Cold Spells - IFS - Open Data Visio

Here we will focus on:

2t 2 metre temperature,
mn2t3 minimum temperature at 2 metres in the last 3 hours, and
10fgg10 10 metre wind gust of at least 10 m/s in Argentina on 29 June at 00 UTC.

1. Set Up Your Environment and Find ECMWF Open Data¶

If the packages are not installed yet, uncomment the code below and run it.

# !pip3 install earthkit ecmwf-opendata

from ecmwf.opendata import Client
import earthkit.data as ekd
import earthkit.plots as ekp
import earthkit

List of parameters to retrieve from open datasets¶

The selected values below can be modified.

Parameters available on a single level:

PARAM_SFC = ["mn2t3", "2t"]
LEVELTYPE = "sfc"

DATES = [20250629, 20250630, 20250701]
TIME = 0
STEPS = 6
STREAM = "oper"
TYPE = "fc"
MODEL = "ifs"

Get the data using the ECMWF Open Data API¶

def get_open_data(date, time, step, stream, _type, model, param, leveltype, levelist=[]):
    client = Client(source="aws")
    list_of_files = []
    # Get the data for all dates
    for _date in DATES:
        filename = f"{model}_{''.join(param)}_{''.join(map(str, levelist))}_{_date}.grib2" if levelist else f"{model}_{''.join(param)}_{leveltype}_{_date}.grib2"
        data = client.retrieve(
            date=_date,
            time=time,
            step=step,
            stream=stream,
            type=_type,
            levtype=leveltype,
            levelist=levelist,
            param=param,
            model=model,
            target=filename
            )
        list_of_files.append(filename)
    return data, list_of_files

2. 2-metre temperature and minimum temperature at 2 metres in the last 3 hours¶

data, list_of_files = get_open_data(date=DATES,
                                    time=TIME,
                                    step=STEPS,
                                    stream=STREAM,
                                    _type=TYPE,
                                    model=MODEL,
                                    param=PARAM_SFC,
                                    leveltype=LEVELTYPE,
                                    levelist=[])

# Select data from 29 June 2025
ds = ekd.from_source("file", list_of_files[0])
ds.ls()

t2m = ds.sel(shortName="2t")
t2m.ls()

t2min_K = ds.sel(shortName="mn2t3")

md_t2min = t2min_K.metadata()
ds_t2min = t2min_K.values - 273.15
t2min = ekd.FieldList.from_array(ds_t2min, md_t2min)
t2min.ls()

3. 10 metre wind gust of at least 10 m/s¶

The input values can be set here.

PARAM_SFC = ["10fgg10"]
LEVELTYPE = "sfc"

DATES = [20250629, 20250630, 20250701]
TIME = 0
STEPS = "0-24"
STREAM = "enfo"
TYPE = "ep"
MODEL = "ifs"

The dump() method inspects all the namespace keys of a parameter.

data, list_of_files = get_open_data(date=DATES,
                                    time=TIME,
                                    step=STEPS,
                                    stream=STREAM,
                                    _type=TYPE,
                                    model=MODEL,
                                    param=PARAM_SFC,
                                    leveltype=LEVELTYPE,
                                    levelist=[])

# Select data from 29 June 2025
wg10 = ekd.from_source("file", list_of_files[0])[0]
wg10.dump()

4. Data visualisation¶

The plots below show analyses of 2 metre temperature and minimum temperature at 2 metres in the last 3 hours on 29 June at 00 UTC.

figure = ekp.Figure(domain=[-80, -20, -55, -10], size=(9, 6), rows=1, columns=2)

t2m_shade = ekp.styles.Style(
    colors="Spectral_r",
    levels=range(-40, 50, 2),
    units="celsius",
)

t2min_shade = ekp.styles.Style(
    colors="Spectral_r",
    levels=range(-40, 50, 2),
)

figure.contourf(t2m, style=t2m_shade)
subplot = figure.add_map(0, 1)
subplot.contourf(t2min, style=t2min_shade)

figure.title("IFS: {variable_name} over South America\n {base_time:%Y-%m-%d %H} UTC (+{lead_time}h)\n")

figure.coastlines(resolution="low")
figure.gridlines()

figure.legend(location="bottom", label="Temperature (˚C)")

figure.save(fname=f"./plots/{''.join(PARAM_SFC)}_{MODEL}_{DATES[0]}{TIME}-{STEPS}h.png")
figure.show()

<Figure size 900x600 with 0 Axes>

The plot below shows analysis of 10 metre wind gust of at least 10 m/s on 29 June 2025.

chart = ekp.Map(domain=[-80, -20, -55, -10])

wg10_shade = ekp.styles.Style(
    colors="Spectral_r",
    levels=range(10, 100, 10),
    transform_first=True,
)

chart.contourf(wg10, style=wg10_shade)

chart.coastlines(resolution="low")
chart.gridlines()

chart.legend(location="bottom", label="{variable_name} (%)")

chart.title(
    "IFS: {variable_name} over South America\n"
    "{base_time:%Y-%m-%d %H} UTC (+{lead_time}h)\n",
    fontsize=14, horizontalalignment="center",
)
chart.save(f"./plots/{''.join(PARAM_SFC)}_{MODEL}_{DATES[0]}{TIME}-{STEPS}h.png")
chart.show()