An improved snow hydrology for GCMs. Part 1: snow cover fraction, albedo, grain size, and age

Abstract

A new, physically-based snow hydrology has been implemented into the NCAR CCM1. The snow albedo is based on snow depth, solar zenith angle, snow cover pollutants, cloudiness, and a new parameter, the snow grain size. Snow grain size in turn depends on temperature and snow age. An improved expression is used for fractional snow cover which relates it to surface roughness and to snow depth. Each component of the new snow hydrology was implemented separately and then combined to make a new control run integrated for ten seasonal cycles. With the new snow hydrology, springtime snow melt occurs more rapidly, leading to a more reasonable late spring and summer distribution of snow cover. Little impact is seen on winter snow cover, since the new hydrology affects snow melt directly, but snowfall only indirectly, if at all. The influence of the variable grain size appears more important when snow packs are relatively deep while variable fractional snow cover becomes increasingly important as the snow pack thins. Variable surface roughness affects the snow cover fraction directly, but shows little effect on the seasonal cycle of the snow line. As an applicaion of the new snow hydrology, we have rerun simulations involving Antarctic and Northern Hemisphere glaciation; these simulations were previously made with CCM1 and the old snow hydrology. Relatively little difference is seen for Antarctica, but a profound difference occurs for the Northern Hemisphere. In particular, ice sheets computed using net snow accumulations from the GCM are more numerous and larger in extent with the new snow hydrology. The new snow hydrology leads to a better simulation of the seasonal cycle of snow cover, however, our primary goal in implementing it into the GCM is to improve the predictive capabilities of the model. Since the snow hydrology is based on fundamental physical processes, and has well-defined parameters, it should enable model simulations of climatic change in which we have increased confidence.