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Abstract

Snowfall in the Southern Appalachian Mountain region of the eastern US is characterized by much spatiotemporal variability. Annual snowfall totals vary by up to 75 cm, and variations in snowfall intensity can lead to large differences in the local snowfall distribution. Research has shown that the synoptic pattern associated with the snowfall strongly influences the regional-scale distribution of snow cover. However, topographic variability results in locally complex snow cover patterns that are not well understood or documented. In this study, we characterize the snow covered area (SCA) and fractional snow cover associated with different synoptic patterns in 14 individual sub-regions. We analyze 63 snow events using Moderate-resolution Imaging Spectroradiometer standard snow cover products to ascertain both qualitative and quantitative differences in snow cover across sub-regions. Among sub-regions, there is significant variation in the snow cover pattern from individual synoptic classes. Furthermore, the percent SCA follows the regional snowfall climatology, and sub-regions with the highest elevations and northerly latitudes exhibit the greatest variability. Results of the sub-regional analysis provide valuable guidance to forecasters by contributing a deeper understanding of local snow cover patterns and their relationship to synoptic-scale circulation features.  相似文献   
2.
Wilson  Matthew  Lane  Sandi  Mohan  Raghuveer  Sugg  Margaret 《Natural Hazards》2020,100(3):1013-1036
Natural Hazards - As the frequency of natural disasters increases, there has been an emphasis on vulnerability index creation studies. In this study, we test the validity of vulnerability indices...  相似文献   
3.
ABSTRACT

This paper addresses warm season hydroclimatic variability in the southern Appalachian region of the southeastern U.S., where precipitation can vary as much as 127?mm or more, with maximum seasonal totals exceeding 736?mm in extreme cases. Despite the occurrence of droughts, floods, and their socioecological impacts, hydroclimate variability is still poorly understood. This study characterizes the regional scale variations in the hydroclimate by examining the daily distribution of precipitation patterns in different topographic environments. Parameter-elevation relationships on independent slopes model (PRISM) gridded precipitation estimates are used to identify the location and frequency of different types of rainfall events. Several types of clustering algorithms are used as a regionalization approach to define areas where the precipitation regime exhibits similarities in its frequency of occurrence. The results are compared with internal validation statistics and a visualization is used to assess how well the resulting hydroclimatic regions align with different topographic environments. This study reveals the intricate spatial footprint of dry and wet regimes and demonstrates how clustering applications can be used with gridded climate data to determine where extremes are most likely to develop across mountain catchments.  相似文献   
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