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.
Saeed Jahanbakhsh; Fatemeh Jafary shandy; Fereshteh Hosseinalipourgazy
Volume 16, Issue 42 , March 2013, , Pages 113-138
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, ...
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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'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.
