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<ArticleSet>
<Article>
<Journal>
				<PublisherName>دانشگاه کاشان</PublisherName>
				<JournalTitle>مهندسی اکوسیستم بیابان</JournalTitle>
				<Issn>2538-6336</Issn>
				<Volume>7</Volume>
				<Issue>شماره 1 انگلیسی</Issue>
				<PubDate PubStatus="epublish">
					<Year>2018</Year>
					<Month>08</Month>
					<Day>23</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Assessment and Application of Two General Circulation Models (HadCM3 and MPEH5) for Investigating Climate Change (Case Study: Khorramabad Synoptic Station, Iran)</ArticleTitle>
<VernacularTitle>Assessment and Application of Two General Circulation Models (HadCM3 and MPEH5) for Investigating Climate Change (Case Study: Khorramabad Synoptic Station, Iran)</VernacularTitle>
			<FirstPage>21</FirstPage>
			<LastPage>36</LastPage>
			<ELocationID EIdType="pii">114050</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>آسیه</FirstName>
					<LastName>بیاتی</LastName>
<Affiliation>Department of Natural Resources, Agriculture Faculty, Ilam University, Ilam, Iran</Affiliation>

</Author>
<Author>
					<FirstName>محسن</FirstName>
					<LastName>توکلی</LastName>
<Affiliation>Department of Natural resources, Agriculture faculty, Ilam university, Ilam, Iran</Affiliation>

</Author>
<Author>
					<FirstName>ایمان</FirstName>
					<LastName>باباییان</LastName>
<Affiliation>پژوهشکده اقلیم شناسی، سازمان هواشناسی کشور، مشهد.</Affiliation>

</Author>
<Author>
					<FirstName>فاطمه</FirstName>
					<LastName>درگاهیان</LastName>
<Affiliation>سازمان تحقیقات، آموزش و ترویج کشاورزی، موسسه تحقیقات جنگلها و مراتع کشور</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2023</Year>
					<Month>12</Month>
					<Day>01</Day>
				</PubDate>
			</History>
		<Abstract>A popular method for climate change prediction are General Circulation Models which are at coarse spatial resolution and must be downscaled. In this study, observed data of temperature, precipitation and potential evapotranspiration over a base period under two emission scenarios in three time intervals were used to implement SDSM as a downscaling tool for HadCM3 model output. From another standpoint, MPEH5 model predicts data under three emission scenarios for three future periods. Results indicated that all parameters would increase in comparison to the base period. Predictions for all periods under all emission scenarios indicated an increasing trend for all parameters, although it is predicted almost as constant precipitation trend for the future. According to predictions by both models, the greatest increase has been estimated for 2080s under A2 scenario. In SDSM model, the greatest increases in mean monthly temperature would be respectively 6.9, 4.5, 6.2 °C for July and for potential evapotranspiration would be in June by 1.08 mm per day, which are predicted in the 2080s under A2 scenario. For precipitation, the greatest reduction under the same conditions, would be in May by 0.9 mm per day. In LARS-WG model, the greatest increase in mean monthly temperature in the studied station was predicted respectively by 5.5, 5.5, 5.6 °C for August. The greatest reduction in precipitation, would be in February (by 0.88 mm per day). The future uncertainty results of predicted parameters in both models and various scenarios show that uncertainty of the predictions increase towards the end of the century.</Abstract>
			<OtherAbstract Language="FA">A popular method for climate change prediction are General Circulation Models which are at coarse spatial resolution and must be downscaled. In this study, observed data of temperature, precipitation and potential evapotranspiration over a base period under two emission scenarios in three time intervals were used to implement SDSM as a downscaling tool for HadCM3 model output. From another standpoint, MPEH5 model predicts data under three emission scenarios for three future periods. Results indicated that all parameters would increase in comparison to the base period. Predictions for all periods under all emission scenarios indicated an increasing trend for all parameters, although it is predicted almost as constant precipitation trend for the future. According to predictions by both models, the greatest increase has been estimated for 2080s under A2 scenario. In SDSM model, the greatest increases in mean monthly temperature would be respectively 6.9, 4.5, 6.2 °C for July and for potential evapotranspiration would be in June by 1.08 mm per day, which are predicted in the 2080s under A2 scenario. For precipitation, the greatest reduction under the same conditions, would be in May by 0.9 mm per day. In LARS-WG model, the greatest increase in mean monthly temperature in the studied station was predicted respectively by 5.5, 5.5, 5.6 °C for August. The greatest reduction in precipitation, would be in February (by 0.88 mm per day). The future uncertainty results of predicted parameters in both models and various scenarios show that uncertainty of the predictions increase towards the end of the century.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Climate change</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">HadCM3</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">SDSM</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">MPEH5</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">LARS-WG</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Uncertainty</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Khorramabad</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://deej.kashanu.ac.ir/article_114050_ab8915ecb6f26f7078e7cbc8527ba1b0.pdf</ArchiveCopySource>
</Article>
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