The Seasonal Cycle of Snow Cover, Sea Ice and Surface Albedo

Alan Robock Department of Meteorology, University of Maryland, College Park 20742

Search for other papers by Alan Robock in
Current site
Google Scholar
PubMed
Close
Restricted access

We are aware of a technical issue preventing figures and tables from showing in some newly published articles in the full-text HTML view.
While we are resolving the problem, please use the online PDF version of these articles to view figures and tables.

Abstract

Satellite data are used to construct monthly mean snow cover maps for the Northern Hemisphere. The zonally averaged snow cover from these maps is calculated and used, along with zonally averaged sea ice cover and detailed data on land surface types, to calculate the seasonal cycle of zonally averaged surface albedo. A parameterization is presented of the solar zenith angle effect on ocean albedo. The effects of meltwater on the surface, solar zenith angle and cloudiness are all parameterized and included in the calculations of snow and ice albedo. It is found that meltwater effects are very important, but that zenith angle and cloudiness effects are negligible.

The albedo results for January, April, July, and October and the annual average results are compared to calculations by several other workers. The discrepancies are explained in terms of the above-mentioned effects and the averaging methods used. It is found that several other workers failed to weight the albedos by solar radiation when calculating annual averages. The global average surface albedo is calculated to be 0.150.

The data presented here allow a calculation of surface albedo for any land or ocean 10° latitude band as a function of surface temperature and ice and snow cover. The relationship between the seasonal cycles of snow and ice cover and surface temperature are also analyzed for possible use in a complete surface albedo parameterization for an energy balance climate model. The correct determination of the ice boundary is found to be more important than the snow boundary for accurately simulating the ice (a.-id snow)-albedo feedback. Annual average calculations are also presented. Northern and Southern Hemisphere sea-ice-temperature regressions give differing results for the seasonal cycle but similar ones for annual average values.

Abstract

Satellite data are used to construct monthly mean snow cover maps for the Northern Hemisphere. The zonally averaged snow cover from these maps is calculated and used, along with zonally averaged sea ice cover and detailed data on land surface types, to calculate the seasonal cycle of zonally averaged surface albedo. A parameterization is presented of the solar zenith angle effect on ocean albedo. The effects of meltwater on the surface, solar zenith angle and cloudiness are all parameterized and included in the calculations of snow and ice albedo. It is found that meltwater effects are very important, but that zenith angle and cloudiness effects are negligible.

The albedo results for January, April, July, and October and the annual average results are compared to calculations by several other workers. The discrepancies are explained in terms of the above-mentioned effects and the averaging methods used. It is found that several other workers failed to weight the albedos by solar radiation when calculating annual averages. The global average surface albedo is calculated to be 0.150.

The data presented here allow a calculation of surface albedo for any land or ocean 10° latitude band as a function of surface temperature and ice and snow cover. The relationship between the seasonal cycles of snow and ice cover and surface temperature are also analyzed for possible use in a complete surface albedo parameterization for an energy balance climate model. The correct determination of the ice boundary is found to be more important than the snow boundary for accurately simulating the ice (a.-id snow)-albedo feedback. Annual average calculations are also presented. Northern and Southern Hemisphere sea-ice-temperature regressions give differing results for the seasonal cycle but similar ones for annual average values.

Save