Assessing the extended‐range forecast skills of the extreme heat events over South China based on three S2S models

Author:

Li Xiaoqi1,Chen Ruidan12ORCID,Qiao Yunting12

Affiliation:

1. School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat‐Sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Zhuhai China

2. Key Laboratory of Tropical Atmosphere–Ocean System, Ministry of Education Zhuhai China

Abstract

AbstractThis paper assesses the extended‐range forecast skills of the extreme heat events (EHEs) over South China based on three subseasonal‐to‐seasonal models (European Centre for Medium‐Range Weather Forecasts [ECMWF], National Centers for Environmental Prediction [NCEP], and China Meteorological Administration [CMA]). Overall, ECMWF has the best skill, NCEP the second and CMA the poorest. The predicting skills of EHEs depend on the predicting skills of relevant circulation. Cases studies (June 4–6, 1999, August 19–29, 2009, and August 3–5, 2010) show that the three models generally predict circulation anomalies weaker than observation, leading to the misses of some extreme heat days (EHDs). In these cases, ECMWF is able to well predict the influence of tropical circulation, capture the major characteristics of mid‐latitude circulation but with a slower propagating speed. NCEP could capture the main signals of tropical (mid‐latitude) circulation, but with slower propagating speed (slower propagating speed, deviated direction or more northward location). CMA might produce some EHDs but is derived from the circulation anomaly with the wrong origin or location. Therefore, ECMWF could predict the EHEs most accurately, NCEP could reasonably predict the formation of EHEs and tend to have more delayed predictions, while CMA has the poorest skill due to the false origins of anomalies. These results suggest potential ways to improve the current models' extended‐range forecast skills.

Funder

National Natural Science Foundation of China

Science and Technology Planning Project of Guangdong Province

Publisher

Wiley

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