Boundary-Layer Meteorology

, Volume 85, Issue 3, pp 391–421

Impact of Atmospheric Surface-layer Parameterizations in the new Land-surface Scheme of the NCEP Mesoscale Eta Model


  • Fei Chen
    • Environmental Modeling Center, NCEP(NWS/NOAA)
  • Zavisă Janjić
    • Environmental Modeling Center, NCEP(NWS/NOAA)
  • Kenneth Mitchell
    • Environmental Modeling Center, NCEP(NWS/NOAA)

DOI: 10.1023/A:1000531001463

Cite this article as:
Chen, F., Janjić, Z. & Mitchell, K. Boundary-Layer Meteorology (1997) 85: 391. doi:10.1023/A:1000531001463


We tested three atmospheric surface-layer parameterization schemes (Mellor-Yamadalevel 2, Paulson, and modified Louis), both ina 1-D mode in the new NCEP land-surface scheme against long-term FIFE and HAPEX observations, and in a coupled 3-D mode withthe NCEP mesoscale Eta model. The differences inthese three schemes and the resulting surface exchange coefficients do not, in general, lead to significant differences in model simulated surface fluxes, skin temperature, andprecipitation, provided the same treatment of roughness length for heat is employed.Rather, the model is more sensitive to the choice of the roughness length for heat. To assess the latter, we also tested two approaches to specifythe roughness length for heat: 1) assuming the roughness length for heat is a fixed ratio of the roughness length for momentum, and 2) relating this ratio to the roughness Reynolds number as proposed by Zilitinkevich.Our 1-D column model sensitivity tests suggested that the Zilitinkevich approach can improve the surface heat fluxand skin temperature simulations. A long-term test with the NCEP mesoscaleEta model indicated that this approach can also reduce forecast precipitation bias. Based on these simulations, in January 1996 we operationally implemented the Paulsonscheme with the new land-surface scheme of the NCEP Eta model, along with the Zilitinkevich formulation to specify the roughness length for heat.

Surface-layer parameterizationLand-surface processRoughness length for heatSoil moisture simulationNumerical weather prediction

Copyright information

© Kluwer Academic Publishers 1997