Gaussian Process Regression‐Based Bayesian Optimisation (G‐BO) of Model Parameters—A WRF Model Case Study of Southeast Australia Heat Extremes

Abstract In Numerical Weather Prediction (NWP) models, such as the Weather Research and Forecasting (WRF) model, parameter uncertainty in physics parameterization schemes significantly impacts model output. Our study adopts a Bayesian probabilistic approach, building on prior research that identifie...

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Bibliographic Details

Published in:	Geophysical Research Letters
Main Authors:	P. Jyoteeshkumar Reddy, Sandeep Chinta, Harish Baki, Richard Matear, John Taylor
Format:	Article
Language:	English
Published:	Wiley 2024-09-01
Subjects:	weather research and forecasting (WRF) bayesian optimisation heat extremes Australia Gaussian process regression (GPR) numerical weather prediction (NWP)
Online Access:	https://doi.org/10.1029/2024GL111074