Journal cover Journal topic
The Cryosphere An interactive open-access journal of the European Geosciences Union
doi:10.5194/tc-2017-73
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
26 Apr 2017
Review status
This discussion paper is under review for the journal The Cryosphere (TC).
Quantifying bioalbedo: A new physically-based model and critique of empirical methods for characterizing biological influence on ice and snow albedo
Joseph M Cook1,2, Andrew J Hodson1,3, Alex S Gardner4, Mark Flanner5, Andrew J Tedstone6, Christopher Williamson6, Tristram DL Irvine-Fynn7, Johan Nilsson4, Robert Bryant1, and Martyn Tranter6 1Department of Geography, University of Sheffield, Winter Street, Sheffield, UK
2College of Life and Natural Sciences, University of Derby, Kedleston Road, Derby, UK
3University Centre in Svalbard (UNIS), Svalbard, Norway
4Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA
5Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor MI 48105, USA
6Centre for Glaciology, University of Bristol, Bristol, UK
7Centre for Glaciology, Aberystwyth University, Aberystwyth, Wales
Abstract. The darkening effects of biological impurities on ice and snow have been recognized as a significant control on the surface energy balance of terrestrial snow, sea ice, glaciers and ice sheets. With a heightened interest in understanding the impacts of a changing climate on snow and ice processes, quantifying the impact of biological impurities on ice and snow albedo ("bioalbedo") and its evolution through time is a rapidly growing field of research. However, rigorous quantification of bioalbedo has remained elusive because of difficulties isolating the biological contribution to ice albedo from that of inorganic impurities and the variable optical properties of the ice itself. For this reason, isolation of the biological signature in reflectance data obtained from aerial/orbital platforms has not been achieved, even when ground-based biological measurements have been available. This paper provides the cell specific optical properties that are required to model the spectral signatures and broadband darkening of ice. Applying radiative transfer theory, these properties provide the physical basis needed to link biological and glaciological ground measurements with remotely sensed reflectance data. Using these new capabilities we confirm that biological impurities can influence ice albedo then identify ten challenges to the measurement of bioalbedo in the field with the aim of improving future experimental designs to better quantify bioalbedo feedbacks. These challenges are: 1) Ambiguity in terminology, 2) Characterizing snow or ice optical properties, 3) Characterizing solar irradiance, 4) Determining optical properties of cells, 5) Measuring biomass, 6) Characterizing vertical distribution of cells, 7) Characterizing abiotic impurities, 8) Surface anisotropy, 9) Measuring indirect albedo feedbacks, and 10) Measurement and instrument configurations.

Citation: Cook, J. M., Hodson, A. J., Gardner, A. S., Flanner, M., Tedstone, A. J., Williamson, C., Irvine-Fynn, T. D., Nilsson, J., Bryant, R., and Tranter, M.: Quantifying bioalbedo: A new physically-based model and critique of empirical methods for characterizing biological influence on ice and snow albedo, The Cryosphere Discuss., doi:10.5194/tc-2017-73, in review, 2017.
Joseph M Cook et al.
Joseph M Cook et al.
Joseph M Cook et al.

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Short summary
Biological growth darkens snow and ice, causing it to melt faster. This process is often referred to as "bioalbedo". Quantifying bioalbedo has not been achieved because of difficulties isolating the biological contribution from the optical properties of ice and snow, and from inorganic impurities in field studies. In this paper, we provide a physical model that enables bioalbedo to be quantified from first principles and we use it to guide future field studies.
Biological growth darkens snow and ice, causing it to melt faster. This process is often...
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