A Fuzzy Logic Algorithm for Convection Initiation Forecast in Taiwan

A fuzzy logic algorithm for convection initiation (CI) forecast utilizing 11 years of surface observations data in Taiwan is developed and investigated. The location and time of 10 years (2011-2020) of weak-synoptic CI and non-CI events were identified by the tracking results of convective thunderstorms by Storm Motion Analysis by Radar Tracking (SMART). The surface characteristics from 232 automatic weather systems, namely temperature, relative humidity, mixing ratio, equivalent potential temperature (θ_e), U-wind, V-wind, wind speed and wind direction, for CI and non-CI events were investigated.
The probability density function (PDF) of all variables were calculated for CI and non-CI events. The normalized PDF of each variable are derived as membership functions. The weighting of each membership function is determined by the overlapping area of PDF. The fuzzy logic result of CI is between 0 to 1. The threshold value of 0.5 is thus applied to define CI and non-CI. The self-check results from fuzzy logic algorithm shown high value of probability of detection (POD), success ratio (SR), and critical success ratio (CSI), as well as low probability of false detection (POFD). An independent year (2021) of CI and non-CI events were applied to examine the applicability of the fuzzy logic algorithm. The results indicate that the scores gradually increase as the time approaching to afternoon (CSI: 0.60~0.70, POD: 0.76~0.84, FAR: 0.25~0.18). The results suggest the potential of utilizing fuzzy logic algorithm for CI forecast.

Keywords: convection initiation; cluster of convection initiation; fuzzy logic algorithm