CMIP6-Based Climate Projections and Trends for Exploring Adaptations and Policies in Pakistan

Abstract

Pakistan is largely dependent on agriculture; climate change induces considerable complexities for its anthropogenic systems, requiring detailed climate projections at fine spatio-temporal scales. This study employs bias-corrected daily climate data based on 13 CMIP6 General Circulation Models (GCMs), which were validated against CRU TS4. 03 datasets to comparatively assess past and projected climate conditions among SSP245 and SSP585 pathways. For two cropping season (Rabi, and Kharif) temperature and precipitation trends were investigated for Pakistan’s main agricultural provinces, Punjab and Sindh. Mann-Kendall and Sen's slope tests were employed to investigate temperature and precipitation variations over time and space.  Our CMIP6 based results reproduces reliable historical data both spatially and temporally, supporting its use in regional climate impact studies. At national scale, Tmin increase more than Tmax. In SSP585, Tmin is projected to increase by 5.22°C, while Tmax is expected to rise by 4.02°C, by 2100. Precipitation too has a more or less steady upward trend by 28% and 53% under SSP245 and SSP585, respectively. Summer and winter temperatures increase strongly in Punjab. Tmin is likely to rise between 1.6°C–4.8°C by 2100 across the different scenarios. Summer precipitation rises moderately under SSP245 at around 20–40% and increases steeply up to 100% under SSP585. In Sindh, both summer and winter temperature increases follow similar trends; summer Tmax can reach up to 4°C in SSP585. Precipitation in Sindh may increase as much as 187% during the summer season in late century. Under SSP585, projections of increasing temperatures indicate growing trends of heat stress across Pakistan, which is impactful for agricultural productivity and water resource management. The research highlights Punjab's increased temperature variability from interactions with westerly systems and Sindh's steady rise in warming, associated with enhanced monsoons. These findings underscore the importance of high-resolution climate models in formulating evidence-based adaptation plans. Major recommendations encompass heat-resilient crop species, improved irrigation infrastructure, and early warning systems. These are critical measures to protect food security and threats from climate change to Pakistan’s agriculture and water sectors.