This study utilized hot and cold indices to evaluate the changes in extreme temperature events that occurred in subtropical highland climates from 1991 to 2020. The modified Mann–Kendall (MMK) test and the Theil–Sen (TS) slope estimator were used to analyze the linear trends in the time series of the extreme temperature indices. The northern highlands of Pakistan (NHP) were considered as a case study region. The results showed that the annual maximum temperature had a slightly increasing tendency (at the rate of 0.14 °C/decade), while the annual minimum temperature had a slightly decreasing tendency (at the rate of −0.02 °C/decade). However, these trends were not significant at the 5% significance level. The decadal averages of the hot indices were the highest in the second decade (2000s), while they were the lowest in the subsequent decade (2010s). In comparison, all the cold indices except the annual minimum value of the maximum temperature (TXn) showed a persistent decline in their decadal averages throughout the 2000s and 2010s. Overall, the frequency of hot days significantly increased in the NHP during the study period. This study found that the hot days and coldest days increased over the past three decades in the NHP. However, there was a decreasing trend in the cold spell duration, cold nights, and the coldest nights over the past three decades, as demonstrated by the trends of the cold spell duration index (CSDI), the temperature of cold nights (TN10p), and the annual minimum value of the minimum temperature (TNn) indices. These changes may impact the environment, human health, and agricultural operations. The findings provide useful insights into the shifting patterns of extreme temperature events in northern Pakistan and have crucial implications for the climate-change-adaptation and resilience-building initiatives being undertaken in the region. It is suggested that the continuous monitoring of extreme temperature events is necessary to comprehend their effects on the region and devise strategies for sustainable development.

In rainfed areas, precipitation variations directly impact wheat growth stages such as emergence, tillering, jointing and booting, and maturity. Evaluating the impact of climate change on precipitation patterns during these critical growth stages is crucial for adapting climate change and ensuring global food security. In this study, projections of five General Circulation models (GCMs) under two shared socioeconomic pathways (SSPs) were used to predict the changing characteristics of precipitation during four main growth stages of wheat in the rainfed region of the Pothwar Plateau, Pakistan. Historical datasets of daily precipitation at six weather stations were analyzed to check the past changes in the precipitation patterns. During the baseline period (1985–2014), the annual average precipitation decreased at a rate of −9.75 mm/decade, while the amount of precipitation during the rabi season (wheat-growing season) decreased at a rate of −20.47 mm/decade. An increase in the precipitation was found during the fourth (flowering) stage of crop growth, while the first three stages experienced a decrease in the precipitation amount. The multimodal ensembled data, under the SSP2-4.5 scenario, revealed a significant decline (at the rate of −16.63 mm/decade) in the future annual precipitation. However, it is projected that, under SSP2-4.5, there may be a slight increase (4.03 mm/decade) in the total precipitation amount during the future rabi season. Under the SSP5-8.5 scenario, average annual precipitation exhibited a slightly increasing trend, increasing by 1.0 mm/decade. However, during the rabi season, there was a possibility of a decrease in precipitation amount, with a rate of 11.64 mm/decade. It is also expected that the precipitation amount may vary significantly during the crown root initiation, jointing and booting, and flowering stages in the near future. These results provide a framework for the planning of wheat production in the Pothwar region of Pakistan, taking into account the potential impact of shifting weather patterns, particularly in terms of uneven precipitation.

Pakistan, one of the world’s most water-stressed countries, is extremely vulnerable to climate change. This study analyzes the prospective effects of climate change on the rainfall in the Hub River Watershed (HRW), Sulaiman-Kirthar mountainous range of Pakistan. The projections of five global climate models (GCMs), from the Coupled Model Intercomparison Project phase 6 (CMIP6), were used. Analysis of future changes in rainfall patterns was performed under two shared socioeconomic pathways (SSPs). Results showed that the historical annual average rainfall was increasing in the HRW. The annual average rainfall is expected to decrease under SSP2–4.5 in HRW. However, under SSP5-8.5, an increasing trend over the next three decades is expected, particularly over the southern part of the HRB. The findings should further our knowledge of how climate change affects the Hub River Basin and motivate stakeholders and planners to develop the best mitigation plans.

This study analyses the dynamics of snow cover in the Neelum Watershed of Pakistan and the expected changes in temperature and precipitation. Google Earth Engine was used to analyze the variability of winter snow cover with the help of MODIS 8-day data from 2000 to 2020. Two model combinations totaling five CMIP6 General Circulation Models were used to interpret future climate projections based on three Shared Socioeconomic Pathways (SSP2-4.5, SSP3-7.0, and SSP5-8.5) for 2021–2050. The modified Mann–Kendall test was used to identify trends, and the Theil–Sen estimator was used to analyze the impact. The results demonstrate that the extent of snow-covered area increased significantly between 2000 and 2020, and approximately 6448.83 km² (approximately 87% of the watershed) was covered by snow in winter. All SSP scenarios indicated positive trends in winter precipitation with average rates of 1.87, 0.44, and 0.80 mm/yr under SSP2-4.5, SSP3-7.0, and SSP5-8.5. In all the scenarios, the minimum temperature (0.0405 °C yr⁻¹) and maximum temperature (0.0305 °C yr⁻¹) are consistently growing, as per temperature predictions. These projected changes indicate the danger of more frequent extreme weather events that will put a strain on the region’s ecosystems, agriculture, and hydropower operations. The findings offer the necessary information to inform strategies regarding climate adaptation and mitigation in the Neelum River basin.