Have We Reached the Limits of Predictability for Tropical Cyclone Track Forecasting?

Author:

Landsea Christopher W.1,Cangialosi John P.1

Affiliation:

1. NOAA/NWS/NCEP/National Hurricane Center, Miami, Florida

Abstract

AbstractThe tropical cyclone is the largest single-day-impact meteorological event in the United States and worldwide through its effects from storm surge, extreme winds, freshwater flooding, and embedded tornadoes. Fortunately, over the last three decades there have been incredible advances in forecast accuracy, especially for the track of the tropical cyclone’s center. Errors have been cut by two-thirds in just 25 years due to global modeling advances, data assimilation improvements, dramatic increases in observations primarily derived from satellite platforms, and use of ensemble forecast techniques. These four factors have allowed for highly accurate synoptic-scale atmospheric initial conditions and forecasts of the steering flow out through several days into the future. However, such improvements cannot continue indefinitely. It is well known in the atmospheric sciences that there exists an inherent “limit of predictability” because of errors at the smallest scales (microscale—meters and seconds) that eventually cascade up to the largest scales (synoptic scale—thousands of kilometers and several days). While there have been estimates of the limits of predictability for tropical cyclone track prediction in the past, our current capabilities have exceeded those somewhat pessimistic earlier outlooks. This essay discusses the current state of the art for tropical cyclone track prediction and reassesses whether reaching the “limit of predictability” is imminent. The ramifications of this eventual conclusion—whether in the short-term or still decades away—could be critical for all users of tropical cyclone track forecast information, including the emergency management community/governments, the media, the private sector, and the general public.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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