The Role of Instability Indices in Forecasting Thunderstorm and Non-Thunderstorm Days across Six Cities in India

Abstract

Thunderstorms are one of the most damaging natural hazards demanding in-depth understanding and prediction. These convective systems form in an unstable environment which is quantitatively expressed in terms of instability indices. These indices are studied over six locations across the Indian landmass in an attempt to predict thunderstorm activity on any given day. A combination of multiple regression, logistic regression, and range analysis provides new insight into the prediction of these storms. A supervised machine learning-based logistic regression model is developed in this study for thunderstorm prediction over Patna and can be further extended for operational forecasting of Thunderstorms over the region. Critical thresholds for the instability indices are determined over the considered locations providing valuable insight into the domain of Thunderstorm prediction

Spatio-temporal changes in the pre-monsoon thunderstorm activities of northeast India over the past four decades

“…The index is most suitable for flat to low elevation areas and does not properly work for high elevation regions, which change with seasons and locations. 36 The pre-monsoon climatology for the 40 years shows that the KI index varies in the range of 25–35, as depicted in Fig. 3, with higher values in southern West Bengal, Assam and Tripura, which well match with CAPE and CIN there.…”

“…The index is made up of Vertical Totals (VT) and Cross Totals (CT), and is thus defined as the total of both indices. 36 A higher TTI number indicates a greater likelihood of thunderstorm occurrence. The index is complete because it covers both vertical and cross total of the environment, and it works best in flat places with low to moderate elevations.…”

Performance analyzes of thermodynamic indices and atmospheric parameters in thunderstorm and non-thunderstorm days in Istanbul, Turkey

“…In this study, skill scores were used to evaluate the performance of thermodynamic indices and atmospheric stability parameters. These methods have been preferred for estimating the stability of the atmosphere in many studies similar to this study (Tyagi et al 2011;Sahu et al 2020;Arora et al 2023). In order to calculate the skill scores, it is necessary to classify the actual TS event observations and the estimation results obtained from the indices and parameters.…”

“…The aviation sector is at the top of the sectors dealing with TSs because they lead to accidents and incidents in the aviation operations ( Studies in the literature have revealed that three basic requirements for TS formation. These are (1) instability in the atmosphere, (2) su cient moisture at lower tropospheric levels, and (3) lifting mechanism(s) (i.e., convection, frontal lifting, convergence) (Bennett et al 2006;Trapp 2013; Kunz et al 2020; Arora et al 2023). Additionally, the necessity of vertical wind shear has been added as the fourth requirement (Ackerman and Knox 2012; Dennis and Kumjian 2017; Özdemir 2021).…”

Performance Analyzes of Thermodynamic Indices and Atmospheric Parameters in Thunderstorm and Non-thunderstorm Days in Istanbul, Turkey

“…The aviation sector is at the top of the sectors dealing with TSs because lead to accidents and incidents in the aviation operations (Islam & van Amstel, 2018;Koutavarapu et al, 2021;Yavuz et al, 2020Yavuz et al, , 2022a. Studies in the literature have identified three basic requirements for TS formation: (1) instability in the atmosphere, (2) sufficient moisture at lower tropospheric levels, and (3) lifting mechanisms (such as convection, frontal lifting, convergence) (Arora et al, 2023;Bennett et al, 2006;Kunz et al, 2020;Trapp, 2013). Additionally, the necessity of vertical wind shear has been recognized as a fourth requirement (Dennis & Kumjian, 2017;O ¨zdemir, 2021).…”