Detection and Attribution of Precipitation Extremes to Human Influence in Iran

Evaluating the susceptibility of regional climates to climate change provides a framework for realistically analyzing potential future climate changes. This paper investigates the impact of human activities on variations in extreme precipitation in Iran by evaluating data provided from ۲۸۶ rain-gauge stations during ۱۹۶۷-۲۰۱۰ and general circulation simulation results of the CanESM۲ model. This investigation was based on six forcing factors, including natural external factors (volcanic aerosols, solar radiation), anthropogenic and a combination of them, Green House Gases (GHGs), changes in land use, and anthropogenic aerosols. Seven precipitation indices, namely Rx۱day (annual maximum ۱-day precipitation), Rx۵day (annual maximum ۵-day precipitation), R۱۰mm (annual count of days with daily precipitation exceeding ۱۰ mm), R۲۰mm (annual count of days with daily precipitation exceeding ۲۰ mm), CDD (consecutive dry days), CWD (consecutive wet days), and PRCPTOT (annual total wet day precipitation), have been analyzed via the optimal fingerprint method. The results revealed that Rx۱day, Rx۵day and CWD increased, while R۱۰mm, R۲۰mm, CDD, and PRCPTOT decreased among which CDD and Rx۱day indices showed significant variations, with values of ۱۸.۴% and ۱۰.۹%, respectively. Furthermore, the obtained results implied that only the impact of anthropogenic forcing, with a value of ۱.۴, was detected and attributed to variations in CDD. Additionally, anthropogenic forcing caused an increase in the return period of a ۲۰-year event by ۱.۹ years for CDD. Although human-induced forcing factors presented marked trends in some cases, their effects were not generally detected and attributed to the change in the observations, apart from one exception.

Keywords:

climate change , Detection and attribution , Precipitation Extremes , Iran