Accessing Climate Data from DWD

Deutscher Wetterdienst (DWD) is Germany's national meteorological service and one of the most comprehensive sources of weather and climate data for German stations. Meteostat integrates several DWD data feeds — covering hourly observations, daily summaries, and monthly records — that you can target directly using the providers parameter.

Available DWD Providers

Provider Enum	Granularity	Covered Area
ms.Provider.DWD_HOURLY	Hourly	Germany
ms.Provider.DWD_POI	Hourly	Europe
ms.Provider.DWD_MOSMIX	Hourly (forecast)	Global
ms.Provider.DWD_DAILY	Daily	Germany
ms.Provider.DWD_MONTHLY	Monthly	Germany
ms.Provider.CLIMAT	Monthly	Global

A full list of available providers is available here.

Be Explicit

Always pass both providers and parameters when targeting a specific DWD source. This avoids unnecessary data fetches and makes the data lineage clear.

Installation

pip install meteostat

The DWD_MOSMIX provider also requires the lxml package for parsing XML data.

Finding a DWD Station

DWD does not only cover stations in Germany, but also provides access to stations across Europe and beyond. However, the majority of DWD's data is for German stations, and the DWD_HOURLY, DWD_DAILY, and DWD_MONTHLY providers are limited to German stations only.

Those are the relevant identifiers for the different DWD feeds:

• DWD_HOURLY, DWD_DAILY and DWD_MONTHLY: national ID; most German stations
• DWD_POI: wmo ID, selected European stations
• DWD_MOSMIX: mosmix ID, thousands of global stations

For example, let's filter for German stations with a national ID:

import meteostat as ms

stations = ms.stations.query("""
    SELECT s.id, n.name, i.value AS national_id, s.latitude, s.longitude
    FROM stations s
    JOIN names n ON s.id = n.station AND n.language = 'en'
    JOIN identifiers i ON s.id = i.station AND i.key = 'national'
    WHERE s.country = 'DE';
""", index_col="id")

print(stations)

Throughout this recipe, Frankfurt Airport (10637) is used as the example station — it has one of the longest continuous DWD records in Germany.

Hourly Observations

DWD_HOURLY provides synoptic observations recorded every hour. The example below retrieves temperature and relative humidity for a full calendar year:

from datetime import datetime
import meteostat as ms

start = datetime(2024, 1, 1)
end   = datetime(2024, 12, 31, 23, 59)

ts = ms.hourly(
    '10637',
    start,
    end,
    providers=[ms.Provider.DWD_HOURLY],
    parameters=[ms.Parameter.TEMP, ms.Parameter.RHUM],
)

df = ts.fetch()

print(df.head())

Sample output:

                     temp  rhum
time
2024-01-01 00:00:00   4.8  92.0
2024-01-01 01:00:00   4.5  93.0
2024-01-01 02:00:00   4.2  94.0
2024-01-01 03:00:00   4.0  95.0
2024-01-01 04:00:00   3.8  95.0

POI Feed

DWD_POI is a richer hourly feed that additionally includes cloud cover, snow depth, wind gusts, and visibility. Use it when you need the full parameter set:

ts = ms.hourly(
    '10637',
    start,
    end,
    providers=[ms.Provider.DWD_POI],
    parameters=[
        ms.Parameter.TEMP,
        ms.Parameter.PRCP,
        ms.Parameter.CLDC,
        ms.Parameter.SNWD,
    ],
)
df = ts.fetch()

Daily Summaries

DWD_DAILY provides daily climate summaries with a full set of parameters including min/max temperatures, precipitation, sunshine duration, and more:

from datetime import date
import meteostat as ms

start = date(2020, 1, 1)
end   = date(2024, 12, 31)

ts = ms.daily(
    '10637',
    start,
    end,
    providers=[ms.Provider.DWD_DAILY],
    parameters=[
        ms.Parameter.TMIN,
        ms.Parameter.TMAX,
        ms.Parameter.PRCP,
        ms.Parameter.TSUN,
    ],
)
df = ts.fetch()
print(df.describe())

Monthly Records

DWD_MONTHLY provides pre-aggregated monthly values published by DWD. Use it for long-running climatological analyses where daily resolution is not required:

from datetime import date
import meteostat as ms

start = date(1950, 1, 1)
end   = date(2024, 12, 31)

ts = ms.monthly(
    '10637',
    start,
    end,
    providers=[ms.Provider.DWD_MONTHLY],
    parameters=[ms.Parameter.TEMP, ms.Parameter.PRCP],
)
df = ts.fetch()
print(df.tail(12))

CLIMAT Reports

CLIMAT is an international monthly exchange format that DWD contributes to. It covers stations worldwide and includes parameters not available in DWD_MONTHLY, such as absolute monthly extremes (txmn, txmx) and mean sea-level pressure:

from datetime import date
import meteostat as ms

start = date(1990, 1, 1)
end   = date(2024, 12, 31)

ts = ms.monthly(
    '10637',
    start,
    end,
    providers=[ms.Provider.CLIMAT],
    parameters=[ms.Parameter.TEMP, ms.Parameter.TMIN, ms.Parameter.TMAX],
)
df = ts.fetch()