Prediction of Climatic Variables using Statistical Downscaling Model (SDSM) in Future under Scenario A2

Document Type : Original Article

Authors

1 Professor, Faculty of Natural Resources, University of Tehran, Karaj, Iran

2 Former student, Faculty of Natural Resources, University of Tehran, Karaj, Iran

3 Associate Professor, Faculty of Natural Resources, University of Tehran, Karaj, Iran

4 Associate Professor, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran

5 Assistant Professor, Soil Conservation and watershed Management Research Institute, Tehran, Iran

Abstract

In recent decades, the increase of temperature has caused the disturbance of climatic balance of the earth and extensive climate changes which is called climate change. The aim of this study is to predict the climate changes using statistical downscaling model (SDSM) based on A2 scenario over future periods. Daily precipitation, minimum and maximum temperature data of Kermanshah synoptic station, for two periods 2015-2040 and 2040-2065, were predicted and compared with the baseline period. The first 27 years of data (1988-1961) were used for calibration and the second 12 years (1989-2001) were used for validation of the model as well. The results showed that based on the A2 scenario, in the periods of 2015- 2040 and 2040- 2065, the average annual precipitation decreases, the average minimum and maximum temperature increases compared to the baseline period in the Kermanshah synoptic station. Since the precipitation reduction and temperature increase are one of the main factors of desertification, so it is necessary for decision makers and planners in Kermanshah province to adopt necessary solutions for mitigation and adaptation with new climatic conditions.

Keywords

Desert Management
Volume 4, Issue 7 - Serial Number 7
7 Articles
March 2016
Pages 12-25

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History

  • Receive Date: 02 February 2016
  • Revise Date: 17 April 2015
  • Accept Date: 13 May 2015

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