Using models and satellite observations to evaluate the strength of snow albedo feedback

Snow albedo feedback (SAF) is important for global climate change, with strong regional impacts over northern continental areas. SAF calculated from the seasonal cycle is a good predictor of SAF in climate change among a suite of coupled climate models. A previous linear decomposition of the simulated total SAF (NET) found 80% was related to the albedo contrast of snow covered and snow-free land (SNC), and 20% was related to the temperature dependence of snow albedo (TEM). By contrast, recent work using snow cover and surface albedo derived from APP-x satellite observations found that TEM and SNC contributed almost equally to NET. In the present study, revised estimates of TEM and SNC for northern land areas are calculated for the period 1982-99 using a simplified and reproducible method for comparing SAF in models and observations. The observed NET is -1.11% K-1, of which 69% comes from SNC and 31% from TEM; the approximate additivity of SNC and TEM indicates that these two terms fully explain the total SAF. Regionally, the SNC term dominates equatorward of 65 degrees N, while TEM dominates over the Arctic. The mean of 17 CMIP3 climate models shows NET is 7% larger than observed, caused primarily by a bias in TEM equatorward of 65 degrees N. A newer model (NCAR CCSM4) with improved land surface and snow schemes reproduces observed values of NET and SNC closely. However, TEM in all models examined is 50-100% weaker than observed over the Arctic. There is a strong correlation between SAF in the seasonal cycle and SAF in climate change for all components, but the correlation is weakest for TEM. The TEM term also exhibits a much larger spread in the seasonal cycle than in climate change, which partially explains a discrepancy between previous published studies examining TEM.