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contributor authorSaito, Masanori
contributor authorYang, Ping
contributor authorLoeb, Norman G.
contributor authorKato, Seiji
date accessioned2019-10-05T06:51:48Z
date available2019-10-05T06:51:48Z
date copyright3/13/2019 12:00:00 AM
date issued2019
identifier otherJAS-D-18-0308.1.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4263659
description abstractAbstractSnow albedo plays a critical role in the surface energy budget in snow-covered regions and is subject to large uncertainty due to variable physical and optical characteristics of snow. We develop an optically and microphysically consistent snow grain habit mixture (SGHM) model, aiming at an improved representation of bulk snow properties in conjunction with considering the particle size distribution, particle shape, and internally mixed black carbon (BC). Spectral snow albedos computed with two snow layers with the SGHM model implemented in an adding?doubling radiative transfer model agree with observations. Top-snow-layer optical properties essentially determine spectral snow albedo when the top-layer snow water equivalent (SWE) is large. When the top-layer SWE is less than 1 mm, the second-snow-layer optical properties have nonnegligible impacts on the albedo of the snow surface. Snow albedo enhancement with increasing solar zenith angle (SZA) largely depends on snow particle effective radius and also internally mixed BC. Based on the SGHM model and various sensitivity studies, single- and two-layer snow albedos are parameterized for six spectral bands used in NASA Langley Research Center?s modified Fu?Liou broadband radiative transfer model. Parameterized albedo is expressed as a function of snow particle effective radii of the two layers, SWE in the top layer, internally mixed BC mass fraction in both layers, and SZA. Both single-layer and two-layer parameterizations provide band-mean snow albedo consistent with rigorous calculations, achieving correlation coefficients close to 0.99 for all bands.
publisherAmerican Meteorological Society
titleA Novel Parameterization of Snow Albedo Based on a Two-Layer Snow Model with a Mixture of Grain Habits
typeJournal Paper
journal volume76
journal issue5
journal titleJournal of the Atmospheric Sciences
identifier doi10.1175/JAS-D-18-0308.1
journal fristpage1419
journal lastpage1436
treeJournal of the Atmospheric Sciences:;2019:;volume 076:;issue 005
contenttypeFulltext


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