Spatio-temporal analysis of meteorological variables over India for 21st century approach with CMIP6 climate models

Abstract

Climate change poses a significant threat to human society, causing loss of livelihoods, human lives, and biodiversity. It affects climatological variables, leading to rising temperatures and precipitation patterns. By the end of the century, global surface temperatures could reach 1.4-5.8°C, increasing disaster severity. According to Germanwatch 2020 report, India is the seventh-most vulnerable nation to climate extremes. Factors such as dense population, diverse climatic regions and huge population engagement at agriculture makes India one of the world's most vulnerable countries. Through this study suitable climatic models for the eight different regions according to the Koppen’s climatic classification was identified by computing Correlation coefficient, Root mean square error and mean bias error. Future changes meteorological variables (precipitation, max and min temperature) simulated from CMIP6 climatic models under four shared socioeconomic pathway scenarios (SSP126, SSP245, SSP370 and SSP585) were evaluated. In this work, the future and historic meteorological variable’s trend pattern was investigated with Modified Mann-Kendall (MMK) test and Sen’s slope test for the entire India for four different climatic seasons (Monsoon, Autumn, Winter and Summer). The study identified that, for the upcoming future the precipitation and temperature projected increasing trend for all the SSPs. Particularly, SSP 585 case projected relatively more increase than the other scenarios. High precipitation as well as more variability is the case for the SSP 585 scenario. Projected Monsoon and Autumn seasons witnessed more rainfall. Western region of India has more chances of rainfall decrease and risk of dry spell. Over all, remarkable variation of meteorological variable trend between different regions as well as seasons was witnessed over the considered timespan. Moreover the correlation between precipitation and maximum temperature was also analysed using the wavelet coherence plot.