Results 121 to 130 of about 24,097 (273)

The Impact of the Sulfur Allotropes and Sulfur Hydrides on the Venus Cloud Chemistry

Journal of Geophysical Research: Planets, Volume 131, Issue 5, May 2026.
Abstract Venus is home to vivid sulfur chemistry, with SO2 ${\text{SO}}_{2}$ as the major sulfur gas species and a global cloud layer between 47 and 70 km composed of H2SO4 ${\mathrm{H}}_{2}{\text{SO}}_{4}$ and H2 ${\mathrm{H}}_{2}$O. The chemistry in the clouds has been extensively studied with 1D models, but none is able to reproduce the three orders
Maxence Lefèvre, Franck Lefèvre, Anni Määttänen, Robert Skog, Benjamin Frandsen, Aurélien Stolzenbach, Ashwin Braude   +6 more
wiley   +1 more source

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

Journal 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

A Warm-Bin-Cold-Bulk Hybrid Cloud Microphysical Model [PDF]

, 2012
ONISHI, Ryo, TAKAHASHI, Keiko, 大西, 領, 高橋, 桂子   +3 more
core   +1 more source

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

Geophysical 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, Xin Hong, Zhijun Zhao, Zeyu Gan, Pengxiang Ouyang, Haixia Xiao, Renhe Zhang, Xujun Wei, Miao Cai, Feng Lu   +9 more
wiley   +1 more source

Perspectives on Systematic Cloud Microphysics Scheme Development With Machine Learning

Journal of Advances in Modeling Earth Systems
Cloud microphysics—the collection of processes that govern the small‐scale formation, evolution, and interactions of liquid droplets and ice crystals in clouds and precipitation—remains a major source of uncertainty in weather and climate models ...
Kara D. Lamb, Clare E. Singer, Kaitlyn Loftus, Hugh Morrison, Margaret Powell, Joseph Ko, Jatan Buch, Arthur Z. Hu, Marcus vanLier Walqui, Pierre Gentine   +9 more
doaj   +1 more source

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

Geophysical 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, Giulio Mandorli, Lilli Johanna Freischem, Alejandro Casallas, Adrian Mark Tompkins   +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

Geophysical 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

Geophysical 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, Tianning Su, Hewei Tang, Peter Bogenschutz, Stephen A. Klein, Charles Jackson, Peter Caldwell   +6 more
wiley   +1 more source

Diurnal Variation of Tropical Ice Cloud Microphysics: Evidence from Global Precipitation Measurement Microwave Imager (GPM-GMI) Polarimetric Measurements. [PDF]

Geophys Res Lett, 2018
Gong J, Zeng X, Wu DL, Li X.
europepmc   +1 more source

Microphysical fingerprints in anvil cloud albedo

Atmospheric Chemistry and Physics
Abstract. Improved understanding of anvil cloud radiative effect (CRE) and feedback is critical for reducing uncertainty in climate projections, with recent research highlighting cloud microphysics and anvil albedo as requiring further investigation. In this study, we use nine observation-informed model experiments to simulate a 24 d period from the ...
Declan L. Finney, Alan M. Blyth, Paul R. Field, Martin I. Daily, Benjamin J. Murray, Mengyu Sun, Paul J. Connolly, Zhiqiang Cui, Steven Böing   +8 more
openaire   +2 more sources