Evaluating the impact of climate change on extreme temperature and precipitation events over the Kashmir Himalaya

Abstract

The frequency and severity of climatic extremes is expected to escalate in the future primarily because of the increasing greenhouse gas concentrations in the atmosphere. This study aims to assess the impact of climate change on the extreme temperature and precipitation scenarios using climate indices in the Kashmir Himalaya. The analysis has been carried out for the twenty-first century under different representative concentration pathways (RCPs) through the Statistical Downscaling Model (SDSM) and ClimPACT2. The simulation reveals that the climate in the region will get progressively warmer in the future by increments of 0.36–1.48 °C and 0.65–1.07 °C in mean maximum and minimum temperatures respectively, during 2080s (2071–2100) relative to 1980–2010 under RCP8.5. The annual precipitation is likely to decrease by a maximum of 2.09–6.61% (2080s) under RCP8.5. The seasonal distribution of precipitation is expected to alter significantly with winter, spring, and summer seasons marking reductions of 9%, 5.7%, and 1.7%, respectively during 2080s under RCP8.5. The results of extreme climate evaluation show significant increasing trends for warm temperature-based indices and decreasing trends for cold temperature-based indices. Precipitation indices on the other hand show weaker and spatially incoherent trends with a general tendency towards dry regimes. The projected scenarios of extreme climate indices may result in large-scale adverse impacts on the environment and ecological resource base of the Kashmir Himalaya.

Event‐based extreme precipitation variability analysis over a part of the Hindu Kush Himalayan region

“…The percentages of total frequency and volume contribution of four EEP patterns computed with IMD data are plotted in Figure 5. Here we used the inverse distance weightage (IDW) method as this interpolation method for smother representation of the results (Figures 5–14) as it is most appropriate and has been widely used in high altitude regions (Ahsan et al, 2022; Das et al, 2022; Saha et al, 2022). The percentage of the total frequency of TDP1 and TDP2 is similar (ranging between 30% and 40%).…”

Complementary use of multi-model climate ensemble and Bayesian model averaging for projecting river hydrology in the Himalaya

“…The imprints of global climate change are well established from the observational datasets in the Jhelum basin and its impacts are already being felt (Ahsan et al, 2021a). Few studies e.g., (Ahsan et al, 2021b) have also attempted to estimate the magnitude of climatic changes over the 21 st century. However, these studies are limited in scope because the projections are based on a single GCM.It has been found that GCM outputs inherit considerable uncertainty in them and thus use of a single GCM can yield inaccurate results (Khan et al, 2021).…”

Assessing indigenous community’s perspectives and attitudes toward tourism development impacts in the northwestern Himalayas, India

“…However, the tourism impacts and non-tourism activities on socio-cultural and environmental issues are hard to separate and evaluate (Briassoulis 2002 ). Mountain ecosystems like the Himalayas are especially susceptible to climate change owing to limited adaptive ability, resources, and cascade effects on downstream environments (Ahsan et al 2021 , p 0.2, Ahsan et al 2022 , p. 1665). The increased pressure on the population, commercial forestry, tourism activities, and economic prosperity are the leading causes of the destruction of the environment in the Himalayan ecosystem (Rawat and Sharma 1997 ).…”