dailymeteo

Python client for meteorological data from DailyMeteo:

• get_meteo: daily, monthly or annual values and long-term means for a location, World, 1961 to the present, from the DailyMeteo API. Monthly, annual and long-term mean values are free; daily data need an API key and are billed per returned day.
• 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, var="tmean",     # "tmax", "tmin", "prcp"
                  time_scale="mon",           # "ann"; "day" needs api_key="..." from https://app.dailymeteo.com/
                  start="2020-01", end="2020-12")
# or time=["2020-01", "2020-07"]

# climate normals 1961-1990 and 1991-2020 for July
dm.get_meteo(lat, lon, var="tmax", agg_level="ltm", time_scale="mon", time="07")

The result is a pandas.DataFrame with columns timestamp and value. Locations without data (e.g. sea) give NaN.

Account: credits, point history, area downloads

acc = dm.Account("you@example.com", "password")   # or DAILYMETEO_EMAIL / DAILYMETEO_PASSWORD
acc.credits()                                      # plan, API credits, bulk credits
dm.get_meteo(lat, lon, var="tmax", time_scale="day", start="2020-07-01", end="2020-07-31", account=acc)
acc.bulk_download(lat, lon)                        # every variable, daily, whole record; CSV by email (1 bulk credit)
area = "POLYGON((20.0 44.0,20.3 44.0,20.3 44.3,20.0 44.3,20.0 44.0))"
acc.estimate_area(area, ["tmax", "prcp"], "2020-07-01", "2020-07-31")   # cost in credits
acc.area_download(area, ["tmax", "prcp"], "2020-07-01", "2020-07-31")   # clipped GeoTIFFs by email (max 3,000 km²)

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")

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.