H∞ Filtering for Bias Correction in Post-Processing of Numerical Weather Prediction

Journal of the Meteorological Society of Japan

Jaechan LIM¹  Hyung-Min PARK² 

[1] Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, USA;Department of Electronic Engineering, Sogang University, Republic of Korea

关键词: Kalman filtering;    H-infinity filtering;    model post-processing;    numerical weather prediction;   

DOI  :  10.2151/jmsj.2019-041

学科分类：大气科学

来源: Meteorological Society of Japan

【 摘 要 】

 In this paper, we propose an H-infinity (H∞) filtering approach for the prediction of bias in post-processing of model outputs and past measurements. This method adopts a minimax strategy that is a solution for zero-sum games. The proposed H∞ filtering approach minimizes maximum possible errors whereas a recently proposed approach that adopts Kalman filtering (KF) minimizes the mean square errors. The proposed approach does not need the information of noise statistics unlike the method based on the KF, while the training process is required. We show that the proposed approach outperforms the method based on the KF in experiments by applying real weather data in Korea.

【 授权许可】

Unknown