Impacts of climate change on extreme precipitation events in arid (Bandar Abbas) and semi-arid (Shahrekord) stations in Iran

The aim of this paper is to project extreme precipitation events in an arid and a semiarid station. In order to project climate change based on general circulation models (GCMs), we have applied LARS-WG[1] downscaling tool. This stochastic weather generator down-scaled the climate of two synoptic stations using HADCM3 model and A2 emission scenario for 2040. We extracted extreme precipitation events, as daily 90th and 10th percentile for rainy days (considered if daily precipitation was greater than 1 mm), for based and projected data. The research outcomes showed an increase both in 90th percentile by 13 mm and in 10th percentile by 0.2 mm in arid station, Bandar Abbas. In the semiarid station, Shahrekord, the 90th percentile precipitation increased by 6.1 mm and the 10th percentile precipitation decreased by 3.4 mm. In total, for both stations, 90th percentile precipitations showed a more stable trend than the 10th percentile. 1. Long Ashton Research Station-Weather Generator