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  • Author or Editor: K. K. Szeto x
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M. D. MacKay
,
F. Seglenieks
,
D. Verseghy
,
E. D. Soulis
,
K. R. Snelgrove
,
A. Walker
, and
K. Szeto

Abstract

The Canadian Regional Climate Model has been used to estimate surface water balance over the Mackenzie River basin during the water year 1998–99 in support of the Canadian Global Energy and Water Cycle Experiment (GEWEX) Enhanced Study (CAGES). The model makes use of a developmental third-generation physics parameterization package from the Canadian Centre for Climate Modelling and Analysis GCM, as well as a high-resolution land surface dataset. The surface water balance is simulated reasonably well, though Mackenzie basin annual mean daily maximum and minimum temperatures were both colder than observed by 1.7°C. The cold bias contributed to a longer snow-covered season and larger peak snow water equivalent than was observed, though snow accumulated realistically compared with two independently observed estimates after 1 November. Mackenzie basin annual precipitation was simulated as 496 mm, about 9% larger than observed, and PE was 225 mm. Net soil moisture change during this water year was found to be −26 mm, though because of a spinup problem in the Liard subbasin, the value is more likely closer to −14 mm.

The simulation was used to drive offline two different hydrologic models in order to simulate streamflow hydrographs at key stations within the Mackenzie basin. Results suggest that when subgrid-scale routing and interflow are included, streamflow timing is improved. This study highlights the importance of orographic processes and land surface initialization for climate modeling within the Mackenzie GEWEX Study.

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B. F. Ryan
,
J. J. Katzfey
,
D. J. Abbs
,
C. Jakob
,
U. Lohmann
,
B. Rockel
,
L. D. Rotstayn
,
R. E. Stewart
,
K. K. Szeto
,
G. Tselioudis
, and
M. K. Yau

Abstract

The Global Energy and Water Cycle Experiment has identified the poor representation of clouds in atmospheric general circulation models as one of the major impediments for the use of these models in reliably predicting future climate change. One of the most commonly encountered types of cloud system in midlatitudes is that associated with cyclones. The purpose of this study is to investigate the representation of frontal cloud systems in a hierarchy of models in order to identify their relative weaknesses. The hierarchy of models was classified according to the horizontal resolution: cloud-resolving models (5-km resolution), limited-area models (20-km resolution), coarse-grid single-column models (300 km), and an atmospheric general circulation model (>100 km). The models were evaluated using both in situ and satellite data.

The study shows, as expected, that the higher-resolution models give a more complete description of the front and capture many of the observed nonlinear features of the front. At the low resolution, the simulations are unable to capture the front accurately due to the lack of the nonlinear features seen in the high-resolution simulations. The model intercomparison identified problems in applying single-column models to rapidly advecting baroclinic systems. Mesoscale circulations driven by subgrid-scale dynamical, thermodynamical, and microphysical processes are identified as an important feedback mechanism linking the frontal circulations and the cloud field. Finally it is shown that the same techniques used to validate climatological studies with International Satellite Cloud Climatology Project data are also valid for case studies, thereby providing a methodology to generalize the single case studies to climatological studies.

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