Output formats

The response shape is controlled by two parameters:

• output-format — json (inline) or netcdf (a downloadable file).
• output-schema — for JSON, list (pandas-friendly) or xarray (an xarray Dataset dict).

All timestamps are ISO 8601 strings. With timezone=UTC (default) they end in Z; with another timezone they carry that UTC offset.

JSON — list (pandas)

Returns an array with one object per queried point. Each object has ref_datetime, valid_datetime, and one array per requested variable, all the same length. (For a single point requested as scalar latitude/longitude, a single object may be returned instead of a one-element array.)

[
  {
    "ref_datetime":   ["2023-08-01T00:00:00Z", "2023-08-01T00:00:00Z"],
    "valid_datetime": ["2023-08-01T00:00:00Z", "2023-08-01T01:00:00Z"],
    "Temperature":    [17.4, 17.1],
    "WindSpeed":      [5.2, 5.0]
  }
]

import requests, pandas as pd

resp = requests.get(
    "https://api.rebase.energy/weather/v2/point/historical",
    headers={"Authorization": "your_api_key"},
    params={
        "model": "DWD_ICON-EU",
        "latitude": "60.1, 59.3",
        "longitude": "16.5, 18.1",
        "variables": "Temperature, WindSpeed",
        "start-date": "2023-08-01",
        "end-date": "2023-08-03",
    },
)
points = resp.json()
dfs = [pd.DataFrame(p) for p in points]          # one DataFrame per point
df0 = dfs[0].set_index(["ref_datetime", "valid_datetime"])
print(df0.head())

Column names match exactly what you requested, including levels — e.g. requesting WindSpeed:100 yields a WindSpeed:100 column.

JSON — xarray

With output-schema=xarray the response is a single xarray Dataset serialized via Dataset.to_dict() (attrs / dims / coords / data_vars). This is the natural choice for grids (type=grid). Dimensions include point, reference_time, valid_time, and, where applicable, latitude / longitude / height.

import requests, xarray as xr

resp = requests.get(
    "https://api.rebase.energy/weather/v2/area/operational",
    headers={"Authorization": "your_api_key"},
    params={
        "model": "DWD_ICON-EU",
        "latitude": "60.0, 60.5, 61.0",
        "longitude": "16.0, 16.5, 17.0",
        "variables": "Temperature",
        "output-schema": "xarray",
    },
)
ds = xr.Dataset.from_dict(resp.json())
print(ds)

NetCDF (pre-signed URL)

For large requests, set output-format=netcdf. The response is a small JSON envelope with a pre-signed download URL rather than the data inline:

{
  "file": "https://api.rebase.energy/weather/v2/download/eyJ0eXAi...",
  "create_time": "2026-06-30T08:21"
}

• The file URL is generated on demand and expires (default ~1 week).
• The file may still be building when the envelope returns. Either poll the file URL (it returns 404 until ready, 200 when complete) or pass wait=true to have the API block until the file is fully generated before responding.
• Large queries are expected to use this format rather than inline JSON.

import requests, xarray as xr

resp = requests.get(
    "https://api.rebase.energy/weather/v2/area/historical",
    headers={"Authorization": "your_api_key"},
    params={
        "model": "DWD_ICON-EU",
        "latitude": "60.0, 61.0",
        "longitude": "16.0, 17.0",
        "variables": "Temperature, WindSpeed",
        "start-date": "2023-08-01",
        "end-date": "2023-08-31",
        "output-format": "netcdf",
        "wait": "true",
    },
)
file_url = resp.json()["file"]

# Download and open
nc = requests.get(file_url)
with open("forecast.nc", "wb") as f:
    f.write(nc.content)
ds = xr.open_dataset("forecast.nc")
print(ds)