Atmospheric circulation is important to determine the surface climate and environment, and affect regional climate and surface features. In this study, to quantify its effect, the classification system, developed by Lamb is applied to obtain circulation information for Ardabil, North West Province in Iran, on a daily basis, and is a method to classify synoptic weather for study area. For that purpose, daily mean sea-level pressure (MSLP) for extreme precipitation days from 1971 to 2007 is used to derive six circulation indices and to provide a circulation catalogue with 27 circulation types. The frequency of circulation types over different periods is computed and described. Five circulation types are most recognised in this study: E, SE, A, C and CSE. The catalogue and the associated indices provide a tool to interpret the regional climate and precipitation, and deal with the linkage between the mean extreme regional precipitations in north western of Iran and the large-scale circulation. Five circulation types E, A, SE, C and CSE are associated with high precipitation and rainy seasons (spring and September) but the most precipitation rate is resulted of cyclone family. Low pressure of north latitudes and central area of Iran with low pressure of gang from Pakistan and India.  SE is almost dominant circulation type over the years. The cold season started from august to march is characterized by frequent directional flows, especially E, SE, A, C and CSE whereas in  warm period (Apr–Aug) SE, NE, AE have  smaller role, especially in July, August and September more frequent flows dominated by SE and E. 

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.