Pakistan will be 100 years by the end of mid-21st century. Within its continued lifespan, it has borne witness to various climate change hazards exclusively conveyed under the umbrella of the Intergovernmental Panel on Climate Change (IPCC) Assessment Reports (ARs). Recently published IPCC’s AR6 establishes its distinctiveness by addressing co-benefits, risks, interactions, trade-offs and economic development factors associated with magnitude of climate change factors, both regionally and globally. With heavy exposure to climate change indications in recent times, implications of such factors to shared socioeconomic narratives needed attention, especially over Pakistan region. To address this, a moderate resolution General Circulation Model (GCM) viz. MRI-ESM2-0 of Coupled Model Intercomparison Project phase 6 (CMIP6) was engaged to detect magnitude of potential risks associated with five Shared Socio-economic Pathways (SSPs) in the future. Change in mean state of global climate extracted over local realm was integrated with Gantt-like charts to depict severity and abruptness of the studied pathways to potential threats and balances over provinces and regions of Pakistan. Results revealed realms of risk that potentially placed the provinces and the regions at par with globally provoked hazards, yet simultaneously co-befitted them with tradeoff of boosts in economic development based on fossil fuel investments. Nevertheless predictions of such nature are constrained with global and local policy interventions, and hence are conveyed as spectrum of potential implications of the global climate change on national realms in the future.

Emergence of climate change signal attributed to change in mean temperature can bring serious implications to economic stability of developing countries like Pakistan. Likewise, unawareness of vulnerability in regions of a country can direct mitigation efforts towards unwanted areas instead of towards ones that are genuinely deprived of. To address these two issues for Pakistan, we adopted a compendium of five metrics by using climate model data of near surface mean monthly temperature from output of a general circulation model MRI-ESM2-0 of Meteorological Research Institute (MRI), simulated under historical (1850-2014) and projected (2015-2100) periods for five shared socioeconomic pathways (SSPs) described in the sixth assessment report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) originally published in the year 2021. To identify potential hotspot regions, we used four out of the five metrics i.e., change in mean (DM–vulnerability metric), standard Euclidean distance (SED–vulnerability metric), change in standard deviation (DSD–stability metric), and standard score (Z-Score–stability metric) statistics for regional bounds of Pakistan. To investigate emergence of climate change signal, we computed the fifth metric viz. signal to noise ratio (SNR–agility metric) from time series of the near surface mean monthly temperature and checked how rapidly the subject signal emerged out of variability in the studied data under different scenarios. On the estimation of vulnerability and stability, our results revealed that the Himalayan region of Pakistan (the northeast corner) repeatedly appeared to be the most qualified region to be acclaimed as a hotspot due to its reach to optimal echelons in the associated metrics of the DM (more than four degrees), the SED (up to one), the DSD (close to null) and the Z-Score (close to null) under all the studied SSP scenarios. On the estimation of agility, our results revealed that owing to allegedly sustainable scenarios (with low to medium challenges to mitigation), the SSP1, the SSP2, and the SSP4 delayed the evolution of climate change signal (between 2070 to 2100) by at least two decades as compared to allegedly perplexing (high challenges to mitigation) SSP3 and SSP5 scenarios that accelerated the appearance of the signal by crossing the SNR threshold fairly earlier (between 2040 to 2060) in the 21^st century. With such knowledge at hand, this scientific contribution can advise policymakers and stakeholder agencies to exercise conversant decisions and to equip themselves with evidence to prioritize and target their resources in an informed way over Pakistan region.