Assessment Based on the Forecast Error for the Transition Period between the Jianghuai Meiyu and North China Rainy Seasons in 2016


During the transition period between the Jianghuai Meiyu and North China rainy seasons in 2016, there was a high-impact rainstorm event, connecting these two rainy seasons. However, both the short and medium range forecasts predicted a rain band that was too far south; this error can have serious implications for flood preparedness. This study discusses the causes of the forecast error using the ECMWF deterministic and ensemble models. The results show that the prediction of a too-weak westerly trough at the 500-hPa level is the dominant factor. Specifically, a weaker predicted 500-hPa westerly trough reduces the strength of the low vortex at 850 hPa; correspondingly, the shear line to the east of the vortex and the Meiyu front are weaker and farther south, and the monsoon is also weaker, which causes the large area of humidity convergence to be shifted southward. Finally, the heavy rainfall is located farther south with weaker intensity. And vice visa, when a stronger westerly trough is predicted, the location of rain band will be northward. This conclusion may be useful for meteorological decision making in medium range and will help to improve capabilities of risk reduction.

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This work was jointly supported by the National Key Technology Research and Development Program of the Ministry of Science and Technology of China (2015BAC03B04), and the National Program on Global Change and Air-Sea Interaction (GASI-IPOVAI-03). We thanks Prof. Fuqing Zhang for constructive suggestion and comments.

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Jie Ma and Ruiqiang Ding designed the research. Zhiping Zong performed the data analysis, prepared all figures and led the writing of the manuscript.

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Correspondence to Ruiqing Ding.

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Ma, J., Zong, Z., Jianping, L. et al. Assessment Based on the Forecast Error for the Transition Period between the Jianghuai Meiyu and North China Rainy Seasons in 2016. Asia-Pacific J Atmos Sci (2020).

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  • Rainy season
  • Risk reduction
  • Forecast error