Improving modeled snow albedo estimates during the spring melt season

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Abstract

Snow albedo influences snow‐covered land energy and water budgets and is thus an important variable for energy and water fluxes calculations. Here, we quantify the performance of the three existing snow albedo parameterizations under alpine, tundra, and prairie snow conditions when implemented in the Noah land surface model (LSM)—Noah's default and ones from the Biosphere‐Atmosphere Transfer Scheme (BATS) and the Canadian Land Surface Scheme (CLASS) LSMs. The Noah LSM is forced with and its output is evaluated using in situ measurements from seven sites in U.S. and France. Comparison of the snow albedo simulations with the in situ measurements reveals that the three parameterizations overestimate snow albedo during springtime. An alternative snow albedo parameterization is introduced that adopts the shape of the variogram for the optically thick snowpacks and decreases the albedo further for optically thin conditions by mixing the snow with the land surface (background) albedo as a function of snow depth. In comparison with the in situ measurements, the new parameterization improves albedo simulation of the alpine and tundra snowpacks and positively impacts the simulation of snow depth, snowmelt rate, and upward shortwave radiation. An improved model performance with the variogram‐shaped parameterization can, however, not be unambiguously detected for prairie snowpacks, which may be attributed to uncertainties associated with the simulation of snow density. An assessment of the model performance for the Upper Colorado River Basin highlights that with the variogram‐shaped parameterization Noah simulates more evapotranspiration and larger runoff peaks in Spring, whereas the Summer runoff is lower.
Original languageEnglish
Pages (from-to)7311-7331
Number of pages21
JournalJournal of geophysical research : Atmospheres
Volume119
Issue number12
DOIs
Publication statusPublished - 20 Aug 2014

Keywords

  • METIS-304669
  • ITC-ISI-JOURNAL-ARTICLE
  • ITC-HYBRID

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