Automatic Tracking of Pregenesis Tropical Disturbances Within the Deviation Angle Variance System

Abstract

The deviation angle variance (DAV) method is an objective tool for estimating the intensity of tropical cyclones (TCs) using geostationary infrared (IR) brightness temperature data. At early stages in TC development, the DAV signal can be also a robust predictor of tropical cyclogenesis. However, one of the problems with using the DAV method at these early stages is that the operator has to subjectively track potentially developing cloud systems, sometimes before they are clearly identifiable. Here, we present a method that allows us to automatically track the evolution of cloud clusters using only the raw IR imagery and the resulting DAV maps. We have compared our objective method with results manually obtained on a limited data set spanning a 12-day period during the 2010 hurricane season in the western North Pacific and tuned the performance of the method to the manual results. The performance of the method was then tested by comparing the results with best track and invest files produced by the Joint Typhoon Warning Center for the four-year period 2009-2012. The long-term results agree well with the best track and invest files for the disturbances analyzed in terms of start time, end time, and locations of disturbances. The automatic tracking method presented in this letter may be used to reduce the dependence of tropical cyclogenesis DAV analyses on the expertise and ability of the operator.