pyart.map.grid_ppi_sweeps#

pyart.map.grid_ppi_sweeps(radar, target_sweeps=None, grid_size=801, grid_limits='auto', max_z=12000.0, el_rounding_frac=0.25, add_grid_altitude=True, **kwargs)[source]#

Separately grid PPI sweeps to an X-Y plane considering only horizontal distances in grid RoI and weighting function. Gridding is performed using the grid_from_radars method, which receives any additional input parameters. Note that h_factor and dist_factor should not be included in kwargs (required for valid gridding results)

Parameters:

  • radar (Radar) – Radar volume containing PPI sweeps.

  • target_sweeps (int or list) – sweeps to grid. Using all sweeps in radar if None.

  • grid_size (int or 2-tuple) – grid dimension size. Using sizes for the X-Y plane if tuple. This input parameter is ignored if grid_shape is given explicitly via kwargs.

  • grid_limits (3-tuple with 2-tuple elements or ‘auto’) – if ‘auto’ using the maximum horizontal range rounded up to the nearest kilometer and limiting vertically up to max_z.

  • max_z (float) – maximum height to consider in gridding (only used if grid_limits is ‘auto’)

  • el_rounding_frac (float) – A fraction for rounding the elevation elements. This variables is also used to represent the sweep for altitude estimation.

  • add_grid_altitude (bool) – adding a sweep-dependent altitude estimate corresponding to the X-Y plane if True. This output field is useful considering the slanted PPI scans.

Returns:

radar_ds (xarray.Dataset) – Radar data gridded to the X-Y plane with a third dimension representing the different sweep elevations.