Modified treatment of intercepted snow improves the simulated forest albedo in the Canadian Land Surface Scheme

The Canadian Land Surface Scheme (CLASS) was modified to correct an underestimation of the winter albedo in evergreen needleleaf forests. Default values for the visible and near‐infrared albedo of a canopy with intercepted snow, αVIS,cs and αNIR,cs, respectively, were too small, and the fraction of...

Full description

Saved in:
Bibliographic Details
Published inHydrological processes Vol. 29; no. 14; pp. 3208 - 3226
Main Authors Bartlett, Paul A., Verseghy, Diana L.
Format Journal Article
LanguageEnglish
Published Chichester Blackwell Publishing Ltd 01.07.2015
Wiley Subscription Services, Inc
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:The Canadian Land Surface Scheme (CLASS) was modified to correct an underestimation of the winter albedo in evergreen needleleaf forests. Default values for the visible and near‐infrared albedo of a canopy with intercepted snow, αVIS,cs and αNIR,cs, respectively, were too small, and the fraction of the canopy covered with snow, fsnow, increased too slowly with interception, producing a damped albedo response. A new model for fsnow is based on zI*, the effective depth of newly intercepted snow required to increase the canopy albedo to its maximum, which corresponds in the model with fsnow = 1. Snow unloading rates were extracted from visual assessments of photographs and modelled based on relationships with meteorological variables, replacing the time‐based method employed in CLASS. These parameterizations were tested in CLASS version 3.6 at boreal black spruce and jack pine forests in Saskatchewan, Canada, a subalpine Norway spruce and silver fir forest at Alptal, Switzerland, and a boreal maritime forest at Hitsujigaoka, Japan. Model configurations were assessed based on the index of agreement, d, relating simulated and observed daily albedo. The new model employs αVIS,cs = 0.27, αNIR,cs = 0.38 and zI* = 3 cm. The best single‐variable snow unloading algorithm, determined by the average cross‐site d, was based on wind speed. Two model configurations employing ensemble averages of the unloading rate as a function of total incoming radiation and wind speed, and air temperature and wind speed, respectively, produced larger minimum cross‐site d values but a smaller average. The default configuration of CLASS 3.6 produced a cross‐site average d from October to April of 0.58. The best model employing a single parameter (wind speed at the canopy top) for modelling the unloading rate produced an average d of 0.86, while the two‐parameter ensemble‐average unloading models produced a minimum d of 0.81 and an average d of 0.84. © 2015 Her Majesty the Queen in Right of Canada. Hydrological Processes published by John Wiley & Sons, Ltd.
Bibliography:istex:1D3772B1542FA0511BFDDEF79E6BFDC56383335D
ark:/67375/WNG-QSN2XNSN-D
ArticleID:HYP10431
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0885-6087
1099-1085
DOI:10.1002/hyp.10431