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A new Snow-SVAT to simulate the accumulation and ablation of seasonal snow cover beneath a forest canopy

Tribbeck, Melody J.; Gurney, Robert J.; Morris, Elizabeth M.; Pearson, David W.C.. 2004 A new Snow-SVAT to simulate the accumulation and ablation of seasonal snow cover beneath a forest canopy. Journal of Glaciology, 50 (169). 171-182. 10.3189/172756504781830187

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Abstract/Summary

A new snow-soil-vegetation-atmosphere transfer (Snow-SVAT) scheme, which simulates the accumulation and ablation of the snow cover beneath a forest canopy, is presented. The model was formulated by coupling a canopy optical and thermal radiation model to a physically based multi-layer snow model. This canopy radiation model is physically based yet requires few parameters, so can be used when extensive in situ field measurements are not available. Other forest effects such as the reduction of wind speed, interception of snow on the canopy and the deposition of litter were incorporated within this combined model, SNOWCAN, which was tested with data taken as part of the Boreal Ecosystem-Atmosphere Study (BOREAS) international collaborative experiment. Snow depths beneath four different canopy types and at an open site were simulated. Agreement between observed and simulated snow depths was generally good, with correlation coefficients ranging between r(2) = 0.94 and r(2) = 0.98 for all sites where automatic measurements were available. However, the simulated date of total snowpack ablation generally occurred later than the observed date. A comparison between simulated solar radiation and limited measurements of sub-canopy radiation at one site indicates that the model simulates the sub-canopy downwelling solar radiation early in the season to within measurement uncertainty.

Item Type: Publication - Article
Digital Object Identifier (DOI): 10.3189/172756504781830187
Programmes: BAS Programmes > Other
ISSN: 0022-1430
NORA Subject Terms: Glaciology
Earth Sciences
Date made live: 15 Mar 2012 11:37
URI: http://nora.nerc.ac.uk/id/eprint/12482

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