3647

3446

كارشناسي ارشد

آب

اصفهان :دانشگاه صنعتي اصفهان ، دانشكده عمران

1386

هشت ،138،[II]ص. :مصور ، جدول ، نمودار

ص.ع.به فارسي و انگليسي

مسعود رضا حسامي كرماني

13/5/86

كيوان اصغري، بهروز احمدي

مهندسي عمران

ID3446

به فارسي و انگليسي :قابل رويت به صورت نسخه ديجيتال

AbstractScientists believe that rising concentration of greenhouse gases in the atmosphere willcause changes to our climate Global Climate Models GCMs have been developed toestimate this change in the future However the coarse resolution of GCMs makes itimpossible to use them in the local impact studies Spatial resolutions of Most GCMs aregenerally greater than 2 0 for both latitude and longitude Therefore there is a need todownscale the prediction of GCMs to local and regional scales In this study a regressionbased statistical downscaling method for estimating the daily precipitation andtemperature maximum and minimum over north of Iran is evaluated Statisticaldownscaling was performed using ASD Automated regression based StatisticalDownscaling model and the predictors were selected with backward stepwise regression We have used the outputs from the second generation Canadian Coupled Global ClimateModel CGCM2 to test this approach and compare results with observed temperatureand precipitation from five meteorological stations in north of Iran The NCEP NationalCenter of Environmental Prediction reanalysis data over the 1961 1975 period was usedfor calibration of the regression model Also climate change trend is estimated with theSen s slope The results indicate the difficulty of downscaling precipitation and high performance ofthe model to predict temperature Observed mean temperature has increased over 1961 2004 and the rate of increasing is much higher in minimum temperature than inmaximum temperature

مسعود رضا حسامي كرماني

كيوان اصغري، بهروز احمدي