Rainfalls with short persistency are the tangible characteristics of arid and semiarid regions such as Iran. Iran is an arid and semiarid region with dramatic tempo-spatial changes of rainfall. In this regard, the short persistency of rainfall is approximately observed from 1 to 7 days in whole parts, while the greater ones are only separated in eastern parts of Iran. According to the results, the rainfall persistency is ranged from 1 to 45 days, but the maximum amount and rainy days are generated by rainfalls with short persistency. So, the rainfall events with long persistency are considered as an extreme event with extreme variability. One-day precipitations generate the maximum rainy days and rainfall amounts, especially in eastern parts of Iran. Decrease in the one-day precipitations contribution to eastern parts may indicate to decrease in regional precipitation. However, decrease in contribution in western parts may indicate to increased amounts of rainfall at other persistency rates. Our results revealed that the contribution of the one-day precipitation to general rainfall has reductive trends in almost 17.5 % of the whole Iran. The most integrated and significant reductive trend of one-day precipitation contribution to rainfall spreads northeastern and eastern parts of Iran. However, in the western parts of Iran, decreasing one-day precipitation contribution to rainy days affects to increase in the diurnal rainfall. The mentioned variability can be considered as the climate change signals in respect of one-day precipitation.
Precipitation variability analysis, on different spatial and temporal scales, has been of great concern during the past century because of the attention given to global climate change by the scientific community. According to some recent studies, the Iranian territory has been experienced a precipitation variability, especially in the last 50 years, and the arid and semi-arid areas seem to be more affected. The present study aims to analyze precipitation extreme indices over a wide time interval and a wide area, detecting potential trends and assessing their significance. The investigation is based on a wide range of daily and multi-day precipitation statistics encompassing basic characteristics and heavy precipitation. Two different methods of trend analysis and statistical testing are applied, depending on the nature of the statistics. Linear regression is used for statistics with a continuous value range, and logistic regression is used for statistics with a discrete value range. The trends are calculated on annual and seasonal bases for the years 1951–2007. Statistical analysis of the database highlight that a clear trend signal is found with a high number of sites with a statistically significant trend. In winter, significant increases are found for all statistics related to precipitation strength and occurrence. In spring, statistically, significant increases are found only for the statistics related to heavy precipitation, whereas precipitation frequency and occurrence statistics show little systematic change. The trend signal is strongest in highlands and mountainous terrains. In autumn and summer, the heavy and basic precipitation statistics did not show statistically significant trends.
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