Papers
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Climate sensitivity and relative humidity changes in global storm-resolving model simulations of climate change
T. Merlis, Kai-Yuan Cheng, Ilai Guendelman, Lucas M. Harris, Christopher S. Bretherton, M. Bolot, Linjiong Zhou, Alex Kaltenbaugh, S. K. Clark, Gabriel A. Vecchi, Stephan FueglistalerScience Advances • 2024 The climate simulation frontier of a global storm-resolving model (GSRM; or k-scale model because of its kilometer-scale horizontal resolution) is deployed for climate change simulations. The climate sensitivity, effective radiative forcing, and relative…Probabilistic Emulation of a Global Climate Model with Spherical DYffusion
Salva Rühling Cachay, Brian Henn, Oliver Watt‐Meyer, Christopher S. Bretherton, Rose YuICML•ML4ESM • 2024 Data-driven deep learning models are on the verge of transforming global weather forecasting. It is an open question if this success can extend to climate modeling, where long inference rollouts and data complexity pose significant challenges. Here, we…Probabilistic Emulation of a Global Climate Model with Spherical DYffusion
Salva Rühling Cachay, Brian Henn, Oliver Watt‐Meyer, Christopher S. Bretherton, Rose YuICML•ML4ESM • 2024 Data-driven deep learning models are on the verge of transforming global weather forecasting. It is an open question if this success can extend to climate modeling, where long inference rollouts and data complexity pose significant challenges. Here, we…The precipitation response to warming and CO2 increase: A comparison of a global storm resolving model and CMIP6 models.
Ilai Guendelman, Timothy M. Merlis, Kai-Yuan Cheng, Lucas M. Harris, Christopher S. Bretherton, Max Bolot, Lin Zhou, Alex Kaltenbaugh, Spencer K. Clark, Stephan FueglistalerGeophysical Research Letters • 2024 Global storm-resolving models (GSRMs) can explicitly resolve some of deep convection are now being integrated for climate timescales. GSRMs are able to simulate more realistic precipitation distributions relative to traditional CMIP6 models. In this study, we…Emulation of cloud microphysics in a climate model
W. Andre Perkins, Noah D. Brenowitz, Christopher S. Bretherton, Jacqueline M. NugentJAMES • 2024 We present a machine learning based emulator of a microphysics scheme for condensation and precipitation processes (Zhao-Carr) used operationally in a global atmospheric forecast model (FV3GFS). Our tailored emulator architecture achieves high skill (≥94%) in…A machine learning parameterization of clouds in a coarse-resolution climate model for unbiased radiation
Brian Henn, Yakelyn R. Jauregui, Spencer K. Clark, Noah Brenowitz, Jeremy McGibbon, Oliver Watt‐Meyer, Andrew G. Pauling, Christopher S. BrethertonJAMES • 2024 Coarse-grid weather and climate models rely particularly on parameterizations of cloud fields, and coarse-grained cloud fields from a fine-grid reference model are a natural target for a machine-learned parameterization. We machine-learn the coarsened-fine…Application of the AI2 Climate Emulator to E3SMv2's global atmosphere model, with a focus on precipitation fidelity
James P. C. Duncan, Elynn Wu, Jean-Christoph Golaz, Peter M. Caldwell, Oliver Watt-Meyer, Spencer K. Clark, Jeremy McGibbon, Gideon Dresdner, Karthik Kashinath, Boris Bonev, Michael S. Pritchard, and Christopher S. BrethertonAuthorea • 2024 Can the current successes of global machine learning-based weather simulators be generalized beyond two-week forecasts to stable and accurate multiyear runs? The recently developed AI2 Climate Emulator (ACE) suggests this is feasible, based upon 10-year…Improving Stratocumulus Cloud Amounts in a 200‐m Resolution Multi‐Scale Modeling Framework Through Tuning of Its Interior Physics
Liran Peng, P. Blossey, W. Hannah, C. Bretherton, C. Terai, A. Jenney, M. PritchardJournal of Advances in Modeling Earth Systems • 2024 High‐Resolution Multi‐scale Modeling Frameworks (HR)—global climate models that embed separate, convection‐resolving models with high enough resolution to resolve boundary layer eddies—have exciting potential for investigating low cloud feedback dynamics due…Global Precipitation Correction Across a Range of Climates Using CycleGAN
Jeremy McGibbon, S. K. Clark, Brian Henn, Anna Kwa, Oliver Watt‐Meyer, W. Perkins, Christopher S. Bretherton, S. K. ClarkGeophysical Research Letters • 2024 Accurate precipitation simulations for various climate scenarios are critical for understanding and predicting the impacts of climate change. This study employs a Cycle‐generative adversarial network (CycleGAN) to improve global 3‐hr‐average precipitation…Neural Network Parameterization of Subgrid‐Scale Physics From a Realistic Geography Global Storm‐Resolving Simulation
Oliver Watt‐Meyer, Noah D. Brenowitz, S. K. Clark, Brian Henn, Anna Kwa, Jeremy McGibbon, W. Perkins, Lucas Harris, Christopher S. BrethertonJournal of Advances in Modeling Earth Systems • 2024 Parameterization of subgrid‐scale processes is a major source of uncertainty in global atmospheric model simulations. Global storm‐resolving simulations use a finer grid (less than 5 km) to reduce this uncertainty by explicitly resolving deep convection and…