A key component of the surface energy balance over land is the albedo

defined as the ratio of the integrated total of reflected solar radiation to the integral of the incoming solar radiation. Climate is sensitive to albedo variation and its changes by natural variations and human activities. Predictions of climate change typically use a GCM linked to a land surface model. Land surface models

e. g. Biosphere Atmosphere Transfer Scheme（BATS）

estimate albedo of trees over snow roughly with the parameters of roughness length

Z 0

and snow depth

d . Based on their work

we further consider the difference in directional to hemisphere albedo for different solar zenith angle（ SZA ）

and leaf area index（ LAI ）dependence. In order to keep the basic feature of BATS model and add these two new features

we simplified geometric optical and radiative transfer（GORT）hybrid model to reach this purpose. In this paper

we take the conifer as an example. And we validate the model initially with observational data from MODIS and from BOREAS. Results show that: this model can simulate the observations well. This model can be rather simple to retrieve the albedo of remote sensing pixel. It can be a strong tool for understanding the climate system.