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.