Analysis of extreme weather events over Pune district of western Maharashtra using RClimDex model

Introduction

Tragedies resulting from extreme weather occurrences account for over 85% of all natural disasters worldwide (Obasi, 1994) [19] . According to Chhabra et al. (2015) [6] , extreme weather events like flood, occurrence of drought, stormy rainfall and cyclone put a major impact on human society. According to Plummer et al (1999) [21] , extreme meteorological events cause the majority of natural disasters worldwide. Therefore, there is a great deal of interest in researching climate extremes. According to the Inter-governmental Panel on Climate Change (IPCC, 2014) [10] study, the average global Tmax and Tmin temperatures across the terrestrial surface have risen by more than 0.1 ℃ per ten years since 1950. The evolving patterns of climate extremes demanded increased attention. The changes that occur in the frequency of extreme weather events are considered an indicator of climatic variability. India's agricultural production systems are quite susceptible to climatic fluctuations. The ideal climatic parameters for each crop must be met in order to maximize output. It is crucial to have adequate understanding of the agro-climatic resources of the location/region in order to produce maximum output possible while utilizing farm resources sustainably. With more frequent occurrences of extreme weather events including droughts, floods, heat or cold waves, cyclones, and hailstorms due to climate change, the sensitivity of agricultural production systems to various climatic aberrations is growing. It is necessary to analyze historical data on climatic factors using proper statistical tools to enable the creation of location-specific technologies and adaptation strategies. Also, it is crucial to comprehend a region's climatic characteristics in order to enhance agricultural operations and boost farmer output and profits. The choice of agricultural systems and resource management alternatives for greater profitability depends on the micro-scale characterization of the agro-climate. This climate microanalysis may be incorporated into a bottom-up strategy to create a national climate database. This study highlighted regional variations in the frequency and intensity of extreme weather events across five districts in Western Maharashtra. This study aided climatic analysis of the study area and made it possible to comprehend the climatic characteristics of the region concerned.

Materials and Methods

This chapter deals with description of study area, data collected for the study and their sources and methodologies adopted for research work of "Analysis of extreme weather events of Western Maharashtra region using RClimDex model" using temperature and precipitation data from 1982-2022 are briefly presented. The data was first homogenized, and then quality control was performed in RClimDex model.

Location and Extent

Western Maharashtra is division of Maharashtra state also called as "Desh" is the region adjacent to Western Ghats between the Godavari River and Krishna River, a part of Deccan Plateau. It is bordered by the Konkan region to West and the states of Karnataka and Goa to South. The Pune district is situated near the Western Ghats, with Deccan Plateau to the east. The diverse landscape of study region includes hills, valleys and Plateaus. The entire Pune climate is whole dry. The hot season, which lasts until early June, comes after the cold season, which runs from November to February. On an average, there are 53 rainy days (i.e. days with rainfall of 2.5 mm or more) in a year in the Pune district. This number varies from 30 at Daund and Jejuri to 104 days at Khandala. The heaviest rainfall in 24 hours recorded at any station in this district was 578.0 mm at Lonavala. The highest maximum temperature ever recorded at Pune was 43. RClimDex includes a simple-procedure for available meteorological data quality control that was provided in ClimDex, as in it, the quality-controlled data is required before the indices can be computed and analysed. The software modifies the following aspects:

1. The deviation (eccentricity) in the daily precipitation, daily average temperature, daily minimum temperature and daily maximum temperature data were identified. 2. The unreasonable data (outliers) mainly included data that the daily minimum temperature is greater than the daily maximum temperature and the daily precipitation is negative.

Results and Discussion

The primary objective of the research was to compute temperature and precipitation based extreme indices during the period from 1982 to 2022 for Pune district from Western Maharashtra using RClimDex model (Zhang and Yang 2004) [25] . The indices have been utilized to monitor climate change and undertake investigations regarding extreme weather events. ( [22,5,17] . This study highlights shifting pattern of temperature and precipitation over Pune district as well as the regional variations in frequency and intensity of extreme weather events. Using the RClimDex model, extreme weather events were assessed. The significance of the variations that arise from the RClimDex model's computation was investigated more thoroughly. The p-value and a comparison of the estimate and error slopes were used to test the significance. This test was used to calculate the magnitude of trends. If the p-value is less than 0.05, significant changes will be identified. Significant changes were recognized when p-value was less than 0.05 and slope estimate was larger than the slope error value.

Pune District

The data revealed that, there were no frost days or ice days in Pune district (Table 3), indicating that the range of daily temperatures for Pune district does not fall at significant cold extremes, which would lead to the formation of frost and ice in the study area. The number of cold days (FD15) showed significant decreasing trend (p=0.007). The annual number of summer days (SU25) in Pune district indicated a non-significant decreasing (negative) trend, whereas for the number of summer days (very hot days) (SU38) trend was found significantly increasing. Table 3 shows a significant increase in the annual count of days when the TN (daily minimum) temperature was greater than 20° C, i.e. the number of tropical nights (TR20) in the Pune district from 1982 to 2022 (p=0). Arthur DeGaetano et al. (2002) [2] observed similar trends regarding minimum temperature indices. The increasing trends for annual count of number of tropical nights (TR20) and number of tropical nights (user defined) (TR23) with p=0 indicated warming of region. The extreme temperature index cold spell duration indicator (CSDI) was found to be significantly decreasing (p=0.001) with slope estimate = -0.297 over Pune district during the period of 1982-2022 also the other temperature extreme viz. warm spell duration indicator (WSDI) has followed non-significant decreasing trend over same period with slope estimate is negative 0.092. Cold spell duration indicator (CSDI) was found decreasing from 40-60 days to 10-15 days from 2022-2010. The decadal trend for CSDI was found decreasing for the period of 1990-2000. In the case of WSDI the decadal trend showed decrease from 0 days in year 1989, 1991, 1993, to 38 days in year 2000. The decadal trend for WSDI was found to be decreasing gradually from 2010 to 2020. The warmest daily maximum temperature (TXx) with p= 0.226 and the value of slope estimate is -0.015 and annually minimum value of daily minimum temperature (TNn) have showed non-significant decreasing trend with p=0.838 over period, whereas the warmest daily minimum temperature (TNx) has showed increasing trend over the period of time (p=0.42). The coldest daily maximum air temperature (TXn) for the Pune district decreased significantly from 1982 to 2022 (p=0.034). Similar conclusions were obtained by Singh et al (2015) [3] in the research performed on the detailed analysis of extreme temperature indices for the Sutlej river basin from 1970 to 2005. The number of cool nights (TN10p) showed significant decrease over Pune district (p=0) whereas number of warm nights (TN90p) showed significant increase in Pune district (p=0.002).

The decadal trend for this index TN10p decreased from 14 nights in 1990 to seven nights in 2000 year. In 2010 five cool nights were observed while in year 2016 14 nights were recorded. This showed significant decreasing trend over Pune district from 1982-2022. These outcomes are consistent with the findings of Manton et al. (2001) [15] in the assessment of trends in extreme daily temperature and rainfall for Southeast Asia and the South Pacific from 1961 to 1998. While the decadal trend of number of cool days (TX10p) showed non-significant increasing trend, the decadal trend for number of warm days (TX90p) showed non-significant decreasing trend during the period of 1982-2022 over Pune district (p=0.57). [13] showed similar outcomes.

The consecutive dry days (CDD) where maximum number of consecutive days with RR<1 mm was found to be increasing over period of 1982-2022 but non-significantly (p=0.286) whereas the consecutive wet days (CWD) where maximum number of consecutive days with RR≥1 mm was found to be significantly increasing over the period of 1982-2022 for Pune district (p=0.002). Singh W. R et al (2021) [24] showed similar trends in the study carried over Arunachal Pradesh. The simple daily intensity index (SDII), the annual total wet-day precipitation (PRCPTOT) and the annual number of very wet days (R95p), where annual total precipitation when RR > 95th percentile all showed a significantly increasing trend over the 1982-2022 period for Pune district (p=0.002; p=0, and p=0, respectively). In contrast, the extremely wet days (R99p) showed an increasing trend, but non-significantly over the same period (p=0.102). From the study it is clear that the intensity as well as duration of rainfall has increased over the studied period over Pune district. Out of nine precipitation indices 6 indices showed significantly positive (increasing) trend while the other 3 indices showed positive trend but non-significantly (Table 4).

Conclusion

The study on 27 core indices based on daily temperature and daily precipitation in case of Pune district indicated that the number of cold days (FD15), number of cool nights (TN10p), Diurnal Temperature Range (DTR), cold spell duration indicator (CSDI) and the coldest daily maximum temperature (TXn) showed significantly decreasing (negative) trend whereas number of very hot days (SU38), annual count of number of tropical nights (TR20) and number of hot nights (TR23), warm nights (TN90p), cool days (TX10p), warmest daily minimum temperature (TNx) and the coldest daily maximum air temperature (TXn) have showed increasing trend in Pune district. In terms of the precipitation based extreme indices out of nine indices 6 showed significantly positive (increasing) trend whereas only 3 indices indicated positive trend but nonsignificantly. This study aided climatic analysis of the study area and made it possible to comprehend the climatic characteristics of the region concerned. The findings in the study can be used by scientists for future investigations and also can be used by policy makers.

Acknowledgement

AcknowledgementI place my deep sense of gratitude to Department of Agriculture, Government of Maharashtra, India Meteorological Department, Pune and Department of Agricultural Meteorology, College of Agriculture, Pune for their valuable help, meticulous guidance and cooperation.

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