QUANTITATIVE ASSESSMENT OF RELATIVE HUMIDITY, K INDEX, AND TT INDEX USING PROGRAMMATIC ANALYSIS

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, thunders...

Full description

Saved in:
Bibliographic Details
Published inJournal of mechanics of continua and mathematical sciences Vol. 20; no. 6; pp. 225 - 245
Main Authors Ghosh, Indrajit, Roy, Ananya, Gupta, Vanshika, Bhattacharya, Shruti
Format Journal Article
LanguageEnglish
Published Institute of Mechanics of Continua and Mathematical Sciences 01.06.2025
Subjects
atmospheric instability
climate modeling
computational programming
error analysis
k index
relative humidity
tt index
weather forecasting
Online AccessGet full text

Cover

More Information
Summary: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.
ISSN:0973-8975
2454-7190
DOI:10.26782/jmcms.2025.06.00014