| Popis: |
Information of probable change in a regional climate system can play an important role in the government’s policies. The present study investigates the climate variations over the Sistan-and-Baluchestan Province, the second biggest province of Iran with scarce direct observations, in basis of surface air temperature and precipitation. To this aim, three datasets of (I) in-situ data, (II) gridded data from Climatic Research Unit (CRU, in 1979-2020), and (III) outputs of historical runs (during 1979-2020) and simulations under the SSP5-8.5 and SSP3-7.0 scenarios (in 2021-2050) of twenty-seven Global Climate Models (GCMs) from the latest Coupled Model Intercomparison Project (CMIP6) were utilized. The climatic analysis was conducted in three steps of (I) evaluation of models' performance comparing with CRU data in 1979-2020, (II) rank the models based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in Multi-Criteria Decision Making (MCDM) technique including eight metrics and (III) analysis of performance of the high-ranked models for 2021-2050. Results showed that CMIP6-GCMs generated lower satisfactory and consistency in simulating precipitation than temperature. The three models of CESM2-WACCM-FV2, MPI-ESM1-2-LR and IITM-ESM (MPI-ESM1-2-LR and UKESM1-0-LL and ACCESS-CM2) outperformed the others in simulating temperature (precipitation), while the MIROC6 (MIROC-ES2L) model performed the weakest. The MPI-ESM1-2-LR, UKESM1-0-LL and ACCESS-CM2 models achieved the highest rank for the both climate variables. Regarding the high-ranked models, analysis of the CMIP6-GCMs for 2021-2050 showed that the increase of 2.5-3.4 (2.2-3.1) K for the maximum temperature in SSP5-8.5 (SSP3-7.0) scenario is probable. Both scenarios showed an increasing (decreasing) trend for temperature (precipitation) in the future. Conclusively, the considered area will experience a remarkable increase in temperature and significant decrease in precipitation amount. It should be noted that the results from the global models will be exacerbated by any mistake in policy making. |
