ecmwf-opendata 0.0.14

A package to download ECMWF open data

ecmwf-opendata

A package to download ECMWF open data

from ecmwf.opendata import Client

client = Client()

client.retrieve(
    date=-1,
    time=6,
    step=144,
    stream="waef",
    type="cf",
    target="data.grib",
    param="mwd",
)

Download examples

Download a single surface parameter at a single forecast step from ECMWF's 00UTC HRES forecast

from ecmwf.opendata import Client

client = Client(source="ecmwf")

client.retrieve(
    time=0,
    stream="oper",
    type="fc",
    step=24,
    param="2t",
    target="data.grib2",
)

• For HRES Atmospheric model products at time=06 or time=12, use stream = "scda",

Download the Tropical Cyclone tracks from ECMWF's 00UTC HRES forecast (Set I-iii)

from ecmwf.opendata import Client

client = Client(source="ecmwf")

client.retrieve(
    time=0,
    stream="oper",
    type="tf",
    step=240,
    target="data.bufr",
)

• The downloaded data are encoded in BUFR edition 4
• For the HRES Tropical Cyclone tracks at time=06 and time=18 use:

...
   stream = "scda",
   step = 90,
...

Download a single surface parameter at a single forecast step for all ensemble members from ECMWF's 12UTC 00UTC ENS forecast

from ecmwf.opendata import Client

client = Client(source = "ecmwf")

client.retrieve(
   time = 0,
   stream = "enfo",
   type = "pf",
   param = "msl",
   target = "data.grib2"
)

• To download a single ensemble member, use the number keyword: number = [1,].
• All of the odd numbered ensemble members use number = [num for num in range(1,51,2)].
• To download the control member, use type = "cf".

Download the Tropical Cyclone tracks from ECMWF's 00UTC ENS forecast

The Tropical Cyclone tracks are identified by the keyword type = "tf".

from ecmwf.opendata import Client

client = Client(source="ecmwf")

client.retrieve(
    time=0,
    stream="enfo",
    type="tf",
    step=240,
    target="data.bufr",
)

• The downloaded data are encoded in BUFR edition 4
• For the ENS Tropical Cyclone tracks at time=06 and time=18 replace step = [240,] with step = [144,].

Download the ensemble mean and standard deviation for all parameters at a single forecast step from ECMWF's 00UTC ENS forecast

The ensemble mean and standard deviation are identified by the keywords type = "em":

from ecmwf.opendata import Client

client = Client(source="ecmwf")

client.retrieve(
    time=0,
    stream="enfo",
    type="em",
    step=24,
    target="data.grib2",
)

and type = "es", respectively:

from ecmwf.opendata import Client

client = Client(source="ecmwf")

client.retrieve(
    time=0,
    stream="enfo",
    type="es",
    step=24,
    target="data.grib2",
)

Download the ensemble probability products

The ensemble probability products are identified by the keywordtype = "ep". The probability products are available only for time=00 and time=12.

Two different productsa are available.

Probabilities - Instantaneous weather events - Pressure levels

The probability of temperature standardized anomalies at a constant pressure level of 850hPa are available at 12 hourly forecast steps.

from ecmwf.opendata import Client

client = Client(source="ecmwf")

client.retrieve(
    time=0,
    stream="enfo",
    type="ep",
    step=[i for i in range(12, 361, 12)],
    levtype="pl",
    levelist=850,
    param=[
        "ptsa_gt_1stdev",
        "ptsa_gt_1p5stdev",
        "ptsa_gt_2stdev",
        "ptsa_lt_1stdev",
        "ptsa_lt_1p5stdev",
        "ptsa_lt_2stdev",
    ],
    target="data.grib2",
)

Probabilities - Daily weather events - Single level

The probabilities of total precipitation and wind gusts exceeding specified thresholds in a 24 hour period are available for step ranges 0-24 to 336-360 by 12​​. These are specified in the retrieval request using, e.g.: step = ["0-24", "12-36", "24-48"].

from ecmwf.opendata import Client

client = Client(source="ecmwf")

steps = [f"{12 * i}-{ 12 * i + 24}" for i in range(29)]

client.retrieve(
    time=0,
    stream="enfo",
    type="ep",
    step=steps,
    levtype="sfc",
    param=["tpg1", "tpg5", "10fgg10"],
    target="data.grib2",
)

ECMWF open data license

By downloading data from the ECMWF open data dataset, you agree to the their terms: Attribution 4.0 International (CC BY 4.0). If you do not agree with such terms, do not download the data. Visit this page for more information.

License

Apache License 2.0 In applying this licence, ECMWF does not waive the privileges and immunities granted to it by virtue of its status as an intergovernmental organisation nor does it submit to any jurisdiction.