Spectral Gridding (Springsteel)

grid_radar_volume_spectral(radar_volume, moment_dict, grid_type_dict,
    output_file, index_time, sgrid, power_threshold;
    missing_key="SQI", valid_key="DBZ", heading=-9999.0,
    institution="", source="", include_derivatives=false)

Grid a radar volume onto a Springsteel spectral grid and perform spectral analysis.

This is the high-level spectral gridding workflow:

1. Extract quadrature coordinates from sgrid in Daisho format
2. Compute ROI from grid spacing
3. Call grid_volume (reuses entire existing gridding engine)
4. Populate the Springsteel physical array
5. Mask fill values, perform spectral + grid transforms, restore fills
6. Write CF-compliant NetCDF output
7. Return the populated sgrid for further analysis

Arguments

• radar_volume: Radar volume data structure.
• moment_dict: Dictionary mapping moment names to integer indices.
• grid_type_dict: Dictionary mapping moment indices to interpolation type symbols.
• output_file: Path to the output NetCDF file.
• index_time: Reference time for the output dataset.
• sgrid: Pre-configured SpringsteelGrid (from create_radar_grid).
• power_threshold: Minimum beam power weight.
• missing_key, valid_key: Moment names for QC gating.
• heading: Platform heading in degrees.
• institution, source: Metadata strings for NetCDF output.
• include_derivatives: Whether to include derivative fields in output.

Returns

The populated SpringsteelGrid with spectral coefficients and physical values.

See also: create_radar_grid, write_radar_netcdf

grid_radar_volume_spectral(radar_volume, output_file, index_time, sgrid, p::DaishoParameters; heading=-9999.0, institution="", source="", include_derivatives=false)

Parameter-struct overload reading gridding config from p.gridding and the moment map from p.moments.

grid_radar_volume_spectral(volumes::AbstractVector{<:Volume}, output_file,
    index_time, sgrid, p::DaishoParameters; heading=-9999.0,
    institution="", source="", include_derivatives=false)

Multi-radar overload: accumulate every sweep of every volume onto ONE shared Springsteel grid centered on the centroid of the radar reference positions (via volume_reference_position), so overlapping radars line up on a common origin. Everything else matches the single-volume form.

grid_radar_ppi_spectral(radar_volume, moment_dict, grid_type_dict,
    output_file, index_time, sgrid, power_threshold;
    missing_key="SQI", valid_key="DBZ", heading=-9999.0,
    institution="", source="", include_derivatives=false)

Grid a radar PPI scan onto a 2D Springsteel spectral grid and perform spectral analysis.

See grid_radar_volume_spectral for the full workflow description.

grid_radar_ppi_spectral(radar_volume, output_file, index_time, sgrid, p::DaishoParameters; heading=-9999.0, institution="", source="", include_derivatives=false)

Parameter-struct overload reading gridding config from p.gridding and the moment map from p.moments.

grid_radar_column_spectral(radar_volume, moment_dict, grid_type_dict,
    output_file, index_time, sgrid, power_threshold;
    missing_key="SQI", valid_key="DBZ",
    institution="", source="", include_derivatives=false)

Grid a radar column onto a 1D Springsteel spectral grid and perform spectral analysis.

See grid_radar_volume_spectral for the full workflow description.

grid_radar_column_spectral(radar_volume, output_file, index_time, sgrid, p::DaishoParameters; institution="", source="", include_derivatives=false)

Parameter-struct overload reading gridding config from p.gridding and the moment map from p.moments.

create_radar_grid(geometry, moment_dict;
    xmin=0.0, xmax=0.0, xdim=0,
    ymin=0.0, ymax=0.0, ydim=0,
    zmin=0.0, zmax=0.0, zdim=0,
    mubar=3, quadrature=:gauss,
    BCL=NaturalBC(), BCR=NaturalBC(),
    BCU=NaturalBC(), BCD=NaturalBC(),
    BCB=NaturalBC(), BCT=NaturalBC())

Create a Springsteel spectral grid configured for radar data analysis.

Maps Daisho's radar moment dictionary and grid specification to a SpringsteelGrid. The xdim, ydim, zdim parameters specify the number of B-spline cells in each dimension; the actual number of physical grid points is cells × mubar.

Dimension mapping: i = X (easting), j = Y (northing), k = Z (altitude).

Arguments

• geometry::String: Grid geometry type ("R", "RR", or "RRR").
• moment_dict::Dict: Dictionary mapping moment names to indices (e.g., Dict("DBZ" => 1, "VEL" => 2)).
• xmin, xmax: X-dimension domain bounds (meters).
• xdim: Number of B-spline cells in X.
• ymin, ymax: Y-dimension domain bounds (meters, for RR/RRR).
• ydim: Number of B-spline cells in Y.
• zmin, zmax: Z-dimension domain bounds (meters, for RRR).
• zdim: Number of B-spline cells in Z.
• mubar: Quadrature points per cell (default: 3).
• quadrature: Quadrature rule (default: :gauss).
• BCL, BCR: Left/right boundary conditions for X. Accepts a Springsteel BoundaryConditions (e.g. NaturalBC(), DirichletBC(), NeumannBC()) or a legacy module-qualified Dict (e.g. CubicBSpline.R0, CubicBSpline.R1T1). Default: NaturalBC().
• BCU, BCD: Upper/lower boundary conditions for Y. Same accepted forms as BCL.
• BCB, BCT: Bottom/top boundary conditions for Z. Same accepted forms as BCL.

Returns

A typed SpringsteelGrid (R_Grid, RR_Grid, or RRR_Grid).

Example

moment_dict = Dict("DBZ" => 1, "VEL" => 2)
sgrid = create_radar_grid("RRR", moment_dict;
    xmin=-50000.0, xmax=50000.0, xdim=10,
    ymin=-50000.0, ymax=50000.0, ydim=10,
    zmin=0.0, zmax=15000.0, zdim=5)

See also: get_springsteel_gridpoints_zyx, populate_physical!

create_radar_grid(p::DaishoParameters)
create_radar_grid(cfg::SpringsteelGridConfig, vars::Dict{String,Int})

Build a Springsteel grid from the geometry-general [grid.springsteel] config (any supported spline-i geometry: R/RZ/RR/RRR, RL/RLZ/RLR, SL/SLZ/SLR). The Springsteel variable map is built via field_index_dict (1-based indices in field-name-sorted order, order-independent of the source TOML).

Axis mapping into SpringsteelGridParameters: per-axis min/max → iMin/iMax etc.; spline cells → num_cells (i) or jDim/kDim = cells × mubar; Chebyshev points → kDim. Boundary conditions map the axis' min side to Springsteel's BCL/BCD/BCB and max side to BCR/BCU/BCT. Output resampling counts (regular_out) are injected after construction (see _with_regular_out), defaulting to cells + 1 on spline axes.

Note the gridding engine itself currently traverses only the Cartesian R/RR/RRR grids; the other geometries can be built (and transformed/written) but not yet gridded onto — build_springsteel_grid_spec raises a clear error for them.

radar_vars(p::DaishoParameters) -> Dict{String,Int}

The Springsteel variable map for hand-built grids: field name → 1-based column index in field-name-sorted order, identical to field_index_dict. Pass it as vars when constructing a Springsteel.SpringsteelGridParameters yourself — the escape hatch for grids the [grid.springsteel] schema cannot express (per-variable spectral filters, Fourier/Chebyshev-primary geometries). The gridding entry points validate the grid's vars against the configured [fields] and refuse mismatches, since the gridded-array column order must line up with the spectral-grid variable order.

volume_reference_position(volume::Volume) -> (lat, lon)

Reference (latitude, longitude) of a volume: the stationary position, or the first sweep's georeference when a mobile platform reports (0, 0).

build_springsteel_grid_spec(sgrid; reference_latitude, reference_longitude) -> GridSpec
build_springsteel_grid_spec(sgrid, volume::Volume) -> GridSpec

Build a Daisho GridSpec whose per-axis coordinate sets reproduce the Springsteel grid's quadrature lattice, centered on the given reference position (the volume form uses volume_reference_position). The unified accumulator engine then grids onto exactly the Springsteel node layout.

Cartesian tensor-product assumption. Springsteel Cartesian grids factorize as node(i,j,k) = (X[i], Y[j], Z[k]), so the per-axis coordinate sets fully describe the lattice. Non-Cartesian (cylindrical/spherical) grids raise an ArgumentError — that is where future per-node gridpoints + metric-ROI work plugs in.

compute_roi(sgrid::SpringsteelGrid)

Compute horizontal and vertical radius-of-influence from a Springsteel grid's quadrature point spacing.

Uses h_factor/v_factor × average quadrature-point spacing (default 0.75, the legacy Daisho convention). The accumulator-path Springsteel provider passes p.gridding.horizontal_roi_factor / vertical_roi_factor.

Arguments

• sgrid: A SpringsteelGrid.
• h_factor: Horizontal ROI fraction of the mean horizontal node spacing.
• v_factor: Vertical ROI fraction of the mean vertical node spacing (3D only).

Returns

• For 3D grids: (h_roi, v_roi) tuple.
• For 2D grids: (h_roi,) tuple (single horizontal ROI).
• For 1D grids: (roi,) tuple.

See also: create_radar_grid

get_springsteel_gridpoints_zyx(sgrid::SpringsteelGrid)

Extract Gaussian quadrature coordinates from a Springsteel grid and reshape them into Daisho's array format with [z, y, x] ordering.

Arguments

• sgrid: A SpringsteelGrid (RGrid, RRGrid, or RRR_Grid).

Returns

• For RRR (3D): Array{Float64, 4} of shape (kDim, jDim, iDim, 3) with [:, :, :, 1] = z, [:, :, :, 2] = y, [:, :, :, 3] = x.
• For RR (2D): Array{Float64, 3} of shape (jDim, iDim, 2) with [:, :, 1] = y, [:, :, 2] = x.
• For R (1D): Vector{Float64} of shape (iDim,) with x-coordinates.

See also: create_radar_grid, populate_physical!

populate_physical!(sgrid, radar_grid, moment_dict)

Copy Daisho's gridded radar data into a Springsteel grid's physical array (slot 1).

Handles fill value translation:

• true missing (gate not measured, the io fill_value) → NaN
• undetect (scanned, no echo, the io undetect) → preserved as-is
• valid values → copied as-is

Arguments

• sgrid::SpringsteelGrid: Target spectral grid.
• radar_grid::Array: Daisho radar grid with shape (n_moments, zdim, ydim, xdim) for 3D, (n_moments, ydim, xdim) for 2D, or (n_moments, xdim) for 1D.
• moment_dict::Dict: Mapping of moment names to column indices.

See also: create_radar_grid, get_springsteel_gridpoints_zyx

write_radar_netcdf(filename, sgrid, radar_volume, moment_dict;
    ref_lat=0.0, ref_lon=0.0, institution="", source="", heading=-9999.0,
    include_derivatives=false)

Write a Springsteel spectral grid with radar data to a CF-compliant NetCDF file.

Calls Springsteel.write_netcdf with radar-specific global attributes, then patches in radar variable attributes and grid mapping via NCDatasets.

Arguments

• filename: Output NetCDF file path.
• sgrid: A SpringsteelGrid with populated physical and spectral arrays.
• radar_volume: Daisho radar volume for metadata extraction.
• moment_dict: Dictionary mapping moment names to indices.
• ref_lat, ref_lon: Reference latitude/longitude for projection.
• institution, source: Metadata strings.
• heading: Platform heading in degrees.
• include_derivatives: Whether to include derivative fields in output.

See also: radar_global_attributes, grid_radar_volume_spectral

radar_global_attributes(radar_volume, ref_lat, ref_lon;
    institution="", source="", heading=-9999.0)

Build a CF-compliant global attribute dictionary for radar NetCDF output.

Arguments

• radar_volume: Daisho radar volume data structure.
• ref_lat: Reference latitude for the Transverse Mercator projection (degrees).
• ref_lon: Reference longitude for the Transverse Mercator projection (degrees).
• institution: Institution name string.
• source: Source instrument description.
• heading: Platform heading in degrees (default: -9999.0 for missing).

Returns

Dict{String,Any} of CF-compliant global attributes.

See also: write_radar_netcdf