Authors:
Indrajit Ghosh,Ananya Roy,Vanshika Gupta,Shruti Bhattacharya,DOI NO:
https://doi.org/10.26782/jmcms.2025.06.00014Keywords:
Relative Humidity,K Index,TT Index,Atmospheric Instability,Computational Programming,Climate Modeling,Error Analysis,Weather Forecasting,Abstract
This study conducted a quantitative analysis to evaluate the statistical significance of climatic parameters such as Relative Humidity (RH), K Index and Total Totals (TT) Index. Given Kolkata's susceptibility to various atmospheric extreme events—including discomfort indices, cyclones, thunderstorms, hailstorms and torrential rains—the city was selected as the focus for this analysis. The research aimed to develop accurate predictive models by performing extensive statistical analyses on available upper air data from Kolkata across all three seasons: summer, winter and the monsoon. Python was utilized for statistical computations to derive semi-empirical relationships between RH, geopotential height and pressure. The primary objective was to establish predictive equations that could be validated against real-time data. The models demonstrated a low Mean Squared Error (MSE) of approximately 20.69, indicating their potential as reliable tools for significant statistical assessments.Refference:
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