Assessing Snow Albedo Feedback in Simulated Climate Change

Abstract

In this paper, the two factors controlling Northern Hemisphere springtime snow albedo feedback in transient climate change are isolated and quantified based on scenario runs of 17 climate models used in the Intergovernmental Panel on Climate Change Fourth Assessment Report. The first factor is the dependence of planetary albedo on surface albedo, representing the atmosphere's attenuation effect on surface albedo anomalies. It is potentially a major source of divergence in simulations of snow albedo feedback because of large differences in simulated cloud fields in Northern Hemisphere land areas. To calculate the dependence, an analytical model governing planetary albedo was developed. Detailed validations of the analytical model for two of the simulations are shown, version 3 of the Community Climate System Model (CCSM3) and the Geophysical Fluid Dynamics Laboratory global coupled Climate Model 2.0 (CM2.0), demonstrating that it facilitates a highly accurate calculation of the dependence of planetary albedo on surface albedo given readily available simulation output. In all simulations it is found that surface albedo anomalies are attenuated by approximately half in Northern Hemisphere land areas as they are transformed into planetary albedo anomalies. The intermodel standard deviation in the dependence of planetary albedo on surface albedo is surprisingly small, less than 10% of the mean. Moreover, when an observational estimate of this factor is calculated by applying the same method to the satellite-based International Satellite Cloud Climatology Project (ISCCP) data, it is found that most simulations agree with ISCCP values to within about 10%, despite further disagreements between observed and simulated cloud fields. This suggests that even large relative errors in simulated cloud fields do not result in significant error in this factor, enhancing confidence in climate models. The second factor, related exclusively to surface processes, is the change in surface albedo associated with an anthropogenically induced temperature change in Northern Hemisphere land areas. It exhibits much more intermodel variability. The standard deviation is about 1 ⁄3 of the mean, with the largest value being approximately 3 times larger than the smallest. Therefore this factor is unquestionably the main source of the large divergence in simulations of snow albedo feedback. To reduce the divergence, attention should be focused on differing parameterizations of snow processes, rather than intermodel variations in the attenuation effect of the atmosphere on surface albedo anomalies.

The Changing Face of Arctic Snow Cover: A Synthesis of Observed and Projected Changes

“…Also, Fernandes et al (2009) noted that the CMIP3 models do not properly capture the spatial and temporal characteristics of Northern Hemisphere snow temperature sensitive regions documented by Groisman et al (1994a). Inadequate representation of snow-albedo feedbacks may be contributing to this, as previously noted by Qu and Hall (2006).…”

Sensitivity of the regional European boreal climate to changes in surface properties resulting from structural vegetation perturbations

“…However, the parameterization of snow albedo in relation to high-latitude vegetation has been pointed out as a source of uncertainty in high-latitude climate modeling (e.g., Qu and Hall, 2006;Loranty et al, 2014). Loranty et al (2014) found that on average the CMIP5 model tree cover and albedo do not correlate well.…”

Sensitivity studies on the impacts of Tibetan Plateau snowpack pollution on the Asian hydrological cycle and monsoon climate

“…The 2007 IPCC report listed the radiative forcing induced by "soot on snow" as one of the important anthropogenic forcings affecting climate change. It is important to understand the control of snow cover evolution because most of the interannual variability in mid-and high-latitude planetary albedo is caused by changes in snow and sea-ice cover (Qu and Hall, 2006). Modeling studies have shown that the long-term average of snow accumulation or melt patterns may significantly alter global and regional climate and have a strong impact upon the general circulation and hydrological cycle (e.g., Barnett et al, 1988;Qian et al, 2009a).…”