State Key Laboratory of Numerical Modeling for Atmospheric Sciences and
Geophysical Fluid Dynamics (LASG)
Institute of Atmospheric Physics, Chinese Academy of Sciences
Vol.15/No.15 April 2021
CSSP-China Workshop on Seasonal Typhoon Forecasts
Prof. RALF said in the opening remarks that the Imperial College London is very supportive of the CSSP project and actively seeks in-depth cooperation in the field of typhoon season forecasting. “We expect to establish a practical and feasible cooperation mechanism to further strengthen the strategic partnership between Chinese and British climate scientists. The aim of this cooperation is to promote the transformation of internationally leading climate science into climate services for the benefits of people in both countries.” said Prof. RALF.
Prof. BAO Qing and Dr. LI Jinxiao from the IAP, CAS were invited to attend the meeting and give a report. Dr. LI Jinxiao systematically introduced the composition of CAS FGOALS-f2, a new generation of IAP/LASG typhoon dynamical ensemble seasonal prediction system, and the skill of hindcasting/real-time seasonal prediction of typhoons. The report was well received. Prof. BAO Qing reported the latest advance. The prediction system has completed 20-year hindcast and has started the real-time prediction from 2020. The relevant dataset will upload to the sub-seasonal to seasonal (S2S) project phase 2 certified by the World Meteorological Organization.
Six speakers from different organizations introduced the research work of typhoon season prediction at this workshop, and the discussions were enthusiastic during the conference. Two simultaneous interpreters were hired to perform the real-time translation so as to achieve better communication. At the end of the meeting, the participants conducted a lively discussion on the needs of users and the next cooperation opportunity. As a result, a number of consensus and cooperation intentions were reached. Prof. Toumi Ralf expressed his appreciation for the progress made by Chinese and British scientists in typhoon prediction. He hoped that in the future, the prediction dataset of multiple organizations could be shared and cooperation could involve more partners including insurance, energy and other companies to make prediction information more widely used.
Editors: Chuanyi Wang (firstname.lastname@example.org), Kangjun Chen(email@example.com)