عنوان مقاله [English]
1-Introduction Trend detection is an active area of interest for both hydrology and climatology in order to investigate climate changes scenario and improve climate impact research(Saidi et al., 2013). The assumption of stationary seems to be invalid as a result of anthropogenic influence and the natural variability of the climate system (Karpouzos et al., 2010). One of the most significant consequences of global warming due to increase in greenhouse gases would be an increase in magnitude and frequency of extreme precipitation events (Joshi and Rajeevan, 2006). In the global warming scenario, climate models generally predict an increase in large precipitation events (Houghtonet al 2001). Climate simulations indicate that a warmer climate could result in an increase in the proportion of precipitation occurring in extreme events (Karl et al., 1995). It seems to be generally accepted that the expected climatic changes are not necessarily associated with a higher intensity of extreme values, but rather with a higher frequency of the occurrence of extreme values. There are many indices for examining the extreme rainfall events (Peterson et al. 2001). The joint working group on climate change detection of World Meteorological Organization (WMO-CCL) and the research program on Climate Variability and Prediction CLIVAR (Peterson et al., 2001) recommended 15 indices on extreme rainfall. These indices are similar to indices that recommended by Expert Team of Climate Change Detection and Indices (ETCCDI). In this study the percentile thresholds indices including 90, 95 and 99 have been applied. The aim of this study is changes of extreme precipitation frequency in Iran. 2- Data and Methods In order to doing this research, interpolated daily precipitation from Asfazari data base during 1/1/1340 to 11/10/1383(15992 days) has been used. One data base with dimension 15992×7187 created. For each calendar days of year calculated 90, 95 and 99 percentiles over pixels. Three new matrixes have been created with dimension 366×7187. If daily precipitation amount over each pixels during study period was equal or over the three mentioned percentile considered as extreme precipitation. The frequency of extreme days on the each pixel separately counted for every months of year. The significance of trend evaluated by non parametric Mann Kendal test at 95% confidence level. 3- Results and Discussion The result of this study showed that trend of extreme precipitation occurrence over Iran is significant. In general the extension of negative trend of extreme precipitation occurrence is more than positive trend in semi warm seasons of year. The contrast observed for the cold months (December, January and March). In July, the trend of extreme precipitation occurrence frequency over the north parts of Iran is positive. The extensive negative trend observed during September while for the positive trend observed in December and January. General we can say that trend over elevation especially on Zagros mountain range is positive while over low lands trend is negative in yearly scale. Frequency of extreme precipitation is increasing over southwestern and western parts of country in November and March. It seems to that in spatial view increase and decrease of extreme precipitation occurrence is well agreement with increase and decrease of precipitation over Iran. This is clear in the Southwest part of Iran especially. The distribution of precipitation over Iran is controlled by the interaction of the tropical air mass (Sudan Low), the Monsoon, the Persian Gulf, the Mediterranean low pressures, the Siberian high pressure and the western passenger high pressures. It seems that changes in intensity of mentioned synoptic systems during recent decades are the reason for the variability in extreme precipitation occurrence over Iran.