Papers
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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…Tropical Cirrus Are Highly Sensitive to Ice Microphysics Within a Nudged Global Storm‐Resolving Model
R. Atlas, C. Bretherton, A. Sokol, P. Blossey, M. F. KhairoutdinovGeophysical Research Letters • 2024 Cirrus dominate the longwave radiative budget of the tropics. For the first time, the variability in cirrus properties and longwave cloud radiative effects (CREs) that arises from using different microphysical schemes within nudged global storm‐resolving…Kilometer-scale global warming simulations and active sensors reveal changes in tropical deep convection
Maximilien Bolot, Lucas M. Harris, Kai-Yuan Cheng, Timothy M. Merlis, Peter N. Blossey, Christopher S. Bretherton, Spencer K. Clark, Alex Kaltenbaugh, Linjiong Zhou & Stephan Fueglistaler NPJ Climate and Atmospheric Science • 2023 Changes in tropical deep convection with global warming are a leading source of uncertainty for future climate projections. A comparison of the responses of active sensor measurements of cloud ice to interannual variability and next-generation global storm…ACE: A fast, skillful learned global atmospheric model for climate prediction
Oliver Watt‐Meyer, Gideon Dresdner, J. McGibbon, Spencer K. Clark, Brian Henn, James Duncan, Noah Brenowitz, K. Kashinath, Michael S. Pritchard, B. Bonev, Matthew E. Peters, Christopher S. BrethertonNeurIPS • Tackling Climate Change with Machine Learning • 2023 Existing ML-based atmospheric models are not suitable for climate prediction, which requires long-term stability and physical consistency. We present ACE (AI2 Climate Emulator), a 200M-parameter, autoregressive machine learning emulator of an existing…