Results 181 to 190 of about 94,605 (282)

The Impact of OCO‐2 Seasonally Dependent Sampling on Carbon Flux Estimation in the Northern Tropical Africa

open access: yesGeophysical Research Letters, Volume 53, Issue 4, 28 February 2026.
Abstract The large annual carbon source over northern tropical Africa (NTA), inferred from satellite CO2, remains highly debated. Using observing system simulation experiments with Orbiting Carbon Observatory‐2 (OCO‐2) sampling, we show that seasonally dependent sampling can lead to overestimated annual fluxes.
Junjie Liu   +4 more
wiley   +1 more source

Evaluation of GFSv16 for Near‐Real‐Time Data Impact Studies During the Atmospheric River Reconnaissance Program 2022

open access: yesJournal of Geophysical Research: Atmospheres, Volume 131, Issue 4, 28 February 2026.
Abstract Landfalling Atmospheric Rivers (ARs) are crucial for the water resources on the U.S. West Coast, but can also cause hazardous weather and water events there. Yet, accurately predicting AR impacts on precipitation remains a challenge. This study investigates the influence of dropsonde data from AR Reconnaissance (AR Recon) on improving weather ...
Vijay Tallapragada   +13 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

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

open access: yesAdvanced Functional Materials, Volume 36, Issue 13, 12 February 2026.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva   +9 more
wiley   +1 more source

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