Challenges in Unifying Physically Based and Machine Learning Simulations Through Differentiable Modeling: A Land Surface Case Study

Abstract Differentiable geoscientific modeling has shown promise for leveraging machine learning (ML) to unify physically based and data‐based modeling. Here, we critically analyze this promise in the context of large‐scale parameter optimization with the Noah‐MP land model as an example. The differ...

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Bibliografiske detaljer

Principais autores:	Shahryar K. Ahmad, Sujay V. Kumar, Clara Draper, Rolf H. Reichle
Format:	Artigo
Sprog:	Inglês
Udgivet:	Wiley 2025-02-01
Serier:	Geophysical Research Letters
Fag:	machine learning land surface model calibration soil moisture genetic algorithm transferability
Online adgang:	https://doi.org/10.1029/2024GL112893
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