Plotting GRIB data

GRIB (GRIdded Binary) is the standard format for NWP (numerical weather prediction) model output at operational centres such as ECMWF. earthkit-plots reads GRIB files via earthkit-data’s GRIB backend and provides the same plotting API as for any other source type.

import earthkit.data as ekd

import earthkit.plots as ekp

Loading a GRIB file

ekd.from_source("sample", ...) fetches a small ERA5 GRIB sample. For a local GRIB file use ekd.from_source("file", "/path/to/file.grib").

grib = ekd.from_source("sample", "era5-monthly-mean-2t-199312.grib").to_fieldlist()
grib

Inspecting the contents

ls() gives a summary of the fields in the file — useful when a GRIB file contains multiple parameters, levels or time steps.

grib.ls()

	parameter.variable	time.valid_datetime	time.base_datetime	time.step	vertical.level	vertical.level_type	ensemble.member	geography.grid_type
0	2t	1993-12-01	1993-12-01	0 days	0	surface	0	regular_ll

Basic plot

Pass the earthkit-data FieldList directly to any plotting method. GRIB files carry rich metadata (parameter name, units, level type, valid time, …) which earthkit-plots uses automatically for titles, unit conversion and style selection.

ekp.geo.plot(grib)

<earthkit.plots.components.maps.Map at 0x14c18f210>

Automatic style selection

plot() inspects the GRIB metadata and selects an appropriate style and plot method automatically:

chart = ekp.Map(domain="Europe")
chart.plot(grib, units="celsius")
chart.legend()
chart.coastlines()
chart.title("{variable_name} – {time:%B %Y}")
chart.show()

Format agnosticism

The plotting code above is essentially identical to the netCDF and xarray examples — the only line that changes is how the data object is created:

# GRIB
data = ekd.from_source("sample", "era5-monthly-mean-2t-199312.grib")

# netCDF
data = ekd.from_source("sample", "era5-monthly-mean-2t-199312.nc")

# xarray
data = ekd.from_source("sample", "era5-monthly-mean-2t-199312.nc").to_xarray()

# In every case, the plot call is identical:
chart = ekp.Map(domain="Europe")
chart.plot(data, units="celsius")

This format agnosticism is a deliberate design goal of earthkit-plots: your visualisation code should not need to change just because your data arrives in a different format.