| dc.description.abstract | A fuzzy logic algorithm for convection initiation (CI) forecast utilizing 11-year surface observation data in July, August, and September in Taiwan is developed and investigated. The location and time of 10-year (2011-2020) 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 191-232 automatic weather stations, namely temperature, relative humidity, water vapor mixing ratio (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 statistical results show that the CI event, under the weak-synoptic condition, mainly occurred during the afternoon hours (13-17 LST) with a peak occurrence between 14-16 LST with the highest occurrence frequency in the central Taiwan regions in Chiayi, Yunlin, and Changhua. The surface environment analysis revealed significant differences in moisture-related variables and the zonal wind component (U-wind). In north Taiwan, CI events have higher moisture propagated inland with the sea breeze, resulting in higher equivalent potential temperature (θ_e). Both CI and non-CI events have evident boundaries of the U-wind, indicating the confinement of sea breeze to the southern region during null events. Sounding data show that during CI events, the lower to mid-level winds were southwest winds, the water vapor mixing ratio was ~0.5-1.5 g/kg higher and the equivalent potential temperature was ~1.5-3.4 K higher. These indicate a more humid environment with higher energy that favors convection initiations.
The probability density functions (PDFs) of all variables were calculated for CI and non-CI events. The normalized PDFs of each variable are derived as membership functions. The weighting of each membership function is determined by the reciprocal of the overlapping area of PDF. The self-check results from the fuzzy logic algorithm show 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 was 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 the fuzzy logic algorithm for the CI forecast.
Additionally, the usage frequency of each station of each variable demonstrated that water vapor the mixing ratio and the θ_e in central and northern Taiwan were the primary variables for the fuzzy logic algorithm to determine CI events. This suggests that moisture-related variables in central and northern Taiwan have a significant influence on CI events. Other variables played auxiliary roles, with wind-related variables such as the U-wind component, V-wind component, wind speed, and wind direction. | en_US |