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Climate change has significantly increased the frequency and intensity of human thermal stress, with relatively more severe impacts than those of pure temperature extremes. Despite its major threats to public health, limited studies have assessed spatiotemporal changes in human thermal stress in densely populated regions, like South Asia (SAS). The present study assessed spatiotemporal changes in human thermal stress characteristics in SAS, based on daily minimum, maximum, and mean universal thermal climate indices (i.e., UTCImin, UTCImax, and UTCImean) using the newly developed High-spatial-resolution database of the Thermal-stress Indices over South and East Asia for the period 1981–2019. This study is the first of its kind to assess spatiotemporal changes in UTCI indices over the whole of SAS. The study also carried out extreme events analysis of the UTCI indices and explored their nexus with El Niño-Southern Oscillation (ENSO) index. Results revealed a significant increase in heat stress in SAS, with the highest human thermal stress in western Afghanistan, the Indo-Gangetic Plain, and southeastern, and central parts. The extreme event analysis showed that the study region is likely to observe more frequent and intense heat extremes in the coming decades. The correlation of UTCI indices with ENSO exhibited a robust positive coherence in southeastern and central India, southern Pakistan, and northwestern Afghanistan. The findings of the study are critical in understanding human thermal stress and adopting effective risk reduction strategies against heat extremes in SAS. To better understand the dynamic mechanism of thermal extremes, the study recommends a detailed investigation of the underlying drivers of UTCI variability in SAS.

Winter (December to March) precipitation is the major source of rainfed agriculture, storage, and perennial water flow in the western river system of Pakistan. Hence, this study uses precipitation data and variables of land–ocean and atmosphere from the Pakistan Meteorological Department and European Centre for Medium-Range Weather Forecasts (ECMWF) and fifth-generation reanalysis data (ERA5), respectively, to investigate the changes in winter precipitation and its sensitivity to different land–ocean and atmosphere variables, which are rarely investigated in Pakistan. Non-parametric techniques, such as the modified Mann–Kendal, Sen slope, kernel density-based probability function (PDF), empirical orthogonal function (EOF), and correlation analysis, were used to assess the changes and modes of variability in winter precipitation. The overall seasonal precipitation showed a significant decreasing trend with a (−0.1 mm d−1 yr−1) in the seasonal mean and monthly precipitation, except in February which showed a significant increase (>0.11 mm d−1 yr−1). The highest decrease in daily precipitation (<−0.1 mm d−1 yr−1) was in the north, with a moderate decrease in the southeast. The extreme precipitation indices exhibited an erratic decreasing tendency, but the maximum daily precipitation index increased; post-2000 precipitation extremes displayed an increase, and the seasonal and monthly precipitation exhibited the highest deviations during the drought period (1995–2000). The leading precipitation mode (EOF1) is sensitive to the local land surface processes and significantly correlated (>0.60) with the central Pacific and Indian Ocean’s basin-wide sea surface temperature, corroborating the influence of ENSO-induced meridional/zonal deviation of Hadley–Walker circulations. The Hadley and Walker cells affect the south-westerlies’ jet stream strength, impacting the water vapor transport and precipitation over Pakistan. These changes in the precipitation magnitude will affect rain-fed agriculture, especially the Rabi cropping pattern and perennial river flow.