Grid cell plots

grid_cells renders each grid cell as a filled polygon (or pixel) coloured by its data value. Unlike contourf, there is no interpolation between cells — the boundary between two adjacent cells is a hard edge, so the native grid structure remains clearly visible.

Key properties:

• For HEALPix and reduced Gaussian grids, the fast nnshow nearest-neighbour pixel backend is used automatically, producing efficient renderings even at high resolution.

• For regular lat/lon grids, matplotlib’s pcolormesh is used, which also preserves sharp cell boundaries.

• The resample argument is not supported — cell boundaries are always preserved. Use contourf with resample=Bilinear(...) if you need smooth rendering.

Example: HEALPix 2 m temperature

We load a HEALPix GRIB file and plot the individual pixel cells.

import earthkit.data as ekd

import earthkit.plots as ekp

data = ekd.from_source("sample", "healpix-h128-nested-2t.grib")

chart = ekp.Map(domain="Europe")

chart.grid_cells(data, units="celsius")

chart.coastlines()
chart.gridlines()
chart.legend()
chart.title()

chart.show()

Applying a style

Pass a Style object to control the colour map, levels and units.

style = ekp.styles.Style(
    colors="Spectral_r",
    levels=range(-10, 35, 5),
    units="celsius",
    extend="both",
)

chart = ekp.Map(domain="Europe")

chart.grid_cells(data, style=style)

chart.coastlines()
chart.gridlines()
chart.legend()
chart.title()

chart.show()

Regular lat/lon data

grid_cells works equally well on regular lat/lon GRIB or netCDF data. For regular grids, pcolormesh is used under the hood.

ll_data = ekd.from_source("sample", "era5-2t-msl-1985122512.grib").to_fieldlist()
temperature = ll_data.sel({"parameter.variable": "2t"})

chart = ekp.Map(domain="Europe")

chart.grid_cells(temperature, units="celsius")

chart.coastlines()
chart.gridlines()
chart.legend()
chart.title()

chart.show()

Comparing grid_cells with contourf

The difference between grid_cells and contourf is most apparent when zooming in to a region where individual cells are visible. contourf smooths across cell boundaries; grid_cells does not.

figure = ekp.Figure(rows=1, columns=2, domain=["France", "Spain"])

ax = figure.add_map()
ax.grid_cells(data, style=style)
ax.title("grid_cells — sharp boundaries")

ax = figure.add_map()
ax.contourf(data, style=style)
ax.title("contourf — interpolated")

figure.coastlines()
figure.borders()
figure.legend(location="right")

figure.show()

Overlaying grid cells with contour lines

A useful combination is grid_cells for the shaded background and contour for isolines on top.

chart = ekp.Map(domain="Europe")

chart.grid_cells(data, style=style)
chart.contour(data, units="celsius", colors="black", linewidths=0.5)

chart.coastlines()
chart.gridlines()
chart.legend()
chart.title()

chart.show()