Evaluating biases in simulated snow albedo feedback in two generations of climate models

Abstract

AbstractThis study presents a comprehensive evaluation of snow albedo feedback (SAF) in two generations of climate models (Coupled Model Intercomparison Project versions 3 (CMIP3) and 5 (CMIP5)). A comparison of the models is performed against a multiobservation‐based reference data set (mOBS) derived from the seasonal cycle of albedo, snow cover, and temperature. The observed total SAF shows low uncertainty and is generally well simulated by the CMIP3 and CMIP5 ensemble mean, except for a low (high) bias over the Arctic (northern boreal forest). Most CMIP5 models overestimate the snow cover component of SAF (SNC) and underestimate the temperature sensitivity component (TEM). The high bias in SNC is due to simulated snow albedos 4–5% brighter than observed driving unrealistically large albedo contrasts. However, overall representation of surface albedo—and mean climate—has improved, as fewer CMIP5 models exhibit large cold temperature, or high snow, biases. The low bias in TEM is related to overly persistent snow albedo during spring, particularly over southern Eurasia and North America. There is large observational uncertainty in the reference data set mOBS that is traced primarily to the different snow cover products, with a secondary contribution from the albedo products and a small contribution from the temperature products. The conclusion is that the model mean tends to simulate the multiobservation mean very closely; however, this masks considerable spread in both models and observations. There is clear motivation for producing improved submonthly snow cover products for the purpose of model evaluation.