Offline implementation and evaluation of the Canadian Small Lake Model with the Canadian Land Surface Scheme over western Canada

Offline implementation and evaluation of the Canadian Small Lake Model with the Canadian Land... AbstractThe Canadian Small Lake Model (CSLM), version 2, was run with the Canadian Land Surface Scheme (CLASS), version 3.6.1, in an offline regional test over western Canada. Forcing data were derived from ERA-Interim reanalyses, downscaled using the Canadian Regional Climate Model (CRCM5). The forcing precipitation field was adjusted using monthly data from the CANGRD observation-based dataset. The modelled surface air temperature was evaluated against CANGRD data, the modelled albedo against MODIS data, and the modelled snow water equivalent against CMC and GlobSnow data. The lake simulation itself was evaluated using the ARC-Lake dataset. Summer surface lake temperatures and the lake ice formation and breakup periods were well simulated, except for slight warm/cold summer/fall surface temperature biases, early ice breakup and early ice formation, consistent with warm/cold biases in the climate simulation. Tests were carried out to investigate the sensitivity of the CSLM simulation to the default values assigned to the shortwave extinction coefficient and the average lake depth, and changing the former from 0.5 to 2.0 m−1 and the latter from 10.0 to 50.0 or 5.0 m had minimal effects on the simulation. Comparisons of the average annual variations of the simulated net shortwave radiation, turbulent fluxes, snow pack and maximum and minimum daily surface temperatures between the land and the lake fractions for tundra, boreal and southern regions showed patterns consistent with those expected. Finally, a test of the CSLM over the large resolved lakes in the model domain demonstrated a performance comparable to that for sub-grid lakes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Hydrometeorology American Meteorological Society

Offline implementation and evaluation of the Canadian Small Lake Model with the Canadian Land Surface Scheme over western Canada

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1525-7541
eISSN
1525-7541
D.O.I.
10.1175/JHM-D-16-0272.1
Publisher site
See Article on Publisher Site

Abstract

AbstractThe Canadian Small Lake Model (CSLM), version 2, was run with the Canadian Land Surface Scheme (CLASS), version 3.6.1, in an offline regional test over western Canada. Forcing data were derived from ERA-Interim reanalyses, downscaled using the Canadian Regional Climate Model (CRCM5). The forcing precipitation field was adjusted using monthly data from the CANGRD observation-based dataset. The modelled surface air temperature was evaluated against CANGRD data, the modelled albedo against MODIS data, and the modelled snow water equivalent against CMC and GlobSnow data. The lake simulation itself was evaluated using the ARC-Lake dataset. Summer surface lake temperatures and the lake ice formation and breakup periods were well simulated, except for slight warm/cold summer/fall surface temperature biases, early ice breakup and early ice formation, consistent with warm/cold biases in the climate simulation. Tests were carried out to investigate the sensitivity of the CSLM simulation to the default values assigned to the shortwave extinction coefficient and the average lake depth, and changing the former from 0.5 to 2.0 m−1 and the latter from 10.0 to 50.0 or 5.0 m had minimal effects on the simulation. Comparisons of the average annual variations of the simulated net shortwave radiation, turbulent fluxes, snow pack and maximum and minimum daily surface temperatures between the land and the lake fractions for tundra, boreal and southern regions showed patterns consistent with those expected. Finally, a test of the CSLM over the large resolved lakes in the model domain demonstrated a performance comparable to that for sub-grid lakes.

Journal

Journal of HydrometeorologyAmerican Meteorological Society

Published: Mar 16, 2017

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