EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Subseasonal prediction of the July 2021 extreme rainfall event over Henan China in S2S forecasting systems

Yuhan Yan, Congwen Zhu, and Boqi Liu
Yuhan Yan et al.
  • Chinese Academy of Meteorological Sciences, State Key Laboratory of Severe Weather and Institute of Climate System, China (

Unprecedented heavy rainfall reaches the warming Earth more frequently, creating the need for effective risk-warning alerts that utilize subseasonal-to-seasonal (S2S) forecasting to integrate information from nowcasting, weather, and seasonal predictions. A record-breaking flooding event occurred in Zhengzhou, Henan Province of China during 17–23 July 2021, causing 398 total of deaths and vast economic losses.

A number of studies have shown this super severe heavy flooding occurred under the background of multiscale circulation interactions and the impacts of remote tropical cyclones. Here, we evaluated the predictability of this extreme rainfall event and the impacts of tropical cyclones (TCs) using subseasonal-to-seasonal (S2S) operational models. Most S2S models can reasonably predict the wet-in-north and dry-in-south monthly rainfall pattern over China in July. Only four models captured the location, probability, and sudden intensification of the Zhengzhou rainfall extremes in advance of one week, largely due to their reasonable prediction of the variability of the western North Pacific subtropical high in mid-latitudes. Although the chance of exceeding the new record daily rainfall is only approx. 0.7% in mid-late July, they provide a high probability of this heavy weekly rainfall one week in advance. However, the S2S models still underestimated the super extremeness of this event. The prediction discrepancies came from the poor predictability of Typhoon IN-FA and its impact on the daily evolution of the extreme rainfall event, even within a few days forecast lead. Compared with the observation, the prediction bias of tropical disturbance changed the environmental monsoon airflow to induce the earlier warning of rainfall extremes prior to the formation of IN-FA. After the formation of IN-FA, the prediction bias of the typhoon’s moving speed distorted the typhoon location, which incorrectly predicted the moisture convergence center and underestimated their remote impacts on this heavy rainfall event. Future research should improve our awareness of the challenges that remain in the S2S forecasts.

How to cite: Yan, Y., Zhu, C., and Liu, B.: Subseasonal prediction of the July 2021 extreme rainfall event over Henan China in S2S forecasting systems, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15077,, 2023.