El Niño

This example demonstrates how to: - Retrieve some interesting data from the Copernicus Climate Data Store (CDS) using earthkit-data - Create three subplots comparing different time steps and add a shared legend

Retrieving the data

In this example we will visualise how sea surface temperature was affected by the El Niño event of 1997.

import earthkit.maps
import earthkit.data

YEARS = {
    1993: "Normal conditions",
    1997: "El Niño",
    1998: "La Niña",
}

data = earthkit.data.from_source(
    "cds", "reanalysis-era5-single-levels-monthly-means",
    {
        "product_type": "monthly_averaged_reanalysis",
        "variable": "sea_surface_temperature",
        "year": list(YEARS),
        "month": "12",
        "time": "00:00",
        "area": [20, 100, -20, -60],
        "grid": [0.25, 0.25],
    },
)

data.ls()

	centre	shortName	typeOfLevel	level	dataDate	dataTime	stepRange	dataType	number	gridType
0	ecmf	sst	surface	0	19931201	0	0	an	0	regular_ll
1	ecmf	sst	surface	0	19971201	0	0	an	0	regular_ll
2	ecmf	sst	surface	0	19981201	0	0	an	0	regular_ll

Plotting the data

style = earthkit.maps.styles.Style(
    colors="Spectral_r",
    levels=range(15, 33),
    units="celsius",
)

chart = earthkit.maps.Chart(domain=[100, 300, -20, 20], rows=3)

chart.plot(data, style=style)

chart.land(color="#555", zorder=10)
chart.gridlines(xlocs=range(-180, 180, 20), ylocs=range(-20, 20, 10))

for subplot, conditions in zip(chart, YEARS.values()):
    subplot.title(f"{conditions} - ERA5 {{short_name!u}} monthly mean: {{time:%B %Y}}")

chart.title("{variable_name} in {time:%B} of {time:%Y}", fontsize=14)

chart.legend(label="{variable_name!l} ({units})", ticks=range(15, 33))

chart.show()