-Lorente et al. (2025) Air–sea interaction heat and momentum fluxes based on vessel's experimental observations over Spanish waters
This paper presents a quality-controlled dataset of air–sea interaction heat and momentum fluxes derived from experimental observations aboard four research vessels over Spanish waters from 2011 to 2023, providing crucial regional data for climate studies and validation of models.
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Abbas et al. (2025) Southward to northward shifting trends of monsoonal precipitation and their connections with atmospheric circulations over Pakistan: A comparative study of 1961–1990 and 1991–2020
This study analyzes the southward-to-northward shifting trends of monsoonal precipitation and their connections with atmospheric circulations over Pakistan from 1961 to 2020. It reveals a significant northward shift in precipitation, with regional increases in core monsoon areas and decreases in coastal and southern regions, largely influenced by the Indian Ocean Dipole (IOD) and El Niño-Southern Oscillation (ENSO).
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Achite et al. (2025) Multivariate uncertainty analysis of severity–duration–magnitude–frequency curves using Khoudraji copula and bootstrap method
## Identification - **Journal:** Hydrological Sciences Journal - **Year:** 2025...
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Zhang et al. (2025) Regional greening intensifies transpiration water consumption but enhances the positive feedback process between vegetation and precipitation
This study quantifies the hydrological impacts of regional greening in the Yellow River Basin, revealing that while vegetation restoration intensifies transpiration and overall evapotranspiration, it also significantly enhances the precipitation recycling ratio and generates additional precipitation, suggesting an underestimation of regional vegetation carrying capacity.
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Jehanzaib et al. (2025) The influence of plantation forest legacy on blanket bog hydrology
This research investigates the hydrological impact of legacy plantation forestry (clear-felled areas) on streamflow in a small (0.21 square kilometers) blanket bog catchment in Ireland. The study found that streamflow increased by 106% annually in the degraded catchment compared to an intact blanket bog, with significant seasonal variations.
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Lei et al. (2025) PANet: a physics and action informed network for water level prediction in canal systems
This study introduces PANet, a multi-step water level prediction model for canal systems that integrates Integral Delay theory and action-informed structures to simultaneously model hydrological delays, Markovian properties, and the impact of operational interventions. PANet achieves superior accuracy and stability, significantly outperforming mainstream deep learning models in multi-step forecasting tasks.
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Heyvaert et al. (2025) Land data assimilation of satellite‐based surface soil moisture: Impact on atmospheric simulations over the contiguous United States
This study investigates the effectiveness of surface soil moisture (SSM) data assimilation (DA) in enhancing land initialisation within coupled land-atmosphere models. It finds that SSM DA improves atmospheric predictions, particularly 2-meter air temperature, with greater impact in regions exhibiting stronger land-atmosphere coupling.
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Bundy et al. (2025) Derecho impacts on United States crop condition ratings and yield
This study quantifies the impacts of derechos on corn and soybean conditions and modeled yield across the United States over a nine-year period (2015–2023), revealing significant declines comparable to hurricane impacts, with vulnerability influenced by wind speed, crop stage, and pre-storm conditions.
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Adeyeri et al. (2025) Asymmetric heatwave intensification under divergent climate change mitigation pathways amplifies urban–rural exposure disparities
This study projects future heatwave characteristics and population exposure under different climate change mitigation pathways (SSP370, SSP585) using bias-corrected climate models, revealing asymmetric heatwave intensification and significant, often comparable, exposure disparities between urban and rural populations globally.
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Kuang et al. (2025) Climate change accelerates the evolution of reorganized river-lake systems on the Tibetan Plateau
This study reveals how climate change has accelerated the reorganization of the Zonag and Yanhu Lake drainage basins on the Tibetan Plateau, leading to their connection with the Yangtze River headwaters since 2019, with significant ecological and socio-economic consequences including increased flood risks and sandstorms.
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Tumajer et al. (2025) Longer growing seasons will not offset growth loss in drought-prone temperate forests of Central-Southeast Europe
This study uses the VS-Lite growth model calibrated with 2013 tree-ring chronologies from Central-Southeast Europe to predict that while extended growing seasons may temporarily offset drought-induced growth loss until the 2040s-2050s, high-emission climate scenarios will lead to significant long-term growth reduction in drier temperate forests, as growing season extension becomes insufficient to compensate for declining summer growth rates.
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Dixey et al. (2025) Addressing how spatial resolution affects image velocimetry outputs: implications for measurements from space
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Ranzi et al. (2025) A Multi‐Century Meteo‐Hydrological Analysis in the Italian Alps: Daily Streamflow (1862–2022) at Different Time Scales
This paper reconstructs and analyzes a 161-year daily streamflow time series for the Adige river in the Italian Alps to identify and quantify the impact of natural and anthropic factors on hydrological changes. The study reveals a significant decline in annual streamflow and runoff coefficient, primarily driven by human activities such as water withdrawals, enhanced evapotranspiration due to temperature increase, and afforestation, rather than precipitation changes.
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Roussel et al. (2025) Saharan dust impacts on the surface mass balance of Argentière Glacier (French Alps)
This study quantifies the impact of Saharan dust and black carbon on the surface mass balance (SMB) of Argentière Glacier (French Alps) from 2019-2022, revealing that mineral dust significantly reduced annual SMB, particularly in 2022, with impacts up to 1.2 meters water equivalent (m w.e.) at specific locations.
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Cheng et al. (2025) Climatological characteristics of tropical cyclones simulated in the global-regional integrated forecasting system (GRIST) model
This study evaluates the climatological characteristics of tropical cyclones (TCs) simulated by the Global-Regional Integrated Forecasting System (GRIST) model at 60 km and 15 km resolutions. It finds that while the model generally reproduces TC activity well, especially in the North Pacific, it consistently underestimates TC intensity and activity in the North Atlantic due to large-scale circulation biases and poor representation of African easterly waves.
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Marčiš et al. (2025) Corrigendum to “A combined effect of heat and drought limits the growth of Central European silver fir” [Agricultural and Forest Meteorology 371 (2025) 1–11 / 110610]
Information not available in the provided corrigendum.
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Raoult et al. (2025) Parameter Estimation in Land Surface Models: Challenges and Opportunities With Data Assimilation and Machine Learning
This paper reviews the current state, challenges, and opportunities in parameter estimation for land surface models (LSMs) using data assimilation (DA) and machine learning (ML), particularly focusing on carbon-water-vegetation interactions. It highlights how ML can enhance computational efficiency and address poorly represented processes, advocating for international collaboration to improve LSM predictive capabilities.
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Zheng et al. (2025) Spatiotemporal variation of snow cover over the Tibetan Plateau based on the MODIS fractional snow cover product: 2000–2023
This study investigates the spatiotemporal variations of snow cover and its climatic responses across the Tibetan Plateau from 2000 to 2023 using MODIS fractional snow cover data, revealing a widespread decline in snow cover driven by distinct temperature and precipitation factors across different circulation regimes.
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Monte et al. (2025) Skilful seasonal predictions of droughts in the Mediterranean region
This study investigates the skill of seasonal prediction systems (SPSs) in forecasting meteorological drought in the Mediterranean region using SPI3 and SPEI3 indices. It demonstrates that optimized multi-model ensembles (MME) significantly enhance drought prediction skill, outperforming individual systems and climatology across most of the region.
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Kashyap et al. (2025) Ecological droughts increased in India with changing Indian summer monsoon and human interventions
This study investigates ecological droughts, their drivers, and implications in India during the Indian Summer Monsoon (2000–2019) using remote sensing and machine learning. It finds that ecological droughts are increasing in ecologically fragile pristine forests and croplands, primarily driven by meteorological aridity (23.9%) and ocean warming (18.2%), leading to declining vegetation health.
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Archer et al. (2025) Characteristics of gauged abrupt wave fronts (walls of water) in flash floods in Scotland
This study characterizes abrupt wave front floods (AWFs) in Scotland using gauged river level and discharge data, revealing their widespread occurrence, downstream intensification, and the inadequacy of traditional flood forecasting models to represent their distinct hazard to human life.
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Wang et al. (2025) Spatially synchronized structures of global hydroclimatic extremes
This study develops DOMINO-SEE, a multilayer event-based complex climate network framework, to analyze global synchronizations of meteorological droughts, pluvials, and drought-pluvial 'seesaw' extremes using 67 years of precipitation reanalysis data. It reveals pronounced spatial asymmetries in teleconnected synchronizations, dominated by oceanic regions and southern mid-latitudes, and highlights significant cross-hemisphere seesaw patterns affecting global breadbasket regions.
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Sourp et al. (2025) Assessment of Snow Cover Fraction Parameterizations for High Resolution Snowpack Reanalyses
This study assesses the performance of various snow cover fraction (SCF) parameterizations within a 100 m resolution data assimilation framework in a mountainous region, finding that a simple asymptotic parameterization consistently performs best for improving high-resolution snow depth estimates through remote sensing SCF assimilation.
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Jiang et al. (2025) Assessing the Simulation of Ephemeral-Snow Duration in the Tibetan Plateau
This study evaluates the capability of a land surface model to simulate ephemeral snow duration over the Tibetan Plateau's interior basins using optimized atmospheric forcing data, revealing systematic biases including overestimation of short snow durations and underestimation of long durations, and proposing a physical scheme adjustment for improvement.
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Chang et al. (2025) Historical evolution and future trend of meteorological drought in the upper Yangtze River basin
This study analyzed historical (1961-2018) and projected future (2019-2099) meteorological drought trends in the upper Yangtze River basin using SPI and SPEI and CMIP6 models, finding a historical intensification of droughts post-2000 and a projected transition to significantly drier conditions with more frequent, longer, and more intense droughts after 2040 under higher emission scenarios.
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Zubair et al. (2025) Agricultural drought forecasting using remote sensing: A hybrid modeling framework by integrating wavelet transformation and machine learning techniques
This study developed an innovative hybrid modeling framework integrating wavelet transform preprocessing with ensemble machine learning models (XGBoost, AdaBoost, Random Forest) to enhance agricultural drought prediction. The framework significantly improved prediction accuracy, with XGBoost achieving the highest performance (R² = 0.964) in forecasting the Vegetation Health Index (VHI).
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Silver et al. (2025) rOPTRAM: An R package for satellite-derived soil moisture in rangelands using the OPTRAM model
This paper introduces rOPTRAM, an R package that implements the OPtical TRapezoid Model (OPTRAM) for satellite-derived soil moisture estimation in rangelands. The package streamlines image acquisition, automates trapezoid edge delineation with multiple curve fitting options, and is validated across diverse rangeland sites.
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Devitt et al. (2025) Spatiotemporal changes in UK heavy rainfall events not captured by intensity-based methods
This study investigates the evolving spatiotemporal characteristics of heavy rainfall events across the UK using a high-resolution, convection-permitting ensemble. It reveals that future winter events become more localized with increased peak intensities, while summer events expand spatially, leading to greater total precipitation volumes, highlighting changes beyond simple intensity shifts.
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Argañaraz et al. (2025) Building a High‐Resolution Climate Gridded Dataset in Complex Terrain: Validating Different Methods in the Abruzzo Region in Italy
This study compares different interpolation methods to create high-resolution daily gridded maps of precipitation and temperature for Abruzzo, central Italy, and validates the resulting local dataset (ADAMO) against global datasets. It finds that universal kriging performs best, and the locally derived ADAMO dataset significantly outperforms global datasets in regions with high topographic variability.
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Goelzer et al. (2025) Interactive coupling of a Greenland ice sheet model in NorESM2
This study describes the first interactive coupling of the Greenland Ice Sheet model (CISM) within the Norwegian Earth System Model (NorESM2), detailing the model setup and initialization procedure. Experiments under historical and high-emission future scenarios reveal a limited impact of dynamic ice sheet changes on the global climate response compared to a fixed ice sheet simulation.
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Shaw et al. (2025) Moist Adiabatic Scaling Explains Mean and Fast Upper‐Level Jet Stream Wind Response to Climate Change
This paper derives a moist adiabatic scaling that explains the observed increase in upper-level jet stream strength and shear under climate change, demonstrating that the response is primarily driven by the increase in surface moisture gradient following the Clausius-Clapeyron relation.
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Han et al. (2025) Connection of Autumn North Asian Snow With Mid‐Winter Tibetan Plateau Snow
This study detects a teleconnection where excessive October-November North Asian snow leads to a weakened stratospheric polar vortex, which subsequently causes an anomalous anticyclone over the Tibetan Plateau, resulting in decreased January snowfall and snow depth.
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Silva et al. (2025) A hydrological model to assess current and future freshwater availability: application to climate change impacts on hydrology in the Amazon River Basin through mid-century
This study developed and applied an enhanced Hydro-BID hydrological model to assess current and future freshwater availability in the Amazon River Basin (ARB) through mid-century under various climate change scenarios. The findings project a predominant decrease in freshwater availability across the ARB, with significant spatial variability and intensified impacts under high-emissions scenarios, particularly during low-water months.
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Lin et al. (2025) Monitoring surface water in floodplains by satellites: Progress, challenges, and perspectives
This review systematically summarizes advancements in satellite remote sensing for monitoring floodplain hydrological variables, identifies current challenges, and proposes a future multi-source, multi-variable, and automated framework for improved global-scale monitoring.
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Amestoy et al. (2025) Integrated river basin assessment framework combining probabilistic streamflow reconstruction, Bayesian bias correction, and drought storyline analysis
This study develops a generalizable framework for assessing water availability and drought vulnerability in complex river basins. Applied to the Delaware River Basin using a reconstructed 1960s drought, the framework demonstrates significant vulnerabilities for New York City's drinking water supply and highlights tensions with saltwater intrusion risks under modern management.
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Rezaei et al. (2025) Modelling phosphorus and potassium dynamics in drip-irrigated potato systems using coupled agro-hydrological model
This study combined field experiments with coupled DSSAT and HYDRUS-2D models to investigate phosphorus (P) and potassium (K) dynamics in drip-fertigated potato systems under semi-arid conditions, revealing limited vertical mobility for both nutrients but greater lateral movement for K, and demonstrating that frequent, low-concentration fertigation significantly enhances nutrient availability and uptake efficiency.
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Du et al. (2025) Quantile‐Based Fire Weather Index Better Informs Detection and Variability of Wildfire Risks in China
This study developed a quantile-based Fire Weather Index (QFWI) for China, demonstrating its superior accuracy in indicating wildfire occurrences compared to the standard FWI. It revealed that China's wildfire risks exhibit inter-decadal variability, decreasing pre-1990 due to reduced wind speed and increasing post-1990 primarily due to rising temperature and decreasing humidity, signaling heightened future risks.
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Yang et al. (2025) Probabilistic assessment for drought risk: Integrating drought hazard, ecological sensitivity, economic vulnerability, and their coupling coordination
This study developed a robust drought risk assessment framework integrating Eco-DRR capacity and the coupling coordination of drought risk components. Applied to county-level cities in China's three northeastern provinces (2000-2022), the framework revealed generally low/moderate drought hazards, high ecological sensitivity, low economic vulnerability, and low/moderate overall drought risk, with specific spatial patterns and probabilistic classifications for cities.
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Tripathy et al. (2025) Spatiotemporal dynamics of surface and rootzone soil moisture droughts
This study employed a Complex Network framework and event synchronization to analyze summer surface and root-zone soil moisture droughts across the contiguous United States, identifying the Ohio River Valley as a central drought hub and revealing a west-to-east propagation pattern with stronger spatial coherence in root-zone soil moisture.
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Liu et al. (2025) Temporal persistence of postfire flood hazards under present and future climate conditions in southern Arizona, USA
This study investigates the temporal evolution of post-fire hydrologic parameters and quantifies changes in flash flood peak discharges under future climate conditions in a 49.4 km² watershed in southern Arizona. It finds that while soil hydraulic properties recover over three post-fire years, climate change-driven rainfall intensification will significantly increase the magnitude and persistence of post-fire flood hazards, potentially doubling the likelihood of 100-year floods by mid-century under medium emissions scenarios.
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Khadke et al. (2025) Vapor pressure deficit dominates sap flow variability across forest biomes
This study investigates the causal drivers of sap flow (SAPFlow) across 15 global forest sites using information theory-based process networks and wavelet analysis. It finds that vapor pressure deficit (VPD) is the dominant causal driver of SAPFlow variability across all forest types, forming a coupled system with soil water content (SWC) mediated by land-atmosphere feedback.
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Lei et al. (2025) Synergizing machine learning and modified physical models for hydrology modeling: A case study of modified SIMHYD and TANK models
This study investigates the effectiveness of hybrid hydrological models (HMs) that combine machine learning with original and modified physical models (SIMHYD, TANK) across 569 catchments in the United States. It finds that HMs with modified physical layers offer superior runoff predictability and improved reasoning ability for evaporation and baseflow compared to those with original physical models.
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Kapoor et al. (2025) QDeepGR4J: Quantile-based ensemble of deep learning and GR4J hybrid rainfall-runoff models for extreme flow prediction with uncertainty quantification
This paper introduces QDeepGR4J, a quantile regression-based ensemble extension of the DeepGR4J hybrid rainfall-runoff model, to quantify uncertainty in multi-step streamflow predictions and identify extreme flow events. The framework significantly improves predictive accuracy and uncertainty interval quality, demonstrating its suitability as an early warning system for floods.
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Lin et al. (2025) Characteristics of Extratropical Cyclones and Associated Precipitation Across the Huang‐Huai River Basin, East China
This study analyzed extratropical cyclone (ETC) characteristics and precipitation patterns in the Huang-Huai River Basin (HHRB) from 1979 to 2022, finding that ETCs contribute approximately 60% of the region's total precipitation, with distinct types playing crucial roles in summer floods and droughts.
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Lanjie et al. (2025) Efficient urban flood surface reconstruction: integrating deep learning with hydraulic principles for sparse observations
This study proposes a novel deep learning framework, Sparse-Point Learning and Interpolated Surface Reconstruction (SPIR), to efficiently and accurately simulate high-resolution urban flood inundation by integrating a lightweight neural network with hydrodynamic-informed interpolation. The framework significantly reduces computational time while maintaining high prediction accuracy compared to traditional hydrodynamic models.
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Ma et al. (2025) Comprehensive drought detection, spatiotemporal variations, and attribution across different agricultural climate zones in Eastern China using a copula-based drought index
This study developed a novel Copula-based Multivariate Standardized Drought Index (MSDI) to assess drought spatiotemporal variations and attribution across different agricultural climate zones in Eastern China from 2001–2020. Findings reveal a general worsening of drought conditions characterized by a southward shift and increased frequency, intensity, and severity of short-term events, with dominant drivers varying regionally.
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Li et al. (2025) Assessing the Impact of Land‐Use Types on Historical Dryness/Wetness Trends Over Global Land Areas
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Wu et al. (2025) Evaluation of Present and Future Relationships Between Daily Precipitation and Temperature in Eastern China
This study examines historical and future precipitation-temperature relationships over eastern China, assessing the performance of CMIP6 models and ERA5 reanalysis, and projecting increased sensitivity of extreme precipitation to warming, highlighting rising flood risks.
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Tan et al. (2025) Seasonal Prediction of Summer Extreme High Temperature Days in Western North America Based on the Dynamic Origins of the Cross-Pacific Rossby Waves
This study explores the physical processes controlling the three leading modes of summer extreme high-temperature days (EHDs) over western North America (WNA) and establishes a physics-based empirical model (PEM) that effectively predicts their spatial pattern based on cross-Pacific Rossby wave trains.
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Zhang et al. (2025) The effects of increased evapotranspiration on precipitation in the Yellow River Basin
This study quantifies the impact of increased evapotranspiration (ET) on precipitation in the Yellow River Basin (YRB), finding that ET significantly contributes to local and downwind precipitation, partially offsetting the observed ET increase.
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Teng et al. (2025) A dual-band parametric method for angular normalization of land surface thermal radiation for single-angle thermal infrared image
This study develops a dual-band parametric angular normalization (DPAN) method to correct the thermal radiation directionality (TRD) effect in single-angle thermal infrared remote sensing data, demonstrating its effectiveness in reducing angular effects and enabling operational land surface temperature product normalization without requiring multi-angle or multi-temporal observations.
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Xue et al. (2025) A study of the dependence between soil moisture and precipitation in different ecoregions of the Northern Hemisphere
This study quantifies the spatiotemporal distribution and driving mechanisms of the nonlinear dependence between soil moisture and precipitation across different ecoregions of the Northern Hemisphere. It reveals that negative dependence is widespread, particularly in surface soil, and is primarily driven by land surface temperature and air temperature–gross primary production interactions, with distinct seasonal and annual patterns influenced by freeze–thaw cycles and long-term climate variability.
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Brigode et al. (2025) Using century-long reanalysis and a rainfall-runoff model to explore multi-decadal variability in catchment hydrology at the European scale
This study evaluates the capacity of century-long global reanalyses (NOAA 20CR, ERA-20C) to simulate multi-decadal catchment hydrology across over 2000 European catchments using a rainfall-runoff model, finding reasonable performance, especially for mean flows, and revealing significant alternating wet and dry periods.
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Modi et al. (2025) Understanding the relationship between streamflow forecast skill and value across the western US
This study investigates the complex relationship between seasonal streamflow forecast skill and economic value in unmanaged snow-dominated basins across the western US, finding that while forecast skill is explained by errors in mean and variability, forecast value is more influenced by irregular error structures impacting categorical measures like hit and false alarm rates, meaning high skill does not always translate to high value.
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Estey et al. (2025) Spaceborne estimates of canopy temperature and soil moisture predict daily and annual subalpine tree growth
This study evaluated the potential of satellite-based canopy temperature (TC) and soil moisture (SM) to predict daily and annual tree growth dynamics in a subalpine forest. The models successfully predicted daily stem radial growth with moderate precision (R² = 0.56) and annual growth performance with high precision (R² = 0.76), demonstrating the efficacy of thermal satellite remote sensing for tracking tree growth.
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Li et al. (2025) Atmospheric circulation regimes modulating Eurasian winter decadal cooling
This study identifies three comparable decadal Eurasian winter cooling episodes since 1901, demonstrating that the Scandinavian pattern (SCAND) and North Atlantic Oscillation (NAO) are intrinsic atmospheric regimes modulating these events, with a projected 30% likelihood of another analogous cooling episode by 2050 due to internal variability.
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Gonzalez-Mora et al. (2025) A climate-informed statistical framework to indirectly estimate trends in future seasonal high flows in snow-dominated watersheds using short-term climate variability indices
This study developed a climate-informed statistical framework to indirectly estimate future seasonal high flow trends in snow-dominated watersheds using short-term climate variability indices (SCIs). It found that future high flow variability can be anticipated using highly correlated SCIs, with a single SCI explaining at least 50% of the variability.
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Szturc et al. (2025) Can we reliably estimate precipitation with high resolution during disastrously large floods?
This study evaluates the reliability of various real-time and offline precipitation estimation techniques during a disastrous flood in the upper and middle Odra River basin in September 2024. It finds that rain gauge measurements, radar data adjusted to rain gauges, and multi-source estimates (RainGRS) provide the most reliable high-resolution precipitation fields for flood protection, especially for extreme events in mountainous areas.
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Patel et al. (2025) Advances in remote sensing and GIS applications in watershed hydrology: a systematic review
This systematic review analyzes the advancements in remote sensing (RS) and Geographic Information Systems (GIS) applications in watershed hydrology from 2000 to 2024, with a detailed focus from 2018, highlighting the increasing integration of artificial intelligence (AI) and multi-source modeling for improved hydrological predictions.
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Schepen et al. (2025) Forecasting agricultural drought: the Australian Agricultural Drought Indicators
This study evaluates the skill of the Australian Agricultural Drought Indicators (AADI) system, which forecasts agricultural drought using biophysical and agro-economic models driven by the ACCESS-S2 climate model. It demonstrates that antecedent landscape conditions significantly enhance predictive skill for crop yields, pasture growth, and farm profit, providing earlier and more confident drought warnings than rainfall deficits alone.
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Papastamkou et al. (2025) Assessing impacts on irrigated agriculture using an ecosystem-based approach in a Mediterranean reservoir/lake
This study investigates the impact of ecosystem-based water management and climate change on irrigation water deficits in Lake Kerkini, Greece, using the MIKE HYDRO Basin model, revealing significant increases in deficits under ecological and climate change scenarios.
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Andréassian et al. (2025) Time shift between precipitation and evaporation has more impact on annual streamflow variability than the elasticity of potential evaporation
Using 4122 catchments from four continents, this study investigates how annual streamflow variability depends on climate variables (rainfall and potential evaporation) and on the synchronicity between precipitation and potential evaporation. The analysis reveals that, across diverse climates, the time shift between precipitation and evaporation is the second most important factor, after precipitation, in explaining annual streamflow anomalies, significantly improving prediction models.
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Pektaş et al. (2025) Spatio‐Temporal Change of Climate Regions in Türkiye
This study investigates climate zone shifts in Türkiye from 1954 to 2023 using high-resolution reanalysis data and clustering methods. It reveals a significant trend towards aridification, marked by the contraction of humid regions, the emergence of a new arid zone, and a substantial increase in semi-arid areas across the country.
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Abbaszadeh et al. (2025) Coupling the ParFlow Integrated Hydrology Model within the NASA Land Information System: a case study over the Upper Colorado River Basin
This study evaluates the newly coupled ParFlow-LIS/Noah-MP model in the Upper Colorado River Basin, demonstrating its enhanced capability to simulate three-dimensional groundwater flow and improve soil moisture representation in complex topography compared to standalone LIS/Noah-MP. The coupled model provides new hydrologic prediction capabilities for both surface and subsurface processes.
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Yang et al. (2025) Improving streamflow simulation through machine learning-powered data integration and its potential for forecasting in the Western U.S.
This study evaluated an LSTM-based data integration approach incorporating streamflow (Q) and snow water equivalent (SWE) observations to improve streamflow estimations across various lag times and timescales in the Western U.S. Integrating daily Q observations provided the most significant improvements, boosting the median Kling-Gupta Efficiency (KGE) from 0.80 to 0.96 for 1-day lagged data.
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Маргес et al. (2025) Просторово-часовий аналіз динаміки поверхневих температур басейну річки Супій із застосуванням регресійного аналізу
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Matthews et al. (2025) Dynamic assessment of rainfall erosivity in Europe: evaluation of EURADCLIM ground-radar data
This study evaluates the ground radar-based EURADCLIM dataset for quantifying rainfall erosivity across Europe, finding that it initially overpredicts erosivity due to radar artifacts but significantly improves with an 80 mm h⁻¹ I30 threshold, offering unique spatial detail for soil erosion prediction.
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Zhou et al. (2025) Evaluation of the Linkage Between the Variations in Jet Stream Shape and Surface Air Temperature From CMIP6
This study evaluates the capability of CMIP6 models (AMIP and historical runs) to simulate the relationship between jet stream shapes and surface air temperature, finding that AMIP simulations generally outperform historical runs and that models capture key regional temperature anomalies linked to jet patterns and Arctic Oscillation-like circulation.
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Troy et al. (2025) Can runoff modeled at coarse resolution simulate floods at finer resolutions? A case study over the Ohio River Basin
This study evaluates a computationally efficient flood modeling framework that couples the coarse-resolution Variable Infiltration Capacity (VIC) land surface model with a newly developed 1 km resolution kinematic wave routing model over the Ohio River Basin. The framework successfully reproduces flood characteristics, demonstrating that while sub-daily temporal resolution has minimal impact, coarser spatial resolutions lead to significant underestimation of flood peaks.
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Fazli et al. (2025) Quantifying single, compound and cascading climate extremes: Implications for agricultural resilience in California
This study quantifies the spatiotemporal dynamics of single, compound, and cascading climate extremes in California's Central Valley from 1951 to 2025, revealing increasing heatwaves and droughts, northward shifting hotspots, and differential vulnerability for almonds and grapes, which informs agricultural resilience strategies.
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Zhou et al. (2025) An efficient flow path traversal algorithm for watershed delineation from raster digital elevation models for multicore architectures
This study proposes a novel and efficient flow path traversal algorithm for watershed delineation from raster flow direction grids, specifically designed for multicore central processing unit (CPU) architectures, demonstrating superior performance compared to existing sequential and parallel methods.
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Zeleke et al. (2025) Using a standardized event-based tool for drought analysis: Application to propagation predictability patterns
This study develops a standardized, Python-based methodology using SWAT+ model outputs to analyze meteorological and hydrological drought propagation, revealing diverse propagation behaviors in the Awash Basin.
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Amell et al. (2025) Probabilistic Near‐Real‐Time Retrievals of Rain Over Africa Using Deep Learning
This paper introduces Rain over Africa (RoA), a public, near-real-time precipitation retrieval algorithm for the African continent based on Meteosat thermal infrared observations. RoA provides precipitation estimates with low latency and detailed uncertainty descriptions, demonstrating accuracy comparable to slower methods and improved timeliness over established products like IMERG for land regions.
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Lu et al. (2025) A micro–macro coupled approach to assess urban road traffic flood risk at the city scale
This study developed a micro-macro coupled dynamic risk assessment model, integrating hydrodynamic-hydrological, multi-agent, and system dynamics models, to evaluate urban road traffic flood risk and the effectiveness of mitigation strategies at the city scale. The model demonstrated that comprehensive mitigation measures significantly reduce dangerous vehicles and validate preemptive flood prevention strategies.
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Mirabbasi et al. (2025) Investigating the Dependence Structure of Temperature and Precipitation Concentration with Evapotranspiration in Finland
This study performed a first-of-its-kind trivariate analysis using Vine copulas to investigate the dependence structure between temperature concentration (TCI), precipitation concentration (PCI), and potential evapotranspiration (PET) across nine Finnish meteorological stations (1980–2021), revealing significant spatial variations in their joint probabilities and highlighting region-specific flood risks.
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Oware et al. (2025) Evaluating E3SM Global Storm‐Resolving Model Simulations of Deep Convection: Insights From DP‐SCREAM During TRACER
This study evaluates the performance of the Doubly Periodic Simple Cloud-Resolving E3SM Atmosphere Model (DP-SCREAM) in simulating deep convection in the coastal Houston region, finding it reproduces diurnal cycles well but exhibits persistent biases in cloud representation that are partially addressed by sensitivity experiments on mixing length and buoyancy flux.
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Maisonnier et al. (2025) A new biogeochemical modelling framework (FLaMe-v1.0) for lake methane emissions on the regional scale: development and application to the European domain
This study presents a new physical-biogeochemical modelling framework (FLaMe-v1.0) for simulating lake methane (CH4) emissions at regional scales, applying it to the European domain. The model estimates a total annual CH4 emission of 0.97 ± 0.23 Tg CH4 yr−1 from European lakes (0.1–1000 km2), highlighting strong spatio-temporal variability and the importance of carbon biogeochemical dynamics.
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Habash (2025) Su-Enerji̇-Gida-Ekosi̇stem Baği Yaklaşimi Kapsaminda Akarsu Akişlarinin Modellenmesi̇ İçi̇n Yapay Zeka Tabanli Bi̇r Çerçeve: Türki̇ye Deki̇ Su Havzalarinin Kapsamli Bi̇r Değerlendi̇rmesi̇
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Zuecco et al. (2025) Trees use predominantly summer water in a pre-Alpine catchment
This study utilized a 6-year isotopic dataset in a pre-Alpine catchment to investigate the seasonal origin of water sources for soil and plants, revealing that beech and chestnut trees predominantly use summer precipitation with rapid water turnover, even during dry years.
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Choudhary et al. (2025) Comprehensive Evaluation of Precipitation Reanalysis Products and CMIP6 Models Using Statistical and Machine Learning Techniques With Nature‐Inspired Optimization
This study developed a comprehensive strategy combining reanalysis products, trend analysis, and optimized machine learning models to improve precipitation forecasts and evaluate hydroclimatic variability in the Upper Godavari Sub-basin, India, finding MERRA2 reanalysis and the RF-HHO model to be most accurate for prediction.
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Zhou et al. (2025) Global uncertainty assessment of vegetation indices from NASA's Harmonized Landsat and Sentinel-2 Project
This study globally assessed the between-sensor uncertainties of 21 Vegetation Indices (VIs) derived from NASA's Harmonized Landsat and Sentinel-2 (HLS) version 2.0 surface reflectance data. It found high consistency (R² > 0.94) for most VIs, but uncertainties increased with large view azimuth angle differences, high solar zenith angles, terrain shadows, and elevated aerosol levels, particularly at the extreme ends of VI value ranges.
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Nieves et al. (2025) AI-driven insights beneath the surface: deeper ocean layers at play in severe hurricane forecasting
This study developed a convolutional neural network–random forest (CNN-RF) framework that leverages three-dimensional ocean anomaly data down to 500 meters to significantly improve 72-hour lead-time severe hurricane forecasts, demonstrating the critical importance of deeper ocean layers.
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Kim et al. (2025) Simultaneous Multiscale Data Assimilation of GOES‐16 ABI All‐Sky Radiances and Radar Reflectivity on a Dryline Convection Event
This study investigates the impact of simultaneous multiscale data assimilation (MDA) of GOES-16 all-sky radiance and radar reflectivity on a dryline convection event. It demonstrates that MDA significantly improves multiscale analysis of atmospheric features and enhances the predictability of convective systems compared to single-scale data assimilation (SDA).
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Dommo et al. (2025) Assessing the Response of Surface Cloud Radiative Effects to Stratospheric Aerosol Injections Over West and Central Africa
This study investigates the response of surface cloud radiative effects (CREs) to Stratospheric Aerosol Injection (ARISE-SAI-1.5) compared to a climate change scenario (SSP2-4.5) across three African regions. Findings indicate ARISE-SAI-1.5 mitigates shortwave cloud cooling decreases and enhances longwave warming, primarily driven by changes in liquid water path and fractional cloud cover.
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Chepfer et al. (2025) Variability and Trends in Cloud Properties Over 17 Years From CALIPSO Space Lidar Observations
This study investigates fingerprints of cloud changes using 11 years of CALIPSO space lidar data, finding statistically insignificant decreases in opaque cloud cover and increases in altitude, suggesting the record may be too short or imprecise for confident detection of climate change signals.
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Liu et al. (2025) The spatiotemporal characteristics of extreme drought events in China from 1961 to 2022 via a copula function
This study systematically analyzed extreme drought events in China from 1961 to 2022 using the Standardized Precipitation Index (SPI) and copula functions, revealing significant spatiotemporal variations in drought trends and severity across different regions. It highlights increased drought severity in Northeast and South China, while Northwest China and the Qinghai–Tibet Plateau experienced increased humidity.
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Azhar et al. (2025) Comprehensive portfolio of adaptation measures to safeguard against evolving flood risks in a changing climate
This review compiles and critically analyzes a comprehensive portfolio of 39 flood adaptation measures, classifying them into four groups and evaluating their advantages, disadvantages, co-benefits, and tradeoffs to inform successful, socially just, practically feasible, and technically sound adaptation strategies against evolving flood risks in a changing climate.
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Granata et al. (2025) The anatomy of drought in Italy: statistical signatures, spatiotemporal persistence, and forecasting potential
This study comprehensively analyzes six-month Standardized Precipitation–Evapotranspiration Index (SPEI-6) time series across Italy using advanced statistical, persistence, clustering, and deep learning methods to characterize drought patterns and improve forecasting, revealing a tripartite drought structure and regional forecasting skill.
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Sahithi et al. (2025) Rising compound heatwave exposure in India: insights from CMIP6 climate model projections
This study analyzes the variability of daytime-only, nighttime-only, and compound heat waves (HWs) and their impact on population exposure across India under various Shared Socioeconomic Pathways (SSPs) scenarios. The findings project significant increases in compound and nighttime-only HWs and associated population exposure, particularly in Northwest and Central Northeast India, while daytime-only HWs may decline in some regions.
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Zhang et al. (2025) Climate warming shortens the propagation time from meteorological drought to groundwater drought over 1960–2100
This study investigates how climate warming influences the propagation time from meteorological drought to groundwater drought in the Ganjiang River Basin from 1960 to 2100, revealing that warming shortens the propagation time for drought onset and center, while prolonging it for drought end, primarily due to increased evapotranspiration and groundwater storage anomalies.
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Tran et al. (2025) A Machine Learning Approach for Improving the Accuracy of Gridded Precipitation With Uncertainty Quantification
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Vallés et al. (2025) SERGHEI v2.1: a Lagrangian model for passive particle transport using a two-dimensional shallow water model (SERGHEI-LPT)
This paper introduces SERGHEI v2.1, a new Lagrangian particle transport (LPT) model coupled with a 2D shallow water model, designed to simulate passive particle advection and turbulent diffusion. The study evaluates the accuracy and computational efficiency of various numerical schemes, concluding that the online Euler method offers the best compromise for large-scale applications.
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Lu et al. (2025) Atmospheric rivers emerge as future freshwater reserves and heat stocks
This study assesses the evolving roles of global atmospheric rivers (ARs) in moisture and energy transport under climate change, projecting that by 2100, 70% of mid-latitude ARs will exceed Amazon River-scale moisture transport, intensifying flood risks and shifting poleward. It also reveals their crucial role in redistributing heat and energy on subseasonal scales, with distinct heat archetypes influencing regional precipitation and temperature patterns.
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Poudel et al. (2025) Uncertainty in estimating the relative change of design floods under climate change: a stylized experiment with process-based, deep learning, and hybrid models
This study conducts a stylized model-as-truth experiment across 30 Massachusetts basins to evaluate uncertainty in estimating relative changes of design floods under climate change using process-based, deep learning, and hybrid hydrological models. Findings reveal that structural limitations and equifinality dominate uncertainty in change estimates, which are significantly reduced in variance through regional pooling.
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Gallois (2025) Projet Aqui-FR - Phase 4 - Plateforme nationale de modélisation AQUI-FR : Calibration de l’application hydrogéologique "Eaudyssée-Loire" sous forçage SURFEX V8F
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Vischer et al. (2025) Spatially resolved rainfall streamflow modeling in central Europe
This study develops an end-to-end, spatially resolved neural network pipeline for rainfall-streamflow modeling in central Europe, addressing the limitations of previous aggregated approaches in large and human-impacted catchments. The pipeline demonstrates improved accuracy, data efficiency, and interpretability, particularly for larger river basins.
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Mathias et al. (2025) A theoretical appraisal of the GR4J rainfall-runoff modelling framework
This study theoretically appraises the GR4J rainfall-runoff model, linking its heuristic components to physically-based processes and proposing modifications to eliminate operator splitting. The revised model structure maintains calibration and validation performance across 671 UK catchments while offering improved physical interpretability and computational efficiency.
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Pan et al. (2025) A semi-infinite type-2 fuzzy multi-objective programming model for irrigation water resource management under uncertainties
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Roy et al. (2025) The next Landsat: Mission turning point?
This correspondence raises awareness about the pending decision on the Landsat Next (LNext) mission architecture, outlining the originally envisioned advanced observation requirements derived from extensive user needs assessments and contrasting them with a recently proposed descoped mission that would only meet existing Landsat-9 capabilities. The paper advocates for the original LNext design to ensure future scientific and operational capacity for Earth observation.
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Qian et al. (2025) Extratropical Cyclones Act as a “Bridge” to the Concurrent Impact of ENSO on the Arctic Oscillation During Boreal Winter
This study reveals that extratropical cyclones (ECs) over the North Atlantic act as a crucial "bridge" for the concurrent impact of the El Niño-Southern Oscillation (ENSO) on the Arctic Oscillation (AO) during boreal winter, demonstrating this concurrent influence is more significant than the one-year-lagged effect. The mechanism involves ENSO-induced shifts in the westerly jet stream, modulating atmospheric baroclinicity and EC activity, which ultimately drives the AO pattern.
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Navale et al. (2025) Investigating Land‐Atmosphere Interactions in the North West Himalaya Through Recycled Precipitation: Seasonal Dynamics, Trends, and Topographic Impacts
This study investigates land-atmosphere interactions and their trends in the North West Himalaya (NWH) over two decades (2001–2020) using the WRF model, revealing a high summer recycling ratio and varying links between terrestrial and atmospheric segments influenced by topography and seasonality.
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Stuivenvolt‐Allen et al. (2025) Atmospheric Nonlinearity Controls ENSO Asymmetry in a Hybrid Statistical‐Dynamical Climate Model
This study investigates the causes of El Niño Southern Oscillation (ENSO) asymmetry, finding that while oceanic nonlinearities would lead to stronger La Niñas, the observed asymmetry (stronger El Niños) is critically dependent on nonlinear atmospheric wind-stress responses to sea surface temperature anomalies.
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Bansal et al. (2025) Lake bathymetry and GLOF modelling of Drang Drung glacial lake, Ladakh, India, using machine learning techniques
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Sodhi et al. (2025) Limits to the Practical Predictability of Convective‐Scale Forecast Systems With World‐Class Data Assimilation
This study investigates the uncertainty and error growth in two advanced radar data assimilation systems for thunderstorm forecasting, revealing significant remaining uncertainty in unobserved atmospheric properties and concluding that substantial new measurement technologies or radical ideas are necessary for accurate forecasts.
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Reale et al. (2025) Response of Early Winter Precipitation and Storm Activity in the North Atlantic–European–Mediterranean Region to Indian Ocean SST Variability
This study investigates the influence of Indian Ocean Dipole (IOD) variability on early winter precipitation and storm activity in the North Atlantic–European–Mediterranean (NAEM) region, revealing a significant December-specific teleconnection characterized by a positive NAO-like pattern, altered precipitation, and reduced cyclone activity driven by changes in baroclinicity.
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Yu et al. (2025) Research on the reciprocal feedback relationship and influencing factors between meteorological and agricultural drought in Northeast China
This study quantifies meteorological and agricultural drought dynamics and their reciprocal feedback mechanisms in Northeast China (2000–2023) using advanced statistical and machine learning methods, revealing significant spatiotemporal variations and key influencing factors like precipitation and temperature.
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Rajulapati et al. (2025) Prevailing Climate Patterns for Concurrent High Temperature and Low Precipitation Days in Canada
This study evaluated the changing frequency of concurrent daily High Temperature and Low Precipitation (HTLP) across Canada and its relationship with large-scale climate patterns. It found a significant increase in HTLP in the Canadian Arctic and southern British Columbia, with four specific climate indices identified as significant influencers.
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Singh et al. (2025) Physics‐Aware Probabilistic Modeling of Subsurface Soil Moisture Using Diffusion Processes Across Different Climate Settings
This study developed a physics-aware probabilistic denoising diffusion model to estimate subsurface soil moisture (10–40 cm) solely from surface observations, demonstrating robust and accurate performance across 24 globally distributed sites with diverse climate settings and varying temporal resolutions. The model eliminates the need for site-specific physical parameters by integrating Fickian diffusion principles as weak physical constraints within a data-driven framework.
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Guillaume‐Castel et al. (2025) ENSO Diversity Explains Interannual Variability of the Pattern Effect
This study systematically assesses the dominant modes of sea surface temperature (SST) variability influencing the top of atmosphere energy budget. It identifies Eastern Pacific and Modoki El Niño–Southern Oscillation (ENSO) as the two leading interannual modes most relevant to the pattern effect, exhibiting distinct radiative signatures due to subtle shifts in SST anomaly locations.
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Allwayin et al. (2025) Investigating Characteristic Droplet Size Distributions in Large Eddy Simulations of Stratocumulus Clouds
This study investigates the existence and properties of characteristic cloud droplet size distributions within Large-Eddy Simulations (LES) of stratocumulus clouds using both Lagrangian and bin microphysics schemes. It finds localized characteristic distributions in bin microphysics simulations, but notes that simulated clouds are significantly more uniform than observed, potentially due to poorly resolved entrainment interfaces or uniform large-scale forcing in LES.
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Takaya et al. (2025) Influence of Soil Moisture on Surface Air Temperature in Monsoons
This study quantifies the influence of soil moisture on surface air temperature across monsoon regions using information-theoretic causal analysis, revealing a significant, seasonally linked influence, even in wet tropical conditions, and a strong connection between land desiccation and pre-monsoon hot days.
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Dong et al. (2025) Evolution and Characteristics of Mesoscale Convective Systems over the Congo Basin
This study constructs a 20-year climatology of Mesoscale Convective System (MCS) characteristics and rainfall over the Congo basin to understand their life cycle, structure, and environmental drivers. It reveals distinct seasonal patterns, with September–November MCSs producing more rainfall despite being less intense, and identifies trends of increasing MCS intensity but declining precipitation feature rain rates and longer upscale growth times from 2001 to 2020.
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Rautiainen et al. (2025) An operational SMOS soil freeze–thaw product
This paper introduces an updated operational SMOS Level-3 Soil Freeze–Thaw (FT) product, detailing its L-band passive microwave-based classification algorithm with enhanced noise reduction. Validation against in situ measurements and reanalysis data demonstrates improved accuracy in detecting the day of first freezing, providing crucial data for carbon cycle studies in high-latitude environments.
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Ji et al. (2025) Distinct hydrologic response patterns and trends worldwide revealed by physics-embedded learning
This study introduces a high-resolution, physics-embedded, big-data-trained hydrologic model to accurately capture global hydrologic response patterns and their shifts. The model reveals widespread and significant shifts in green-blue-water partitioning and baseflow ratios worldwide over the past two decades, with critical implications for flood risks, water supply, and aquatic ecosystems.
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Khare et al. (2025) Estimates of global surface water dynamics harnessing near real-time land cover observations and open science geospatial capabilities
This study developed the first 10 m resolution Global Surface Water Extents (GSWE) dataset for 2015–2023 using Sentinel-2 Dynamic World products, estimating 2.5 million km² of permanent and 8 million km² of seasonal waters globally, and providing an operational framework for actionable water information.
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Navarro et al. (2025) Seamless seasonal to multi-annual predictions of temperature and Standardized Precipitation Index by constraining transient climate model simulations
This study develops a computationally inexpensive analog-based method to generate seamless seasonal to multi-annual predictions of surface air temperature (TAS) and Standardized Precipitation Index (SPI) by constraining CMIP6 simulations, demonstrating competitive skill compared to state-of-the-art initialized systems and offering continuous monthly initializations.
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Ding et al. (2025) Dual Synoptic Pathways of Winter Extreme Precipitation over the Tibetan Plateau: Classification, Moisture Origin, and Rossby Wave Activity
This study identified two distinct types of winter extreme precipitation events over the Tibetan Plateau (TP) between 1980 and 2020, driven by different hemispheric-scale Rossby wave trains, with Type 2 events showing a significant increase in frequency while Type 1 events declined.
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Zeng et al. (2025) Emerging remote sensing techniques for hydrological applications
This editorial provides a systematic overview of 31 publications within a special issue, highlighting advancements in remote sensing techniques, including multi-sensor platforms and machine learning, for monitoring and modeling hydrological variables and their operational applications.
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Dai et al. (2025) Human Influence on Changes in Seasonal Extreme Precipitation Across Different Land Regions
This study conducted a detection and attribution analysis of extreme precipitation changes across the Northern and Southern Hemispheres from 1950 to 2018, finding significant intensification in the Northern Hemisphere driven over 70% by anthropogenic greenhouse gases, while changes in the Southern Hemisphere were more regionally and seasonally complex.
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He et al. (2025) A multi-band remote sensing method for small-and-medium river discharge estimation based on fused Sentinel-2/Landsat images
This study developed a framework for estimating discharge in small and medium rivers using fused Sentinel-2 and Landsat 8 satellite images. The framework, which integrates a modified image fusion model and a novel multi-band remote sensing (MBRS) method, demonstrated enhanced discharge inversion capabilities, particularly with a Random Forest-based MBRS model.
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Alexander et al. (2025) Less Intense Daily Precipitation Maxima in Regional Compared to Global Gridded Products
This study consistently evaluates the annual wettest day (Rx1day) across global and regional gridded observational precipitation datasets, revealing that regional products are consistently drier than their global counterparts, yet the long-term trend in Rx1day aligns with the expected 7%/°C increase per global mean temperature rise.
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McMichael et al. (2025) Investigation of Ship‐Induced Mesoscale Circulation Mechanics and Aerosol Plume Spreading Rates
This study employs large-eddy simulations to investigate the physical mechanisms controlling the spreading rate of ship-emitted aerosol plumes in precipitating stratocumulus clouds. It finds that cloud droplet sedimentation and collision-coalescence are the primary drivers of plume buoyancy and horizontal spreading, while the effective radius has a negligible influence.
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Bałdysz et al. (2025) Detecting Localized Floods in Tropical Regions With CYGNSS SmallSat Constellation: A Proof of Concept From the Maritime Continent
This study demonstrates a novel methodology utilizing CYGNSS SmallSat data to detect and monitor small- to regional-scale flooding events in Sumatra, identifying key parameters for flood detection to improve risk assessment and forecasting in tropical regions.
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Han et al. (2025) Spatial series approach to estimate soil moisture over wheat fields from a single SAR image
This study introduces a spatial series approach (SSA) to estimate soil moisture (SM) over wheat fields using a single Synthetic Aperture Radar (SAR) image, leveraging backscattering intensity ratios (BIRs) to implicitly account for vegetation and roughness effects. The method achieves stable SM retrieval with a root mean square error (RMSE) of approximately 10% and a correlation coefficient (R) exceeding 0.7, offering a robust solution for SM monitoring in scenarios with limited time-series SAR data.
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Lan et al. (2025) Biogeophysical warming effects of vegetation growth in the temperate water-limited region
This study quantifies the biogeophysical effects of vegetation growth on land surface temperature (LST) in temperate water-limited regions, revealing distinct diurnal and seasonal LST trends and identifying key drivers (ET, Albedo, SM, LAI) across different land use types from 2000 to 2020.
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Unknown (2025) Mountain glaciers will lose their cooling capacity as they shrink
This paper highlights that the protective microclimates currently found on mountain glaciers, which slow melting, will decay as glaciers shrink, leading to increased sensitivity of glacier temperatures to atmospheric warming by the latter half of the 21st century.
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Akbari et al. (2025) Enhancement of border irrigation systems: Leveraging simulation–optimization techniques
This study proposes a novel simulation–optimization model for designing open-end border irrigation systems to enhance hydraulic performance under field constraints. Integrating a modified hydro-empirical SCS simulation framework with the Grey Wolf Optimizer, the model significantly improves distribution uniformity and requirement efficiency, substantially reduces total applied water, and identifies shortening the advance phase as the most effective strategy for performance enhancement.
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Zhuang et al. (2025) Integrating social media data and machine learning methods for flash flood susceptibility mapping in China
This study integrates social media data and five machine learning algorithms to map flash flood susceptibility across China, revealing spatiotemporal patterns and key influencing factors, while demonstrating the utility of social media for risk assessment.
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Hendrickx (2025) Bodemvocht schatten met SWIM²: Inverse modellering met bodemvochtsensoren voor verbeterde voorspellingen van irrigatiebehoefte
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Boisier et al. (2025) Increasing water stress in Chile revealed by novel datasets of water availability, land use and water use
This study evaluates past, present, and future water stress in Chile using novel, national-scale datasets of water availability, land use, and water use. It reveals a steady increase in water stress in central Chile, primarily driven by rising water consumption and reduced availability, projecting permanent megadrought-like conditions and extreme water stress in many basins under adverse climate scenarios.
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Han et al. (2025) Baseflow Separation for Improving Dam Inflow Prediction Using Data-Driven Models: A Case Study of Four Dams in South Korea
This study developed and evaluated data-driven models (Deep Neural Network and Random Forest) coupled with a baseflow separation process to improve dam inflow prediction accuracy in four South Korean dams, demonstrating that baseflow separation significantly enhances predictive performance.
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Cho et al. (2025) Thermodynamic Differences Between Moderately and Extremely Long Heat Waves in South Korea
This study categorizes South Korean summer heat waves over 52 years into moderately and extremely long events, revealing that extremely long events are sustained by distinct thermodynamic processes involving persistent high-pressure systems, subsidence, land-atmosphere interactions, and delayed surface cooling, which differ from shorter events.
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Liu et al. (2025) Effects of green infrastructure composition and configuration on runoff regulation in watersheds: A global meta-analysis
This meta-analysis quantified the global effects of green infrastructure (GI) composition and configuration on watershed runoff characteristics, revealing that shrubland and forest land have strong regulatory effects, while higher GI patch density increases runoff. The study also identified critical forest land area thresholds for watershed ecological security.
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Kelley et al. (2025) State of Wildfires 2024–2025
This report systematically tracks global and regional fire activity for the 2024–2025 fire season, analyzing the causes of prominent extreme wildfire events and projecting their likelihood under future climate scenarios. It found that global fire-related carbon emissions totaled 2.2 Pg C (9% above average) despite below-average global burned area, driven by extreme seasons in South America and Canada, with climate change significantly increasing the likelihood of these events.
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Weißenborn et al. (2025) Neural networks in catchment hydrology: a comparative study of different algorithms in an ensemble of ungauged basins in Germany
This study comparatively evaluates Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU) for daily discharge prediction in 35 ungauged basins in Hesse, Germany. It finds that all models show significant predictive capabilities, with CNN exhibiting slightly superior accuracy, while GRU offers the best computational efficiency, and the inclusion of static catchment features consistently improves performance.
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Baiamonte et al. (2025) Exploring the impact of average water content on wetting bulb expansion from a buried point source
This study investigates the influence of the average volumetric water content (θavg) on the expansion of the wetting bulb from a buried point source in a subsurface drip irrigation (SDI) system. By calibrating a k parameter for θavg within Philip's analytical model using six years of experimental data, the study significantly improved the accuracy of wetting front travel time (tt) estimations, reducing the standard error from 15012 seconds to 1560 seconds.
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Lin et al. (2025) A Theory for the Spurious Pressure Waves in Compressible Large Eddy Simulations of Shallow Cumulus Clouds
This paper investigates the omnipresent spurious pressure waves in large-eddy simulations (LES) of shallow cumulus clouds, proposing an analytic theory that links their generation to latent heating and suggesting more frequent microphysics updates for stabilization.
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Tau et al. (2025) Thermal Response of Lakes to Cyclic Environmental Forcing
This study develops and tests precise mathematical expressions to predict the thermal response of lakes to cyclic environmental forcing and global changes, demonstrating that lake surface temperature departure from equilibrium depends on the forcing period, thermal response time, lake/thermocline depth, and wind speed.
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Chen et al. (2025) Do Tropical Cyclone Outer Size Forecasts Improve Simultaneously With Intensity Forecasts?
This study evaluates the tropical cyclone (TC) intensity and outer size forecast performance of five NOAA numerical models for 15 North Atlantic hurricanes from 2020 to 2022, revealing little correlation between intensity and size forecast accuracy, with higher resolution improving intensity but not size forecasts, and initial storm size influencing size prediction challenges.
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Qin et al. (2025) Remote Influence of Andean Convection on Amazonian Rainfall and Its Mechanisms
This study investigates the Wet Andes-Dry Amazon (WADA) precipitation bias in climate models, demonstrating that Andean convection significantly reduces Amazonian rainfall during austral summer through rapid, weather-timescale atmospheric teleconnections involving moisture budget changes and Kelvin waves.
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Oerlemans et al. (2025) Flood exposure in Rotterdam's unembanked areas from 1970 to 2150: sensitivities to urban development, sea level rise, and adaptation
This study quantifies historical (1970-2020) and projected (to 2150) residential flood exposure in Rotterdam's unembanked areas, attributing changes to urban development, sea level rise, and the Maeslant storm surge barrier. It finds that without further adaptation, flood exposure is projected to increase significantly by 2150, primarily driven by sea level rise, despite the historical mitigating effect of the Maeslant barrier.
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Cao et al. (2025) Brief communication: Reanalyses underperform in cold regions, raising concerns for climate services and research
This study quantifies the relative quality of five state-of-the-art reanalyses in cold regions, revealing that the ensemble spread for mean annual air temperature and maximum snow water equivalent is significantly higher in these areas compared to other regions, raising concerns for climate services and research.
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Tang et al. (2025) Multi-indicator comparison in characterizing spatiotemporal patterns of water disasters and corresponding agricultural applications in the Middle-and-lower Yangtze River
This study systematically compared five hydrometeorological indicators to characterize spatiotemporal drought and flooding patterns in the Middle-and-lower Yangtze River Region, revealing increasing trends in both disasters and identifying high-risk zones for cotton and rapeseed, with rapeseed facing significantly higher risks.
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Zhang et al. (2025) Synoptic Origins of Extreme Riverine Floods Over the North China Plain With Focus on the Tail Behaviors
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Zhang et al. (2025) Asymmetry of Tropical Pacific Precipitation Responses to El Niño and La Niña in a Changing CO 2 Pathway
This study constructs an idealised scenario of symmetrical CO2 ramp-up and ramp-down phases to analyse changes in the asymmetric precipitation response to El Niño (EN) and La Niña (LN). It finds that during the CO2 ramp-down phase, both EN and LN precipitation anomalies shift eastward and southward compared to the ramp-up phase, with EN shifts being more pronounced, primarily driven by circulation changes and an EN-like climatological sea surface temperature warming pattern.
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Liu et al. (2025) Precession Affects the Timing and Duration of Summer and Rainy Season in East Asia
This study uses an Earth System Model to reconstruct a full precession cycle, revealing how precession significantly impacts the timing and duration of the East Asian summer and rainy season due to changes in perihelion timing, surface temperature, and subtropical high system shifts.
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Ji et al. (2025) Distinct Hadley circulation attributable to rapid and slow El Niño decay and its regional impacts
This study reveals that rapid decay (RD) El Niño events induce an equatorially asymmetric global Hadley Circulation (HC), contrasting with the quasi-symmetric structure during slow decay (SD) events. These distinct HC configurations, driven by anomalous sea surface temperatures in the central-eastern Pacific, lead to opposing regional precipitation impacts across the Indo-Pacific Warm Pool coastal countries.
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Liu et al. (2025) Quantifying winter wheat phenology patterns in the North China Plain using Solar-Induced Chlorophyll Fluorescence
This study compared winter wheat phenology derived from Solar-Induced Chlorophyll Fluorescence (SIF) with other remote sensing indicators across the North China Plain from 2000 to 2023, finding that SIF-derived metrics offered superior stability and clearer delineation of growth stages, with phenological shifts primarily driven by rising temperatures.
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Song et al. (2025) Indirect assimilation of radar reflectivity data with an adaptive hydrometer retrieval scheme for severe short-term weather forecasts
This study develops an adaptive blending scheme for hydrometeor retrieval in indirect radar reflectivity assimilation, combining temperature-based and background hydrometeor-dependent methods. It demonstrates that this new scheme improves the accuracy of short-term severe weather forecasts by enhancing hydrometeor distributions and thermodynamic/dynamic structures.
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Eslami et al. (2025) Climatic, topographic, and groundwater controls on runoff response to precipitation: evidence from a large-sample data set
This study utilized ensemble rainfall-runoff analysis (ERRA) across 189 Iranian catchments to quantify how climatic, topographic, and groundwater factors control peak runoff response to precipitation, revealing that steeper slopes, smaller catchment areas, shallower groundwater, and more humid climates lead to higher peak runoff.
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Cho et al. (2025) Remote Sensing of Live Fuel Moisture for Wildfires Using SMAP Satellite Observations
This study evaluates the relationship between Live Fuel Moisture (LFM) and remotely sensed Vegetation Water Content (VWC) and Soil Moisture (SM) derived from SMAP L-band brightness temperature, demonstrating that MEP-retrieved VWC serves as a strong, scalable proxy for LFM in the Western U.S. for wildfire risk assessment.
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Wang et al. (2025) Corrigendum to “Variability and uncertainty in net ecosystem carbon exchange modeling: Systematic estimates at global flux sites via ensemble machine learning” [Agricultural and Forest Meteorology, 374 (2025), 110784]
This corrigendum addresses and corrects errors in citation information and acknowledgments within an earlier published article titled "Variability and uncertainty in net ecosystem carbon exchange modeling: Systematic estimates at global flux sites via ensemble machine learning."
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Wang et al. (2025) Loss and recovery of terrestrial carbon sinks induced by 2020 extreme precipitation in the Yangtze River Valley
This study investigated the impact of extreme precipitation in the Yangtze River Valley in June-July 2020 on terrestrial carbon sinks, finding a significant decline in net biome productivity primarily due to reduced gross primary production, followed by a rapid recovery in August.
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Li et al. (2025) Different Effects of Two ENSO Types on the Northern Mid‐to‐High Latitude Surface Air Temperature Distribution in Late Winter
This study investigates the distinct late winter Northern Hemisphere surface air temperature responses to Eastern Pacific (EP) and Central Pacific (CP) ENSO types. It finds that EP El Niño induces a "north cold, south warm" Eurasian temperature dipole, contrasting with a "north warm, south cold" pattern during CP El Niño, driven by differences in tropical Pacific convection and subsequent atmospheric wave trains.
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Han et al. (2025) Estimation of canopy fAPAR using optical reflectance and airborne LiDAR data
This study developed a physically-based model (fAPARRL) that integrates optical reflectance and airborne LiDAR data to improve the estimation of the fraction of absorbed photosynthetically active radiation (fAPAR), demonstrating superior accuracy and robustness compared to traditional vegetation index- and LiDAR-based methods.
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Lin et al. (2025) MJO Energy Budget Residuals in CMIP6: A Focus on Vertical Resolution
This study investigates how the vertical resolution of model output influences the Madden-Julian Oscillation (MJO)-related moist static energy (MSE) budget, finding that limited vertical levels in daily output lead to significant budget residuals due to overestimated vertical MSE advection caused by unrealistic dry static energy (DSE) gradients.
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Han et al. (2025) Assessing the effects of controlled drainage on regional hydrological cycle and crop waterlogging and drought based on a coupled agro-hydrological model
This study developed a coupled agro-hydrological model to assess the regional impacts of controlled drainage (CD) on hydrological cycles and crop water stress in the Huaihe River Basin, China. The research quantified how CD regulates groundwater-soil water interactions and crop yields across different precipitation regimes, proposing precipitation-specific management schemes to mitigate waterlogging and drought.
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Stephens et al. (2025) Corrigendum to “Substantial increases in burned area in circumboreal forests from 1983 to 2020 captured by the AVHRR record and a new autoregressive burned area detection algorithm” [Remote Sensing of Environment 325(2025) 114789]
This corrigendum addresses a data processing error in a previous study, which led to a slight overestimation of burned area in circumboreal forests from 1983 to 2020, and provides revised quantitative results while affirming the original conclusion of substantial increases in burned area.
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Li et al. (2025) Investigating the effect of urban form on land surface temperature at block and grid scales based on XGBoost-SHAP
This study integrates XGBoost-SHAP to investigate the effects of urban factor indexes (UFIs) on land surface temperature (LST) at block and grid scales, and across local climate zones (LCZs). It reveals seasonal and scale-dependent LST patterns, identifying key UFI contributors and specific thresholds for warming or cooling effects.
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Wang et al. (2025) Hybrid Gaussian process regression-based harmony assessment in a water–land–energy–food–carbon-emission coupled system
This study developed an improved Gaussian process regression model (AOA-L-BFGS-GPR) to assess the dynamic harmony of water–land–energy–food–carbon-emission (WLEFC) coupled systems. Applied to Heilongjiang Province, China, the research identified key obstacles and projected future harmony under different SSP pathways, demonstrating the framework's utility for sustainable agricultural development.
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Song et al. (2025) Modelling water and land resources synergy and trade-off in a major grain-producing area, China
This study develops a novel water-carbon-food-ecology (WCFE) nexus framework to spatially optimize water and land resource allocation in China's Sanjiang Plain. It demonstrates significant water savings, enhanced carbon sequestration, and improved ecological connectivity under both conventional and water-saving irrigation scenarios, albeit with a slight reduction in economic benefits.
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Nguyen et al. (2025) Toward real-time high-resolution fluvial flood forecasting: A robust surrogate approach based on overland flow models
This study presents a hybrid framework integrating machine learning with physics-based hydrodynamic models to enable efficient real-time high-resolution fluvial flood forecasting. It demonstrates that ML-based surrogate models, trained on TELEMAC outputs, achieve substantial computational efficiency while preserving accuracy for flood inundation prediction in the Cambodia floodplain.
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Chenevat (2025) Commande optimale de l'irrigation : Double modélisation mathématique et agronomique vers une application au modèle Optirrig
N/A (Paper text is unreadable)
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Kwon et al. (2025) Synoptic systems influence the effectiveness of spectral nudging in high-resolution simulations of extreme precipitation
This study investigates the effectiveness of spectral nudging (SN) in convection-permitting model simulations of warm-season extreme precipitation in South Korea, finding that SN improves simulations by maintaining synoptic circulations consistent with observations, with its effectiveness depending on synoptic conditions, domain size, and the dominant wave scales of the event.
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Ghosh et al. (2025) Optimal Configuration of a Convection-Permitting Regional Climate Model in Simulating Precipitation Extremes: The Saguenay Flood
This study evaluates the added value of convection-permitting (2.5 km) simulations and the impact of spectral nudging and initial soil moisture conditions on extreme precipitation characteristics using the CRCM6/GEM5 regional climate model for the July 1996 Saguenay flood. It finds significant improvements in reproducing precipitation extremes with the 2.5 km model, with spectral nudging enhancing spatial and temporal patterns, and initial soil moisture conditions improving rainfall intensity capture.
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Lima et al. (2025) STABLE: An open-source atmospheric blocking and subtropical ridge detection system
This paper introduces STABLE, an open-source Python algorithm for detecting and tracking atmospheric blockings (ABs) and subtropical ridges (SRs), demonstrating improved accuracy and adaptability over previous methods through validation with reanalysis data.
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Wu et al. (2025) Hotspots of summer heatwaves in East Asia and their associated radiative and dynamical forcing
This study classifies daily heatwave circulation over East Asia from 1979 to 2022, identifying three distinct hotspots, and quantitatively attributes their formation to specific atmospheric circulation patterns, cloud changes, water vapor, and atmospheric dynamics.
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Pappaccogli et al. (2025) MLUCM BEP + BEM: an offline one-dimensional multi-layer urban canopy model based on the BEP + BEM scheme
This study develops and validates MLUCM BEP + BEM, an offline one-dimensional multi-layer urban canopy model, demonstrating its reliable reproduction of urban surface-atmosphere fluxes with significantly reduced computational demands compared to coupled mesoscale models.
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Legarth et al. (2025) Characteristics of Extreme Precipitation and Flood Producing Atmospheric Rivers in the Alouette Watershed of British Columbia and the Development of a Modified Severity Scale
This study investigated the influence of various Atmospheric River (AR) characteristics on extreme precipitation and streamflow in the Alouette watershed, British Columbia, Canada, identifying key AR features like approach angle, Integrated Water Vapor Transport (IVT), rain-on-snow, and antecedent soil moisture as strong predictors of extreme streamflow, and recommending an enhanced AR severity scale for the region.
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Mishra et al. (2025) Assessment of EOS-07 MHS satellite observations and retrieval of specific humidity profiles using a random forest-based algorithm
This study presents a preliminary performance assessment of the EOS-07 MHS satellite instrument, validating its brightness temperature observations and developing a random forest-based algorithm for retrieving specific humidity profiles, which demonstrated good agreement with reanalysis and radiosonde data and improved atmospheric forecasts when assimilated into a numerical weather prediction model.
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Efrat et al. (2025) Modeling seasonal water status and predicting yield in almond orchards using UAV multi-sensor and meteorological data
This study developed a scalable framework integrating UAV multi-sensor, meteorological, and irrigation data with Random Forest models to accurately predict seasonal plant water status (Stem Water Potential, SWP; Trunk Growth Rate, TGR) and yield in almond orchards. The research revealed that distinct water stress profiles, identified by fuzzy clustering, are strongly linked to significant yield reductions, offering actionable insights for precision irrigation.
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Li et al. (2025) Ubiquity and Causes of Soil Water Preferential Flow Across 17 Ecoregions
This study quantifies the ubiquity and drivers of soil water preferential flow (PF) across 17 diverse ecoregions in the USA using high-frequency soil moisture data. It reveals that PF is widespread, occurring in up to 60% of rainfall events, and is primarily driven by peak rainfall intensity, soil texture, antecedent soil moisture variability, humid climate, and net primary productivity.
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Graff et al. (2025) Sensitivity of winter Arctic amplification in NorESM2
This study investigates the drivers of uncertainty in Arctic climate change projections by performing sensitivity experiments with NorESM2, modifying five key processes. The results show that these modifications consistently enhance future Arctic warming, with the amplitude of additional winter warming varying by approximately 9 K, primarily driven by an enhanced greenhouse effect.
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Luo et al. (2025) A framework for assessing the impact trends of neglecting water surface evaporation and substituting streamflow on water budget closure
This study introduces a framework to quantify the impact of neglecting water surface evaporation (WSE) and substituting runoff (R) for observed streamflow (Q) on water budget closure across 62 global river basins. It reveals that these practices introduce significant, context-dependent uncertainties, particularly when the water surface area ratio is high or in humid basins.
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Filippucci et al. (2025) Development of HYPER-P: HYdroclimatic PERformance-enhanced Precipitation at 1 km/daily over the Europe-Mediterranean region from 2007 to 2022
This study introduces HYPER-P, a high-resolution (1 km, daily) precipitation product for Europe and the Mediterranean basin (2007-2022), developed by downscaling and merging remote sensing, reanalysis, and in situ observations. The merged product, particularly the configuration including ERA5-Land, consistently outperforms individual parent datasets and reference products, especially in regions with sparse gauge coverage and complex topography.
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Zhao et al. (2025) The potential of AI global weather models for reference evapotranspiration forecasting: a comparison with numerical weather prediction models
This study evaluates the potential of AI global weather models (GraphCast) for daily reference evapotranspiration (ET0) forecasting in mainland China, comparing its performance against numerical weather prediction models (ECMWF, JMA) and demonstrating significant improvements through XGBoost post-processing. The GraphCast-XGBoost model is recommended for 1–7 day lead times.
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Colleoni et al. (2025) smash v1.0: a differentiable and regionalizable high-resolution hydrological modeling and data assimilation framework
This paper introduces smash v1.0, an open-source, differentiable, and regionalizable framework for high-resolution hydrological modeling and data assimilation. It demonstrates the framework's capabilities in local calibration (median Kling–Gupta efficiency > 0.8 at 3 km resolution) and regionalization (Kling–Gupta efficiency > 0.6 and Nash–Sutcliffe efficiency > 0.6 at 500 m resolution) across various scales and model structures.
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Shaw et al. (2025) Mountain glaciers recouple to atmospheric warming over the twenty-first century
This study assesses how temperature decoupling over mountain glaciers changes under warming, finding that local cooling is maximized in the 2020s-2030s before widespread glacier retreat leads to a recoupling of glacier air temperatures with their surroundings, increasing their sensitivity to warming.
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Pan et al. (2025) Capabilities of microwave-based soil moisture products in capturing extreme hydrological conditions
This study evaluates the capabilities of microwave-based soil moisture products in capturing both long-term average errors and short-term extreme hydrological events (droughts and floods). It finds that retrieval algorithms govern long-term accuracy, while L-band products are superior for detecting short-term extremes.
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Delhasse et al. (2025) Exploring the Greenland Ice Sheet’s response to future atmospheric warming-threshold scenarios over 200 years
This study uses a coupled regional atmospheric-ice sheet model (MAR-PISM) to project the Greenland Ice Sheet's response to various atmospheric warming scenarios and a climate reversal over 200 years, finding that warming beyond +1.4 °C triggers non-linear mass loss, but a rapid climate reversal can stabilize the ice sheet at a reduced state.
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Shi et al. (2025) Meter-level resolution surface soil moisture estimation over agricultural fields from time-series quad-pol SAR with constraints of coarse resolution CCI data products
This study developed a novel time-series L-band quad-polarimetric SAR algorithm, constrained by coarse-resolution soil moisture products, to estimate meter-level surface soil moisture over agricultural fields. The method achieved high accuracy, with root mean square errors ranging from 0.03 to 0.08 cm³/cm³ and correlation coefficients between 0.5 and 0.86 across various crop types.
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Darnell et al. (2025) The interplay of future emissions and geophysical uncertainties for projections of sea-level rise
This study disentangles the relative contributions of future CO2 emissions and geophysical uncertainties to sea-level rise projections, finding that emissions trajectories become the primary driver of variability by mid-century, while accelerated Antarctic Ice Sheet melting and equilibrium climate sensitivity are key geophysical uncertainties.
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Huerta et al. (2025) Enhancing daily precipitation reconstruction: An improved version of the reddPrec R package
This paper introduces an improved version of the reddPrec R package for daily precipitation reconstruction, featuring enhanced quality control, homogenization, and flexible machine learning models with dynamic covariates. Case studies in Switzerland and Spain demonstrate its superior accuracy in gap-filling and grid creation, and its effectiveness in detecting and adjusting data inhomogeneities.
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Béland (2025) Mapping wood area in forests from ground lidar and estimating their light interception using radiative transfer modeling
This study quantifies the partitioning of photosynthetically active radiation (PAR) and near-infrared radiation (NIR) absorption between leaves and woody structures in two broadleaf forests using ground lidar and radiative transfer modeling. It reveals that woody structures absorb 30–35 % of incoming NIR within the canopy space, while leaves account for approximately 90 % of absorbed PAR.
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Su et al. (2025) Unravelling the hidden drivers of crop sensitivity to precipitation in the arid and semi-arid regions of Northwest China
This study investigates the spatiotemporal sensitivity of maize and wheat to precipitation across the Loess Plateau from 2001 to 2023, revealing how aridity, soil texture, and elevated atmospheric CO₂ modulate crop responses and providing insights for adaptive agricultural management.
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Scheuerer et al. (2025) Multi-decadal streamflow projections for catchments in Brazil based on CMIP6 multi-model simulations and neural network embeddings for linear regression models
This study develops an interpretable linear regression model, enhanced with neural network embeddings, to link monthly streamflow anomalies to precipitation and temperature anomalies. The model is used to generate multi-decadal streamflow projections for 157 Brazilian catchments based on CMIP6 multi-model simulations, predicting reduced streamflow in northern/central/southeastern Brazil and increased streamflow in southern Brazil.
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Gou et al. (2025) Predicting land-surface specific humidity from radiative temperature and ambient weather for evapotranspiration modelling: Lessons from South Australian field sites
This study develops an empirical "Tr-Weather" method to estimate land-surface specific humidity using surface radiative temperature and ambient micrometeorological variables, demonstrating its superior performance for evapotranspiration (ET) modeling, especially under sunny conditions, compared to using ambient specific humidity.
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Mielke et al. (2025) GRACE‐FO and Future Satellite Gravity Missions Will Need to Account for Global Cloud Water Convergence
This study identifies and quantifies over 50,000 extreme cloud water mass change events globally from 2002 to 2023, demonstrating that these events, comparable in magnitude to water vapor variations, are detectable by GRACE-FO and show increasing frequency and intensity, necessitating their integration into gravity field processing for improved hydrological and climate research.
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Shang et al. (2025) A rainfall similarity-based dataset construction framework for enhanced urban inundation prediction using machine learning
This study proposes a rainfall similarity-based framework to construct high-quality datasets for machine learning models, significantly enhancing urban inundation prediction accuracy by incorporating process-oriented rainfall features. The framework improves predictive performance, with Random Forest models showing particular synergy and achieving inundation-extent accuracy exceeding 85 %.
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Sutanto et al. (2025) Future intensification of compound and consecutive drought and heatwave risks in Europe
This study projects the future intensification of single and compound/consecutive drought and heatwave events across Europe and their impacts in Germany under climate change scenarios, finding significant increases in event characteristics and impacts across multiple regions.
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Pradhan et al. (2025) Atmospheric Rivers intensify extreme precipitation and flooding across Australia
This study quantifies the impact of Atmospheric Rivers (ARs) on extreme precipitation and flooding across Australia, revealing that ARs significantly increase the magnitude (20–70% higher) and frequency (2 to 12 times shorter return periods) of these events, particularly in southeast Australia.
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Douglas et al. (2025) Effects of temperature overshoot amplitude on regional climate
This study investigates regional climate responses to global temperature overshoot scenarios, finding that while global temperature may be reversible, regional impacts on temperature and precipitation vary significantly and some extreme temperature changes persist for centuries, with the magnitude of overshoot being a critical factor.
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Meng et al. (2025) Soil salinity patterns reveal changes in the water cycle of inland river basins in arid zones
This study quantitatively analyzed soil salinization changes in the Shiyang River basin of Northwest China from 2002 to 2022 using remote sensing, revealing that human activities, particularly water conservancy projects and agricultural irrigation, are the primary drivers of intensifying salinization patterns.
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Saberian et al. (2025) HydroQuantum: A new quantum-driven Python package for hydrological simulation
This research introduces "HydroQuantum," a new Python package leveraging quantum computing for hydrological simulations. It demonstrates the potential of quantum algorithms, specifically QLSTM, for daily streamflow and stream water temperature simulations, showing promising results for streamflow but underperformance for stream water temperature compared to classical LSTM.
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Magnini et al. (2025) Informativeness of teleconnections in frequency analysis of rainfall extremes
This study proposes a reproducible framework to assess the informative content of teleconnections for regional frequency analysis of rainfall extremes in North-Central Italy. It identifies significant spatial patterns of correlation between specific climate indices (WeMOI, EA-WR) and rainfall extreme statistics, demonstrating that climate-informed regional models can improve the goodness-of-fit compared to stationary approaches.
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Zhao et al. (2025) Eco-evolutionary modelling of global vegetation dynamics and the impact of CO 2 during the late Quaternary: insights from contrasting periods
This study uses an eco-evolutionary optimality (EEO)-based modeling approach to quantify the relative impacts of climate fluctuations and CO2 levels on global vegetation dynamics and gross primary production (GPP) during the Last Glacial Maximum (LGM) and mid-Holocene (MH) compared to pre-industrial (PI) conditions. It reveals that low CO2 was nearly as important as climate in reducing GPP and increasing C4 plant abundance at the LGM, and it significantly offset positive climate impacts on GPP during the MH.
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Cao et al. (2025) Research on the Characteristics of the Convective Initiation During the Warm Season Over the Tibetan Plateau
This study investigates the temporal and spatial characteristics of convective initiation (CI) over the Tibetan Plateau during the warm season using FengYun-4A satellite data. It reveals that CI predominantly occurs on windward slopes, linked to monsoon activity, and exhibits distinct diurnal and day-night spatial patterns.
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Staudinger et al. (2025) How well do process-based and data-driven hydrological models learn from limited discharge data?
This study systematically compares the learning behavior of process-based and data-driven hydrological models under varying discharge data availability, selection strategies, and spatial input resolutions. It finds that while process-based models initially outperform data-driven ones with limited data, Long Short-Term Memory (LSTM) networks achieve superior and continuously improving performance with sufficient training data, demonstrating the critical role of data quantity, memory, and spatial input in model learning.
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Wang et al. (2025) Saudi Rainfall (SaRa): hourly 0.1° gridded rainfall (1979–present) for Saudi Arabia via machine learning fusion of satellite and model data
This paper introduces Saudi Rainfall (SaRa), a high-resolution, hourly, gridded precipitation product for the Arabian Peninsula developed using machine learning fusion of satellite and model data. SaRa significantly outperforms 19 other state-of-the-art precipitation products in the region across various evaluation metrics.
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Badawy (2025) Assessment of Vapour Pressure Deficit Trends and Their Connections to Climate Variability in the Nile Delta
This study analyzed three decades (1990–2020) of vapour pressure deficit (VPD) variability in Egypt's Nile Delta, revealing a statistically significant increase in atmospheric aridity driven primarily by rising air temperatures and decreasing relative humidity, with implications for agricultural resilience and water management.
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Teng et al. (2025) Can alternating irrigation technology drive water saving in agricultural irrigation? Evidence from China
This study empirically investigates the macro-level impact of Alternating Irrigation Technology (AIT) on agricultural irrigation water consumption (AIWC) across 31 provinces in China from 2004 to 2023. It finds that AIT significantly reduces AIWC, primarily by expanding effective irrigation areas and improving the effective irrigation rate of farmland, with the water-saving effect being more pronounced in major grain-producing areas and regions with higher R&D investment.
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Cohen et al. (2025) Reply to: Observed warming of cold extremes is not captured with a fixed threshold definition
This paper replies to a critique regarding the definition of cold extremes, re-examining trends in Arctic and mid-latitude cold extremes using a moving threshold definition, and concludes that the original findings of inconsistent warming in mid-latitude cold extremes remain robust.
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Wang et al. (2025) A flood susceptibility prediction method for climate change scenarios driven by coupled land simulation and spatiotemporal dual convolution synergy
This study develops a novel comprehensive framework coupling the PLUS model and a spatiotemporal dual attention network (STDAN) to dynamically predict flood susceptibility and land use changes under future CMIP6 climate scenarios. Applied to Shenzhen, the method projects an increase in flood susceptibility by 2030 across all scenarios compared to 2020, with the SSP585 scenario showing the highest increase.
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Yin et al. (2025) Distinct Eurasian Teleconnection Wave Trains Contributing to the Intraseasonal Variations of East Asian Jet Streams
This study reveals that intraseasonal variations of East Asian polar-front and subtropical jets are preceded by Eurasian wave trains originating from the Iceland and Norwegian Sea, with Atlantic Sea Surface Temperature (SST) anomalies playing a crucial role in stimulating these upstream Rossby wave sources.
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Rooij (2025) Fitting the junction model and other parameterizations for the unsaturated soil hydraulic conductivity curve: KRIAfitter version 1.0
This paper introduces and evaluates a novel "junction model" for unsaturated soil hydraulic conductivity (UHCC) that simplifies the conceptualization of water domains (films or capillaries) and documents the associated Fortran fitting code, KRIAfitter. The junction model often provides good fits to observed data with fewer parameters compared to existing multi-domain models, offering a more parsimonious alternative, though some complex soil behaviors may still require models with more parameters.
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Wang et al. (2025) Multi-scale evaluation of six fused evapotranspiration products over mainland China: Accuracy, consistency and uncertainty
This study comprehensively evaluates the accuracy, consistency, and uncertainty of six fused evapotranspiration (ET) products over mainland China from 1982 to 2017, revealing that AutoML performs best at the site scale while REA exhibits the lowest uncertainty.
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King et al. (2025) ESD Ideas: Extended net zero simulations are critical for informed decision making
This paper argues that extended, millennial-length Earth System Model simulations of net zero emissions are crucial for understanding long-term committed climate changes, particularly regional extremes and the impact of delayed emissions cessation, to inform robust policymaking.
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Sun et al. (2025) Causal pathways underlying global soil moisture–precipitation coupling
This study employs an information flow technique on satellite observations and reanalysis data to map global surface soil moisture-precipitation (SSM-P) coupling hotspots and identify the dominant sensible heat or evapotranspiration-mediated causal pathways, revealing that most CMIP6 models fail to reproduce these patterns.
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Vaccaro et al. (2025) Assessing microtensiometers for monitoring stem water potential in mandarin (Citrus reticulata Blanco) orchard under different irrigation regimes
This study assessed the reliability of microtensiometers (MTs) for continuous stem water potential (Ψstem) monitoring in a mandarin orchard under two irrigation regimes. It found MTs promising for real-time monitoring, but their first-order response dynamics (characterized by significant time lags and signal attenuation) necessitate the development of compensation protocols for direct application of readings to existing crop-specific Ψstem thresholds.
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Yuan et al. (2025) Enhancing runoff prediction with causal lag-aware attention and multi-scale fusion in transformer models
This study addresses the non-causal issue in Transformer models for runoff prediction by proposing a novel Causal Lag-Aware Attention Mechanism, a multi-scale fusion module, and a frequency-domain-based loss function, achieving significant improvements in prediction accuracy over existing state-of-the-art Transformer models.
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Yue et al. (2025) The Unevenness of Warm‐Season Precipitation Over the Steep Terrain in North China and Its Related Environmental Conditions
This study investigates the underlying mechanisms governing the spatial unevenness of precipitation over complex terrains in North China, identifying distinct environmental conditions and fine-scale characteristics for strongly uneven (terrain-influenced, convective) versus weakly uneven (synoptic-driven, widespread) precipitation events.
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Xu et al. (2025) Three decades evolution of land subsidence driven by anthropogenic activities in the Yellow River Delta (YRD) from continuous SAR interferometry
This study developed a novel Trend-Adaptive Functional Modeling and Connection method (TAFMC) to integrate multi-sensor InSAR time series, enabling the first continuous, three-decade (1992-2024) monitoring of land subsidence in the Yellow River Delta (YRD) and revealing its evolution driven by anthropogenic activities. It found subsidence up to 220 cm, with rates decreasing after 2021, and identified new subsidence funnels linked to the brine industry and shrimp aquaculture.
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Blackport et al. (2025) Observed warming of cold extremes is not captured with a fixed threshold definition
This paper demonstrates that the previously reported lack of warming trends in mid-latitude cold extremes by Cohen et al. (2023) is an artifact of using a fixed threshold definition. By employing a moving threshold, this study reveals clear and statistically significant warming trends in cold extremes, consistent with overall climate warming.
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Ning et al. (2025) Atmospheric Freezing Level Height Changes
This study updates global freezing level height (FLH) changes to 2023 using observations and models, revealing significant FLH increases, particularly in extra-tropical and high northern latitudes, which are linked to accelerated glacier mass loss driven by tropical sea surface temperature variability.
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Zhang et al. (2025) Characterizing snow droughts and deluges in the Sacramento River Basin, California using GNSS-derived snow depth (2009–2023)
This study retrieves daily snow depth using GNSS Interferometric Reflectometry (GNSS-IR) at four stations in the Sacramento River Basin (2009–2023) to characterize snow droughts and deluges, revealing that 57.1 % of snow drought events exhibited compound characteristics driven by both precipitation and temperature anomalies.
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Gao et al. (2025) Climate change and human activities amplify runoff variability risks in lower reaches of large rivers
This study developed a three-tiered attribution framework to analyze spatiotemporal runoff variations and their drivers in the Yellow River Basin (1952–2021), revealing that cumulative climatic and, predominantly, human activities amplify runoff variability risks in downstream regions with significant seasonal fluctuations.
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Li et al. (2025) Damage intensity increases ice mass loss from Thwaites Glacier, Antarctica
This study incorporates ice damage processes into an ice-sheet model for the Thwaites Glacier basin, demonstrating that explicitly accounting for ice damage significantly increases projected ice mass loss, more than doubling it by 2300 compared to simulations that neglect damage.
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Hong et al. (2025) The Effects of Ice Habit Models on Passive Microwave Snowfall Rate Retrievals
This study investigates the significant impact of ice habit models on snowfall rate (SFR) derived from space-borne passive microwave observations, revealing that an optimal ice habit choice is environmentally dependent. It proposes a machine learning model that integrates multiple ice habits, improving SFR retrieval accuracy by approximately 10% overall.
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Li et al. (2025) Revisiting the Role of Ocean Circulation Changes in Polar Ocean Heat Transport Anomalies under Global Warming
This study introduces a novel passive-active decomposition to re-evaluate the contributions of ocean circulation and passive ocean temperature changes to polar ocean heat transport anomalies, demonstrating that circulation changes have a significantly weaker effect than inferred from the standard decomposition.
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Liang et al. (2025) Reducing Uncertainty in Climate Projections for the Mid and High Latitudes of the Northern Hemisphere
This study applies emergent constraints derived from observed global warming and Arctic sea ice loss to significantly reduce uncertainty in projected air temperature and precipitation changes over Northern Hemisphere mid-to-high latitude land areas.
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Du et al. (2025) Regional Variability in Summer Extreme Precipitation over Northern China and Associated Atmospheric Teleconnections from 1961 to 2022
This study comprehensively analyzes summer extreme precipitation in northern China from 1961 to 2022, revealing distinct regional trends and underlying atmospheric and oceanic drivers. It finds a significant increase in extreme precipitation in western northern China, while eastern northern China shows no significant changes, with different large-scale circulation patterns and North Atlantic sea surface temperature anomalies modulating each region.
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Yeo et al. (2025) Trends and Climate Sensitivity of Precipitation Correlation Distances Across the Contiguous U.S.
This study quantifies changes in the length scale of seasonal precipitation correlations across the contiguous United States from 1950 to 2019, revealing significant decreases in summer precipitation correlation distance in several regions, which indicates increased spatial variability.
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Koster et al. (2025) Investigations into the Subseasonal Predictability of Soil Moisture and Streamflow
This study investigates the subseasonal predictability of soil moisture and streamflow using an offline land modeling system forced by S2S forecasts. It finds that the offline system's hydrological forecasts are comparable in skill to fully coupled S2S systems, with skill influenced by soil column depth and improved streamflow forecasts achievable through climatological precipitation forcing.
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Sardeshmukh et al. (2025) Learning ENSO Dynamics from Data
This study estimates the relative roles of dominant positive and negative feedbacks on El Niño–Southern Oscillation (ENSO) directly from observational data, revealing a critical competition between destabilizing positive feedbacks (zonal wind, subsurface ocean) and a stabilizing negative surface shortwave flux feedback due to cloud shielding, which primarily renders ENSO asymptotically stable.
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Chen et al. (2025) Impact of El Niño‐Southern Oscillation and Madden‐Julian Oscillation on the US Puget Sound Regional Hydroclimate
This study investigates the connections of El Niño–Southern Oscillation (ENSO) and Madden–Julian Oscillation (MJO) to hydroclimate conditions and extremes in the Puget Sound basin. It finds that ENSO significantly modulates cold season temperature and runoff, leading to snow drought, while MJO phases 6–7 trigger extreme precipitation, temperature, snowmelt, and runoff at short lags, offering potential for improved regional water resource prediction.
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Brivoal et al. (2025) Implementation of an intermediate-complexity snow-physics scheme (ISBA-Explicit Snow) into a sea ice model (SI 3 ): 1D thermodynamic coupling and validation
This study implements an intermediate-complexity snow-physics scheme (ISBA-Explicit Snow) into the SI3 sea ice model, validating its 1D thermodynamic coupling against observations and another advanced snow model. The coupled model realistically simulates dynamic snow properties, leading to more accurate snow-ice interface temperatures and heat transfer compared to simpler schemes.
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Wang et al. (2025) Satellite observations reveal ecosystem resistance and resilience to short-term water stress driven by dominant vegetation along a rainfall gradient in Australia
This study quantified ecosystem resistance and resilience to short-term water stress (2000-2018) along Australia's North Australian Tropical Transect using satellite-derived GPP and flux tower data. It found that resistance and resilience patterns are primarily driven by dominant vegetation types along the rainfall gradient, with semi-arid grasslands exhibiting low resistance but high resilience, while mesic woody savannas and arid shrublands show higher resistance but lower resilience.
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Oh et al. (2025) Scalable, adaptive and risk-informed design of hydrological sensor networks
This study introduces a data-driven framework for designing streamflow monitoring networks that enhances hydrological predictions and integrates socio-environmental constraints. The framework, utilizing rank-revealing QR decomposition, demonstrates superior streamflow reconstruction at ungauged locations compared to existing methods, while also being scalable and adaptable to flood risk.
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Zhang et al. (2025) A seamless global daily 5 km soil moisture product from 1982 to 2021 using AVHRR satellite data and an attention-based deep learning model
This study generated a consistent and seamless global daily 5 km surface soil moisture (0–5 cm) product spanning 1982–2021 using an attention-based deep learning model (AtLSTM) trained with AVHRR satellite data and other multi-source inputs. The resulting GLASS-AVHRR SM product demonstrates superior accuracy, spatiotemporal completeness, and richer spatial details compared to existing long-term global soil moisture datasets.
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Yan et al. (2025) Intensifying impacts of compound drought and heatwave events on water use efficiency in U.S. corn and soybean
This study investigates the spatiotemporal impacts of compound drought and heatwave events on U.S. corn and soybean water use efficiency (WUE) from 1960 to 2018, finding significant reductions in WUE (corn: 14.7%, soybean: 11.3%) and intensifying adverse effects in substantial production areas over time.
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Martel et al. (2025) Exploring the ability of LSTM-based hydrological models to simulate streamflow time series for flood frequency analysis
This study investigates six methods to improve the peak streamflow simulation skill of Long Short-Term Memory (LSTM) models for flood frequency analysis (FFA) in ungauged catchments. It demonstrates that hybrid LSTM-hydrological model implementations can simulate peak streamflow as well as, or better than, traditional distributed hydrological models.
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Shao et al. (2025) Varying flood exposure due to uncertain data of flood hazard and population distribution
This study comparatively assessed flood exposure in China using 25 combinations of five population and five flood hazard datasets, revealing substantial variations in exposure estimates primarily driven by flood hazard data differences, while consistently showing a disproportionately high population share in floodplains.
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Liu et al. (2025) Understanding copula-based multivariate standardized drought indices for characterizing meteorological, hydrological and agricultural droughts across global land areas
This study systematically evaluates the Copula-based Multivariate Standardized Drought Index (CMSDI) for characterizing meteorological, hydrological, and agricultural droughts across global land areas, demonstrating its applicability and reliability in monitoring diverse composite drought conditions using bivariate and vine copulas.
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Lu et al. (2025) Deficit irrigation alleviates the increase in soil salinity content in saline-alkali regions of China and improves irrigation water productivity: A meta-analysis
This meta-analysis investigated the effects of deficit irrigation (DEI) on soil salinity content, crop yield, and irrigation water productivity (IWP) in saline-alkali regions of China, finding that DEI significantly increased IWP by 29.77% while slightly increasing soil salinity by 2.52% and decreasing crop yield by 6.77%. The study identified optimal DEI strategies based on irrigation practices, climatic conditions, and soil properties using machine learning.
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Khanam et al. (2025) Predictive understanding of socioeconomic flood impact in data-scarce regions based on channel properties and storm characteristics: application in High Mountain Asia (HMA)
This study introduces a novel geomorphologically guided machine learning method to predict socioeconomic flood impacts in data-scarce regions. Applied to High Mountain Asia (HMA), the model effectively identifies flood susceptibility hotspots and their evolution from 1980 to 2020, demonstrating its versatility for ungauged areas.
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Katata et al. (2025) Reconstruction of the Background Air Temperature Record in Japan (1916–2023): Implications for Climate Change and Urbanisation Bias in the 20th Century
This study reconstructed long-term annual mean temperature trends in rural Japan (1916-2023) using newly digitized data, revealing a lower warming rate (+0.11 °C per decade) compared to JMA stations (+0.15 °C per decade) due to urbanization bias, and uncovering a significant climatic jump (decreasing trend) in the 1960s after bias removal.
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Zhang et al. (2025) Quantifying the relative importance of factors influencing rainfall partitioning in a rainfed apple orchard
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Kamali et al. (2025) Evaluating the environmental and economic effects of groundwater quotas and markets using multi-agent system simulation and centralized optimal model
This study evaluates the environmental and economic impacts of groundwater quotas and markets in the Ardabil Plain, Iran, using a multi-agent system simulation (MASS) model and a centralized optimal model (COM). It finds that decentralized, self-interested agents under uniform quotas perform poorly compared to a centralized optimal approach, while permit trading can enhance economic benefits and, in some scenarios, reduce environmental violations.
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Park et al. (2025) Arctic stratospheric ozone as a precursor of ENSO events since 2000s
This study reveals a significant shift in the relationship between Arctic stratospheric ozone (ASO) and El Niño–Southern Oscillation (ENSO) since the 2000s, demonstrating that springtime ASO variations now serve as a precursor to subsequent winter ENSO events via a Eurasian teleconnection pathway.
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Dhote et al. (2025) Unveiling the First Impressions of the Wide‐Swath Altimetry SWOT Mission Over the Ganga River, India
This study evaluates the performance of Surface Water and Ocean Topography (SWOT) mission's node and raster products for river hydrodynamics over a 210 km stretch of the Ganga River, finding varying accuracies for water surface elevation and slope, with node products generally more accurate for WSE but raster products providing better spatial detail.
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Hossan et al. (2025) Retrieval and validation of total seasonal liquid water amounts in the percolation zone of the Greenland ice sheet using L-band radiometry
This study presents a microwave retrieval algorithm for quantifying total seasonal liquid water amounts (LWA) in the Greenland Ice Sheet's percolation zone using NASA SMAP L-band radiometry. The retrieved LWA shows good agreement with two independent energy and mass balance models, demonstrating the potential for advancing understanding of ice sheet melt processes and improving sea level rise projections.
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Cai et al. (2025) Boreal forest cover change since 2000 contributes to cold winters in Eurasia
This study investigates the impact of observed boreal forest cover change (2000-2020) on winter climate using an Earth System Model, revealing that afforestation in western Europe drives Eurasian winter cooling by enhancing snow-albedo feedback, stimulating planetary waves, and weakening the stratospheric polar vortex.
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Bianchi et al. (2025) Synchrony of Wind, Solar and Hydroelectric Resources Over Argentina and Its Climatic Drivers
This study comprehensively analyzes the interannual complementarity of wind, solar, and hydroelectric resources in Argentina over 38 years, assessing the impact of low-frequency ocean-atmosphere variations. It finds limited complementarity with the current spatial distribution of renewable capacity, emphasizing the significant control of climatic drivers and the need for alternative spatial schemes for future energy development.
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Wang et al. (2025) Polarised Changes in Sub‐Daily Precipitation Extremes and Underlying Mechanisms Over Southwest China in a Warmer Climate
This study statistically analyzed sub-daily precipitation extremes (SPEs) over Southwest China from 1971–2024, revealing simultaneous increases in both wet and dry SPEs driven by atmospheric circulation changes and thermodynamic factors in a warming climate.
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Cruz‐Pérez et al. (2025) Climate Projections and Temperature Evolution in the Canary Islands: High Resolution Analysis at Island Scale
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Guo et al. (2025) The inclusion of time-lag response reveals contrasting effects of meteorological and agricultural drought on agroecosystem water use efficiency in Africa
This study disentangles the contrasting time-lag effects of meteorological and agricultural droughts on agroecosystem water use efficiency (WUE) in Africa, revealing agricultural drought as the predominant contributor with a longer time-lag and distinct thresholds for abrupt shifts in WUE.
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Mu et al. (2025) Waveguide Teleconnection Mechanisms Driving Summer Compound Heat‐Humidity Extremes in China Land Monsoon Region
This study reveals consistently increasing trends of summer compound heat-humidity extremes (CHHEs) across the China Land Monsoon (CLM) region from 1961–2022, attributing this rise to a weakening British Okhotsk Corridor (BOC)-Silk Road Pattern (SRP) nexus since 2000, which is modulated by North Atlantic sea surface temperature anomalies.
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Deng et al. (2025) Economic consequences of cascading drought-flood events: evidence from central Europe
This study empirically compares cascading drought-flood events (CDFEs) with flood-only events (FEs) in Central Europe, revealing that CDFEs are associated with significantly higher streamflow, deeper water depths, and greater economic losses.
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Filipiak et al. (2025) Assessing Dynamic and Thermodynamic Variability in Initial and Boundary Conditions for Snowstorm Prediction in the Northeast United States
This study investigated the impact of different initial condition sources on winter precipitation prediction in the Northeast United States, finding that relative humidity variability in initial and boundary conditions was the primary source of uncertainty in model simulations, heavily influencing precipitation accumulation discrepancies.
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He et al. (2025) A novel index for directly indicating fractional vegetation cover based on spectral differences between vegetation and soil
This study introduces the Vegetation Coverage Index (VCI), a novel remote sensing index designed for directly estimating fractional vegetation cover (FVC) by leveraging spectral differences between vegetation and soil. VCI demonstrates comparable or superior accuracy to existing methods, particularly in the presence of non-photosynthetic vegetation, and exhibits broad applicability across various satellite sensors.
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Laly (2025) Lidars mobiles pour la mesure de la vapeur d'eau et les applications météo-climatiques
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Pradhan et al. (2025) Diurnal variability of global precipitation: insights from hourly satellite and reanalysis datasets
This study comprehensively intercompared the diurnal variability of global precipitation using five state-of-the-art hourly satellite and reanalysis datasets, revealing consistent broad spatial patterns but significant regional uncertainties in precipitation amount, frequency, and intensity, particularly at higher latitudes.
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Song et al. (2025) TIF: A time-series-based image fusion algorithm
This study developed the Time-series-based Image Fusion (TIF) algorithm to generate 10-meter surface reflectance time series by synthesizing Landsat 8/9 and Sentinel-2 A/B data. TIF consistently outperformed state-of-the-art methods in accuracy and efficiency, offering a practical pathway for creating 10-meter Harmonized Landsat and Sentinel-2 (HLS) products for fine-scale Earth observations.
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Unknown (2025) Natural land disturbances are worsening but humans are not off the hook
High-resolution satellite maps of the contiguous USA over 35 years reveal a fundamental shift in land disturbances, showing a decrease in human-directed disturbances while 'wild' disturbances (e.g., fire, vegetation stress, wind, geohazards) are surging, alongside evolving patterns in their frequency, size, and severity.
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Chen et al. (2025) Global patterns and trends of vegetation water use efficiency inferred from solar-induced chlorophyll fluorescence from 2001 to 2020
This study developed a novel satellite-based framework integrating solar-induced chlorophyll fluorescence (SIF) and plant physiological theory to globally assess vegetation (WUET) and ecosystem (WUE) water use efficiency from 2001 to 2020. It revealed distinct global trends for WUET and WUE, attributing them to CO2 fertilization, vapor pressure deficit, and vegetation structure, and projected future changes under climate scenarios.
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Dommo et al. (2025) Assessment of Anticipated Changes in Extreme Temperature and Precipitation Under 1.5°C and 2°C Warming Over the Mississippi River Basin
This study analyzes projected changes in extreme precipitation and temperature indices over the Mississippi River Basin under 1.5°C and 2°C global warming scenarios and two Shared Socio-economic Pathways, finding an exacerbation of most extreme events, significant sensitivity to warming levels and emission scenarios, and a predominant contribution of internal climate variability to total uncertainty.
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Zhou et al. (2025) Unraveling nonlinear urban waterlogging responses to rainfall structure: A data-driven analysis in a highly urbanized megacity
This study investigates the nonlinear relationships between rainfall structure and urban waterlogging in Shanghai using a long-term dataset and data-driven models. It reveals that short-term rainfall intensities, temporal asymmetry, and peak-mean ratios are more critical drivers of waterlogging than total rainfall volume, exhibiting complex non-monotonic and threshold effects.
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Brunner et al. (2025) Spatially Compounding Drought‐Flood Events Are Favored by Atmospheric Blocking Over Europe
This study investigates the occurrence, seasonality, and large-scale atmospheric drivers of spatially compounding drought-flood events across Europe using streamflow and precipitation observations. It reveals that these events exhibit strong seasonality, occurring most frequently in winter, spring, and June, and are primarily favored by specific blocking and Zonal weather regimes.
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Wang et al. (2025) Estimation and mechanism analysis of global evapotranspiration based on a physics-informed deep-learning model
This paper introduces a physics-informed deep-learning model, Self-attention Influence (SAI), for global evapotranspiration (ET) estimation, demonstrating superior spatial extrapolation and robustness, especially in data-poor regions, and providing explainable insights into ET mechanisms and climate impacts.
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Liu et al. (2025) The CO 2 Balancing Act: Why Global Warming and Greening Don't Dry Earth as Much as We Thought
This study develops a novel physical model to quantify the complex interplay between evapotranspiration, atmospheric CO₂ concentration, and climate/vegetation changes, revealing that CO₂-induced stomatal closure significantly offsets global terrestrial drying effects from warming and greening, thereby exposing systematic biases in traditional drought indicators.
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Xiao et al. (2025) Modeling Dynamic Flood Population Exposure in Coupled Human‐Water Systems: The Role of Reservoir Regulation and Population Movement
This study calculates dynamic flood population exposure by integrating hydrological modeling with human mobility data, revealing that reservoir operations reduce hazard levels for a portion of the exposed population and that nighttime flood exposure significantly surpasses daytime levels due to diurnal population fluctuations.
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Wondzell et al. (2025) Rethinking Paired‐Catchment Studies: Should We Be Replicating Our Controls?
This paper addresses the statistical uncertainty in paired-catchment studies by developing a bootstrapped sampling method using reference-by-reference comparisons to determine minimum detectable effect sizes (MDES) for changes in streamflow.
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Feng et al. (2025) Linkages of Multiple Types of Compound Droughts and Hot Events at the Global Scale
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He et al. (2025) APPLE-GO: Modeling high-spatial resolution forest canopy reflectance with effect of Adjacent Pixels using Path Length Extended Geometric Optical theory
This study introduces APPLE-GO, a novel high-spatial resolution forest canopy reflectance model that comprehensively accounts for shading and cross-radiation effects from adjacent pixels. The model demonstrates high accuracy in calculating the bi-directional reflectance factor (BRF), validated against a 3D radiative transfer model and satellite observations.
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Yin et al. (2025) Addressing Data Imbalance in Hydrological Machine Learning: Impact of Advanced Sampling Methods on Performance and Interpretability
This study evaluates advanced sampling methods, particularly feature space coverage sampling (FSCS), in hydrological machine learning applications to address data imbalance. It demonstrates that FSCS significantly enhances model accuracy, feature importance estimation, and interpretability for predicting forest cover types and saturated hydraulic conductivity, even with smaller training sets.
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Xu et al. (2025) A One‐Dimensional Variational Precipitation Retrieval Algorithm Considering Cloud Types for Western North Pacific Tropical Cyclones Using FengYun‐3E Microwave Sounders
This study develops an enhanced one-dimensional variational (1DVAR) precipitation retrieval algorithm for tropical cyclones using Chinese FengYun-3E (FY-3E) passive microwave observations. The algorithm significantly improves retrieval accuracy and reduces systematic bias by incorporating precipitation-type differentiation and utilizing the Advanced Radiative Transfer Modeling System (ARMS) as the forward operator.
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D’Odorico et al. (2025) Deciphering tree drought responses across species: linking leaf water potentials with remote sensing greenness and photoprotection dynamics
This study investigated the drought responses of seven common European tree species in a temperate forest, integrating drone-based multispectral imagery with leaf water potential and pigment measurements. It found that the Photochemical Reflectance Index (PRI) strongly correlated with leaf water potentials, capturing both drought-induced declines and post-rainfall recovery, while the Normalized Difference Vegetation Index (NDVI) primarily detected greening losses in some species but failed to reflect recovery.
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Boers et al. (2025) Destabilization of Earth system tipping elements
This review demonstrates how interactions between Earth system tipping elements can generate spurious signals and mask genuine signs of destabilization. It presents observation-based evidence that the stability of the Greenland Ice Sheet, Atlantic Meridional Overturning Circulation, South American monsoon system, and Amazon rainforest has declined in recent decades, suggesting they are nearing critical thresholds.
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Tong et al. (2025) Evolution and prediction of drought-flood abrupt alternation in mainland China using an improved index
This study develops and validates a daily Drought-Flood Abrupt Alternation Index (DFAI) to overcome limitations of monthly indices, revealing increased DFAA frequency and intensity across mainland China from 1961–2022 and projecting intensified events under future climate change scenarios despite stable or decreasing frequency.
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Brennan et al. (2025) Insights from hailstorm track analysis in European climate change simulations
This study investigates the impact of a 3 K global warming scenario on European hailstorms using kilometer-scale climate simulations and an object-based tracking algorithm. It reveals significant shifts towards more intense hailstorms with larger hail diameters, expanded swath areas, and increased associated hazards (precipitation, wind), driven by enhanced convective available potential energy and specific humidity.
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Engdahl (2025) Impacts of Uncertain Permeability Fields on the Transient Hydrologic Response in Coupled Surface‐Subsurface Simulations of a Headwaters Catchment
This study assesses the confidence of an Integrated Hydrologic Model (IHM) simulation of a first-order basin under transient conditions, using an ensemble of 250 permeability realizations and varying recharge signals. It finds high confidence in surface water simulations but lower confidence in groundwater, with groundwater uncertainty decreasing over time after a recharge increase, and determines the ensemble sizes needed for convergence.
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Rondeau‐Genesse et al. (2025) Storyline analytical framework for understanding future severe low-water episodes and their consequences
This study develops a storyline analytical framework to project the impacts of future severe low-water episodes in Quebec, based on the 2021 drought, under +2 °C and +3 °C global warming scenarios, revealing significant deterioration in river conditions and extended low-water durations.
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Soundharajan et al. (2025) A Meta‐Analysis to Disentangle the Impacts of Climate and Land Use Changes on Streamflow
This meta-analysis quantitatively assesses the individual and combined impacts of precipitation, temperature, and land use/land cover (LULC) changes on streamflow. It finds that precipitation is the dominant driver, explaining nearly half of streamflow variance, followed by nuanced LULC effects (agriculture increases, forests decrease), while temperature has a minimal and inconsistent influence.
