Fate of Rainfall Over the North Indian States in the 1.5 and 2°C Warming Scenarios

Abstract

Rise in mean temperature put a great deal of uncertainty about how weather and climate extremes may play out, particularly in India's varied climatic zones. Consequently, it is important to understand the possible changes in both magnitude and direction of weather and climate extremes like rainfall for different warming levels of 1.5 and 2°C scenarios concerning preindustrial and present levels. Hence in the present study, the precipitation behavior of seven North Indian states that is, Haryana, Himachal Pradesh, J&K, Punjab, Rajasthan, Uttar Pradesh, and Uttarakhand carefully studied using CMIP5 models. Future projections of precipitation has been done for the Paris Agreement global warming level of 1.5 and 2°C scenarios. Along with model validation and future projections of precipitation, the return period of extreme rainfall is also discussed to understand the behavior of the occurrence of extreme precipitation. Statistical analysis shows that the ensemble means have the least error as compared to the other six CMIP5 models. Therefore, future analysis has been done with the ensemble mean. Our findings show that the precipitation is likely to decrease in the 1.5°C scenarios, while it is likely to increase in the 2°C scenarios. The occurrence and intensity of extreme rainfall events are likely to be more frequent in all the models. The return period of the extreme rainfall events is likely to increase in all the states in both the warming scenarios. A three‐fold rise is likely to increase extreme rainfall events in the 2°C scenario.

Evaluation of Precipitation Frequency and Intensity as Estimated by the GPM IMERG Precipitation Product at Daily and Hourly Scales over the Tibetan Plateau

“…The hourly PA of the IMERG hourly precipitation product reached its maximum at about 20 and 21 LST and had its minimum at 10 LST (Figure 9b). The diurnal variation of PF was broadly consistent with that of hourly PA, but the peak occurred about three hours earlier (17)(18)(19). In contrast to the observed result, the strongest PI occurred at about 22 LST, which is about one hour later than the peak of the hourly PA (Figure 9b).…”

“…Many previous studies have made efforts to evaluate the applicability of IMERG precipitation products (hereafter referred to as IMERG) to many regions [6][7][8][9][10][11][12][13][14][15]. In general, IMERG can capture the major heavyrainfall regions in both the northern and southern hemispheres and has been evaluated for many regions of the world, such as India, the Brazilian Amazon rainforest, Far East Asia, Pakistan and Türkiye [16][17][18][19][20][21]. Due to the vast coverage and complex terrain distribution of China, many previous studies have also evaluated the performance of IMERG for different regions [22][23][24][25].…”

Efficacy of Machine Learning in Simulating Precipitation and Its Extremes Over the Capital Cities in North Indian States

“…Additionally, all states face challenges related to the impact of climate change on agriculture 49,50 . Understanding this interplay between natural processes and human activities across this vast region with its varying elevations and temperatures is crucial for developing effective management strategies and sustainable development practices 30,49 .…”

“…The 2013 Uttarakhand disaster, which involved rapid monsoon progression and heavy precipitation, resulted from a combination of these large-scale circulations, orographic lifting, and intense convective activity 29 . These extreme precipitation events are known to exacerbate due to climate change with increased frequency and intensity 30,16 .…”

“…For India, a few literatures are available for extreme precipitation analysis 30,[42][43][44] , however relatively fewer for extreme precipitation modelling using machine learning 37,45,46 . The limited availability of highquality and comprehensive meteorological data in India and complexity of the regional topography and climate are also prominent contributing factor for limited number of research.…”