New methods for studying the spatiotemporal variation of snow cover based on combination products of MODIS Terra and Aqua
New methods for studying the spatiotemporal variation of snow cover based on combination products of MODIS Terra and Aqua
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DOI：
10.1016/j.jhydrol.2009.03.028
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发表时间：
2009-06
影响因子：
6.4
通讯作者：
Xianwei Wang;H. Xie
中科院分区：
文献类型：
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作者：
Xianwei Wang;H. Xie
基于Terra和Aqua的MODIS雪盖产品（云量小于10%）的多天组合，本研究开发了新的雪盖指数（SCI）、雪盖持续时间/天数（SCD）图、雪盖开始日期（SCOD）图和雪盖融化日期（SCMD）图，每个水文年一个，以进一步研究雪盖的时空变化。利用2001 - 2005年中国新疆北方逐日积雪深度观测资料对新地图进行了验证。结果表明，SCD图与研究区20个站点的积雪天数现场观测结果总体一致性为90%，SCOD和SCMD图与现场观测结果也具有良好的一致性，平均值向前移动了1周。由于初秋和春末的短暂降雪事件，分别向后移动了1周。首次提出的积雪指数（SCI）（km ~ 2·d）包含了1个水文年的积雪持续时间和覆盖范围，表明2001-2002年水文年积雪最多，2005-2006年积雪最少。SCD地图提供了水文年中每个像素的积雪持续时间/天数，SCOD和SCMD地图则给出了积雪开始和融化的具体日期。SCD、SCI、SCOD和SCMD可以一起提供任何感兴趣区域积雪状况时空变化的关键信息。这可能是当地水务机构规划用水和减轻雪灾的关键信息。长期获得MODIS类型的积雪数据是研究积雪变化与全球气候变化关系的关键。
Based on multi-day combination of Terra and Aqua MODIS snow cover products (cloud cover less than 10%), this study developed new snow cover index (SCI), snow-covered duration/days (SCD) map, snow cover onset dates (SCOD) map and snow cover melting dates (SCMD) map, one each per hydrological year, to further examine the spatiotemporal variations of snow cover. Daily in situ snow depth observations in northern Xinjiang, China from 2001 to 2005 were used to validate the new maps. Our results indicate that the SCD maps had an overall agreement of 90% with in situ observations of snow cover days at 20 stations in the study area, and the SCOD and SCMD maps also had good agreements with the in situ measurements, with a mean value of 1 week forward shift and 1 week backward shift, respectively, due to transient snowfall events in early fall and in late spring. The snow cover index (SCI) (km2day), first proposed here, contains both snow cover duration and extent for 1 hydrological year and indicates that the 2001–2002 hydrologic year had the most snow cover while the 2005–2006 had the least. While the SCD map provides the snow cover duration/days of each pixel in a hydrologic year, the SCOD and SCMD maps give specific dates when the snow cover begins and when it melts away at the pixel. Together, SCD, SCI, SCOD and SCMD can provide crucial information on spatiotemporal variation of snow cover conditions for any region of interest. This could potentially be critical information for local water agencies for planning water use and for mitigating snow-caused disaster. Long term availability of MODIS type of snow cover data for producing such datasets is key to study the connection between snow cover change and global climate change.