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Table of Contents

Input definition

Table of Contents

Input definition

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Input data may be specified either by giving a path in the Input data may be specified either by giving a path in the Source parameter or by giving a GRIB-based data object in the Data parameter. Note that you should specify either Source or Data, not both.

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regrid_lambert_conformal = mv.regrid(
    grid_definition_mode = "lambert_conformal",
    first_point          = [50.88,-1.66],
    dx_in_metres         = 2500,
    dy_in_metres         = 2500,
    nx                   = 739,
    ny                   = 949,
    lad_in_degrees       = 63,
    lov_in_degrees       = 15,
    data                 = t_2m_rgg
    )

regrid_laea = mv.regrid(
    grid_definition_mode         = "lambert_azimuthal_equal_area",
    first_point                  = [66.982143,-35.034024],
    dx_in_metres                 = 5000,
    dy_in_metres                 = 5000,
    nx                           = 1000,
    ny                           = 950,
    standard_parallel_in_degrees = 52,
    central_longitude_in_degrees = 10,
    data                         = t_2m_rgg
    )

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It is up to the user to specify if the input consists of wind fields. Set this appropriatelly in order to perform the correct processing.

Possible options are:

Spectral to grid inverse transform

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• Finite Element-based interpolation with linear base functions
  • Linear: FEM with supporting triangular mesh
  • Bilinear: FEM with supporting quadrilateral mesh (for reduced grids, possibly containing triangles instead of highly-distorted quadrilaterals)
• Grid box method (based on Model grid box and time step)
  • Grid Box Average: input/output grid box intersections interpolation preserving input value integrals (conservative interpolation)
  • Grid Box MaximumStatistics: input/output grid box intersections value maximumstatistics - see parameter Interpolation Statistics for possible computations
• K-nearest neighbours based:
  • K-Nearest Neighbours: general method combining nearest method (choice of  neighbours) and distance weighting (choice of interpolating neighbour values)
  • Nearest Neighbour: parametrised version of K-Nearest Neighbours to chose a nearest neighbouring input point to define output point value
  • Nearest LSM: interpolated output point takes input only from input points of the same type (land or sea — requires setting land/sea masks)
• Structured methods, exploiting grid structure and configurable stencil for fast interpolations (non cacheable, so do not benefit from speedups on subsequent runs)
  • Structured Bilinear: bilinear interpolation
  • Structured Bicubic: bicubic interpolation
  • Structured Biquasicubic: computationally economic bicubic interpolation
• Automatic: see above.

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Associated options supporting Nearest Method Grid Box Statistics (described above):

• Distance: in [m] choice of closest points by distance to input point
• Distance Tolerance: in [m] tolerance checking the farthest from nearest points (when Nearest Method is Nclosest or nearest)
• Nclosest: choice of n-closest input points to input point

Interpolation Statistics

Associated options supporting Nearest Method (described above). Possible values are:

• count
• count_above_upper_limit
• count_below_lower_limit
• maximum
• minimum
• mode_real
• mode_integral
• mode_boolean
• median_integral
• median_boolean
• mean
• variance
• skewness
• kurtosis
• stddev
• automatic

Distance Weighting

Only available if Interpolation is K Nearest Neighbours. General way on how to interpolate input neighbouring point values to output points, including the Inverse Distance Weighting (IDW) class methods (see Wikipedia), which operates over input points returned by Nearest Method. Possible values are:

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Select one of the predefined names from the following:

LSM File Input/Output

Provide the path to an input/output LSM GRIB file.

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Activates a nabla (differential) operator processing on the fields. Possible options are:

Nabla Poles Missing Values

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