Results 151 to 160 of about 30,389 (290)

Exploring Ways to Reduce Biases in a Hybrid Global Climate Model With Machine‐Learned Moist Physics

open access: yesJournal of Advances in Modeling Earth Systems, Volume 18, Issue 5, May 2026.
Abstract In a previous study (Han et al., 2023, https://doi.org/10.1029/2022ms003508), we implemented a deep convolutional residual neural network for moist physics into the 3‐D real‐geography CAM5 and carried out a stable multi‐year integration successfully. However, the simulation has large temperature and moisture biases in high latitude troposphere
Yilun Han, Guang J. Zhang, Yong Wang
wiley   +1 more source

The Dissipation Regime of Turbulence on Mars Observed With Microphone Data From the Mars 2020 Perseverance Rover

open access: yesGeophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract Turbulent winds are a regular occurrence in planetary boundary layers. Turbulence affects mixing, energy fluxes and forcing on the surface environment. Energy injected into an atmosphere generates eddies of many scales down to a size where molecular viscous forces dominate, termed the Kolmogorov length scale.
Alexander E. Stott   +13 more
wiley   +1 more source

Antarctic Meltwater‐Stratification Feedback Is Less Pronounced Under High Climate Forcing

open access: yesGeophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract Several studies have shown sub‐surface warming in the Southern Ocean via an increase in meltwater flux from the Antarctic Ice Sheet (AIS), which can lead to a positive feedback through enhanced basal melting. In this study, we investigate how the feedback strength is related to the prevailing climate in a coupled climate–ice‐sheet model.
Moritz Kreuzer   +6 more
wiley   +1 more source

Short‐Term Forecasting of Cloud Physical Properties Based on Fourier Neural Operator Method

open access: yesGeophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract Accurately understanding the evolution and development of cloud physical properties (CPP) in advance is crucial for extreme weather forecasting and early warning. This study utilized the Fourier neural operator (FNO) method to develop a short‐term forecasting model of Cloud (Cloud‐FNO).
Feng Zhang   +9 more
wiley   +1 more source

Bayesian Estimates of Ice Optical Properties for Lake Ice Modeling

open access: yesGeophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract Ice and snow cover on frozen lakes is a natural barrier to solar radiation, reducing the transfer of energy that controls under‐ice thermal dynamics and biological productivity. Direct measurements of under‐ice irradiance remain scarce due to logistical constraints.
G. Donini   +21 more
wiley   +1 more source

Long-Term Impact of Urban Areas on Meteorological Conditions Over Central Europe. [PDF]

open access: yesAnn N Y Acad Sci
Villalba-Pradas A   +4 more
europepmc   +1 more source

Spatial Patterns of Shallow Clouds: Challenging the Concept of Defined Regimes

open access: yesGeophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract Tropical shallow clouds are a major source of uncertainty in Earth's climate sensitivity, especially through their spatial arrangement, which global climate models do not represent. Efforts to understand their organization have partly relied on classifying observed scenes, identifying four patterns as archetypal regimes.
Giovanni Biagioli   +4 more
wiley   +1 more source

Uniformity in Heavy Precipitation Microphysics During the Northward Advancement of Summer Monsoon in China Unveiled by Objective Weather Typing

open access: yesGeophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract The microphysical evolution of the East Asian summer monsoon precipitation during its northward advance across China remains unclear, due to the mixing of diverse weather systems in past studies. Applying objective synoptic classification to a decade of satellite observations, we isolate canonical monsoon‐type heavy precipitation across South,
Ji Yang, Long Wen, Qingyuan Liu, Ji Nie
wiley   +1 more source

Process‐Oriented Calibration of a Turbulence Scheme in the DOE's Global Storm‐Resolving Model Using Machine Learning

open access: yesGeophysical Research Letters, Volume 53, Issue 8, 28 April 2026.
Abstract A process‐oriented calibration framework is developed for the Simplified Higher‐Order Closure (SHOC) turbulence scheme in DOE's Simple Cloud Resolving E3SM Atmospheric Model (SCREAM). This framework leverages machine learning surrogates and observational constraints to efficiently calibrate SHOC adjustable parameters across two convective ...
Yunyan Zhang   +6 more
wiley   +1 more source

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