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dailymeteo

Python client for meteorological data from DailyMeteo:

  • get_meteo: daily, monthly or annual values for a location, World, 1961 to the present, from the DailyMeteo API (API key required).
  • meteoeurope1km: download of the MeteoEurope1km gridded dataset from Zenodo. It covers Europe at 1 km for 1961–2020: TMAX, TMIN, TMEAN, PRCP and SLP, with aggregates and climate normals.

It is the Python counterpart of get_meteo, get_coordinates and get_meteoeurope1km in the R package meteo. Spatial interpolation (RFSI, STRK) is available only in R.

Installation

pip install dailymeteo

Point data from the DailyMeteo API

import dailymeteo as dm

lat, lon = dm.get_coordinates("Belgrade")
df = dm.get_meteo(lat, lon, api_key="...",   # API key from https://app.dailymeteo.com/
                  var="tmean",                # "tmax", "tmin", "prcp"
                  agg_level="agg",            # "ltm" for long-term means
                  time_scale="day",           # "mon", "ann"
                  start="2020-01-01", end="2020-01-31")
# or time=["2020-01-01", "2020-01-15"]

The result is a pandas.DataFrame with columns timestamp and value.

MeteoEurope1km gridded dataset

from dailymeteo import meteoeurope1km as meu

# list archives: one ZIP per year with daily Cloud-Optimized GeoTIFFs
meu.files(var="tmean", product="day", years=[2001, 2002])

# download, verify MD5, unzip; interrupted downloads are resumed
meu.download(var="tmean", product="day", years=[2001, 2002], dest_dir="meteoeurope1km", unzip=True)

# aggregates and climate normals
meu.download(var="prcp", product="ltm_diff", dest_dir="meteoeurope1km")
product Content Archives
day daily data one per year (about 1–3.5 GB)
mon monthly aggregates one per decade
ann annual aggregates, 1961–2020 one
ltm_day daily climate normals one per period (period="1961-1990" / "1991-2020")
ltm_mon_ann monthly and annual climate normals one per period
ltm_diff difference of normals, 1991–2020 minus 1961–1990 one

Aggregates are means for temperatures and sums for precipitation. For SLP only daily data are available.

Rasters are in the Equi7 Europe projection (EPSG:27704) at 1000 m. Values are Int16 in tenths of the unit, so divide by 10 to get °C, mm or hPa. NoData is −9999.

meu.catalog() lists all Zenodo records of the dataset.

Citation

Sekulić, A., & Kilibarda, M. (2026). MeteoEurope1km (1961–2020): daily gridded meteorological dataset for Europe at a 1-km spatial resolution. Zenodo. https://doi.org/10.5281/zenodo.23264155

License

GPL-2.0-or-later, the same as the R package meteo.

Metadata

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