Geospatial Snow Estimation for Engineering Applications and Operations

被引:0
|
作者
Deeb, E. [1 ]
Polashenski, C. [1 ]
Courville, Z. [1 ]
Hiemstra, C. [1 ]
Wagner, A. [1 ]
Eylander, J. [1 ]
Davis, R. [1 ]
机构
[1] Cold Reg Res & Engn Lab, Hanover, NH 03755 USA
关键词
Characterization; modeling; remote sensing; snow; VARIABILITY; DEPTH;
D O I
暂无
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The U.S. Army Corps of Engineers supports accurate terrestrial, atmospheric, and environmental awareness from tactical to global scale in support of its national security, international development, and humanitarian functions. Moreover, the Cold Regions Research and Engineering Laboratory specifically estimates geospatial snow properties in support of the Corps civil works mission which include managing waterways in snow impacting watersheds, winter vehicle mobility, and other national intelligence functions. Snow is a spatially and temporally evolving medium that has a diverse set of impacts on engineering applications and operations. While some operational organizations provide general snow information with a regional to global perspective, the time and length scales do not match tactical or engineering requirements. Fine-scale spatial representation of snow requires observations or simulation of several snow characteristics including snow depth, density, albedo, stratigraphy, microstructure, and temperature. The Remote Snow Assessment Team at the Cold Regions Research and Engineering Laboratory has addressed user needs through the use of a combined multi-sensor, modeling framework to improve global snow characterization and enable assimilation of remotely sensed observations. Case studies from both military and civil works applications are highlighted showing successful methods developed to provide high spatial/temporal resolution snow products, snow climatologies from historical analyses, and solutions to solve snow issues with respect to water resource management, flood hazard assessment, and winter mobility modeling.
引用
收藏
页码:231 / 237
页数:7
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