ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Evaluation of Pentad-Scale Prediction Skill of the Fengshun Model for Midsummer Temperature over China
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Abstract:
Using hindcast datasets from the Fengshun model and the S2S-ECMWF model during 2017–2022, together with CMA-RA and NCEP reanalyses and station temperature observations, the pentad-scale prediction skill for midsummer (July–August) temperature over China is evaluated. Three metrics are adopted: temporal anomaly correlation coefficient (TCC), spatial anomaly correlation coefficient (ACC), and integrated prediction score (IPS). The verification results based on different reference datasets (station observations, CMA-RA1.0, and NCEP) are generally consistent. Overall, the Fengshun model shows higher prediction skill than the S2S-ECMWF model, with TCC, ACC, and IPS values improved by 7.9%, 18.4%, and 1.5%, respectively. Higher TCC skill is found in the Huang-Huai, Jiang-Huai, Central China, South China, East China, and Xinjiang regions, while lower skill appears in Northeast China, Inner Mongolia, the Tibetan Plateau, and Southwest China. The Fengshun model performs better at 1-pentad and 4–8-pentad leads, with the highest skill at a 6-pentad lead within the subseasonal range, mainly due to its improved prediction of 500 hPa geopotential height anomalies over key circulation regions..
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