مؤسسه ژئوفیزیک دانشگاه تهران فیزیک زمین و فضا 2538-371X 46 4 2021 01 20 The Evaluations of NEX-GDDP and Marksim Downscaled Data Sets Over Lali Region, Southwest Iran The Evaluations of NEX-GDDP and Marksim Downscaled Data Sets Over Lali Region, Southwest Iran 213 230 76438 10.22059/jesphys.2020.295152.1007186 FA Nejat Zeydalinejad Ph.D. Student, Department of Mineral Geology and Hydrogeology, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran Hamid Reza Nassery Professor, Department of Mineral Geology and Hydrogeology, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran Ali Reza Shakiba Associate Professor, Department of Remote Sensing and GIS, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran 0000-0003-1977-3372 Farshad Alijani Assistant Professor, Department of Mineral Geology and Hydrogeology, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran 0000-0002-0124-1215 Journal Article 2020 01 08 Downscaling of climatic variables is a difficult problem in the climate change impact studies. However, some climatic data sets exist that have been universally downscaled. These data sets introduce climatic data even in regions with scarce observations. In this study, NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) and Markov simulation (Marksim) downscaled data sets were evaluated over Lali region, southwest Iran by comparing the monthly RMSE, average and variance differences between the observation data and General Circulation Models' (GCMs') outputs during the time period 2010-2016. The NEX-GDDP data set contains 21 GCMs under two Representative Concentration Pathways (RCPs), i.e. RCP4.5 and RCP8.5, from 1951 to 2099, and the Marksim data set includes 17 GCMs under all RCPs from 2010 to 2095. Results acknowledged the ability of both data sets in projecting the climatic variables in the study area. Finally, NorESM1-M and GFDL-CM3 depicted the best operation for precipitation and temperature, respectively. Downscaling of climatic variables is a difficult problem in the climate change impact studies. However, some climatic data sets exist that have been universally downscaled. These data sets introduce climatic data even in regions with scarce observations. In this study, NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) and Markov simulation (Marksim) downscaled data sets were evaluated over Lali region, southwest Iran by comparing the monthly RMSE, average and variance differences between the observation data and General Circulation Models' (GCMs') outputs during the time period 2010-2016. The NEX-GDDP data set contains 21 GCMs under two Representative Concentration Pathways (RCPs), i.e. RCP4.5 and RCP8.5, from 1951 to 2099, and the Marksim data set includes 17 GCMs under all RCPs from 2010 to 2095. Results acknowledged the ability of both data sets in projecting the climatic variables in the study area. Finally, NorESM1-M and GFDL-CM3 depicted the best operation for precipitation and temperature, respectively. https://jesphys.ut.ac.ir/article_76438_74872eee5d694451ad4be92de4a64ddc.pdf