Mayuri Chetia, Karishma Sarma and Ujjal Deka Baruah
Abstract
This study utilizes ERA5 reanalysis data to analyze the spatial distribution and temporal temperature trends across India from 1980 to 2023. We generated monthly, seasonal, and annual average temperature maps using the R programming language through raster dataset processing. The Ordinary Least Squares (OLS) method and the non-parametric Theil-Sen slope estimator were used for linear regression analysis to identify trends. At the same time, Pettittâs test detected significant change points in the time series. Results indicate a transparent temperature gradient of 0.0178 °C temperature increase over time, with the coldest regions located in the northern Himalayan areas, while central and southern India experience higher temperatures ranging from 25 °C to 29.4 °C. Seasonal analysis reveals that winter temperatures vary significantly with latitude, with lower latitudes generally experiencing higher temperatures. This study underscores the influence of topography on temperature variations in India, highlighting the stark climatic contrasts between its northern and southern regions.