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Status: Unchecked ×Keyword: model error estimation ×Clear all

2 claims from 1 paper

1. Earth and Planetary Sciences › Meteorological Phenomena and Simulations

   Machine Learning for Model Error Inference and Correction

   Bonavita and Laloyaux · Journal of Advances in Modeling Earth Systems · 2020

   The paper shows neural networks can reproduce weak-constraint 4D-Var model error results in ECMWF's IFS model, and discusses how machine learning might best fit into weather data assimilation and forecasting.

   Unchecked2 claims
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   1. UncheckedUsing neural networks inside weak-constraint 4D-Var could let model error correction be applied across the whole atmospheric column, not just the stratosphere.“We show that the use of ANN models inside the weak‐constraint 4D‐Var framework has the potential to extend the applicability of the weak‐constraint methodology for model error correction to the whole atmospheric column.”
   2. UncheckedArtificial neural networks can reproduce the main results of weak-constraint 4D-Var in ECMWF's operational IFS weather model.“Specifically, we show that artificial neural networks (ANNs) can reproduce the main results obtained with weak‐constraint 4D‐Var in the operational configuration of the IFS model of the European Centre for Medium‐Range Weather Forecasts (ECMWF).”