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Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators
Autor:
Mahesh, Ankur, Collins, William, Bonev, Boris, Brenowitz, Noah, Cohen, Yair, Elms, Joshua, Harrington, Peter, Kashinath, Karthik, Kurth, Thorsten, North, Joshua, OBrien, Travis, Pritchard, Michael, Pruitt, David, Risser, Mark, Subramanian, Shashank, Willard, Jared
Studying low-likelihood high-impact extreme weather events in a warming world is a significant and challenging task for current ensemble forecasting systems. While these systems presently use up to 100 members, larger ensembles could enrich the sampl
Externí odkaz:
http://arxiv.org/abs/2408.03100
Autor:
Mahesh, Ankur, Collins, William, Bonev, Boris, Brenowitz, Noah, Cohen, Yair, Harrington, Peter, Kashinath, Karthik, Kurth, Thorsten, North, Joshua, OBrien, Travis, Pritchard, Michael, Pruitt, David, Risser, Mark, Subramanian, Shashank, Willard, Jared
In Part I, we created an ensemble based on Spherical Fourier Neural Operators. As initial condition perturbations, we used bred vectors, and as model perturbations, we used multiple checkpoints trained independently from scratch. Based on diagnostics
Externí odkaz:
http://arxiv.org/abs/2408.01581
Akademický článek
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