Results 141 to 150 of about 1,316 (257)

Kilometer-scale convection-allowing model emulation using generative diffusion modeling. [PDF]

Sci Adv
Pathak J, Cohen Y, Garg P, Harrington P, Brenowitz N, Durran D, Mardani M, Vahdat A, Xu S, Kashinath K, Pritchard M.   +10 more
europepmc   +1 more source

High‐Resolution Particle Imaging Reveals the Importance of Phytodetrital Aggregate Flux and Mesopelagic Grazing for Carbon Storage in the Southern Ocean

Global Biogeochemical Cycles, Volume 40, Issue 8, August 2026.
Abstract The biological, chemical, and physical processes in the mesopelagic zone that impact carbon flux to the deep ocean are poorly understood, particularly in the Southern Ocean, despite their importance to deep ocean carbon storage. Using a CTD‐mounted underwater imaging system, the Underwater Vision Profiler 5, we observed distributions of large ...
S. H. O’Daly, G. M. M. Hennon, T. B. Kelly, R. Kiko, R. M. Lekanoff, J. L. Pretty, S.‐M. Schröder, A. M. P. McDonnell   +7 more
wiley   +1 more source

Improved wildfire smoke exposure estimates for human health studies in the western United States. [PDF]

Air Pollut Model Appl
Holmes HA, Faulstich SD, Lee J, Riss CS, Loría-Salazar SM, Strickland MJ.   +5 more
europepmc   +1 more source

Estimating Submesoscale‐Driven Particulate Organic Carbon Flux From Remote Sensing at a Dynamic Upwelling Front

Journal of Geophysical Research: Oceans, Volume 131, Issue 8, August 2026.
Abstract Submesoscale (1–10 km) vertical velocities at fronts enhance the exchange of particulate organic carbon (POC) and heat between the surface ocean and depth. While POC and temperature can be readily assessed in situ, direct quantification of flux remains uncertain due to the observational challenges of measuring submesoscale vertical velocities ...
Sarah E. Lang, Melissa M. Omand, Mara A. Freilich, Andrey Y. Shcherbina, J. Thomas Farrar, Leo Middleton, Ernesto Rodríguez   +6 more
wiley   +1 more source

Oceanic memory of tropical cyclones moderates the Kuroshio current. [PDF]

Nat Commun
Zhang D, Ma Z, Cheng L, Lin Y, Xu F, Zhang Z, Zheng Y, Fei J, Mann ME.   +8 more
europepmc   +1 more source

YOLO‐Based Detection and Localization of Rocket Induced Traveling Ionospheric Disturbances

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract During rocket launches, atmospheric disturbances significantly impact the ionosphere, generating Traveling Ionospheric Disturbances (TIDs). These disturbances can affect radio communications and navigation systems and may pose risks to high‐speed aerospace vehicles.
Zhou Chen, Jiahao Zeng, Jing‐Song Wang, Yan Guo, Cunqun Fan, Fabao Yan, Hui Zhu   +6 more
wiley   +1 more source

A Multi-Source Sensor Dataset for Spain: Integrating Air Quality, Meteorological, Mobility and Calendar Records. [PDF]

Sensors (Basel)
Bonastre-Egea J, Bueno-Crespo A, Morales-García J.   +2 more
europepmc   +1 more source

OceanForecastBench: A Benchmark Data Set for Data‐Driven Global Ocean Forecasting

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Global ocean forecasting aims to predict key ocean variables such as temperature, salinity, and currents, which is essential for understanding and describing oceanic phenomena. In recent years, data‐driven deep learning‐based ocean forecast models, such as XiHe, WenHai, LangYa and AI‐GOMS, have demonstrated significant potential in capturing ...
Yi Han, Haoming Jia, Xiang Wang, Huizan Wang, Wei Wu, Jianming Zheng, Peikun Xiao   +6 more
wiley   +1 more source

Precipitation nowcasting with radar data for evaluating multiple horizons using U-Net-based algorithm in Eastern Amazon. [PDF]

PLoS One
Rocha R, Ferreira D, Oliveira E, Arruda H, Viademonte S, Paes AP, Jesus E, Costa C, Franco V, Saraiva I, Tedeschi R, Nogueira A, Alves R, Carvalho E.   +13 more
europepmc   +1 more source

MAUSAM: An Observations‐Focused Assessment of Global AI Weather Prediction Models During the South Asian Monsoon

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.
Abstract Past evaluation of artificial intelligence (AI) weather prediction has primarily relied on reanalyses, which can obscure important deficiencies due to prevailing biases in reanalyses themselves. Here, we present MAUSAM (Measuring AI Uncertainty during South Asian Monsoon), an evaluation of seven leading AI‐based prediction systems—FourCastNet,
Aman Gupta, Aditi Sheshadri, Dhruv Suri
wiley   +1 more source