Results 1 to 10 of about 2,695 (117)

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

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

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

Machine‐Learned Climate Model Corrections From a Global Storm‐Resolving Model: Performance Across the Annual Cycle

Journal of Advances in Modeling Earth Systems, 2023
One approach to improving the accuracy of a coarse‐grid global climate model is to add machine‐learned (ML) state‐dependent corrections to the prognosed model tendencies, such that the climate model evolves more like a reference fine‐grid global storm ...
Anna Kwa, Spencer K. Clark, Brian Henn, Noah D. Brenowitz, Jeremy McGibbon, Oliver Watt‐Meyer, W. Andre Perkins, Lucas Harris, Christopher S. Bretherton   +8 more
doaj   +1 more source

DYAMOND: the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains

Progress in Earth and Planetary Science, 2019
A review of the experimental protocol and motivation for DYAMOND, the first intercomparison project of global storm-resolving models, is presented. Nine models submitted simulation output for a 40-day (1 August–10 September 2016) intercomparison period ...
Bjorn Stevens, Masaki Satoh, Ludovic Auger, Joachim Biercamp, Christopher S. Bretherton, Xi Chen, Peter Düben, Falko Judt, Marat Khairoutdinov, Daniel Klocke, Chihiro Kodama, Luis Kornblueh, Shian-Jiann Lin, Philipp Neumann, William M. Putman, Niklas Röber, Ryosuke Shibuya, Benoit Vanniere, Pier Luigi Vidale, Nils Wedi, Linjiong Zhou   +20 more
doaj   +1 more source

Tropical Cirrus in Global Storm‐Resolving Models: 1. Role of Deep Convection

Earth and Space Science, 2022
Pervasive cirrus clouds in the upper troposphere and tropical tropopause layer (TTL) influence the climate by altering the top‐of‐atmosphere radiation balance and stratospheric water vapor budget.
J. M. Nugent, S. M. Turbeville, C. S. Bretherton, P. N. Blossey, T. P. Ackerman   +4 more
doaj   +1 more source

Predicting Compound Coastal Flooding in Embayment-Backed Urban Catchments: Seawall and Storm Drain Implications

Journal of Marine Science and Engineering, 2023
Urban coastal flooding is a global humanitarian and socioeconomic hazard. Rising sea levels will increase the likelihood of hydrologic events interacting with high marine water levels.
Boxiang Tang, T. W. Gallien
doaj   +1 more source

Toward Eliminating the Decades‐Old “Too Zonal and Too Equatorward” Storm‐Track Bias in Climate Models

Journal of Advances in Modeling Earth Systems, 2023
Generations of climate models exhibit biases in their representation of North Atlantic storm tracks, which tend to be too far near the equator and too zonal. Additionally, models have difficulties simulating explosive cyclone growth. These biases are one
Sebastian Schemm
doaj   +1 more source

Introduction to EarthCARE synthetic data using a global storm-resolving simulation [PDF]

Atmospheric Measurement Techniques, 2023
Pre-launch simulated satellite data are useful to develop retrieval algorithms and to facilitate the rapid release of retrieval products after launch. Here we introduce the Japanese Aerospace Exploration Agency's (JAXA) EarthCARE synthetic data based on ...
W. Roh, M. Satoh, T. Hashino, S. Matsugishi, T. Nasuno, T. Kubota   +5 more
doaj   +1 more source