30 Nov 2021

30 Nov 2021

Review status: this preprint is currently under review for the journal TC.

Review article: Parameterizations of snow-related physical processes in land surface models

Won Young Lee1,3, Hyeon-Ju Gim2, and Seon Ki Park1,3,4 Won Young Lee et al.
  • 1Severe Storm Research Center, Ewha Womans University, Seoul, Republic of Korea
  • 2Korea Institute of Atmospheric Prediction Systems, Seoul, Republic of Korea
  • 3Center for Climate/Environment Change Prediction Research (CCCPR), EwhaWomans University, Seoul, Republic of Korea
  • 4Dept. of Climate Energy Systems Eng., Ewha Womans University, Seoul, Republic of Korea

Abstract. Snow on land surface plays a vital role in the interaction between land and atmosphere in the state-of-the-art land surface models (LSMs) and the real world. Since the snow cover affects the snow albedo and the ground and soil heat fluxes, it is crucial to detect snow cover changes accurately. It is challenging to acquire observation data for snow cover, snow albedo, and snow depth; thus, an excellent alternative is to use the simulation data produced by the LSMs that calculate the snow-related physical processes. The LSMs show significant differences in the complexities of the snow parameterizations in terms of variables and processes considered. Thus, the synthetic intercomparisons of the snow physics in the LSMs will help the improvement of each LSM. This study revealed and discussed the differences in the parameterizations among LSMs related to snow cover fraction, snow albedo, and snow density. We selected the most popular and well-documented LSMs embedded in the Earth System Model or operational forecasting systems. We examined single layer schemes, including the Unified Noah Land Surface Model (Noah LSM), the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL), the Biosphere-Atmosphere Transfer Scheme (BATS), the Canadian Land Surface Scheme (CLASS), and multilayer schemes of intermediate complexity including the Community Noah Land Surface Model with Multi-Parameterization Options (Noah-MP), the Community Land Model version 5 (CLM 5), the Joint UK Land Environment Simulator (JULES), and the Interaction Soil-Biosphere-Atmosphere (ISBA). First, we identified that BATS, Noah-MP, JULES, and ISBA reflect the snow depth and roughness length to parameterize snow cover fraction, and CLM 5 accounts for the standard deviation of the elevation value for the snow cover decay function. Second, CLM 5 and BATS are relatively complex, so that they explicitly take into account the solar zenith angle, black carbon, mineral dust, organic carbon, and ice grain size for the determinations of snow albedo. Besides, JULES and ISBA are also complicated model which concerns ice grain size, solar zenith angle, new snow depth, fresh snowfall rate, and surface temperature for the albedo scheme. Third, HTESSEL, CLM 5, and ISBA considered the effects of both wind and temperature in the determinations of the new snow density. Especially, ISBA and JULES considered internal snow characteristics such as snow viscosity, snow temperature, and vertical stress for parameterizing new snow density. The future outlook discussed geomorphic and vegetation-related variables for the further improvement of the LSMs. Previous studies clearly show that spatio-temporal variation of snow is due to the influence of altitude, slope, and vegetation condition. Therefore, we recommended applying geomorphic and vegetation factors such as elevation, slope, time-varying roughness length, vegetation indexes, or optimized parameters according to the land surface type to parameterize snow-related physical processes.

Won Young Lee et al.

Status: open (until 25 Jan 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2021-319', Anonymous Referee #1, 05 Jan 2022 reply

Won Young Lee et al.

Won Young Lee et al.


Total article views: 403 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
297 102 4 403 5 2
  • HTML: 297
  • PDF: 102
  • XML: 4
  • Total: 403
  • BibTeX: 5
  • EndNote: 2
Views and downloads (calculated since 30 Nov 2021)
Cumulative views and downloads (calculated since 30 Nov 2021)

Viewed (geographical distribution)

Total article views: 397 (including HTML, PDF, and XML) Thereof 397 with geography defined and 0 with unknown origin.
Country # Views %
  • 1


Latest update: 16 Jan 2022
Short summary
Snow cover or snow albedo plays a vital role in the atmosphere and land surface interaction. Especially, direct observation of snow is difficult and scarce. That's why a reliable Land Surface Model (LSM), including snow physical processes, is significant. In this study, we tried to give meaningful insights for improving the LSM in the future by identifying the main variables or parameters used and examining the different formulas for snow-related processes of the eight LSMs.