WMO Typhoon Landfall Forecast Demonstration Project (2010–22): A Decade of Transition from Track Forecasts to Impact Forecasts

Author:

Yu Hui12ORCID,Chen Guomin12,Wong Wai-Kin3,Vigh Jonathan L.4,Pan Chi-kin3,Lu Xiaoqin12,Zhang Jun A.56,Tang Jie17,Zhao Kun8,Chen Peiyan12,Yu Zifeng17,Yang Mengqi12,Dunion Jason56,Fang Zheqing17,Lei Xiaotu9,Tyagi Ajit10,Chen Lianshou11

Affiliation:

1. Shanghai Typhoon Institute, China Meteorological Administration, Shanghai, China;

2. Key Laboratory of Numerical Modeling for Tropical Cyclone, China Meteorological Administration, Shanghai, China;

3. Hong Kong Observatory, Hong Kong, China;

4. National Science Foundation, National Center for Atmospheric Research, Boulder, Colorado;

5. NOAA/AOML/Hurricane Research Division, Miami, Florida;

6. University of Miami, Miami, Florida;

7. Asia-Pacific Typhoon Collaborative Research Center, Shanghai, China;

8. Nanjing University, Nanjing, China;

9. Shanghai Meteorological Service, China Meteorological Administration, Shanghai, China;

10. India Meteorological Department, New Delhi, India;

11. Chinese Academy of Meteorological Sciences, Beijing, China

Abstract

Abstract The Typhoon Landfall Forecast Demonstration Project (TLFDP) (2010–22) was an international cooperative scientific project conducted under the framework of the WMO. The primary objectives of the TLFDP were to enhance the capability of tropical cyclone (TC) forecasters and support related decision-makers in effective utilization of the most advanced forecasting techniques for the ultimate purpose of reducing and preventing disasters associated with TC landfall. Forty agencies/organizations/projects globally participated in the activities of the TLFDP following its inception in 2010, although the primary focus was on landfalling TCs in the western North Pacific. The TLFDP facilitated collaborations and workshops that realized notable achievements in four key areas: 1) the collection, production, and sharing of TC data; 2) the development and application of TC forecast verification metrics; 3) research on TC forecast skill; and 4) development of new techniques for TC forecasting. An obvious outcome was the shift from prediction of TC features, including track and intensity, toward prediction of TC impacts with more probabilistic conception. The final years of the project also promoted increasing application of artificial intelligence and machine learning techniques in various techniques for analysis and forecasting of TCs. Although the TLFDP ended in 2022, its core activities have continued to be extended through new WMO projects and regional cooperative initiatives.

Publisher

American Meteorological Society

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