...
首页> 外文期刊>Climate research >Patterns of seasonal maximum snow-water equivalent over the Northern Great Plains of the United States analyzed using hybrid-modeled climatology
【24h】

Patterns of seasonal maximum snow-water equivalent over the Northern Great Plains of the United States analyzed using hybrid-modeled climatology

机译:使用混合模式气候学分析美国北部大平原的季节性最大雪水当量模式

获取原文
获取原文并翻译 | 示例
           

摘要

Over the last 20 yr across North America, satellite and in situ observations have indicated a reduction both in the number of snow-cover days and in snow-cover extent in the spring. From a hydrologic perspective, however, the water content of the snowpack is most important. Few studies have examined whether the changes in snow-cover days or snow-cover extent corresponded to changes in the water content of the snowpack. This is due largely to the problems with obtaining quality data on the snow-water equivalent (SWE). This paper uses a long-term, high-resolution hybrid SWE climatology to examine peak seasonal SWE and its impact on the hydrology of the Northern Great Plains. Accumulations of peak SWE, most frequently occurring in February, are greatest over NE Minnesota and decrease towards the south and southwest. There are no long-term trends in the magnitude of SWE, but there are distinct decadal-scale patterns of above- and below-average SWE. In general, the 1950s were below average, the mid-1960s through the 1970s were above average, and the 1980s and early 1990s were again below average. Greater maximum seasonal SWE corresponds with longer snow persistence in the spring and greater March snow-cover area. [References: 24]
机译:在过去的20年中,整个北美地区的卫星观测和现场观测表明,积雪天数和春季积雪程度均减少了。但是,从水文角度来看,积雪的含水量最为重要。很少有研究检查积雪天数或积雪程度的变化是否与积雪的含水量变化相对应。这主要是由于获取有关雪水当量(SWE)的质量数据存在问题。本文使用长期,高分辨率的混合SWE气候学来检验季节性SWE的峰值及其对北部大平原水文学的影响。明尼苏达州东北部的SWE高峰累积最频繁,发生在2月,并且向南和西南方向减少。 SWE的大小没有长期趋势,但是在高于和低于平均水平的SWE上存在明显的年代际尺度模式。总的来说,1950年代低于平均水平,1960年代中期至1970年代高于平均水平,1980年代和1990年代初再次低于平均水平。最大季节性SWE越大,春季的积雪持续时间越长,3月的积雪面积越大。 [参考:24]

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号