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| Titel |
Implementation and evaluation of prognostic representations of the optical diameter of snow in the SURFEX/ISBA-Crocus detailed snowpack model |
| VerfasserIn |
C. M. Carmagnola, S. Morin, M. Lafaysse, F. Domine, B. Lesaffre, Y. Lejeune, G. Picard, L. Arnaud |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1994-0416
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| Digitales Dokument |
URL |
| Erschienen |
In: The Cryosphere ; 8, no. 2 ; Nr. 8, no. 2 (2014-03-17), S.417-437 |
| Datensatznummer |
250116077
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| Publikation (Nr.) |
 copernicus.org/tc-8-417-2014.pdf |
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| Zusammenfassung |
| In the SURFEX/ISBA-Crocus
multi-layer snowpack model, the snow microstructure has up to now been
characterised by the grain size and by semi-empirical shape variables which
cannot be measured easily in the field or linked to other relevant snow
properties. In this work we introduce a new formulation of snow metamorphism
directly based on equations describing the rate of change of the optical
diameter (dopt). This variable is considered here to be equal to
the equivalent sphere optical diameter, which is inversely proportional to
the specific surface area (SSA). dopt thus represents
quantitatively some of the geometric characteristics of a porous medium.
Different prognostic rate equations of dopt, including a
re-formulation of the original Crocus scheme and the parameterisations from
Taillandier et al. (2007) and Flanner and Zender (2006), were evaluated by comparing
their predictions to field measurements carried out at Summit Camp
(Greenland) in May and June 2011 and at Col de Porte (French Alps) during the
2009/10 and 2011/12 winter seasons. We focused especially on results in terms
of SSA. In addition, we tested the impact of the different formulations on
the simulated density profile, the total snow height, the snow water
equivalent (SWE) and the surface albedo. Results indicate that all
formulations perform well, with median values of the RMSD between measured
and simulated SSA lower than 10 m2 kg−1. Incorporating the optical
diameter as a fully fledged prognostic variable is an important step forward
in the quantitative description of the snow microstructure within snowpack
models, because it opens the way to data assimilation of various
electromagnetic observations. |
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