Articles | Volume 14, issue 12
Geosci. Model Dev., 14, 7329–7343, 2021
https://doi.org/10.5194/gmd-14-7329-2021
Geosci. Model Dev., 14, 7329–7343, 2021
https://doi.org/10.5194/gmd-14-7329-2021
Development and technical paper
30 Nov 2021
Development and technical paper | 30 Nov 2021

A versatile method for computing optimized snow albedo from spectrally fixed radiative variables: VALHALLA v1.0

Florent Veillon et al.

Related authors

Brief communication: Reduction in the future Greenland ice sheet surface melt with the help of solar geoengineering
Xavier Fettweis, Stefan Hofer, Roland Séférian, Charles Amory, Alison Delhasse, Sébastien Doutreloup, Christoph Kittel, Charlotte Lang, Joris Van Bever, Florent Veillon, and Peter Irvine
The Cryosphere, 15, 3013–3019, https://doi.org/10.5194/tc-15-3013-2021,https://doi.org/10.5194/tc-15-3013-2021, 2021
Short summary

Related subject area

Cryosphere
Benchmarking the vertically integrated ice-sheet model IMAU-ICE (version 2.0)
Constantijn J. Berends, Heiko Goelzer, Thomas J. Reerink, Lennert B. Stap, and Roderik S. W. van de Wal
Geosci. Model Dev., 15, 5667–5688, https://doi.org/10.5194/gmd-15-5667-2022,https://doi.org/10.5194/gmd-15-5667-2022, 2022
Short summary
SnowClim v1.0: high-resolution snow model and data for the western United States
Abby C. Lute, John Abatzoglou, and Timothy Link
Geosci. Model Dev., 15, 5045–5071, https://doi.org/10.5194/gmd-15-5045-2022,https://doi.org/10.5194/gmd-15-5045-2022, 2022
Short summary
Snow Multidata Mapping and Modeling (S3M) 5.1: a distributed cryospheric model with dry and wet snow, data assimilation, glacier mass balance, and debris-driven melt
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Edoardo Cremonese, Umberto Morra di Cella, Sara Ratto, and Hervé Stevenin
Geosci. Model Dev., 15, 4853–4879, https://doi.org/10.5194/gmd-15-4853-2022,https://doi.org/10.5194/gmd-15-4853-2022, 2022
Short summary
MPAS-Seaice (v1.0.0): sea-ice dynamics on unstructured Voronoi meshes
Adrian K. Turner, William H. Lipscomb, Elizabeth C. Hunke, Douglas W. Jacobsen​​​​​​​, Nicole Jeffery, Darren Engwirda, Todd D. Ringler, and Jonathan D. Wolfe
Geosci. Model Dev., 15, 3721–3751, https://doi.org/10.5194/gmd-15-3721-2022,https://doi.org/10.5194/gmd-15-3721-2022, 2022
Short summary
Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography)
Noah D. Smith, Eleanor J. Burke, Kjetil Schanke Aas, Inge H. J. Althuizen, Julia Boike, Casper Tai Christiansen, Bernd Etzelmüller, Thomas Friborg, Hanna Lee, Heather Rumbold, Rachael H. Turton, Sebastian Westermann, and Sarah E. Chadburn
Geosci. Model Dev., 15, 3603–3639, https://doi.org/10.5194/gmd-15-3603-2022,https://doi.org/10.5194/gmd-15-3603-2022, 2022
Short summary

Cited articles

Bird, R. E. and Riordan, C.: Simple Solar Spectral Model for Direct and Diffuse Irradiance on Horizontal and Tilted Planes at the Earth's Surface for Cloudless Atmospheres, J. Appl. Meteorol. Clim., 25, 87–97, https://doi.org/10.1175/1520-0450(1986)025<0087:SSSMFD>2.0.CO;2, 1986. a
Cess, R. D., Potter, G. L., Zhang, M. H., Blanchet, J. P., Chalita, S., Colman, R., Dazlich, D. A., Genio, A. D. D., Dymnikov, V., Galin, V., Jerrett, D., Keup, E., Lacis, A. A., Le Treut, H., Liang, X. Z., Mahfouf, J. F., Mcavaney, B. J., Meleshko, V. P., Mitchell, J. F. B., Morcrette, J. J., Norris, P. M., Randall, D. A., Rikus, L., Roeckner, E., Royer, J. F., Schlese, U., Sheinin, D. A., Slingo, J. M., Sokolov, A. S., Taylor, K. E., Washington, W. M., Wetherald, R. T., and Yagai, I.: Interpretation of Snow-Climate Feedback as Produced by 17 General Circulation Models, Science, 253, 888–892, https://doi.org/10.1126/science.253.5022.888, 1991. a
Clough, S., Shephard, M., Mlawer, E., Delamere, J., Iacono, M., Cady-Pereira, K., Boukabara, S., and Brown, P.: Atmospheric radiative transfer modeling: a summary of the AER codes, J. Quant. Spectrosc. Ra., 91, 233–244, https://doi.org/10.1016/j.jqsrt.2004.05.058, 2005. a
Domine, F., Taillandier, A.-S., and Simpson, W. R.: A parameterization of the specific surface area of seasonal snow for field use and for models of snowpack evolution, J. Geophys. Res., 112, F02031, https://doi.org/10.1029/2006JF000512, 2007. a
Dumont, M., Brun, E., Picard, G., Michou, M., Libois, Q., Petit, J.-R., Geyer, M., Morin, S., and Josse, B.: Contribution of light-absorbing impurities in snow to Greenland’s darkening since 2009, Nat. Geosci., 7, 509–512, https://doi.org/10.1038/ngeo2180, 2014. a
Download
Short summary
In climate models, the snow albedo scheme generally calculates only a narrowband or broadband albedo. Therefore, we have developed the VALHALLA method to optimize snow spectral albedo calculations through the determination of spectrally fixed radiative variables. The development of VALHALLA v1.0 with the use of the snow albedo model TARTES and the spectral irradiance model SBDART indicates a considerable reduction in calculation time while maintaining an adequate accuracy of albedo values.