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The Cryosphere An interactive open-access journal of the European Geosciences Union
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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 10 Jan 2020

Submitted as: research article | 10 Jan 2020

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This discussion paper is a preprint. It is a manuscript under review for the journal The Cryosphere (TC).

Spectral albedo measurements over snow-covered slopes: theory and slope effect corrections

Ghislain Picard1, Marie Dumont2, Maxim Lamare1,2, François Tuzet1,2, Fanny Larue1, Roberta Pirazzini3, and Laurent Arnaud1 Ghislain Picard et al.
  • 1Univ. Grenoble Alpes, CNRS, Institut des Géosciences de l’Environnement (IGE), UMR 5001, Grenoble, 38041, France
  • 2Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d’Etudes de la Neige, 38000 Grenoble, France
  • 3Finnish Meteorological Institute, Helsinki, Finland

Abstract. Surface albedo is an essential variable to determine the Earth's surface energy budget, in particular for snow-covered areas where it is involved in one of the most powerful positive feedback loops of the climate system. Measurements of broadband albedo are therefore common in meteorology. Measurements of spectral albedo are less frequent but provide richer information, useful to understand the physical and chemical properties driving albedo variations. Both types of measurements are subject to several artefacts. Here we investigate the sensitivity of spectral albedo measurements to surface slope, and propose simple correction algorithms to retrieve the intrinsic albedo of a slope from measurements, as if it were flat. For this, we first derive the analytical equations relating albedo measured on a slope to intrinsic direct and diffuse albedo, the apportionment between diffuse and direct incoming radiation, and slope inclination and aspect. The theory accounts for two main slope effects. First, the slope affects the proportion of solar radiation intercepted by the surface relative to that intercepted by the upward-looking, horizontal, sensor. Second, the upward and downward looking sensors receive reduced radiation from the sky and the surface respectively, and increased radiation from neighbouring terrain. Using this theory, we show that i) slope has a significant effect on albedo (over 0.01) from as little as a ≈ 1° inclination, causing distortions of the albedo spectral shape, ii) the first order slope effect is sufficient to fully explain measured albedo up to ≈ 15°, which we designate as small slope approximation, and iii) for larger slopes, the theory depends on the neighbouring slope geometry and land cover, leading to much more complex equations. Next, we derive four correction methods from the small slope approximation, to be used depending on whether 1) the slope inclination and orientation are known or not, 2) the snow surface is free of impurities or dirty and 3) a single or a time-series of albedo measurements is available. The methods applied to observations taken in the Alps on terrain with up to nearly 20° slopes, prove the ability to recover intrinsic albedo with a typical accuracy of 0.03 or better. From this study, we draw two main recommendations for future field campaigns: first, sloping terrain requires more attention because it reduces the measurement accuracy of albedo even for barely invisible slopes (1–2°). Second, while the correction of the slope effect is possible, it requires additional information such as the spectral diffuse and direction apportionment, and if possible the actual slope inclination and aspect especially when the absence of impurities can not be assumed.

Ghislain Picard et al.
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Ghislain Picard et al.
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Short summary
Surface albedo is an essential variable of snow covered areas. The measurement of this variable over a sloped terrain with leveled sensors is affected by artefacts that need to be corrected. Here we develop a theory of spectral albedo measurement over slopes from which we derive four correction algorithms. The comparison to in-situ measurements taken in the Alps shows the adequacy of the theory and the application of the algorithms show systematic improvements.
Surface albedo is an essential variable of snow covered areas. The measurement of this variable...