Research Article
Design and Construction of Daily-updating Objective Climate Prediction System Based on the Real-time Forecast of CFSv2
@INPROCEEDINGS{10.4108/eai.17-6-2022.2322676, author={Hao Ma and Fei Yu and Ming Yang and Jingwen Ge and Gaofeng Fan and Ying Liu and Zheyong Xu and Jianjiang Wang and Hangyuan Sun}, title={Design and Construction of Daily-updating Objective Climate Prediction System Based on the Real-time Forecast of CFSv2}, proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China}, publisher={EAI}, proceedings_a={ICIDC}, year={2022}, month={10}, keywords={cfsv2; systemic bias correction; extended-range; monthly scale; verification; operation platform}, doi={10.4108/eai.17-6-2022.2322676} }- Hao Ma
Fei Yu
Ming Yang
Jingwen Ge
Gaofeng Fan
Ying Liu
Zheyong Xu
Jianjiang Wang
Hangyuan Sun
Year: 2022
Design and Construction of Daily-updating Objective Climate Prediction System Based on the Real-time Forecast of CFSv2
ICIDC
EAI
DOI: 10.4108/eai.17-6-2022.2322676
Abstract
The CFSv2 forecast products have been widely used in climate prediction operation all over the world. Although the real-time forecast is able to basically capture large pattern of climate anomaly, there still exists obvious bias, which may have enormous impacts on predicted result and thus cannot be neglected. Presently, how to smartly use the massive modeling outputs to improve forecast skill is very important for objective prediction. In this paper, a statistical downscaling strategy for correcting systematic bias through recovering modeling-climatology to its observational counterpart is introduced, and with such methodology, an operational platform conducting real-time 1-30d and 10-30d temperature and precipitation objective prediction is constructed for Zhejiang province.