Extreme rainfall and temperature variability have an impact on biodiversity, livelihood support, ecosystem services, people’s well-being, desertification, water resources, energy and agriculture etc. especially in developing countries (Abatan et al., 2016; Shrestha et al., 2017; Kalyan et al., 2021; Ahmed et al., 2022). Occurrence of extreme climate events such as flash floods, agricultural and meteorological drought, heat, uneven intensity and frequency of rainfall patterns are the most prominent impacts of climate change (Chandniha et al., 2017; Tabari, 2020; Kalita et al., 2023). Intergovernmental Panel on Climate Change (IPCC, 2013) Fifth Assessment Report (AR5) states that the global average temperature has risen by 0.85°C in the period 1880–2012. Warming of the atmosphere will increase its water-holding capacity (Hong and Ying, 2018) which will result in increased uncertain extreme rainfall events. The frequency and intensity of extreme climatic events are expected to continue with a rise in global temperature (IPCC, 2021; Chandole and Joshi, 2023).
Most South Asian countries are agricultural-dependent and developing nations as India’s majority of the population relies on monsoon rainfall. Agricultural seasons, crop selection and variety all depend on the timing of the monsoon rainfall (Ahmed et al., 2022; Kalyan et al., 2023). Earlier, interpolated point-based rain gauge data were the only source for the spatial rainfall distribution (Ahmed, 2023). Now, since the model-based high-resolution rainfall data is available for the Indian region with a large temporal resolution; statistical assessment of rainfall at different time scales may help farmers and other people who are primarily dependent on the rainfall.
On a large scale the recent impacts on human health and ecosystems of climate change and extremes are primarily due to greenhouse gas (GHGs) emissions, global warming and other significant anthropogenic activities (Zhang et al., 2013; Donat et al., 2019; Libertino et al., 2019; Manikandan et al., 2019; Kim et al., 2020; Chaubey et al., 2022; Dubey et al., 2023). It has been also observed by many researchers through various numerical modelling that as GHGs concentrations rise an increasing moisture transport in a doubled CO2 has taken place and will continue over the Indian region which will lead to uncertain extreme rainfall events over the area (Bhaskaran et al., 1995; May, 2002; Sen Roy and Balling Jr, 2004). Its impact will be severe due to its tropical environment, high population density, economic status and dependency on the onset and offset of south-western monsoon (Dash et al., 2009; Choubey et al., 2023). In India > 70% of the total rainfall is concentrated in four monsoon months (June, July, August, September). Even this has a Spatio-temporal variation which impacts the Indian climate and leads to the occasions of scarcity and access of water at the same time in two different regions in non-monsoon periods (Parthasarathy et al., 1994; Dash et al., 2013; Chandniha et al., 2017; Singh et al., 2021).
The Indian south-western monsoon also fluctuates by El Niño–Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) events as it starts from the warming of the Indian Ocean so it may interact with the ENSO-induced (Chaubey et al., 2022; Hussain et al., 2022) ocean circulations which may alter its manifestation towards its intensity. In particular, it hinders the thermal contrast between land and ocean which is reflected in monsoon rainfall frequency and intensity (Goswami et al., 2006; Panda et al., 2014; Benaini et al., 2023). As a result, a significant decrease in low and moderate rain while increased extreme rainfall events have been observed in the 20th century (Dash et al., 2009). The availability of daily gridded rainfall data led to improved climate change studies by detecting multiscale trends across the globe including India (Caesar et al., 2011; Raju and Nandagiri, 2017; Marak et al. 2020; Wang et al. 2020; Ahmed et al., 2022).
Several user-based thresholds have been used in extreme indices calculation but, thresholds based on distributions of climatic variables are more prominent in giving satisfactory results due to their relevance with local weather conditions. Thus, extreme rainfall and temperature indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) become significantly relevant because of their characteristics (frequency, amplitude, persistence) (Zhang et al. 2011; Dietzsch et al., 2017; Agnihotri et al., 2018; Sharma et al., 2018; Kumar et al., 2020). Later ETCCDI were upgraded to Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI). In total, 27 indices were developed based on daily rainfall and temperature data. With indices two user-friendly software were also developed written in R (RClimDex) and FORTRAN (FClimDex) respectively (Alexander et al., 2006). Analysing these indices are extremely important due to their direct relevance to socio-economics, agricultural implication and construction of future climate scenarios at monthly, seasonal and annual scale (Caesar et al., 2011; Jain and Kumar, 2012; Panda et al., 2014). Hence, it is also evident that daily rainfall data is of more importance to determine the spatial pattern of extreme indices trend (Sen Roy, 2009).
It has been observed that in India at a regional scale rainfall variability has impacted societal goals of sustainable development. Flood is one of the frequent and plausible impacts that 55 districts of India have experienced every year in recent times whereas, 75% of the districts are vulnerable to extreme climate events (Mohanty, 2020; Hussain et al., 2022). Concerning the mitigation and adaptation strategies towards the consequences of climate extremes, it’s very important to understand the trend and variability in historical hydro-meteorological data. Somehow, it’s difficult to understand the mass data set thus climate extreme indices calculation is a feasible and statistical way to understand climatic variability by comparing multi-scale time-series data (Badsha et al., 2016). In this paper, detailed information on rainfall extreme indices trends and variability on multiple Spatio-temporal resolutions over Gandhinagar district has been provided that can help to understand regional or microclimatic variability, severe disasters and therefore mitigation strategies.