Disaggregation of screen-level variables in a numerical weather prediction model with an explicit simulation of sub-grid scale land-surface heterogeneity

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Title:Main Title: Disaggregation of screen-level variables in a numerical weather prediction model with an explicit simulation of sub-grid scale land-surface heterogeneity
Description:Abstract: The earth’s surface is characterized by smallscale heterogeneity attributable to variability in land cover, soil characteristics and orography. In atmospheric models, this small-scale variability can be partially accounted for by the so-called mosaic approach, i.e., by computing the landsurface processes on a grid with an explicit higher horizontal resolution than the atmosphere. The mosaic approach does, however, not account for the subgrid-scale variability in the screen-level atmospheric parameters, part of which might be related to land-surface heterogeneity itself. In this study, simulations with the numerical weather prediction model COSMO are shown, employing the mosaic approach together with a spatial disaggregation of the atmospheric forcing by the screen-level variables to the subgrid-scale. The atmospheric model is run with a 2.8 km horizontal grid resolution while the land surface processes are computed on a 400-m horizontal grid. The disaggregation of the driving atmospheric variables at screen-level is achieved by a threestep statistical downscaling with rules learnt from highresolution fully coupled COSMO simulations, where both, atmosphere and surface, were simulated on a 400-m grid. The steps encompass spline interpolation of the grid scale variables, conditional regression based on the high-resolution runs, and an optional stochastic noise generator which restores the variability of the downscaled variables. Simulations for a number of case studies have been carried out, with or without mosaic surface representation and with or without atmospheric disaggregation, and evaluated with respect to the surface state variables and the turbulent surface exchange fluxes of sensible and latent heat. The results are compared with the high-resolution fully coupled COSMO simulations. The results clearly demonstrate the high importance of accounting for subgrid-scale surface heterogeneity. It is shown that the atmospheric disaggregation leads to clear additional improvements in the structures of the two-dimensional surface state variable fields, but to only marginally impacts on the simulation of the turbulent surface exchange fluxes. A detailed analysis of these results identifies strongly correlated errors in atmospheric and surface variables in the mosaic approach as the main reason for the latter. The effects of these errors largely cancel out in the flux parameterization, and thus explain the comparably good results for the fluxes in the mosaic approach without atmospheric disaggregation despite inferior performance for the surface state variables themselves. Inserting noise in the disaggregation scheme leads to a deterioration of the results.
Identifier:10.1007/s00703-012-0183-y (DOI)
Responsible Party
Creators:Annika Schomburg (Author), Victor Venema (Author), Felix Ament (Author), Clemens Simmer (Author)
Publisher:Springer
Publication Year:2013
Topic
TR32 Topic:Atmosphere
Related Subproject:C4
Subjects:Keywords: Numerical Weather Prediction, COSMO, SVAT Modelling
File Details
Filename:2012_Schomburg_MAP.pdf
Data Type:Text - Article
Size:14 Pages
File Size:1 MB
Dates:Accepted: 23.02.2012
Issued: 15.03.2012
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
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Download Permission:Only Project Members
General Access and Use Conditions:For internal use only
Access Limitations:For internal use only
Licence:[TR32DB] Data policy agreement
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Specific Information - Publication
Publication Status:Published
Review Status:Peer reviewed
Publication Type:Article
Article Type:Journal
Source:Meteorology and Atmospheric Physics
Volume:116
Number of Pages:14 (81 - 94)
Metadata Details
Metadata Creator:Annika Schomburg
Metadata Created:03.12.2013
Metadata Last Updated:03.12.2013
Subproject:C4
Funding Phase:2
Metadata Language:English
Metadata Version:V50
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