Item: Linking Large-Scale Wet-Snow Spatial Patterns in Mountainous Terrain to Incident Radiation and Topography
-
-
Title: Linking Large-Scale Wet-Snow Spatial Patterns in Mountainous Terrain to Incident Radiation and Topography
Proceedings: International Snow Science Workshop 2014 Proceedings, Banff, Canada
Authors:
- N. Helbig [ WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland ]
- F. Techel [ WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland ]
- A. van Herwijnen [ WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland ]
- T. Jonas [ WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland ]
Date: 2014-09-29
Abstract: Water percolating through the snow cover can lead to wet-snow instability as well as snowmelt runoff. The accurate prediction of spatial patterns of wet-snow in mountainous terrain therefore has practical applications in both hydrological and avalanche forecasting. Recent research has shown that incident radiation plays a dominant role during the first wetting of the snow cover. We therefore investigated if large-scale meteorological forecast data, corrected for subgrid topographic influences on the shortwave radiation balance, together with subgrid mean slopes can be combined to improve the prediction of large-scale wet-snow avalanche patterns. Required surface albedo was derived from parameterized snow covered fraction based on terrain parameters and measured flat field snow depths. We derived avalanche probability density functions (pdf) for daily mean air temperature and incoming short wave radiation from detailed observations over six winters using time-lapse photography. Based on these pdf's, we computed wet-snow probability maps for a scale of a few kilometers. The probability maps compared well with observed wet-snow avalanche activity patterns. Even though, our method clearly needs to be extended to include snow cover related parameters, it provides a new approach towards an automatic avalanche forecast built upon simple terrain parameters and easy to obtain large-scale meteorological surface variables. The advantage of our method is that it does not require running any sophisticated, small-scale models with demanding model input parameters.
Language of Article: English
Presenters:
Keywords: wet-snow; avalanche forecasting; meteorological models; subgrid parameterization
Page Number(s): 497-501
-
Digital Abstract Not Available
-