Abstract

  Precipitation is considered as one of the most important climate elements affecting different environmental aspects.. Precipitation extremes follow a geographical pattern like all other climate elements. Recognition of such patterns, specifically in those areas where people’s lives depend on precipitations, can determined the amount of success in environmental management as well as in resources planning. High extreme precipitation in Iranian coastal region of Caspian Sea, especially eastern parts, the recognition of spatial auto-correlation of such a phenomenon can facilitate environmental planning and also increasing adaptability with such a disaster. Therefore, in order to analyze auto-correlation of the sum frequency of monthly extreme precipitations of under investigation region, the 99 percentile of precipitation for each pixel of the map is considered. 385 stations were studied during the time period covering 1966 to 2016. We have used spatial statistics techniques to analyze spatial auto-correlation features. Results of the present study showed that the dominant behavior in sum frequency of monthly extreme precipitation under study region followed cluster pattern. The areas with positive auto-correlations were mostly found in internal areas and far from the coastal line over most months. Positive auto -correlated clusters were spread in eastern and western regions and some parts in central areas. G* test approved the frequency of clusters with high and low values. The comparison of our findings with previous studies showed that the geographical location of under investigation region, and also synoptic systems affecting the region have affected the spatial auto-correlation frequency pattern of extreme precipitation occurrence. Precipitation is considered as one of the most important climate elements affecting different environmental aspects.. Precipitation extremes follow a geographical pattern like all other climate elements. Recognition of such patterns, specifically in those areas where people’s lives depend on precipitations, can determined the amount of success in environmental management as well as in resources planning. High extreme precipitation in Iranian coastal region of Caspian Sea, especially eastern parts, the recognition of spatial auto-correlation of such a phenomenon can facilitate environmental planning and also increasing adaptability with such a disaster. Therefore, in order to analyze auto-correlation of the sum frequency of monthly extreme precipitations of under investigation region, the 99 percentile of precipitation for each pixel of the map is considered. 385 stations were studied during the time period covering 1966 to 2016. We have used spatial statistics techniques to analyze spatial auto-correlation features. Results of the present study showed that the dominant behavior in sum frequency of monthly extreme precipitation under study region followed cluster pattern. The areas with positive auto-correlations were mostly found in internal areas and far from the coastal line over most months. Positive auto -correlated clusters were spread in eastern and western regions and some parts in central areas. G* test approved the frequency of clusters with high and low values. The comparison of our findings with previous studies showed that the geographical location of under investigation region, and also synoptic systems affecting the region have affected the spatial auto-correlation frequency pattern of extreme precipitation occurrence.