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<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>University of Tabriz</PublisherName>
				<JournalTitle>Journal of Geography and Planning</JournalTitle>
				<Issn>2008-8078</Issn>
				<Volume>16</Volume>
				<Issue>42</Issue>
				<PubDate PubStatus="epublish">
					<Year>2013</Year>
					<Month>02</Month>
					<Day>03</Day>
				</PubDate>
			</Journal>
<ArticleTitle>The Relationship between Circulation Patterns and Super Heavy Rain over Azerbaijan Region</ArticleTitle>
<VernacularTitle>The Relationship between Circulation Patterns and Super Heavy Rain over Azerbaijan Region</VernacularTitle>
			<FirstPage>113</FirstPage>
			<LastPage>138</LastPage>
			<ELocationID EIdType="pii">32</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Saeed</FirstName>
					<LastName>Jahanbakhsh</LastName>
<Affiliation>University of Tabriz</Affiliation>

</Author>
<Author>
					<FirstName>Fatemeh</FirstName>
					<LastName>Jafary Shandy</LastName>
<Affiliation>Climatology, Payam Noor University Shabestar</Affiliation>

</Author>
<Author>
					<FirstName>Fereshteh</FirstName>
					<LastName>Hosseinalipourgazy</LastName>
<Affiliation>Climatology, Payam Noor University</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2010</Year>
					<Month>09</Month>
					<Day>17</Day>
				</PubDate>
			</History>
		<Abstract>In order to identify synoptic super heavy rain patterns (precipitation exceeding 50 millimeters a day) in Azerbaijan region, the daily precipitation data of 23 rain gauges were studied by six-hour precipitation synopsis from 1963 to 2005. The data were analyzed through hierarchical clustering analysis, specifically Ward cluster analysis in GRADS, MATLAB, and SURFFER softwares to identify the relationship between the higher-atmosphere circulation patterns and super heavy rain events in the studied region. Results demonstrated three different active circulation patterns in the region, for each pattern a single representative day was introduced for super heavy rain events&#039;s analysis. The spatial alignment of the precipitation pattern points out a relationship between the temporal distributions of super heavy rain events in region with the latitude. Significant relationships are existent between EastBlack Sea-NorthMediteranehSea, and Black Sea trough pattern and super heavy rain events in the studied region. The results play an important role in the prediction of heavy rain events in the region.</Abstract>
			<OtherAbstract Language="FA">In order to identify synoptic super heavy rain patterns (precipitation exceeding 50 millimeters a day) in Azerbaijan region, the daily precipitation data of 23 rain gauges were studied by six-hour precipitation synopsis from 1963 to 2005. The data were analyzed through hierarchical clustering analysis, specifically Ward cluster analysis in GRADS, MATLAB, and SURFFER softwares to identify the relationship between the higher-atmosphere circulation patterns and super heavy rain events in the studied region. Results demonstrated three different active circulation patterns in the region, for each pattern a single representative day was introduced for super heavy rain events&#039;s analysis. The spatial alignment of the precipitation pattern points out a relationship between the temporal distributions of super heavy rain events in region with the latitude. Significant relationships are existent between EastBlack Sea-NorthMediteranehSea, and Black Sea trough pattern and super heavy rain events in the studied region. The results play an important role in the prediction of heavy rain events in the region.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Synoptic</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Super heavy rain</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Circulation Pattern</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Cluster analysis</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Azerbaijan</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://geoplanning.tabrizu.ac.ir/article_32_794edf11a18da048dbb946d3b68ec6db.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
