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Analyzing atmospheric circulation patterns characterize prevailing weather in a region. The method of principal component analysis and clustering was used to classify daily atmospheric circulation patterns. The average daily geopotential height of 500 hPa with 0.5° resolution of the ECMWF (1990–2019) were extracted from the Middle East. The S array was used to identify air types, and k-means clustering was used to classify daily air types. All days were divided into eighteen groups. Then, the surface maps and moisture flux divergence at the 850-hPa level of each pattern were studied. The, the connection between circulation patterns and precipitation occurrence is investigated by the PI index. The existence of a variety of precipitation and temperature regimes and consequent dry/wet periods is related to the type and frequency of the circulation patterns. In patterns with south to southwesterly currents, the low-pressure surface center extends from the south of the Red Sea to southern Turkey and is associated with the mid-level trough, where the moisture fluxes converge in the south of the Red Sea, southwest/south of Iran, and east of the Mediterranean Sea. Therefore, according to the intensity of the patterns, the most precipitation falls in the country’s western half, and the Zagros Mountain’s wind side. With the eastward movement of the Cyclonic patterns, the rainfall area extends to the eastern half of the country. With the pattern that the thermal low surface pressure extends to 35 °N latitude and is associated with the mid-level subtropical high, almost no rain occurs in the country.

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Analyzing and classifying atmospheric circulation patterns (CPs) is useful for studying climate variability. These classifications can effectively identify the links between large-scale and regional-local scale processes. This work uses the historical (1975–2014) and projected (2015–2054) simulations of the MPI-ESM1-2-HR model to reproduce the CPs over the Middle East and Iran. Eighteen CPs were identified based on the geopotential height (GPH) of 500 hPa data from Coupled Model Intercomparison Project Phase 6 (CMIP6) in SSP1-2.6, SSP3-7.0, and SSP5-8.5. The method of principal component analysis (PCA) and k-means clustering was used. Then, the possible variability of each pattern in the surface and mid-level of the atmosphere and their expected changes in the frequency of CPs in global warming scenarios were investigated. This research showed that CPs 3, 6, and 11 happen during warm months of the year. The surface thermal low pressure is associated with the subtropical high in the atmosphere mid-level. According to the intensity of the low and the northward development, or the orbital expansion of the subtropical high, this pattern has an increasing (CPs 3 and 6) or decreasing (CP11) trend in the future period. CPs 1 and 12 occur during cold months. In CP1, dynamic high pressure prevails over Iran. However, in CP12, Iran is affected by high pressure from southeastern Europe. They will decrease in future projections. CPs 7 and 16, which often occur in the transition season (spring), show an increase in the projected patterns. CP 18 occurs throughout the year, but its highest frequency is in autumn, and the frequency of occurrence decreases. An increase in 500 hPa geopotential height over the Arabian Sea in all 18 classes and all three SSPs is predicted for future periods. Analysis of the obtained weather types indicates the identification of all effective atmospheric circulation patterns in the study area so that the behavior and frequency of each pattern explain the prevailing atmospheric phenomena in this region.