Regional Variability in Projected Temperature and Rainfall in Indian Punjab – A Case Study using the IPSL-CM5A-MR Modeled Scenario-wise Changes JATINDER KAUR*, PRABHJYOT-KAUR, SHIVANI KOTHIYAL AND S.S. SANDHU Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana-141004, Punjab ABSTRACT Projected changes in climatic entities are guided by the local topographic features of the region. With this objective the present study was conducted by analyzing the projected temperature and rainfall under four representative concentration pathways (RCPs) as simulated by IPSL-CM5A-MR model for seven locations lying in undulating mountainous terrain with humid (UMTH) climate (Ballowal Saunkhri), plain region with sub-humid (PSH) climate (Amritsar, Ludhiana, Patiala), plain region with semi-arid (PSA) climate (Bathinda) and plain region with arid (PA) climate (Abohar, Faridkot). The temperature and rainfall data and their anomalies from the baseline (1970-2015) were analyzed for three time slices i.e. Early (ETS-: 2020-2045); Mid (MTS-: 2045-2070) and Late (LTS-: 2070-2095). In general, the temperature is predicted to increase in all four study areas with a peak increase projected under RCP 8.5. In Punjab state under RCP 2.6, 4.5, 6.0 and 8.5 scenarios by the end of 21 st century, the maximum temperature (Tmax) would increase by +0.1 to +1.4, +0.1 to +2.8, -0.2 to +2.8 and +0.4 to +4.9°C and the minimum temperature (Tmin) by -1.9 to +3.1, -1.1 to +4.7, -1.8 to 4.8 and -1.2 to +7.3°C, respectively, while the rainfall (RF) would decrease by 592, 540, 572 and 565 mm, respectively as compared to baseline 1970-2015. The increase in Tmax and Tmin and decrease in RF from their respective baseline (1970-2015) ranges revealed that amongst all the regions, there would be a peak increase/decrease in UMTH followed by PSH, PSA and PA in decreasing order. Consequently, the growth and yield of agricultural crops would be severely affected and suitable adaptive measures would be needed to offset the adverse effects of changes in climatic parameters. Key words: Climate projection, IPSL-CM5A-MR model, Rainfall, RCPs, Temperature, Punjab Bekele et al., 2019) which have a direct bearing on agricultural entities. The major drivers of climate change are the alterations in socio-economic condi- tions, technology, land use, energy consumption, and emission of GHG and finally the pollution of environmental resources. Climate change in the future will depend on the GHG emission trajectories resulting from socio-economic changes. In 2007, IPCC (Intergovernmental Panel on Climate Change) superseded the earlier SRES (Special Report on Emission Scenarios) (IPCC, 2000) by RCPs (Representative Concentration Pathways) which *Corresponding author, Email: jkbrar7@gmail.com Vol. 23, No. 2, pp. 235-246 (2023) Journal of Agricultural Physics ISSN 0973-032X http://www.agrophysics.in Introduction The earth’s average temperature has increased by 1 o C since the preindustrial time period due to a growing increase in the concentration of greenhouse gases (GHGs) in the atmosphere (Dibike and Coulibaly, 2005; Feng et al., 2014; Bekele et al., 2019). These changes in the climate system at the global level have the ability to change the local climate and these in turn speed up the hydrological process (Kim et al., 2011; Thomas et al., 2018; Research Article