High Speed Method of Detection of Vortex without Empirical Conditions—Application to Risk-Assessment of Tropical Cyclone—

We propose a method to evaluate intensities and influential ranges of detected vortex as an extension of high speed method to detect vortex using a streamline with enhanced curvature, which is useful to identify tropical cyclones in huge climatology data. In the proposed method, center of vortex is detected by iteration of streamline from some initial points automatically. This method has high accuracy and low computational cost, because it does not need to check empirical conditions at all grid points, as in the case of conventional method. This paper exemplifies the accuracy of the vortex risk-assessing method using observational climatology data. Results suggest that this method is available for risk-assessment of tropical cyclones under global warming predicted by high resolution models.