One-Dimensional Snow Water and Energy Balance Model for Vegetated Surfaces

One-Dimensional Snow Water

and Energy Balance Model for Vegetated Surfaces

Jiming Jin1, Xiaogang Gao1, Soroosh Sorooshian1, Zong-Liang Yang1,

Roger Bales2, Robert E. Dickinson2, Shu-Fen Sun1, and Guo-Xiong Wu1

A number of point snow models have long been referenced in the literature. These models assume

that the snow cover overlies a homogeneous surface; therefore, a one-dimensional (vertical) snow

model at one location can represent the whole snow cover. To represent snow cover on more realistic

areas with heterogeneous surfaces, work is needed to extend these point models. We have developed

a three-layer snow model (coupled with a new version of the Biosphere-Atmosphere Transfer

Scheme [BATS] of Dickinson et al. [1997]), which is a simplification of the complex one-dimen-

sional snow property and process model (SNTHERM) of Jordan (1991). This point snow model has

been tested in a bare soil case against the field data. The results are in good agreement with the

observations and with Jordan's model (Jin et al. 1998). Because this snow model is developed for use

in Global Climate Models (GCMs), it needs to be extended to an area where patches of snow, soil,

and vegetation exist. We related this one-dimensional model to the heterogeneous surface by param-

eterizing the snow, soil, and vegetation patches into a mixture with varying fractional coverage for

each surface type, then calculating the dynamic properties and states for each surface type through

energy and mass balance under the grid-uniform atmospheric and radiative forcing. We tested this

areal snow model using the field data from France (grass) and BOREAS (forest) to see the perfor-

mance of this model in these two different land covers.

In conclusion, the agreement of the modeled snow depth with the field observations using the three-

layer snow model is consistent with the results from the multi-layer SNTHERM model. Because of

the substantial reduction of the computational requirement of the model compared to SNTHERM, it

is applicable for use in GCMs. The model adds physical details of snow, such as meltingthawing

cycles and vertical and diurnal variability, to the current GCM snow models. Introducing parameter-

ization of subgrid heterogeneity into the snow model is a way of extending the point model to areas.

The good matches of modeled and observed skin temperature and albedo and the reasonable expla-

nation for the complicated responses of surface fluxes indicate that this approach captured the essen-

tials of subgrid heterogeneity, and its formulations and parameter values are representative.

LASG, Institute of Atmospheric Physics, CAS, Beijing 100080, China

Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona 85721, USA