C011-0006
The Effects of Bubbles and Biotic Impurities on Snow and Ice Radiative Transfer Properties

Tuesday, 8 December 2020
Poster
Chloe Whicker1, Mark Flanner1, Cheng Dang2, Joseph M. Cook3, Christopher Williamson4, Adam Schneider5 and Charles S Zender6, (1)University of Michigan, Department of Climate and Space Sciences and Engineering, Ann Arbor, MI, United States, (2)Joint Center for Satellite Data Assimilation, University Corporation for Atmospheric Research, Boulder, CO, United States, (3)Aberystwyth University, Institute of Biological, Rural and Environmental Sciences,Penglais Campus, Aberystwyth, United Kingdom, (4)University of Bristol, School of Geographical Sciences, Bristol, United Kingdom, (5)University of California Irvine, Department of Earth System Science, Irvine, CA, United States, (6)Univ California Irvine, Department of Earth System Science, Irvine, CA, United States
Abstract:
The Greenland Ice Sheet (GrIS) has been losing mass rapidly over the past few decades, mostly due to increasing surface melt. Surface melt is strongly influenced by the albedo of the ice sheet surface. The albedo declines naturally with increased temperatures and reduced solar zenith angles in the spring and summer as the snow ages and melts to expose the dark bare ice beneath the winter snow. Light absorbing impurities, such as darkly pigmented algae, within the snow and ice also reduce the albedo. Snow and ice algae absorb solar radiation and cause substantial surface melt. However, radiative transfer models have not yet been adequately adapted to represent the physical radiative properties of bare ice and light absorption by ice algae. This work uses physical properties of ice, snow, and cryospheric algae to expand the offline SNow ICe and Aerosol Radiative - Adding Doubling (SNICAR-AD) model to more accurately represent the albedo of snow and ice surfaces. Our updated model allows us to quantify the contributions from cryospheric algae to changes in albedo on snow and ice surfaces and will in turn increase our ability to accurately model GrIS melt. We will show a preliminary evaluation of the SNICAR-AD biologically enabled model over a range of bare ice conditions, including varying bubble concentrations, surface scattering layer thicknesses, and algal concentrations.