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Geosci. Model Dev., 9, 1073-1085, 2016
https://doi.org/10.5194/gmd-9-1073-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Development and technical paper
17 Mar 2016
Parameterization of the snow-covered surface albedo in the Noah-MP Version 1.0 by implementing vegetation effects
Sojung Park1,3,4 and Seon Ki Park1,2,3,4 1Department of Atmospheric Science and Engineering, Ewha Womans University, Seoul, Republic of Korea
2Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Republic of Korea
3Center for Climate/Environment Change Prediction Research, Ewha Womans University, Seoul, Republic of Korea
4Severe Storm Research Center, Ewha Womans University, Seoul, Republic of Korea
Abstract. Snow-covered surface albedo varies depending on many factors, including snow grain size, snow cover thickness, snow age, forest shading factor, etc., and its parameterization is still under great uncertainty. For the snow-covered surface condition, albedo of forest is typically lower than that of short vegetation; thus snow albedo is dependent on the spatial distributions of characteristic land cover and on the canopy density and structure. In the Noah land surface model with multiple physics options (Noah-MP), almost all vegetation types in East Asia during winter have the minimum values of leaf area index (LAI) and stem area index (SAI), which are too low and do not consider the vegetation types. Because LAI and SAI are represented in terms of photosynthetic activeness, stem and trunk in winter are not well represented with only these parameters. We found that such inadequate representation of the vegetation effect is mainly responsible for the large positive bias in calculating the winter surface albedo in the Noah-MP. In this study, we investigated the vegetation effect on the snow-covered surface albedo from observations and improved the model performance by implementing a new parameterization scheme. We developed new parameters, called leaf index (LI) and stem index (SI), which properly manage the effect of vegetation structure on the snow-covered surface albedo. As a result, the Noah-MP's performance in the winter surface albedo has significantly improved – the root mean square error is reduced by approximately 69 %.

Citation: Park, S. and Park, S. K.: Parameterization of the snow-covered surface albedo in the Noah-MP Version 1.0 by implementing vegetation effects, Geosci. Model Dev., 9, 1073-1085, https://doi.org/10.5194/gmd-9-1073-2016, 2016.
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Short summary
Snow albedo varies with snow grain size, snow cover thickness, etc. It also depends on the spatial characteristics of land cover and on the canopy density and structure. The Noah-MP model shows a bias error of albedo in winter due to no proper reflection of the vegetation effect. We developed new parameters, called leaf index and stem index, which reflect the vegetation effect on winter albedo. The Noah-MP's performance in albedo has prominently improved with about 69 % decrease in the RMSE.
Snow albedo varies with snow grain size, snow cover thickness, etc. It also depends on the...
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