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Dataset

Ensemble precipitation forecasts made with Quantile Regression Forests and deterministic Harmonie-Arome inputs

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State Available
Data owner Koninklijk Nederlands Meteorologisch Instituut
Updated 03/27/2024 - 00:00
License CC-BY (4.0)
Thema
  • Air
Publicity level Public
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Description

A gridded 50-member ensemble of precipitation forecasts that are created using a tree-based machine learning method, quantile regression forests, and inputs from the deterministic Harmonie-Arome (HA) forecasts. The target data set is rain-gauge-adjusted radar data that is upscaled by taking 3x3 km means and then a maximum is taken in a 7.5 x 7.5 km box. Inputs to the machine learning model include HA precipitation, and indices of atmospheric instability. Spatial and temporal dependencies are restored using the Schaake Shuffle. Forecasts are available during the extended summer period (mid-April to mid-October). Hourly forecasts are issued 4 times per day (00, 06, 12 en 18 UTC) for 48-hours into the future.

machine-learning precipitation quantile-regression-forests weather-forecast

Owner

Owner information

Data owner:
Koninklijk Nederlands Meteorologisch Instituut

Contact point

Department:
Koninklijk Nederlands Meteorologisch Instituut (KNMI)
Email address:
opendata@knmi.nl

Publication & catalogues

Data publisher:
Koninklijk Nederlands Meteorologisch Instituut

Reuse

Access rights:
Public
Status dataset:
Available

Licence & conditions

License:
CC-BY (4.0)

Location and time

Temporal coverage

Start coverage period:
04/15/2022 - 00:00
End coverage period:
12/31/9999 - 00:00

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Metadata

Language settings

Data language

  • English

Metadata language

  • English

Identifiers

Primary identifier

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Downloads

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