Spatial dispersion of climatic factors in North and central basin of Iran using statistical models
Understanding weather zoning and knowing homogeneous climate regions are essential for land use and regional planning. The aim of this study was to compare three different geographical climate of Iran, the Caspian coastal, mountainous and arid interior of the provinces of Mazandaran, Semnan, Tehran,...
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Kharazmi University
2015-06-01
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| Series: | تحقیقات کاربردی علوم جغرافیایی |
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| Online Access: | http://jgs.khu.ac.ir/article-1-2292-en.pdf |
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| author | Hakimeh Behboudi Mohammad saligheh Ali bayat Akram zakeri Fatemeh jamali |
| author_facet | Hakimeh Behboudi Mohammad saligheh Ali bayat Akram zakeri Fatemeh jamali |
| author_sort | Hakimeh Behboudi |
| collection | DOAJ |
| description | Understanding weather zoning and knowing homogeneous climate regions are essential for land use and regional planning. The aim of this study was to compare three different geographical climate of Iran, the Caspian coastal, mountainous and arid interior of the provinces of Mazandaran, Semnan, Tehran, Qazvin, Qom, and Markazi. In order to do this study, climatic data of 56 synoptic and climatology stations and 19 climatic elements were used by using cluster analysis and factor analysis models. For this purpose, a matrix with dimensions of 56 x 19 and the R configuration and as a database was used for segmentation. By applying factor analysis based on principal components analysis with Varimax orthogonal rotation it was determined that in the climate of these three regions, four factors of humidity, temperature, dust and thunderstorms are affecting more than 85% of the total variance of the climate of this region. The hierarchical cluster analysis method and integration into the matrix of factor scores, four main and several sub-region areas were identified.The main areas are hot, dry desert area, low rainfall mountain slopes, the mountainous and cold and semi-rainy regions and high rainfall and finally the moderate high rainfall. The study of four areas and their local and regional conditions shows that the neighborhood with humidity source such as the Caspian Sea and rough configurations such Alborz Mountains play a decisive role in the formation of north sub-areas. |
| format | Article |
| id | doaj-art-c2d36b5eafc64b9a8a3efdbf48fd8706 |
| institution | Kabale University |
| issn | 2228-7736 2588-5138 |
| language | fas |
| publishDate | 2015-06-01 |
| publisher | Kharazmi University |
| record_format | Article |
| series | تحقیقات کاربردی علوم جغرافیایی |
| spelling | doaj-art-c2d36b5eafc64b9a8a3efdbf48fd87062025-01-31T17:22:23ZfasKharazmi Universityتحقیقات کاربردی علوم جغرافیایی2228-77362588-51382015-06-011536157179Spatial dispersion of climatic factors in North and central basin of Iran using statistical modelsHakimeh Behboudi0Mohammad saligheh1Ali bayat2Akram zakeri3Fatemeh jamali4 Understanding weather zoning and knowing homogeneous climate regions are essential for land use and regional planning. The aim of this study was to compare three different geographical climate of Iran, the Caspian coastal, mountainous and arid interior of the provinces of Mazandaran, Semnan, Tehran, Qazvin, Qom, and Markazi. In order to do this study, climatic data of 56 synoptic and climatology stations and 19 climatic elements were used by using cluster analysis and factor analysis models. For this purpose, a matrix with dimensions of 56 x 19 and the R configuration and as a database was used for segmentation. By applying factor analysis based on principal components analysis with Varimax orthogonal rotation it was determined that in the climate of these three regions, four factors of humidity, temperature, dust and thunderstorms are affecting more than 85% of the total variance of the climate of this region. The hierarchical cluster analysis method and integration into the matrix of factor scores, four main and several sub-region areas were identified.The main areas are hot, dry desert area, low rainfall mountain slopes, the mountainous and cold and semi-rainy regions and high rainfall and finally the moderate high rainfall. The study of four areas and their local and regional conditions shows that the neighborhood with humidity source such as the Caspian Sea and rough configurations such Alborz Mountains play a decisive role in the formation of north sub-areas.http://jgs.khu.ac.ir/article-1-2292-en.pdfzoningprincipal component analysisfactor analysiscluster analysisclimate |
| spellingShingle | Hakimeh Behboudi Mohammad saligheh Ali bayat Akram zakeri Fatemeh jamali Spatial dispersion of climatic factors in North and central basin of Iran using statistical models تحقیقات کاربردی علوم جغرافیایی zoning principal component analysis factor analysis cluster analysis climate |
| title | Spatial dispersion of climatic factors in North and central basin of Iran using statistical models |
| title_full | Spatial dispersion of climatic factors in North and central basin of Iran using statistical models |
| title_fullStr | Spatial dispersion of climatic factors in North and central basin of Iran using statistical models |
| title_full_unstemmed | Spatial dispersion of climatic factors in North and central basin of Iran using statistical models |
| title_short | Spatial dispersion of climatic factors in North and central basin of Iran using statistical models |
| title_sort | spatial dispersion of climatic factors in north and central basin of iran using statistical models |
| topic | zoning principal component analysis factor analysis cluster analysis climate |
| url | http://jgs.khu.ac.ir/article-1-2292-en.pdf |
| work_keys_str_mv | AT hakimehbehboudi spatialdispersionofclimaticfactorsinnorthandcentralbasinofiranusingstatisticalmodels AT mohammadsaligheh spatialdispersionofclimaticfactorsinnorthandcentralbasinofiranusingstatisticalmodels AT alibayat spatialdispersionofclimaticfactorsinnorthandcentralbasinofiranusingstatisticalmodels AT akramzakeri spatialdispersionofclimaticfactorsinnorthandcentralbasinofiranusingstatisticalmodels AT fatemehjamali spatialdispersionofclimaticfactorsinnorthandcentralbasinofiranusingstatisticalmodels |