WGNE Intercomparison of Tropical Cyclone Forecasts by Operational NWP Models: A Quarter Century and Beyond

WGNE Intercomparison of Tropical Cyclone Forecasts by Operational NWP Models: A Quarter Century... AbstractTropical cyclone (TC) track forecasts of operational numerical weather prediction (NWP) models have been compared and verified by the Japan Meteorological Agency (JMA) under an intercomparison project of the Working Group on Numerical Experimentation (WGNE) since 1991. This intercomparison has promoted validation of the global models in the tropics and subtropics. The results have demonstrated a steady increase in the global models’ ability to predict TC positions over the past quarter century.The intercomparison study started from verification for TCs in the western North Pacific basin with three global models. Up to the present date, the verification has been extended to all ocean basins where TCs regularly occur, and 12 global models participated in the project. In recent years, the project has been extended to include verification of intensity forecasts and forecasts by regional models.This intercomparison project has seen a significant improvement in TC track forecasts, both globally and in each TC basin. In the western North Pacific, for example, we have succeeded in obtaining an approximately 2.5-day lead-time improvement. The project has also demonstrated the benefits of multicenter track forecasts (i.e., consensus forecasts). Finally, the paper considers future challenges to TC track forecasting by NWP models that have been identified at the World Meteorological Organization’s (WMO’s) Eighth International Workshop on Tropical Cyclones (IWTC-8). We discuss the priorities and key issues in further improving the accuracy of TC track forecasts, reducing cases of large position errors, and enhancing the use of ensemble information. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bulletin of the American Meteorological Society American Meteorological Society

WGNE Intercomparison of Tropical Cyclone Forecasts by Operational NWP Models: A Quarter Century and Beyond

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0477
eISSN
1520-0477
D.O.I.
10.1175/BAMS-D-16-0133.1
Publisher site
See Article on Publisher Site

Abstract

AbstractTropical cyclone (TC) track forecasts of operational numerical weather prediction (NWP) models have been compared and verified by the Japan Meteorological Agency (JMA) under an intercomparison project of the Working Group on Numerical Experimentation (WGNE) since 1991. This intercomparison has promoted validation of the global models in the tropics and subtropics. The results have demonstrated a steady increase in the global models’ ability to predict TC positions over the past quarter century.The intercomparison study started from verification for TCs in the western North Pacific basin with three global models. Up to the present date, the verification has been extended to all ocean basins where TCs regularly occur, and 12 global models participated in the project. In recent years, the project has been extended to include verification of intensity forecasts and forecasts by regional models.This intercomparison project has seen a significant improvement in TC track forecasts, both globally and in each TC basin. In the western North Pacific, for example, we have succeeded in obtaining an approximately 2.5-day lead-time improvement. The project has also demonstrated the benefits of multicenter track forecasts (i.e., consensus forecasts). Finally, the paper considers future challenges to TC track forecasting by NWP models that have been identified at the World Meteorological Organization’s (WMO’s) Eighth International Workshop on Tropical Cyclones (IWTC-8). We discuss the priorities and key issues in further improving the accuracy of TC track forecasts, reducing cases of large position errors, and enhancing the use of ensemble information.

Journal

Bulletin of the American Meteorological SocietyAmerican Meteorological Society

Published: Nov 18, 2017

References

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