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Prediction of Climate Change Induced Temperature & Precipitation: The Case of Iran

College of Agriculture, Razi University, Kermanshah 6715685438, Iran
College of Agriculture, Ilam University, Ilam 6939177111, Iran
Department of Engineering Management, Kermanshah University of Technology, Kermanshah 6715685438, Iran
Author to whom correspondence should be addressed.
Academic Editor: Hossein Azadi
Sustainability 2017, 9(1), 146;
Received: 17 November 2016 / Revised: 20 December 2016 / Accepted: 16 January 2017 / Published: 22 January 2017
(This article belongs to the Special Issue Land and Food Policy)
Concern about the effects of climatic change on numerous aspects of human life in general and on agricultural production in particular is growing. The utility of HadCM3 as a tool in climate change predictions in cross cultural studies is scarce. Therefore, this study sought to investigate and predict climate change induced temperature and precipitation in Iran. The calibration and validation using the HadCM3 was performed during 1961–2001, using daily temperatures and precipitation. The data on temperature and precipitation from 1961 to 1990 were used for calibration, and, for model validation, data from 1991 to 2001 were used. Moreover, in order to downscale general circulation models to station scales, SDSM version 4.2 was utilized. The least difference between observed data and simulation data during calibration and validation showed that the parameter was precisely modeled for most of the year. Simulation under the A2 scenario was performed for three time periods (2020, 2050, and 2080). According to our simulated model, precipitation showed a decreasing trend whereas temperature showed an increasing trend. The result of this research paper makes a significant contribution to climate smart agriculture in Iran. For example, rural development practitioners can devise effective policies and programs in order to reduce the vulnerability of local communities to climate change impacts. Moreover, the result of this study can be used as an optimal model for land allocation in agriculture. Moreover, a shortage of rainfall and decreased temperatures also have implications for agricultural land allocation. View Full-Text
Keywords: climate change; prediction; global circulation model; HadCM3; SDSM; Iran climate change; prediction; global circulation model; HadCM3; SDSM; Iran
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Saymohammadi, S.; Zarafshani, K.; Tavakoli, M.; Mahdizadeh, H.; Amiri, F. Prediction of Climate Change Induced Temperature & Precipitation: The Case of Iran. Sustainability 2017, 9, 146.

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