Microsoft Planetary Computer

The Planetary Computer includes a vast amount of ECMWF open data available via Azure Storage.

The `earthkit` and `ecmwf-opendata` package¶

When using the ecmwf-opendata Python library, we set source to azure and data hosted on Microsoft’s Azure should be accessed.

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

# !pip3 install ecmwf-opendata earthkit-data earthkit

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

client = Client(source="azure")
request = {
    "date": "2025-08-08 12:00:00",
    "time": 12,
    "type": "fc",
    "step": 0,
    "param": "2t",
}
client.retrieve(request, "azure_2t_data.grib2")
dm_2t = ekd.from_source("file", "azure_2t_data.grib2")
dm_2t.ls()

client = Client(source="https://ai4edataeuwest.blob.core.windows.net/ecmwf/20250625/12z/ifs/0p25/oper/20250625120000-0h-oper-fc.grib2?st=2025-07-01T09%3A54%3A00Z&se=2025-07-02T10%3A39%3A00Z&sp=rl&sv=2024-05-04&sr=c&skoid=9c8ff44a-6a2c-4dfb-b298-1c9212f64d9a&sktid=72f988bf-86f1-41af-91ab-2d7cd011db47&skt=2025-07-02T02%3A32%3A03Z&ske=2025-07-09T02%3A32%3A03Z&sks=b&skv=2024-05-04&sig=qcG7eWdtC7/lhamMO1x8UwyA8A45tGFXAE55Xu5UQKg%3D")
request = {
    "date": "2025-06-25 12:00:00",
    "time": 12,
    "type": "fc",
    "step": 0,
    "stream": "oper",
    "param": "2t",
}
client.retrieve(request, "azure_2t_data.grib2")
dm_2t = ekd.from_source("file", "azure_2t_data.grib2")
dm_2t.ls()

ds = earthkit.data.from_source(
    "ecmwf-open-data",
    source="https://ai4edataeuwest.blob.core.windows.net/ecmwf/20250625/12z/ifs/0p25/oper/20250625120000-0h-oper-fc.grib2?st=2025-07-01T09%3A54%3A00Z&se=2025-07-02T10%3A39%3A00Z&sp=rl&sv=2024-05-04&sr=c&skoid=9c8ff44a-6a2c-4dfb-b298-1c9212f64d9a&sktid=72f988bf-86f1-41af-91ab-2d7cd011db47&skt=2025-07-02T02%3A32%3A03Z&ske=2025-07-09T02%3A32%3A03Z&sks=b&skv=2024-05-04&sig=qcG7eWdtC7/lhamMO1x8UwyA8A45tGFXAE55Xu5UQKg%3D",
    model="ifs",
    date="20250625",
    time=12,
    stream="oper",
    type="fc",
    target="azure_2t_data.grib2",
)
ds.ls()

The `pystac_client` and `planetary_computer` package¶

The example below shows how to download yesterday’s data.

!pip3 install pystac_client planetary_computer
!pip3 install xarray cfgrib

import pystac_client
import planetary_computer
import requests
import xarray as xr

catalog = pystac_client.Client.open(
    "https://planetarycomputer.microsoft.com/api/stac/v1",
    modifier=planetary_computer.sign_inplace,
)
search = catalog.search(
    collections=["ecmwf-forecast"],
    query={
        "ecmwf:stream": {"eq": "oper"},
        "ecmwf:type": {"eq": "fc"},
        "ecmwf:step": {"eq": "0h"},
    },
)
items = search.item_collection()

# select the most recent item
item = max(items, key=lambda item: item.datetime)

url = item.assets["data"].href
url_ecmwf = url.rpartition('?')[0]
filename = str(url_ecmwf.rpartition('oper/')[-1])

r = requests.get(url, stream=True)
with open(filename, mode="wb") as file:
    for chunk in r.iter_content(chunk_size=10 * 1024):
        file.write(chunk)

ds = xr.open_dataset(f'./{filename}', engine='cfgrib',
                     decode_timedelta=True,
                     backend_kwargs={'filter_by_keys': {'typeOfLevel': 'soilLayer'}})
ds

Loading...

import pystac_client
import planetary_computer
import requests
import earthkit.data as ekd

catalog = pystac_client.Client.open(
    "https://planetarycomputer.microsoft.com/api/stac/v1",
    modifier=planetary_computer.sign_inplace,
)
# specify a date range
time_range = "2025-06-01/2025-06-01"

search = catalog.search(
    collections=["ecmwf-forecast"],
    query={
        "ecmwf:stream": {"eq": "oper"},
        "ecmwf:type": {"eq": "fc"},
        "ecmwf:step": {"eq": "0h"},
        },
    datetime=time_range)
items = search.item_collection()

list_of_files = []
for item in items:
    url = item.assets["data"].href
    url_ecmwf = url.rpartition('?')[0]
    filename = str(url_ecmwf.rpartition('oper/')[-1])
    
    r = requests.get(url, stream=True)
    with open(filename, mode="wb") as file:
        for chunk in r.iter_content(chunk_size=10 * 1024):
            file.write(chunk)
    list_of_files.append(filename)

for file_ in list_of_files:
    print(f'File: {file_}')
    ds = ekd.from_source("file", f'./{file_}')
    ds.ls()

Microsoft Planetary Computer

The earthkit and ecmwf-opendata package¶

The pystac_client and planetary_computer package¶

The `earthkit` and `ecmwf-opendata` package¶

The `pystac_client` and `planetary_computer` package¶