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Darand M, Ghaffari M. (2026). Dynamical and Synoptic Characteristics of Extreme Precipitation Events in Western Iran (Case Study: Kurdistan Province). jgs. 25,
URL: http://jgs.khu.ac.ir/article-1-4522-en.html
1- Professor at Department of Climatology, University of Kurdistan, Sanandaj, Iran, Department of Climatology, University of Kurdistan, Sanandaj, Iran , mdarand@uok.ac.ir
2- Department of Climatology, University of Kurdistan, Sanandaj, Iran, Department of Climatology, University of Kurdistan, Sanandaj, Iran
Abstract:   (235 Views)
Extreme precipitation events pose a significant and growing threat to society, often leading to floods, landslides, and widespread socio-economic damage. Daily precipitation data collected from 9 rain gauges during 1/1/1991 to 31/12/2023. To identify days associated with heavy precipitation, the 95th-percentile threshold was employed. Days on which the recorded precipitation exceeded the long-term mean of the 95th percentile at more than half stations were classified as heavy-precipitation days for Kurdistan Province. Based on this threshold and criterion, 210 days were selected. Two data arrays with an S-mode structure were constructed for sea-level pressure and 500-hPa geopotential height. Using Principle Component Analysis (PCA) analysis, components explaining more than one percent of the variance were retained as significant modes. For sea-level pressure, nine components were identified, and for the 500-hPa geopotential height, eight components were extracted. Together, these components explained over 92% of the variance in sea-level pressure and more than 95% of the variance in the 500-hPa geopotential height over the study domain. Cluster analysis (CA) performed on the score matrix of the 17 components was then used to identify the prevailing circulation patterns.
 
     
Type of Study: Research | Subject: climatology

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Creative Commons License
This work is licensed under a Creative Commons — Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)