Machine Learning Emulation of Urban Land Surface Processes

Machine Learning Emulation of Urban Land Surface Processes

Abstract Can we improve the modeling of urban land surface processes with machine learning (ML)? A prior comparison of urban land surface models (ULSMs) found that no single model is “best” at predicting all common surface fluxes. Here, we develop an urban neural network (UNN) trained on the mean pr...

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Bibliographic Details
Main Authors: David Meyer, Sue Grimmond, Peter Dueben, Robin Hogan, Maarten van Reeuwijk
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2022-03-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
machine learning
neural network
Weather Research Forecasting (WRF)
numerical weather prediction (NWP)
coupling
urban land surface
Online Access:https://doi.org/10.1029/2021MS002744

Internet

https://doi.org/10.1029/2021MS002744

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