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Status: Unchecked ×Keyword: imperfect models ×Clear all

1 claim from 1 paper

1. Earth and Planetary Sciences › Meteorological Phenomena and Simulations

   Cross‐Attractor Transforms: Improving Forecasts by Learning Optimal Maps Between Dynamical Systems and Imperfect Models

   Agarwal, Amrhein and Grooms · Geophysical Research Letters · 2025

   The authors propose learning, from data, the best maps between a true dynamical system and an imperfect model's phase space, and report that this consistently reduces forecast errors in the Lorenz-96 system.

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   1. UncheckedIn a Lorenz-96 test, learned maps into and out of an imperfect model use its "shocks" and "drifts" to forecast the reference system more skilfully.“Optimal pre‐ and post‐processing transforms leverage “shocks” and “drifts” in the imperfect model to make more skillful forecasts of the reference system.”