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Contouring one-dimensional X, Y, Z (random) data

If you have X, Y, Z data represented by one-dimensional (1D) arrays of the same length, then NCL will contour this data by first generating a triangular mesh of the data under the hood, and then contouring the triangular mesh. You can also choose to regrid or interpolate your data to a 2D grid before plotting.

Here are the options for contouring 1D data:

  1. Set the sfXArray and sfYArray resources to the X and Y arrays respectively, and pass the 1D Z data to the appropriate gsn_csm contouring routine.

  2. If your X/Y arrays are lon/lat arrays, then in NCL V6.4.0 and later you can attach the special "lat1d" / "lon1d" attributes to your data variable to be plotted. This effectively causes the sfXArray and sfYArray resources to be set for you under the hood.

    See the "Plotting data on map" examples page for more information.

  3. If you have arrays representing polygons that surround each data point, then you can additionally set sfXCellBounds and sfYCellBounds to these arrays for a (potentially) better plot.

  4. You can first regrid or interpolate the data to a rectilinear, or curvilinear grid using ESMF regridding, or functions like like cssgrid, natgrid and triple2grid.

    See the "Random to Grid" examples page.

In all cases, the quality of the resulting plot will be a function of the distribution of the X and Y arrays, the number of sampling points, and the 'shape' of the data be contoured.
contour1d_1.ncl / contour1d_old_1.ncl: The data file for this example is pw.dat, which contains a column of data values, each with a corresponding lat, lon value.

To contour this data correctly over a map, this script attaches the 1D lat/lon arrays to the data using special "lat1d" and "lon1d" attributes. As of NCL V6.4.0, the gsn_csm_xxxxx_map scripts will look for these special attributes in order to correctly plot the data over a map.

If you have an older version of NCL that doesn't recognize the lat1d/lon1d attributes, then see the contour1d_old_1.ncl script, which sets the sfYArray and sfXArray resources to these lat/lon arrays respectively. NCL will internally use the triangular mesh capability to contour this data.

By default, NCL will generate smoothed contours (see first frame) in an area enclosed by a convex hull of the data. If cnFillMode is set to "RasterFill" (see second frame), then no smoothing will take effect, but you may get a blocky look. Raster fill can be significantly faster, but looks smoother if you have more points.

If you have data with concave boundaries, then you may get a "streaking effect" where NCL is trying to fill areas just outside the concave boundary area. This is because the contouring algorithm has no way of knowing where the boundary actually is, and thus creates the appearance of drawing outside the lines.

In order to hide the streaking effect, you can either provide "bounds" for each data value via the sfXCellBounds and sfYCellBounds resources (see the Geodesic examples page) or you can use masking effects to hide streaking areas. See examples mask_8.ncl and mask_11.ncl on the Masking examples page.

See example 1 on the "Plotting station data" page for a similar example using the same data.

contour1d_2.ncl / contour1d_2_640.ncl: This example shows how to contour an ARPEGE grid, which came to us from Christophe Cassou of Meteo-France.

The data for this example are spread across two NetCDF files. The resolution is pretty fine, so raster contours (cnFillMode = "RasterFill") are used.

In the contour1d_2.ncl script, lat/lon information is provided by setting the resources sfXArray and sfYArray. In the contour1d_2_640.ncl script, the special lat1d/lon1d attributes are used.

contour1d_3.ncl / contour1d_3_640.ncl: Gridded sea level pressures are read; then, for demonstration purposes, NOBS are randomly sampled from the grid using generate_unique_indices or random_uniform and small random location perturbations are added.

The resulting lat[*], lon[*], Z[*] arrays are then contoured using the sfYArray and sfXArray resources in the contour1d_3.ncl script, and lat1d/lon1d attributes in contour1d_3_640.ncl.

In this example, the trGridType resource is explicitly set to "TriangularMesh". However, as noted above, this is not necessary.

Note: The input data are on a global grid. Hence, the data are cyclic in longitude. The resulting plot clearly shows [left and right edges] that the "TriangularMesh" is not capable of handling this situation.

contour1d_4.ncl / contour1d_4_640.ncl: This example is very similar to the first one on this page, except the markers are colored according to the labelbar generated by the color contours.

The color contours are made more transparent by setting cnFillOpacityF to 0.5 (default is 1.0). The main purpose of this example is to show how to color the markers based on an existing contour field.

geodesic_1.ncl: sfXArray and sfYArray are set to the model's grid center lat/lon arrays (converted to degrees),and sfXCellBounds and sfYCellBounds are set the model's grid corner lat/lon arrays (also converted to degrees).

The second image shows the structure of a GEODESIC grid, along with its cell centers.