Brief overview

  • Met.3D supports gridded, structured data with a regular, georeferenced longitude-latitude grid, a regular rotated longitude-latitude grid, or aregular projected (e.g. polar stereographic) grid in the horizontal, and either levels of constant pressure (in the following “pressure levels”), hybrid sigma-pressure levels (as used, e.g., by the ECMWF integrated forecast system), or arbitrary model levels with an additionally provided auxiliary 3D pressure field in the vertical.
  • Multiple datasets (that can have different grids) and ensemble datasets are natively supported.
  • Also, trajectory data is supported.
  • Currently, gridded data can be read from NetCDF files following the Climate and Forecast (CF) Metadata Conventions and from ECMWF GRIB files; trajectory data can be read from NetCDF files with a custom formatting.

Note

If your data cannot be read by Met.3D (i.e., if you don’t have access to your datasets after start-up), a (admittedly currently limited) set of error messages is displayed by the software in the start-up output on the text console. Please contact us if you need help.

Note

Display of non-georeferenced data on regular grids (e.g., output from LES models) is possible but requires some hacking on the NetCDF side. Please contact us if you are interested. We are working on making data import for such data easily possible in a future Met.3D version.

Internal data formats in Met.3D

Gridded, structured data

Met.3D supports gridded, structured data with a regular longitude-latitude grid, a regular rotated longitude-latitude grid, or a regular projected (e.g. polar stereographic) grid in the horizontal, and either levels of constant pressure (in the following “pressure levels”), hybrid sigma-pressure levels (as used, e.g., by the ECMWF integrated forecast system), or arbitrary model levels with an additionally provided auxiliary 3D pressure field in the vertical.

Internally, a single 2D or 3D scalar data field (i.e., one forecast variable, one time step, one ensemble member) is treated as the smallest data entity. A single data field is stored in a class derived from MStructuredGrid, these objects store all contextual information required to visualise the field (including latitude and longitude coordinates, pressure or hybrid level, time step and additional metadata). Example of derived classes are MRegularLonLatGrid for 2D fields, MRegularLonLatStructuredPressureGrid for 3D fields on pressure levels, MLonLatHybridSigmaPressureGrid for 3D fields on hybrid sigma-pressure levels. Time series and ensemble sets are composed of these basic data field entities.

Trajectory data

Trajectories are stored as bundles of trajectories (class MTrajectories). A single trajectory in a bundle consists of a simple list of positions in longitude-latitude-pressure space that resemble the trajectory. All trajectories in a bundle share the same time information, i.e. the time for position n is the same for all trajectories. This data layout corresponds to the smallest data entity being the bundle of all trajectories computed for a single ensemble member for the same time steps.

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