Hossein Asakareh; Ali Bayat
Volume 17, Issue 45 , November 2013, , Pages 121-142
Abstract
Principal Component Analysis (PCA) is an optimum mathematical method to decrease variables into some limited components in order to justify the highest variance of primary variables. In this study some statistical characteristics of annual precipitation of Zanjan city including sum of annual precipitation, ...
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Principal Component Analysis (PCA) is an optimum mathematical method to decrease variables into some limited components in order to justify the highest variance of primary variables. In this study some statistical characteristics of annual precipitation of Zanjan city including sum of annual precipitation, number of rainy days, extreme daily precipitation in a year, the ratio of extreme precipitation to the sum of annual precipitation and some characteristics such as Standard Deviation (SD), Skewness (Sk), Kurtosis (Ku), Absolute Mean Deviation (AMD) and Mean Absolute Interannual Variability (MAIV) were was calculated from monthly precipitation for each year, and were introduced principal component analysis technique. The results show that 95% percent of annual precipitation variations can be explained through 4 components. The first component which indicates the highest data variance (42.6%), represents annual precipitation and absolute variability indices including SD, AMD and MAIV. The second component represents the shape of frequency distribution indices (Sk, Ku), the third component represents extreme precipitations and finally the fourth component represents the number of rainy days. The analysis of the trend of components scores show that first and fourth components scores have a significant decreasing and increasing trend, respectively. Round a lines show a precipitation decrease during the period under study from one hand and having uniform temporal distribution on the other hand.
Farnaz Pourasghar; Saeed Jahanbakhsh; Behrooz Sari saraf; Hooshang Ghaemi; Masomeh Tadayoni
Volume 17, Issue 44 , September 2013, , Pages 27-46
Abstract
This is a study of change in annual precipitation amounts and variability in southern part of Iran during 1974-2005. Southern part of Iran has been regionalized based on six factors in 183 stations using Principal Component Analysis (PCA) and Cluster Analysis (CA). The stations were grouped into four ...
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This is a study of change in annual precipitation amounts and variability in southern part of Iran during 1974-2005. Southern part of Iran has been regionalized based on six factors in 183 stations using Principal Component Analysis (PCA) and Cluster Analysis (CA). The stations were grouped into four individual clusters. Topography and latitude play an important role in determining boundaries between identified subdivisions and existence of spatial differences between them as well. Spatial variability and relationship between the precipitation series at 183 of stations were investigated by principal component analysis. A PCA of annual precipitation reveals five components that account for 68% of the total variance. The annual precipitation PCs are controlled by atmospheric circulation. Analysis of the results revealed that annual precipitation in south part of Iran is mainly related to Sudan and Mediterranean wave.
Rasool Gorbani; Karim Hosseinzadeh Delir; pari Shorkri Firoozjah
Volume 16, Issue 39 , May 2012, , Pages 89-108
Abstract
Nowadays rapid development of urbanization, population growth, industrialization, unorganized transport system and urban traffic and green space shortage have caused increase of air pollution concentration in cities, especially in large cities. Therefore, attention into air pollution and factors and ...
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Nowadays rapid development of urbanization, population growth, industrialization, unorganized transport system and urban traffic and green space shortage have caused increase of air pollution concentration in cities, especially in large cities. Therefore, attention into air pollution and factors and causes of increased pollutant concentrations are very important. Hence the purpose of this paper is to identity the effective factors on air pollution at Namaz Square station in Tabriz city.
Therefore, through of component analysis method, main components were determined in each season of year and by the application of multivariate regression model, main factors were defined. Results show that climatic factors (such as temperature, wind speed and direction) human factors (such as crowded population, green space shortage, high traffic, unsuitable roads) have the highest influence in the air pollution. Special attention therefore, to human factors can cause to the decrease of air pollution in urban central area
