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Showing 4 results for Principal Component Analysis

Hakimeh Behboudi, Mohammad Saligheh, Ali Bayat, Akram Zakeri, Fatemeh Jamali,
Volume 15, Issue 36 (6-2015)
Abstract

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.
Nader Parvin,
Volume 17, Issue 46 (12-2017)
Abstract

studying and identifying the middle levels change affecting the formation of a circular pattern creation is inevitable. In this study, the annual rainfall data for selected stations Zab River Basin during the period 2015-1986 were the standard time. After indexing and spatial-temporal threshold, 184 days without rainfall were selected in the wet period of three severe drought in the region. Level 500 HP height data located in the range of 0 to 80 degrees northern latitude and eastern longitude on dry days as a matrix S_Mode were used and these data using principal component analysis were processed using modern statistical methods. Based on the correlation matrix, the main focus of the 500 HP topography of the basin dry days were identified and analyzed. The results show that, in the happening time of dry days, twelve atmospheric middle levels of height change focus have been effective. In this regard, the following two centers having the highest anomalies (R≥0.7) are detected according to the high levels of the atmosphere: 1) the center of Eurasia-Africa, 2) the center of West Africa, respectively, 48% and 10% of the total area of the study. Such changes in middle atmospheric levels cause to strengthen and deepen the traffic axis and on the ridges. In the meantime, the change of first center has the highest impact on creation of stability and domination of dryness in days of Zab River Basin.

H Hossain Asakereh, M Mehdi Doustkamian, M Mohammad Darand,
Volume 21, Issue 60 (3-2021)
Abstract

The purpose of this study is to investigate and analyze turbulence, fluctuations and jumps of Iranian regions. For this purpose, environmental data has been gathered in two parts. In the first part of the data, the results of the interpolation of the daily precipitation observations of 1434 stations of climate and climate were used from the beginning of 1340 to 1383. After the formation of a database to identify the Iranian regions, a cluster analysis was used on average data and annual and monthly rainfall variation coefficients. Silhouette analysis has been used to validate the Iranian rainy areas. In order to investigate disturbances, mutations and fluctuations in Iran's rainy areas, this study was carried out. The results of cluster analysis indicate that Iran's peripheral areas are divided into six classes. In the meantime, the Caspian region (area 4) has the highest rainfall and the lowest coefficient of variation. The distribution of rainfall regime in each of the six areas shows that Iran's precipitation regime is more frequent in winter and spring and sometimes in autumn. Investigation and analysis of rainfall turmoil has shown that rainfall, except in the 4th district (Caspian region), in other areas of distribution of rainfall occurred along with disturbance. Although most disturbances occur in the zagros area, the highest sequence of disturbances is related to the fifth load region. The least sequence of disturbances occurred in the central and eastern part of the country. The results of mutation analysis and fluctuations indicate that rainfall disturbances, except in the early years of precipitation regions two and five in other regions of the other regions, have no significant mutation, while short-term fluctuations of 3-5 years on rainfall Each of the six domains has dominated.

Mrs Zahra Ebadi Nehari, Dr Mahdi Erfanian, Mrs Sima Kazempour Choursi,
Volume 23, Issue 68 (4-2023)
Abstract

Drought is a complex phenomenon caused by the breaking of water balance and it has always an impact on agricultural, ecological and socio-economic spheres. Although the drought indices deriving from remote sensing data have been used to monitor meteorological or agricultural drought, there are no indices that can suitably reflect the comprehensive information of drought from meteorological to agricultural aspects. In this study, the synthesized drought index (SDI) as a synthesized index from the vegetation condition index (VCI), temperature condition index (TCI) and precipitation condition index (PCI) were used for comprehensive drought monitoring in the Urmia Lake Basin (ULB) based on the Principal Component Analysis (PCA). For this purpose, MOD13A3, MOD11A2 and TRMM 3B43 data series were downloaded y for the period of 2001–2012. After initial processing, drought indicators were calculated using LST NDVI and TRMM data, and monthly drought severity maps were prepared. In order to validate SDI index, the Correlation relationship between SDI and SPI indices was obtained in the 3 month period during the growing season. As well as, SDI correlation relationships were investigated with wheat and barley crop yields. The results indicate that drought occurred in 2008 and 2001 in the ULB. The results of validation show that there is a correlation of 80% between the two SDI and SPI indicators. Also, the results of this study showed that the SDI index, as a comprehensive index of drought monitoring, reflects the effects of drought on agriculture.
 

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