Monday, 10 January 2000: 4:30 PM
Yongkang Xue, Uniersity of Maryland, College Park, MD; and S. Sun and Y. Jiao
Based on up to date comprehensive and complex snow cover schemes, a
Simple Snow-Atmosphere-Soil Transfer Model (SAST) has been
developed. This
model includes most important physical processes for simulation of
seasonal snow cover change. The model also makes substantial
simplification and improvement. For example, based on the analysis of
the effect of vapor phase change and vapor movement on mass and energy
balances, a formulation of effective heat conductivity has been
derived which simplifies the description of complex processes
without loss of accuracy. Base on analyses of diurnal and seasonal
variations of snow temperature, an efficient snow cover layering system
has been developed for better prediction. The volumetric specific
enthalpy instead of temperature is used as the prognostic variable.
It simplifies the formulations in phase change processes and reduces
the computational procedures with an efficient implicit
one step test numerical scheme.
The SAST is coupled with SSIB to improve the SSIB prediction
potential in snow cover regime. The coupled model includes the vegetation
regime, snow cover regime and ground surface regime. Their physical
properties are described by the mass and energy balance
equations, respectively. Snow cover
interacts with both vegetation cover above and
ground surface below. In the coupled model, the snow surface temperature
and canopy temperature are solved simultaneously to ensure the energy
and water conservation in the vegetation-snow interface, which is crucial
in the study of snow effects in global as well as regional climate
models. Sensitivity has been conducted to further simplied snow model
for future GCM studies.
The SAST model has been tested in off line model by using long
term Russian and Franch field data. The results show its potential in
predicting seasonal snow cover change. These two data sets along with the
Mammoth snow data are tested further to validate and evaluate the
coupled SSiB/SAST model.
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