Time series trend analysis of temperature along with the study of extremes in the Northwest India

Abstract

This study examines the spatiotemporal dynamics of extreme heat events across all 13 stations selected from Northwest India from 1990 to 2020. After using statistical tools for analyses, a rare and varied landscape in temperature change is observed. During which some cities like Agra and Delhi showed a statistically significant upward trend for maximum and average temperature supporting the global warming concerns and other stations like Amritsar show more elaborated scenario. These stations uncover a variety of trend in different patterns were observed like rise in maximum temperature and minimum temperature remains stationary and even shown decline in temperature trends and all these observation shows that the influences of microclimate and geographical patterns make impact on the temperature variables. Further analysis which was conducted for heat wave also revealed the dynamics of heat waves for all stations. During which annual variations and regional disparities in occurrences and intensity were observed. 2010 and 2019 were the years which showed maximum temperature and Gorakhpur station experienced an intense range of temperature up to 48and#8451;. These events increase the risk to the agriculture sector because productions get affected and health of the local public, mainly the vulnerable populations. The importance of multi-year climatic cycles is proposed by annual variations in heatwaves and maximum temperature values it adds another level of complexity and calls for adaptive strategies and adaption measures. During analysis an quotExtreme Cautionquot heat index category across the stations and decades was observed and this observation makes it more concerning because of the constant thermal threat which demands immediate action. Lastly, this study emphasizes on the pattern of heat waves events in Northwest India. It also highlighted the need of comprehensive regional climate action plans for ongoing monitoring to respond to changing patterns and modified adaption measures at basic level. newline