Shift changes and monotonic trends in autocorrelated temperature series over Iran

Temperature data from 29 synoptic stations in Iran for a period of 40?years (1966–2005) were analyzed to test for the existence of monotonic trends and shift changes in the annual, seasonal, and monthly mean air temperature series using the Mann–Kendall and Mann–Whitney tests. The influences of significant lag-1 serial correlation were eliminated from data by the trend-free pre-whitening method prior to the trend analysis. The magnitude of the temperature trends was derived from the Theil–Sen’s slope estimator. It was found that annual mean air temperature increased at 25 out of the 29 stations, of which 17 stations showed significant monotonic trends. The magnitude of the annual mean air temperature trends averagely was (+)0.224°C per decade. Most of the stations with the significant positive monotonic trends had a significant upward shift change. The analysis indicated that the change point year of the significant upward shift changes was 1972 for the whole stations except the coastal ones. Moreover, the strongest monotonic increasing trends and upward shift changes were observed in summer especially in August and September. The spatial analysis of the mean air temperature trends revealed the highest numbers of significant monotonic trends in the big cities of Iran. These findings provide more insights for better understanding of regional temperature behavior in the study area.     

Hydrological drought in the west of Iran and possible association with large‐scale atmospheric circulation patterns

Drought is a slow‐onset, creeping natural hazard which is an inevitable part of normal climate fluctuation especially in arid and semiarid regions, and its variability can be explained in terms of large‐scale atmospheric circulation patterns. Standardized streamflow index (SSFI) was utilized to characterize hydrological drought in the west of Iran for the hydrological years of 1969–1970 to 2008–2009. The linkage of atmospheric circulation patterns (ENSO, NAO) to hydrological drought was also used to reveal relations of climate variability affecting hydrological drought. River discharges exhibited negative anomalies during the warm phase of ENSO (El Niño) which caused the extreme and severe droughts in the study area, being strongest during the hydrological years of 2007–2008 and 2008–2009. The analysis also indicated the teleconnection impact of ENSO on the hydrological drought severity in the first half of the hydrological year especially between November and March. Moreover, the concurrent and lag correlations revealed a weak relationship between the SSFI drought severity and the NAO index. Copyright © 2012 John Wiley & Sons, Ltd.     

Homogeneity analysis of precipitation series in Iran

Assessment of the reliability and quality of historical precipitation data is required in the modeling of hydrology and water resource processes and for climate change studies. The homogeneity of the annual and monthly precipitation data sets throughout Iran was tested using the Bayesian, Cumulative Deviations, and von Neumann tests at a significance level of 0.05. The precipitation records from 41 meteorological stations covering the years between 1966 and 2005 were considered. The annual series of Iranian precipitation were found to be homogeneous by applying the Bayesian and Cumulative Deviations tests, while the von Neumann test detected inhomogeneities at seven stations. Almost all the monthly precipitation data sets are homogeneous and considered as “useful.” The outputs of the statistical tests for the homogeneity analysis of the precipitation time series had discrepancies in some cases which are related to different sensitivities of the tests to break in the time series. It was found that the von Neumann test is more sensitive than the Bayesian and Cumulative Deviations tests in the determination of inhomogeneity in the precipitation series.