Comparison of methods for area‐averaging surface energy fluxes over heterogeneous land surfaces using high‐resolution non‐hydrostatic simulations

The quantification of subgrid land surface heterogeneity effects on the scale of climate and numerical weather prediction models is of vital interest for the energy budget of the atmospheric boundary layer and for the atmospheric branch of the hydrological cycle. This paper focuses on heterogeneity effects for the exchange processes between land surfaces and the atmosphere. The results are based on high-resolution non-hydrostatic model simulations for the LITFASS area near Berlin. This area represents a highly heterogeneous landscape of 20 × 20 km 2 around the Meteorological Observatory Lindenberg of the German Weather Service (DWD). Model simulations were carried out using the non-hydrostatic model FOOT3DK of the University of K¨ oln with resolutions of 1 km and 250 m. The performance of different area-averaging methods for the turbulent surface fluxes was tested for the LITFASS area, namely the aggregation, mosaic and tile methods. For one tile method (station-tile), the experimental setup of the surface energy balance stations of the LITFASS98 experiment was investigated. Two different simulation types are considered: (1) realistic topography and idealized synoptic forcing; (2) realistic topography and realistic synoptic forcing for LITFASS98 cases. A double one-way nesting procedure is used for nesting FOOT3DK in ‘Lokalmodell’ of the DWD. The mosaic method shows good results, if the wind speed is sufficiently high. During weak-wind convective conditions, errors are particularly large for the latent heat flux on the 20 × 20 km 2 scale. The aggregation method yields generally higher errors than the mosaic method, which even increase for higher wind speeds. The main reason is the strong surface heterogeneity associated with the lakes and forests in the LITFASS area. The main uncertainty of the station-tile method is the knowledge of the area coverage in combination with the representativity of the stations for the land-use type and surface conditions. The results of this study lead to the recommendation to use a mosaic approach or at least a tile approach for downscaling fluxes over heterogeneous surfaces in mesoscale and regional climate models. Copyright  2005 Royal Meteorological Society.

[1]  H. Davies,et al.  A lateral boundary formulation for multi-level prediction models. [numerical weather forecasting , 1976 .

[2]  D. Verseghy,et al.  Modelling evapotranspiration at three boreal forest stands using the CLASS: tests of parameterizations for canopy conductance and soil evaporation , 2003 .

[3]  A. Arola.  Parameterization of Turbulent and Mesoscale Fluxes for Heterogeneous Surfaces , 1999 .

[4]  Roni Avissar,et al.  Using Similarity Theory to Parameterize Mesoscale Heat Fluxes Generated by Subgrid-Scale Landscape Discontinuities in GCMs , 1995 .

[5]  Bruno Monteny,et al.  Effective parameters of surface energy balance in heterogeneous landscape , 1994 .

[6]  Jielun Sun,et al.  Dependence of surface exchange coefficients on averaging scale and grid size , 1995 .

[7]  A. Hense,et al.  An economical method for computing the radiative energy transfer in circulation models , 1982 .

[8]  Yaping Shao,et al.  Effects of land-surface heterogeneity upon surface fluxes and turbulent conditions , 2001 .

[9]  A. Perrier,et al.  HAPEX—MOBLIHY: A Hydrologic Atmospheric Experiment for the Study of Water Budget and Evaporation Flux at the Climatic Scale , 1986 .

[10]  F. Beyrich,et al.  The LITFASS project of DWD and the LITFASS-98 experiment: The project strategy and the experimental setup , 2002 .

[11]  S. Planton,et al.  A Simple Parameterization of Land Surface Processes for Meteorological Models , 1989 .

[12]  Roni Avissar,et al.  An Evaluation of the Scale at which Ground-Surface Heat Flux Patchiness Affects the Convective Boundary Layer Using Large-Eddy Simulations , 1998 .

[13]  E. Batchvarova,et al.  Experimental determination of turbulent fluxes over the heterogeneous LITFASS area: Selected results from the LITFASS-98 experiment , 2002 .

[14]  H. Charnock.  Wind stress on a water surface , 1955 .

[15]  Larry Mahrt,et al.  The bulk aerodynamic formulation over heterogeneous surfaces , 1996 .

[16]  Roger A. Pielke,et al.  A parameterization of heterogeneous land surfaces for atmospheric numerical models and its impact on regional meteorology , 1989 .

[17]  P. J. Mason,et al.  The formation of areally‐averaged roughness lengths , 1988 .

[18]  R. Pielke.  A Comparison of Three-Dimensional and Two-Dimensional Numerical Predictions of Sea Breezes , 1974 .

[19]  C. Duncan.  A numerical investigation of polar lows , 1977 .

[20]  G. Heinemann.  Forcing and feedback mechanisms between the katabatic wind and sea ice in the coastal areas of polar ice sheets , 2003 .

[21]  Armin Raabe,et al.  Numerical Investigations on the Influence of Subgrid-Scale Surface Heterogeneity on Evapotranspiration and Cloud Processes , 1996 .

[22]  J. Deardorff.  A Parameterization of Ground-Surface Moisture Content for Use in Atmospheric Prediction Models , 1977 .

[23]  G. Mellor,et al.  Development of a turbulence closure model for geophysical fluid problems , 1982 .

[24]  Roni Avissar,et al.  Representation of heterogeneity effects in Earth system modeling: Experience from land surface modeling , 1997 .

[25]  Siegfried Raasch,et al.  An Analysis Of Secondary Circulations And Their Effects Caused By Small-Scale Surface Inhomogeneities Using Large-Eddy Simulation , 2001 .

[26]  J. Louis.  A parametric model of vertical eddy fluxes in the atmosphere , 1979 .

[27]  G. Hornberger,et al.  Empirical equations for some soil hydraulic properties , 1978 .