期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2020
卷号：491
期号：1
DOI：10.1088/1755-1315/491/1/012002
语种：English
出版社：IOP Publishing
摘要：In this paper, artificial neural network (ANN) was used for downscaling the outputs of general circulation models (GCMs) to evaluate changes in precipitation and mean temperature for a future period in Urmia at the north-west of Iran. MIROC-ESM-CHEM from IPCC AR5 was selected as an acceptable model based on correlation coefficient (CC) values, which is calculated between precipitation of GCM models and precipitation data prepared by Urmia Meteorological Organization for 1951-2000. As a first step, the most important parameters of the MIROC-ESM-CHEM were selected before the downscaling process by ANN in the base period (1951-2000). Afterward, the future projections of precipitation and mean temperature during 2020-2060 were applied using ANN-based simulation according to the CC method. By comparing the results, the MIROC-ESM-CHEM showed a 2.01% increase under RCP4.5 and a 0.16% decrease under RCP8.5 in annual precipitation. Also, the temperature projection outputs showed the annual mean temperature would increase in the future period in this area, and it is likely to get warmer.
