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Precipitation is a major climatic element with high spatial variations. Temporal and spatial variations may differ in large and small scales. It is, therefore, of utmost importance to study areas with similar gradients in terms of precipitation patterns in order to shed light on the complexities of precipitation variations. In the present study, attempts were made to identify areas with similar gradients experiencing the same precipitation pattern over a 50-year period (1964–2013). To this end, data were collected from synoptic stations in Iran in two phases (i.e., 1434 stations in the first phase and 673 stations in the second one). Alexanderson’s technique was adopted to examine sudden changes in precipitation patterns. The results showed that five regions with similar gradients could be identified in terms of precipitation patterns: negative and high variations, negative and moderate variations, positive and high variations, positive and moderate variations, and little or no variations. The distribution of such regions indicated that the regions with positive trends experienced more annual variations and had further spatial distribution. Furthermore, the findings revealed that the regions with negative precipitation patterns experienced more sudden changes in comparison with those with positive precipitation patterns. Additionally, more variations were observed in the precipitation patterns in recent years. 相似文献
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Climatic Change - Changes in precipitation pattern can lead to widespread impacts across natural and human systems. This study assesses precipitation variability as well as anthropogenic and... 相似文献
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Acknowledgement of Reviewers 总被引：2，自引：0，他引：2
Variations in frequency and intensity of extreme events have substantial impact on water resources and environment, which in turn are reflected on agriculture, society, and economy. We assessed spatiotemporal changes in pattern of daily precipitation to identify drought- and flood-prone areas of Iran. To do this, we generated gridded daily precipitation for the period of 1962–2013 over Iran using measured daily precipitation and the Kriging approach. We applied 11 precipitation indices that were stated by the Expert Team on Climate Change Detection and Indices (ETCCDI) to identify significant changes in frequency and intensity of extreme precipitation events. According to significant changes of these 11 precipitation indices, drought- and flood-prone areas of Iran were, then, detected. We observed significant changes in pattern of daily precipitation over more than half of the country. 40% of the country, which were located in the elevated regions of Iran, particularly along Zagros Mountain, was identified as flood-prone areas. As a result, in these regions, there is a need for flood risk management based on changes in stormwater events such as runoff generated from rain on snow and snowmelt events. In addition, we detected drought-prone areas in large portion of the northwest of Iran and in the low elevated regions of the country that have semiarid or arid climate. This suggests that it is necessary to prepare a long-term drought plan to mitigate impacts of severe drought events. 相似文献
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Spatial variations in extreme precipitation events make hydrological, climatological, social, environmental and agricultural effects on a country. This study presents the spatiotemporal autocorrelation analysis of extreme precipitation events over Iran using gridded data on daily precipitation for the period 1961–2010. The 95th percentile is considered as extreme precipitation factor. The spatial autocorrelation of extreme precipitation is examined by three commonly used spatial autocorrelation statistics, the G i statistic index, Moran’s I global index, and Local Moran’s I (LISA) index, at the 95 and 99% significant confidence level. The results showed a strong significant spatial autocorrelation for extreme precipitation events with the highest Moran’s I value in January. The positive significant autocorrelation of extreme precipitation is observed over the southern parts of the Caspian Sea and Zagros Mountains ranges, while the negative significant autocorrelation is observed over the central and eastern parts of country. In spring and summer the positive autocorrelation cores displace from the Zagros Mountains ranges to the northwestern and southeastern parts. 相似文献
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