Abstract

KNMI collects in-situ meteorological observations in the Netherlands aggregated into hourly, daily, monthly, and annual datasets. These data are derived from the 10-minute automatic measurements since the early 1990s, hourly observations from 1951 and daily observations from 1901. The earliest data starts in 1901 with one station and gradually increases to the current measurement network of more than 50 automatic weather stations.

The weather stations measure essential climate variables (ECVs), surface precipitation, pressure, global radiation, temperature, water vapor, wind speed and direction, clouds, and visibility. Sunshine duration and potential evapotranspiration are calculated from the ECVs. When applicable, minima, maxima, means, and sums are defined or calculated.

This dataset contains meteorological observations since 1901-01-01 at a daily interval. This dataset contains both observations from the Netherlands as well as the Caribbean Netherlands (BES islands). To form this dataset, hourly observations have been aggregated to daily intervals. When applicable, hourly intervals are calculated in which the minimum or maximum occurred during the day. The dataset is updated on a nightly basis.

Supplemental information


Metadata

Dataset name daily-in-situ-meteorological-observations
Dataset version 1.0
Status onGoing
Update frequency daily
File formats NetCDF
Spatial representation type vector
License https://creativecommons.org/licenses/by/4.0/
North bound latitude 55.7
East bound longitude 7.4
South bound latitude 12
West bound longitude -68.5
Dataset edition 1
Dataset manager Klimaat Team
Maintainer KNMI Data Services
Publication date 2025-11-27
Reference system identifier EPSG4326
Dataset start time 2016-05-06
Dataset end time 9999-12-31
Identifier urn:xkdc:ds:nl.knmi::daily-in-situ-meteorological-observations/1.0/
Lineage statement KNMI Robuust Klimatologisch Informatie Systeem (RobuKIS)
Use limitation Because of station relocations and changes in observation techniques, the data in these datasets are inhomogeneous. As a result, these series are not suitable for trend analysis.
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