Results 211 to 220 of about 266,877 (389)

Frozen Soil Hydrological Processes and Their Effects: A Review and Synthesis

open access: yesReviews of Geophysics, Volume 64, Issue 1, March 2026.
Abstract Frozen soils, including seasonally frozen ground and permafrost, are rapidly changing under a warming climate, with cascading effects on water, energy, and carbon cycles. We synthesize recent advances in the physics, observation, and modeling of frozen‐soil hydrology, emphasizing freeze–thaw dynamics, infiltration regimes and preferential flow,
Ying Zhao   +12 more
wiley   +1 more source

Glacier‐Atmosphere Interactions and Feedbacks in High‐Mountain Regions ‐ A Review

open access: yesReviews of Geophysics, Volume 64, Issue 1, March 2026.
Abstract Mountain glaciers are among the natural systems most vulnerable to climate change. However, their interactions with the atmosphere are complex and not fully understood. These interactions can trigger rapid adjustments and climate feedbacks that either amplify or attenuate atmospheric signals, influencing both glacier response and large‐scale ...
T. Sauter   +17 more
wiley   +1 more source

How Can FengYun—3G Satellite Precipitation Radar and Microwave Imager Unveil Multi—Phase Hydrometeors?

open access: yesGeophysical Research Letters, Volume 53, Issue 3, 16 February 2026.
Abstract The observations from Precipitation Measurement Radar (PMR) and Microwave Radiation Imager (MWRI‐RM) onboard FengYun‐3G satellite are first time utilized to derive multi‐phase hydrometeors in clouds. The FY‐3G hydrometeor retrieval algorithm utilizes the Advanced Radiative Transfer Modeling System (ARMS) as its core module. It incorporates PMR‐
Linjun Han, Fuzhong Weng, Xiuqing Hu
wiley   +1 more source

Deep Learning Atmospheric Models Reliably Simulate Out‐of‐Sample Land Heat and Cold Wave Frequencies

open access: yesGeophysical Research Letters, Volume 53, Issue 3, 16 February 2026.
Abstract Deep learning (DL)–based general circulation models (GCMs) are emerging as fast simulators, yet their ability to replicate extreme events outside their training range remains unknown. Here, we evaluate two such models—the hybrid Neural General Circulation Model (NGCM) and purely data‐driven Deep Learning Earth System Model (DLESyM)—against a ...
Zilu Meng   +3 more
wiley   +1 more source

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