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Status: Unchecked ×Keyword: gravity waves ×Clear all

2 claims from 1 paper

1. Earth and Planetary Sciences › Meteorological Phenomena and Simulations

   On the Importance of Learning Non‐Local Dynamics for Stable Data‐Driven Climate Modeling: A 1D Gravity Wave‐QBO Testbed

   Pahlavan, Hassanzadeh and Alexander · Geophysical Research Letters · 2025

   Using a 1D quasi-biennial oscillation model with parameterized gravity waves, the paper shows that learning spatially non-local dynamics matters for the stability of data-driven climate model components.

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   1. UncheckedCommon offline accuracy metrics miss poor learning of non-local dynamics, but a network's receptive field can flag instability in advance, in a 1D testbed.“While common offline metrics fail to identify shortcomings in learning non‐local dynamics, we show that the receptive field (RF) can identify instability a‐priori.”
   2. UncheckedNeural-network gravity wave schemes that predict forcings from wind profiles with 99% accuracy still gave unstable simulations when their receptive fields were too small.“We find that neural network‐based parameterizations, though predicting GW forcings from wind profiles with 99% accuracy, lead to unstable simulations when RFs are too small to capture non‐local dynamics.”