DOI: 10.5194/tc-14-1651-2020
论文题名: Snow albedo sensitivity to macroscopic surface roughness using a new ray-tracing model
作者: Larue F. ; Picard G. ; Arnaud L. ; Ollivier I. ; Delcourt C. ; Lamare M. ; Tuzet F. ; Revuelto J. ; Dumont M.
刊名: Cryosphere
ISSN: 19940416
出版年: 2020
卷: 14, 期: 5 起始页码: 1651
结束页码: 1672
语种: 英语
英文关键词: albedo
; energy budget
; estimation method
; Monte Carlo analysis
; numerical model
; ray tracing
; shortwave radiation
; snowpack
; surface energy
; surface roughness
英文摘要: Most models simulating snow albedo assume a flat and smooth surface, neglecting surface roughness. However, the presence of macroscopic roughness leads to a systematic decrease in albedo due to two effects: (1) photons are trapped in concavities (multiple reflection effect) and (2) when the sun is low, the roughness sides facing the sun experience an overall decrease in the local incidence angle relative to a smooth surface, promoting higher absorption, whilst the other sides have weak contributions because of the increased incidence angle or because they are shadowed (called the effective-angle effect here). This paper aims to quantify the impact of surface roughness on albedo and to assess the respective role of these two effects, with (1) observations over varying amounts of surface roughness and (2) simulations using the new rough surface ray-tracing (RSRT) model, based on a Monte Carlo method for photon transport calculation. The observations include spectral albedo (400-1050 nm) over manually created roughness surfaces with multiple geometrical characteristics. Measurements highlight that even a low fraction of surface roughness features (7 % of the surface) causes an albedo decrease of 0.02 at 1000 nm when the solar zenith angle (θ sĝˆ . For higher fractions (13 %, 27 % and 63 %), and when the roughness orientation is perpendicular to the sun, the decrease is of 0.03-0.04 at 700 nm and of 0.06-0.10 at 1000 nm. The impact is 20 % lower when roughness orientation is parallel to the sun. The observations are subsequently compared to RSRT simulations. Accounting for surface roughness improves the model observation agreement by a factor of 2 at 700 and 1000 nm (errors of 0.03 and 0.04, respectively) compared to simulations considering a flat smooth surface. The model is used to explore the albedo sensitivity to surface roughness with varying snow properties and illumination conditions. Both multiple reflections and the effective-angle effect have a greater impact with low specific surface area (SSA; <10 m2 kg-1 ). The effective-angle effect also increases rapidly with θ sθ s-2 ). This paper highlights the necessity of considering surface roughness in the estimation of the surface energy budget and opens the way for considering natural rough surfaces in snow modelling. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/164513
Appears in Collections: 气候变化与战略
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作者单位: Univ. Grenoble Alpes, CNRS, Institut des Géosciences de l'Environnement (IGE), UMR 5001, Grenoble, 38041, France; Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Etudes de la Neige, Grenoble, 38000, France
Recommended Citation:
Larue F.,Picard G.,Arnaud L.,et al. Snow albedo sensitivity to macroscopic surface roughness using a new ray-tracing model[J]. Cryosphere,2020-01-01,14(5)