Ensemble precipitation forecasts made with Quantile Regression Forests and deterministic Harmonie-Arome inputs
**Data Quality Warning:** Data released prior to 2025-07-10 is unreliable due to a configuration error. Please disregard affected data.
A gridded 51-member ensemble of precipitation forecasts that are created using a tree-based machine learning method, quantile regression forests (QRF), and inputs from the deterministic Harmonie-Arome (HA) Cy43 forecasts. The target data set is rain-gauge-adjusted radar data that is upscaled by taking 3x3 km means and then a rolling maximum is taken in a 9 x 9 km box. Inputs to the machine learning model include HA precipitation, and indices of atmospheric instability. Spatial and temporal dependencies are restored using the minimum divergence Schaake Shuffle (SSh). Hourly forecasts are issued 8 times per day (00, 03, 06, 09, 12, 15, 18 and 21 UTC) for 60-hours into the future.
Standaard
- Datum (publicatie)
- 2025-04-15
- Versie
-
1
- Identifier
- urn:xkdc:ds:nl.knmi::QRF-RT-SSh/v2025/
- Doel van vervaardiging
-
Calibrated and skilful gridded ensemble forecasts of precipitation in the Netherlands
- Status
- continu geactualiseerd
- Contactgegevens voor de data
-
Organisatie Naam Contactpersoon Email Rol Koninklijk Nederlands Meteorologisch Instituut (KNMI)
contactpunt
- Herzieningsfrequentie
- continu
-
DG Discovery Properties Vocabulary 1.0
-
-
Weather forecast
-
Precipitation
-
Machine learning
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Quantile regression forests
-
- Gebruiksbeperkingen
-
pre-operational, so no guaranteed delivery yet
- (Juridische) toegangsrestrictie
- anders
- Overige beperkingen
- Veiligheidsrestricties
- vrij toegankelijk
- Ruimtelijk schema
- grid
- Afstand
- 3000 meters
- Taal
- English
- Karakterset
- utf8
- Onderwerp
-
- klimatologie, meteorologie atmosfeer
))
- Begindatum
- 2025-04-15
- Einddatum
- 9999-12-31
- Aanvullende informatie
-
The Minimum Divergence version of the Schaake Shuffle ([Scheuerer et al., 2017]( https://doi.org/10.1002/2016WR020133)) is used for statistical ensemble member generation. The Quantile Regression Forest algorithm as described by [Taillardat et al., 2016]( https://doi.org/10.1175/MWR-D-15-0260.1)) is used as post-processing method.
- Referentiesysteem identifier
- http://www.opengis.net/def/crs/EPSG/0/4326
- Distributie formaat
-
Naam Versie NetCDF
4
- Distributeur contact
-
Organisatie Naam Contactpersoon Email Rol Koninklijk Nederlands Meteorologisch Instituut (KNMI)
contactpunt
Digitale leverings opties
- OnLine bronnen
-
Protocol URL Naam landingpage
https://dataplatform.knmi.nl/catalog/datasets/index.html?x-dataset=QRF-RT-SSh&x-dataset-version=v2025 KNMI Data Platform
- Niveau kwaliteitsbeschrijving
- dataset
- Algemene beschrijving herkomst
-
Bi-linear interpolation from lambert to regular lat-lon
Metadata
- Metadata ID
- 82ba10ab-f2e4-40c0-91b8-f21454618134 XML
- Taal
- English
- Karakterset
- utf8
- Hierarchisch niveau
- dataset
- Metadata datum
- 2025-12-09T13:03:22.56468Z
- Metadata standaard naam.
-
ISO 19115
- Metadata standaard versie
-
ISO 19115:2003 NL Kernset 1.3 KNMI 2.1.0
- Metadata auteur
-
Organisatie Naam Contactpersoon Email Rol Koninklijk Nederlands Meteorologisch Instituut (KNMI)
contactpunt
- Landinstelling
-
Taalcode Tekencodering Nederlands; Vlaams Engels utf8
Overviews
Ruimtelijke dekking
)))
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