Results 31 to 40 of about 3,005 (252)

The Land‐Ocean Contrast in Deep Convective Intensity in a Global Storm‐Resolving Model

Journal of Advances in Modeling Earth Systems
Observations reveal a clear difference in the intensity of deep convection over tropical land and ocean. This observed land‐ocean contrast provides a natural benchmark for evaluating the fidelity of global storm‐resolving models (GSRMs; global models ...
Tristan H. Abbott, Nadir Jeevanjee, Kai‐Yuan Cheng, Linjiong Zhou, Lucas Harris   +4 more
doaj   +3 more sources

Using Satellite and ARM Observations to Evaluate Cold Air Outbreak Cloud Transitions in E3SM Global Storm‐Resolving Simulations

Geophysical Research Letters
This study examines marine boundary layer cloud regime transition during a cold air outbreak (CAO) over the Norwegian Sea, simulated by a global storm‐resolving model (GSRM) known as the Simple Cloud‐Resolving Energy Exascale Earth System Model ...
X. Zheng, Y. Zhang, S. A. Klein, M. Zhang, Z. Zhang, M. Deng, J. Tian, C. R. Terai, B. Geerts, P. Caldwell, P. A. Bogenschutz   +10 more
doaj   +2 more sources

Response of Global Mesoscale Convective Systems to Increased CO2 and Uniform SST Warming in a Global Storm‐Resolving Model

Earth's Future
Mesoscale convective systems (MCSs) are critical components of global energy and water cycles and significantly contribute to extreme weather events. However, projecting future MCS behavior remains challenging due to the limitations of regional models ...
Wenhao Dong, Ming Zhao, Lucas Harris, Kai‐Yuan Cheng, Linjiong Zhou, V. Ramaswamy   +5 more
doaj   +2 more sources

Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model [PDF]

Geoscientific Model Development
Global storm-resolving models (GSRMs) use strongly refined horizontal grids compared with the climate models typically used in the Coupled Model Intercomparison Project (CMIP) but employ comparable vertical grid spacings.
H. Schmidt, S. Rast, J. Bao, J. Bao, A. Cassim, S.-W. Fang, D. Jimenez-de la Cuesta, D. Jimenez-de la Cuesta, P. Keil, P. Keil, L. Kluft, C. Kroll, C. Kroll, T. Lang, U. Niemeier, A. Schneidereit, A. Schneidereit, A. I. L. Williams, B. Stevens   +18 more
doaj   +2 more sources

Vertical motions in clouds from EarthCare satellite and a global storm-resolving modeling. [PDF]

Sci Rep
Roh W, Satoh M, Matsugishi S, Aoki S, Kubota T, Okamoto H.   +5 more
europepmc   +4 more sources

Reduced cloud cover errors in a hybrid AI-climate model through equation discovery and automatic tuning [PDF]

Scientific Reports
Cloud-related parameterizations remain a leading source of uncertainty in climate projections. Although machine learning holds promise for Earth system models (ESMs), many data-driven parameterizations lack interpretability, physical consistency, and ...
Arthur Grundner, Tom Beucler, Julien Savre, Axel Lauer, Manuel Schlund, Veronika Eyring   +5 more
doaj   +2 more sources

Detecting changes in large-scale metrics of climate in short integrations of a global storm-resolving model of the atmosphere

Environmental Research: Climate
Recent advances have allowed for integration of global storm resolving models (GSRMs) to a timescale of several years. These short simulations are sufficient for studying aggregated statistics of short-timescale and small spatial-scale phenomena; however,
Ilai Guendelman, Timothy M Merlis, Kai-Yuan Cheng, Lucas M Harris, Christopher S Bretherton, Maximilien Bolot, Linjiong Zhou, Alex Kaltenbaugh, Spencer K Clark, Stephan Fueglistaler   +9 more
doaj   +2 more sources

Advancing precipitation prediction using a new-generation storm-resolving model framework – SIMA-MPAS (V1.0): a case study over the western United States [PDF]

Geoscientific Model Development, 2022
Global climate models (GCMs) have advanced in many ways as computing power has allowed more complexity and finer resolutions. As GCMs reach storm-resolving scales, they need to be able to produce realistic precipitation intensity, duration, and frequency
X. Huang, A. Gettelman, W. C. Skamarock, P. H. Lauritzen, M. Curry, A. Herrington, J. T. Truesdale, M. Duda   +7 more
doaj   +1 more source

Improving the Reliability of ML‐Corrected Climate Models With Novelty Detection

Journal of Advances in Modeling Earth Systems, 2023
Using machine learning (ML) for the online correction of coarse‐resolution atmospheric models has proven effective in reducing biases in near‐surface temperature and precipitation rate.
Clayton Sanford, Anna Kwa, Oliver Watt‐Meyer, Spencer K. Clark, Noah Brenowitz, Jeremy McGibbon, Christopher Bretherton   +6 more
doaj   +1 more source

Global System for Atmospheric Modeling: Model Description and Preliminary Results

Journal of Advances in Modeling Earth Systems, 2022
The extension of a cloud‐resolving model, the System for Atmospheric Modeling (SAM), to global domains is described. The resulting global model, gSAM, is formulated on a latitude‐longitude grid. It uses an anelastic dynamical core with a single reference
Marat F. Khairoutdinov, Peter N. Blossey, Christopher S. Bretherton   +2 more
doaj   +1 more source