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  • Author or Editor: D. L. Verseghy x
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Diana L. Verseghy
and
Murray D. MacKay

Abstract

The 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 and downscaled using the fifth-generation Canadian Regional Climate Model (CRCM5). The forcing precipitation field was adjusted using monthly data from the Canadian Gridded Temperature and Precipitation Anomalies (CANGRD) observation-based dataset. The modeled surface air temperature was evaluated against CANGRD data, the modeled albedo against MODIS data, and the modeled snow water equivalent against Canadian Meteorological Centre (CMC) and Global Snow Monitoring for Climate Research (GlobSnow) data. The lake simulation itself was evaluated using the Along Track Scanning Radiometer (ATSR) Reprocessing for Climate: Lake Surface Water Temperature and Ice Cover (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, snowpack, 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 subgrid lakes.

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Murray D. MacKay
,
Diana L. Verseghy
,
Vincent Fortin
, and
Michael D. Rennie

Abstract

A one-dimensional mixed layer dynamic lake model is enhanced with snow and ice physics for an examination of processes governing ice cover and phenology in a small boreal lake. The complete snowpack physics module of the Canadian Land Surface Scheme along with a new snow-ice parameterization have been added to the Canadian Small Lake Model, and detailed meteorological and temperature profile data have been acquired for the forcing and evaluation of two wintertime simulations. During the first winter, simulated ice-on and ice-off biases were −3 and −5 days, respectively. In the second winter simulation, ice-on bias was larger, likely due to the absence of a frazil ice scheme in the model, and simulated ice-off was 6 days late, evidently due to insufficient convective mixing beneath the ice in the weeks leading up to ice-off. Ice cover was simulated about 25% too thin between January and March for this year, though late January simulated snow and snow-ice amounts were close to observed. The impact of snow-ice production on simulated ice cover and phenology was found to be dramatic for this lake. In the absence of this process, January snow was more than twice as deep as observed and March ice thickness was less than one-third of that observed. Without snow-ice production, a reasonable simulation of ice cover could only be restored if 62% of snowfall was removed ad hoc (e.g., through blowing snow redistribution)—an excessive amount for a small, sheltered boreal lake.

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Zhichang Guo
,
Paul A. Dirmeyer
,
Randal D. Koster
,
Y. C. Sud
,
Gordon Bonan
,
Keith W. Oleson
,
Edmond Chan
,
Diana Verseghy
,
Peter Cox
,
C. T. Gordon
,
J. L. McGregor
,
Shinjiro Kanae
,
Eva Kowalczyk
,
David Lawrence
,
Ping Liu
,
David Mocko
,
Cheng-Hsuan Lu
,
Ken Mitchell
,
Sergey Malyshev
,
Bryant McAvaney
,
Taikan Oki
,
Tomohito Yamada
,
Andrew Pitman
,
Christopher M. Taylor
,
Ratko Vasic
, and
Yongkang Xue

Abstract

The 12 weather and climate models participating in the Global Land–Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land–atmosphere coupling and some intriguing commonalities. In this paper, the causes of variations in coupling strength—both the geographic variations within a given model and the model-to-model differences—are addressed. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage—an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first-stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation–precipitation connection, however, also play a key role.

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A. G. Slater
,
C. A. Schlosser
,
C. E. Desborough
,
A. J. Pitman
,
A. Henderson-Sellers
,
A. Robock
,
K. Ya Vinnikov
,
J. Entin
,
K. Mitchell
,
F. Chen
,
A. Boone
,
P. Etchevers
,
F. Habets
,
J. Noilhan
,
H. Braden
,
P. M. Cox
,
P. de Rosnay
,
R. E. Dickinson
,
Z-L. Yang
,
Y-J. Dai
,
Q. Zeng
,
Q. Duan
,
V. Koren
,
S. Schaake
,
N. Gedney
,
Ye M. Gusev
,
O. N. Nasonova
,
J. Kim
,
E. A. Kowalczyk
,
A. B. Shmakin
,
T. G. Smirnova
,
D. Verseghy
,
P. Wetzel
, and
Y. Xue

Abstract

Twenty-one land surface schemes (LSSs) performed simulations forced by 18 yr of observed meteorological data from a grassland catchment at Valdai, Russia, as part of the Project for the Intercomparison of Land-Surface Parameterization Schemes (PILPS) Phase 2(d). In this paper the authors examine the simulation of snow. In comparison with observations, the models are able to capture the broad features of the snow regime on both an intra- and interannual basis. However, weaknesses in the simulations exist, and early season ablation events are a significant source of model scatter. Over the 18-yr simulation, systematic differences between the models’ snow simulations are evident and reveal specific aspects of snow model parameterization and design as being responsible. Vapor exchange at the snow surface varies widely among the models, ranging from a large net loss to a small net source for the snow season. Snow albedo, fractional snow cover, and their interplay have a large effect on energy available for ablation, with differences among models most evident at low snow depths. The incorporation of the snowpack within an LSS structure affects the method by which snow accesses, as well as utilizes, available energy for ablation. The sensitivity of some models to longwave radiation, the dominant winter radiative flux, is partly due to a stability-induced feedback and the differing abilities of models to exchange turbulent energy with the atmosphere. Results presented in this paper suggest where weaknesses in macroscale snow modeling lie and where both theoretical and observational work should be focused to address these weaknesses.

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