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External Data

The information about climatologically constant data from the external data set are one source of information needed to create forcing data for COSMO-CLM. EXTPAR (External Parameter for Numerical Weather Prediction and Climate Application) is the main program for preparing the external data set. The interactive web frontend  WebPEP (Web interface for Preprocessing External data Parameters) is available for generation the external parameter files with EXTPAR.

Please be aware, that the size of the domain of the external data must be larger then the size of the actual COSMO-CLM domain. At least two additional rows of grid points at each of the four sides of the domain are required. It is recommended to chose the domain of the external data set rather large, so that it is possible to change the size of the COSMO-CLM domain, with shifts of start_lon and start_lat, etc. without creating new external data sets.

EXTPAR

See also the documentation in RedC: EXTPAR

Numerical Weather Prediction (NWP) models and Climate models require geographical datasets like the orographic height of the earth surface, the plant cover, the distribution of land and sea and, dependent on the schemes used, a variety of other external parameters. The EXTPAR software package is able to generate external parameters for the models COSMO and ICON. The software can run on the UNIX or Linux system where the raw data is stored. Users (experienced users) can run the scripts to create new external parameters with their own specifications (e.g. the model domain).

The following steps must be performed for the generation of external parameters:

  1. The target grid has to be specified, supported target grids are
    • Rotated and non-rotated longitude-latitude grid (COSMO)
    • Icosahedral Triangular grids (ICON) with optionally higher resolution in selected regions (nesting)
  2. The different raw data sets are aggregated to the target grid considering all raw data elements which are within the target grid element. If the target grid has a higher resolution than the input grid on which the raw data is available either an interpolation is performed or the target grid is filled with the nearest neighbor, but sub-grid scale statistical calculations (e.g. subgrid scale variance of orographic height) are dismissed in this case.
  3. All the different external parameter sets have to be checked for consistency against each other. In case of conflicts default values are set automatically. In the NetCDF output, information on the input data and the processing software is given.


Latest Version: Extpar 5.0.0 (November 2018)

Source Code Administrator: Katie Osterried, C2SM (katherine.osterried@env.ethz.ch)

Language: Fortran 2008, Python

External library requirements: zlib, HDF5, NetCDF


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