Predictability analysis based on ensemble forecasting of the “7·20” extreme rainstorm in Henan, China

Sai TAN, Qiuping WANG, Xulin MA, Lu SUN, Xin ZHANG, Xinlu LV, Xin SUN

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Front. Earth Sci. ›› DOI: 10.1007/s11707-024-1106-1
RESEARCH ARTICLE

Predictability analysis based on ensemble forecasting of the “7·20” extreme rainstorm in Henan, China

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Abstract

A heavy rainstorm occurred in Henan Province, China, between 19 and 21 July, 2021, with a record-breaking 201.9 mm of precipitation in 1 h. To explore the key factors that led to forecasting errors for this extreme rainstorm, as well as the dominant contributor affecting its predictability, we employed the Global/Regional Assimilation and Prediction System-Regional Ensemble Prediction System (GRAPES-REPS) to investigate the impact of the upper tropospheric cold vortex, middle-low vortex, and low-level jet on predictability and forecasting errors. The results showed that heavy rainfall was influenced by the following stable atmospheric circulation systems: subtropical highs, continental highs, and Typhoon In-Fa. Severe convection was caused by abundant water vapor, orographic uplift, and mesoscale vortices. Multiscale weather systems contributed to maintaining extreme rainfall in Henan for a long duration. The prediction ability of the optimal member of GRAPES-REPS was attributed to effective prediction of the intensity and evolution characteristics of the upper tropospheric cold vortex, middle-low vortex, and low-level jet. Conversely, the prediction deviation of unstable and dynamic conditions in the lower level of the worst member led to a decline in the forecast quality of rainfall intensity and its rainfall area. This indicates that heavy rainfall was strongly related to the short-wave throughput, upper tropospheric cold vortex, vortex, and boundary layer jet. Moreover, we observed severe uncertainty in GRAPES-REPS forecasts for rainfall caused by strong convection, whereas the predictability of rainfall caused by topography was high. Compared with the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System, GRAPES-REPS exhibits a better forecast ability for heavy rainfall, with some ensemble members able to better predict extreme precipitation.

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Keywords

numerical weather prediction / ensemble forecast / ensemble sensitivity / predictability / extreme rainfall

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Sai TAN, Qiuping WANG, Xulin MA, Lu SUN, Xin ZHANG, Xinlu LV, Xin SUN. Predictability analysis based on ensemble forecasting of the “7·20” extreme rainstorm in Henan, China. Front. Earth Sci., https://doi.org/10.1007/s11707-024-1106-1

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Acknowledgments

This study was supported by the National Natural Science Foundation of China (Grant No. U2242213) and the National Key R&D Program of China (No. 2017YFC1502000). We acknowledge the High Performance Computing Centre of the Nanjing University of Information Science & Technology for their support.

Competing interests

The authors declare that they have no competing interests.

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