EGU2020-4337
https://doi.org/10.5194/egusphere-egu2020-4337
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Sub-seasonal prediction of rainfall over the South China Sea and its surrounding areas during spring-summer transitional season

Qingquan Li1,2, Juanhuai Wang3, Song Yang4,5,6, Fang Wang1,2, Jie Wu1, and Yamin Hu3
Qingquan Li et al.
  • 1Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081, China(liqq@cma.gov.cn)
  • 2Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Inform
  • 3Guangdong Climate Center, Guangdong Province, Guangzhou 510080, China
  • 4School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China
  • 5Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Guangzhou 510275, China
  • 6Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong, China

        The sub-seasonal characteristics and prediction of rainfall over the South China Sea and surrounding areas during spring-summer transitional season (April-May-June) are investigated using a full set of hindcasts generated by the Dynamic Extended Range Forecast operational system version 2.0 (DERF2.0) of Beijing Climate Center, China Meteorological Administration. The onset and development of Asian summer monsoon and the seasonal migration of rain belt over East Asia can be well depicted by the model hindcasts at various leads. However, there exist considerable differences between model results and observations, and model biases depend not only on lead time, but also on the stage of monsoon evolution. In general, forecast skill drops with increasing lead time, but rises again after lead time becomes longer than 30 days, possibly associated with the effect of slowly-varying forcing or atmospheric variability. An abrupt turning point of bias development appears around mid-May, when bias growths of wind and precipitation exhibit significant changes over the northwestern Pacific and South Asia, especially over the Bay of Bengal and the South China Sea. This abrupt bias change is reasonably captured by the first two modes of multivariate empirical orthogonal function analysis, which reveals several important features associated with the bias change. This analysis may provide useful information for further improving model performance in sub-seasonal rainfall prediction.

How to cite: Li, Q., Wang, J., Yang, S., Wang, F., Wu, J., and Hu, Y.: Sub-seasonal prediction of rainfall over the South China Sea and its surrounding areas during spring-summer transitional season, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4337, https://doi.org/10.5194/egusphere-egu2020-4337, 2020