Applications of SHEBA/FIRE data to evaluation of snow/ice albedo parameterizations

Abstract

Abstract. Climate models use a wide variety. ofparameterizations for surface albedos of the ice-covered ocean. These range from simple broadband albedo parameterizations that distinguish among snow-covered and bare ice to more sophisticated parameterizations that include dependence on ice and snow depth, solar zenith angle, and spectral resolution. Several sophisticated parameterizations have also been developed for thermodynamic sea ice models that additionally include dependence on ice and snow age, and melt pond characteristics. Observations obtained in the Arctic Ocean during 1997-1998 in conjunction with the Surface Heat Budget of the Arctic Ocean (SHEBA) and FIRE Arctic Clouds Experiment provide a unique data set against which to evaluate parameterizations of sea ice surface albedo. We apply eight different surface albedo parameterizations to the SHEBA/FIRE data set and evaluate the parameterized albedos against the observed albedos. Results show that these parameterizations yield very different representations of the annual cycle of sea ice albedo. The importance of details and functional relationships of the albedo parameterizations is assessed by incorporating into a single-column sea ice model two different albedo parameterizations, one complex and one simple, that have the same annually averaged surface albedo. The baseline sea ice characteristics and strength of the ice-albedo feedback are compared for the simulations of the different surface albedos.

Evaluation of snow/ice albedo parameterizations and their impacts on sea ice simulations

“…The simulations were forced by the specified atmospheric forcings from the NCEP (National Center for Environmental Prediction) reanalysis II in 1997 (annually repeating forcing, including surface air temperature, humidity and density, surface downward shortwave and longwave radiation, surface winds and precipitation). As suggested by some studies (Curry et al, 2001;Liu et al, 2005), there are uncertainties in the NCEP atmospheric forcing. However, by comparing model simulations with each other (as opposed to with observations), we can minimize uncertainties caused by the atmospheric forcing, and highlight impacts due to the differences in the snow/ice albedo parameterizations.…”

“…snow depth, ice thickness, spectral band (visible and near infrared bands), and solar zenith angle. As pointed out by Curry et al (2001), most climate modelers have justified using simple snow/ice albedo parameterizations because of the lack of observations against which to evaluate them. However, this situation is gradually improving, because recent field experiments such as the Surface Heat Budget of the Arctic Ocean (SHEBA, Perovich et al, 1999a) provide unprecedented opportunities to evaluate snow/ice albedo parameterizations.…”

“…Toward addressing this issue, Curry et al (2001) evaluated different snow/ice albedo parameterizations using a single-column sea ice model. In this paper, we extend Curry's study to a basin-scale dynamic-thermodynamic sea ice model.…”

“…Surface characteristics that influence the snow/ice albedo includes snow depth, ice thickness, snow/ice metamorphosis and impurity, melt pond fraction and depth, and lead fraction. Currently, a diversity of snow/ice albedo parameterizations is used in climate models (see Barry, 1996;Curry et al, 2001 for reviews). Most parameterizations are very simple, depending on surface type (open water, bare ice, and snow) and/or surface temperature.…”

Seasonal evolution and interannual variability of the local solar energy absorbed by the Arctic sea ice–ocean system

“…This program entailed a year-long field experiment plus an extensive data assimilation and modeling effort. Analysis of the field results provided considerable insights on the surface heat budget Andreas et al, 2002], the ice mass balance [Perovich et al, 2003], and the ice-albedo feedback and solar partitioning [Curry et al, 2001;Perovich et al, 2002a;Perovich, 2005]. The field observations made at one location for 1 year were generalized through a modeling effort that examined the underlying processes governing the surface heat budget.…”