Geospatial analysis of rainfall consistency and transition patterns in Iran

Climate phenomena often manifest as stochastic processes that exhibit disparate outcomes under similar conditions. The objective of this research is to offer a detailed and comprehensive analysis of the transition patterns of various precipitation states in Iran. The primary aim is to investigate sequential changes and their impacts on the stability and behavior of precipitation through the utilization of probabilistic models and precipitation state transition analysis (PSTA) to elucidate more intricate climatic patterns in the region. This study employed daily precipitation data from 411 synoptic stations across Iran spanning from 1970 to 2021. To analyze precipitation changes, kriging interpolation methods were utilized to generate daily precipitation maps and precipitation state transition analysis (PSTA) for scrutinizing precipitation transition patterns. The findings revealed that the central, eastern, and southeastern parts of Iran exhibit the highest frequency of transitions from dry days to dry days, with probabilities exceeding 0.96 in some areas. Conversely, the Caspian region, particularly its western portion, demonstrates the highest frequency of transitions involving rainy days, where the probability of transitioning from a dry day to a rainy day exceeds 0.45. Moreover, the probabilistic maps indicated that the Caspian region has the lowest probability of transitioning from dry days to dry days, often below 0.50, while possessing the highest probability of transitioning to rainy days. These geographical disparities are linked to climatic and geographical factors such as proximity to highlands and access to moisture sources like the Caspian Sea. By elucidating these geographical and climatic distinctions, this study contributes to the enhancement of predictions concerning climatic changes and the stability of precipitation behaviors in various regions of Iran.