Analysis of spatial autocorrelation patterns of heavy and super-heavy rainfall in Iran

作者：Rousta Iman; Doostkamian Mehdi^*; Haghighi Esmaeil; Ghafarian Malamiri Hamid Reza; Yarahmadi Parvane

来源：Advances in Atmospheric Sciences, 2017, 34(9): 1069-1081.

DOI：10.1007/s00376-017-6227-y

• Iran
• heavy rainfall
• super-heavy rainfall
• spatial autocorrelation
• G(i) index

Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran's heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord G (i) statistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran, have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall.

• 出版日期2017-9