Estimating sea ice albedo feedback in a regional climate modeling sensitivity experiment

Abstract

Surface albedo feedback (SAF), or sea ice albedo feedback over the Arctic Ocean, has an important effect on the Arctic climate, even though it is not the leading contributor to polar amplification. Previous model-based studies on SAF have primarily used global climate models to exploit their global coverage and favorable configurations. This study verified the capability of using regional climate models (RCMs) to investigate SAF by designing a sensitivity experiment in terms of sea ice coverage. This study modeled two control cases of the years 1980 and 2012, as well as two sensitivity cases performed by switching the sea ice coverages in the control cases. The results proved the Weather Research and Forecast model capable of separating and quantifying the respective contributions of the atmosphere and the surface albedo to the surface radiation budget. Supported by the ALL/CLR model, the balanced surface shortwave radiation absorption was used to calculate SAF. The experiments overestimated SAF, largely because of the canceled cloud effect during model initialization. This study highlights a new possibility of designing experiments for studying climatic sensitivity and feedback using RCMs. Citation: Lian Y, Li Y S, Cai L. Estimating sea ice albedo feedback in a regional climate modeling sensitivity experiment. Adv Polar Sci, 2016, 27: 264-271, doi: 10.13679/j.advps.2016.4.00264