Study of precipitation variation due to climate change (Case study: Golestan dam basin)

Lower atmosphere. The global concentration of these gases is increasing, mainly due to human activities, such as the combustion of fossil fuels (which release carbon dioxide) and deforestation (because forests remove carbon from the atmosphere). Projections of future climate change are derived from global climate model or general circulation model (GCM) experiments. Climate model projections show an increase in the global mean air temperature by 1 to 3.5˚C by 2100. One of the most important problems in the management and planning of water resources is forecasting of precipitation. This research explored the issues of downscaling the outputs of GCMs using an artificial neural network (ANN) approach. This data used in daily precipitation forecasting. This study focuses on the impact of climate changes on precipitation in the karimisaha (humid climate) and Robat gharebil station (semi-arid climate) in Golestan dam basin in Golestan. GCM model in this research is CGCM3. These data are derived from two scenarios, A2 and B1 for two periods: 2021-2050 and 2071-2100. Precipitation data for 1979 to 2000 period selected for base period. Result showed that Increase monthly average precipitation in winter and autumn to 43 mm in karim ishan station and 32mm in robat gharbil station and decrease in spring and summer to 23 mm in Karim ishan station and 11 mm in robat gharbl station.