Tropical Cyclone Tracking Using a Neighbor Enclosed Area Tracking Algorithm

Abstract

Abstract Tropical cyclone (TC) tracking is essential for calculating TC statistics from gridded datasets. A new method for TC tracking is presented here using neighbor enclosed area tracking (NEAT), which is based on the temporal overlap of enclosed areas above a vorticity threshold and differs from the widely used neighbor point tracking (NPT) method. The parameters of cyclone intensity, vertical-shear, and warm-core criteria were intensively tuned for NEAT and NPT. When these criteria were optimized for the typhoon tracks observed in the western North Pacific based on the Japanese 25-yr Reanalysis Project (JRA-25)/Japan Meteorological Agency (JMA) Climate Data Assimilation System (JCDAS) dataset, the NEAT and NPT algorithms captured approximately 85% of typhoons with little qualitative distortion in the spatial distribution and temporal variability of the TC track density. The grid system dependency of the algorithms was tested by applying NEAT and NPT to a high-resolution general circulation model output. The method presented here can also provide realistic statistics on the TC size, the extratropical transition timing, and the meridional heat transport.