EGU23-17423, updated on 26 Feb 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

The role of multi-scale interaction on subseasonal prediction of extreme events

June-Yi Lee1,2, Pang-Chi Hsu3, Doo-Young Lee1, Young-Min Yang3, and Jinhui Xie3
June-Yi Lee et al.
  • 1Research Center for Climate Sciences, Pusan National University, Busan, South Korea
  • 2Center for Climate Physics, Institute for Basic Science, Busan, South Korea
  • 3Key Laboratory of Meteorological Disaster, Ministry of Education/International Joint Research Laboratory on Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Inform

The northward/northwestward propagation of boral summer intraseasonal oscillation (BSISO) modulates the subtropical variability ad typhoon activity and has significant impacts on the extreme weather and climate events in Asia. BSISO strongly interacts with background mean fields and tends to be stronger and longer in its northward propagation during La Nina than El Nino summers. It is further found that BSISO-related convections are stronger and more organized with northward propagation on 30-60-day timescales during El Nino developing than decaying summers over the western Pacific. Thus, for skillful subseasonal prediction of extreme events in Asia, it is crucial for climate models to well represent BSISO and its interaction with the background mean state and synoptic variability. Our case study shows that the rare extreme flooding event in Henan Province, China, during July 2021 (referred to as the “21.7” flooding event) was a result of scale interactions between the background mean field associated with the weak La Nina condition, intraseasonal oscillations, and synoptic disturbances. The two distinct modes of the BSISO (10-30- and 30-90-day modes) unusually had a crucial combined role in moisture convergence, aided by the increased seasonal-mean moisture content, maintaining persistent rainfall during the 21.7 event. Synoptic-scale moisture convergence was also contributed to the extreme values in the peak day of the event. The five state-of-the art subseasonal-to-seasonal prediction models showed limited skills in predicting this extreme event one to two weeks in advance, partly because of their biases in representing the BSISO and multiscale interactions. Our results highlight that an accurate prediction of subseasonal perturbations and their interactions with the background moisture content is crucial for improving the extended-range forecast skill of extreme precipitation events.

How to cite: Lee, J.-Y., Hsu, P.-C., Lee, D.-Y., Yang, Y.-M., and Xie, J.: The role of multi-scale interaction on subseasonal prediction of extreme events, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-17423,, 2023.