UNCERTAINTIES IN CLIMATE CHANGE SCENARIOS FOR DETERMINING TEMPERATURE AND RAINFALL PATTERNS IN REGIONS WITH MIXED CLIMATE CONDITIONS

Aim of the study This study aims to quantify uncertainty in assessing climate change impact on crop production by using all available climate models (GCMs) under both harsh and mild emission scenarios from 2020 to 2095, which has not yet been done in the studied region to date. Material and methods A comparative study was carried out for Ludhiana district, Punjab, India, in which Global Climate Model (GCM) outputs for daily maximum (T-max) and minimum temperature (T-min) and rainfall under A1B scenario concerning Mid Century (MC) (2020-2050) and End Century (EC) (2070-2095) were extracted from ECHam5-GCM and PRECIS model. DSSAT v.4.6.1 model and Papadakis method were used to study the climate change behavior under these two time-slices. In addition, climate data from RCP scenarios for the future were extracted from five randomly selected GCMs under scenarios RCP 4.5 and RCP 8.5 using the MarkSim DSSAT weather generator. These models were analyzed statistically for RMSE and NRMSE. One of the models, HAD GEM2-ES, was selected as having the least NRSME for the impact assessment studies. Results and conclusions The results showed that the annual minimum temperature would increase by 2.4 degrees C and 2.45 degrees C for EC using ECHAM5 and PRECIS models. In contrast, under RCPs 4.5 and 8.5 scenarios, the mean annual temperature would increase by 1.56 degrees C in MC and 3.11 degrees C in EC compared to that of the baseline period, and 2.75 degrees C in MC and 5.46 degrees C in EC compared to that of the baseline period, respectively. The corresponding likely decrease in annual RF under RCP 4.5 is 98 mm and 90 mm during MC and EC, respectively. The corresponding increase in annual RF under RCP 8.5 is 153 mm and 251 mm, respectively. Hence, our findings show that the uncertainty is prevalent even in relatively small regions, while selecting different climate change scenarios.