An integrated method for extended-range prediction of heavy Precipitation process in the flood season over Hunan Province based on S2S models

Author:

Mao Chengmin1234,Zhang Jianming12,Zeng Yuxing1ORCID,Zhao Hui1,Peng Jiadong1245ORCID,Tang Yihao1,Peng Shaofeng67

Affiliation:

1. a Climate Center of Hunan Province, Changsha, China

2. b Yueyang National Climatological Observatory, Yueyang, Hunan, China

3. c Huaihua Meteorological Bureau, Huaihua, Hunan, China

4. d Key Laboratory of Hunan Province for Meteorological Disaster Prevention and Mitigation, Changsha, China

5. e Turpan Meteorological Bureau, Turpan, Xinjiang, China

6. f Hunan Academy of Forestry, Changsha, China

7. g Shennongguo Oil Eco-Agriculture Development Co. Ltd, Hengyang, Hunan, China

Abstract

Abstract Floods in the middle reaches of Yangtze River threaten millions of people and cause casualties and economic losses. Yet, the prediction of floods especially on the sub-seasonal scale in this region is still challenging. To better predict the floods during the flood season (from April to August) in Hunan Province, the models from the China Meteorological Administration (CMA), the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) that participated in the sub-seasonal to seasonal (S2S) prediction project were chosen to evaluate their extended-range (the next 11–30 days) prediction skills for heavy precipitation. The original prediction score of single model (original score), the score of single model using optimal threshold of heavy precipitation (adjusted score) and the score of multi-model integration (integrated score) were calculated by the scoring rules for heavy precipitation process. The results show that the integrated score in the extended-range is 75.1, which is 10.3 and 6.9 higher than the average scores of original models and adjusted method, respectively. The false alarm (missing) rate of the integrated method is 5.4% (33.9%), which is 8.6% (4.7%) and 2.9% (3.3%) smaller than the average rates of original models and adjusted method, respectively.

Funder

Basic Business Capacity Construction Project of High Resolution Satellite Meteorological Application of Hunan Provincial Meteorological Bureau

Publisher

IWA Publishing

Subject

Management, Monitoring, Policy and Law,Atmospheric Science,Water Science and Technology,Global and Planetary Change

Reference22 articles.

1. Sub-seasonal Predictability of the Onset and Demise of the Rainy Season over Monsoonal Regions

2. CMA 2018 S2S Models [EB/OL]. [2022-08-28]. Available from: http://s2s.cma.cn/Models/.

3. Design and implementation of the global forecast service sharing platform of the World Meteorological Center;Hu;Meteorological Science and Technology,2019

4. Analysis and application of sub-seasonal-seasonal (S2S) forecast data from the National Meteorological Information Center;Hu;Meteorological Science and Technology,2020

5. Predictability and Prediction Skill of the MJO in Two Operational Forecasting Systems

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