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.
