Abstract
Single Spectrum Bipartite Graph (SSBG) model is developed to forecast thunderstorms over Kolkata(22∘32′N,88∘20′E)during the premonsoon season (April-May). The statistical distribution of normal probability is observed for temperature, relative humidity, convective available potential energy (CAPE), and convective inhibition energy (CIN) to quantify the threshold values of the parameters for the prevalence of thunderstorms. Method of conditional probability is implemented to ascertain the possibilities of the occurrence of thunderstorms within the ranges of the threshold values. The single spectrum bipartite graph connectivity model developed in this study consists of two sets of vertices; one set includes two time vertices (00UTC, 12UTC) and the other includes four meteorological parameters: temperature, relative humidity, CAPE, and CIN. Three distinct ranges of maximal eigen values are obtained for the three categories of thunderstorms. Maximal eigenvalues for severe, ordinary, and no thunderstorm events are observed to be(2.6±0.12),(1.88±0.09), and(1.26±.03), respectively. The ranges of the threshold values obtained using ten year data (1997–2006) are considered as the reference range and the result is validated with the IMD (India Meteorological Department) observation, Doppler Weather Radar (DWR) Products, and satellite images of 2007. The result reveals that the model provides 12- to 6-hour forecast (nowcasting) of thunderstorms with 96% to 98% accuracy.
Highlights
Thunderstorm is a mesoscale weather phenomenon with space scale varying from a few kilometers to a couple of 100 kilometers and time scale varying from less than an hour to several hours
The normal probability distribution function [23] is used as the statistical tool to identify the most probable range of values of the selected input parameters (T, relative humidity (Rh), convective available potential energy (CAPE), convective inhibition energy (CIN)) for the occurrence of thunderstorms (Table 1)
There will be a path between two set of vertices, VT and VP, for a particular thunderstorm day if the values in the vertex list of VP match with the threshold values of the parameters
Summary
Thunderstorm is a mesoscale weather phenomenon with space scale varying from a few kilometers to a couple of 100 kilometers and time scale varying from less than an hour to several hours. Severe thunderstorms create lot of damages to the properties and crops, human, and animal fatalities through strong surface wind, lightning, large hail, and occasional tornadoes. Every year, during the premonsoon months of April and May, Kolkata (22◦32 N, 88◦20 E) encounters with severe thunderstorms which are locally known as Nor’westers or Kalbaishakhi. Forecasting severe thunderstorms is a challenge for both meteorologists and atmospheric scientists in India because such highly nonlinear and chaotic phenomena may incur significant detrimental consequences on agricultural productivity and life [1]. There are various conventional methods for day-today forecast of thunderstorms like synoptic weather charts, thermodynamic diagrams (T-Φ gram), Radar observations, and statistical and numerical models. Premonsoon (April-May) thunderstorms of Kolkata are the most devastating weather leading to major loss of life and property on the surface and aviation hazard aloft. It is associated with towering cumulonimbus (Cb), high frequency of lightning, large hail, occasional
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