Research & development

Our unique task is the gathering of information about the atmosphere and the subsurface and the translation of that information to risks to the community



  • Crowdsourced data matches well with official data

    Crowdsourced wind observations can be an invaluable data resource for meteorological studies

    Can citizen scientists help KNMI to improve forecasts and warnings for extreme wind events? The answer is yes according to the new paper by Jieyu Chen, Dr. Kirien Whan, and Dr. Kate Saunders, published in the Quarterly Journal of the Royal Meteorological Society. The research shows that by checking the quality of the data and adjusting for biases there is value in crowdsourced data and that it can be used to complement official observations.
  • topography map of java

    Calibration of seasonal precipitation forecasts in Java (Indonesia) using bias-corrected precipitation and climate indices

    Seasonal rainfall forecasts help farmers make informed planning decisions about their livelihoods. Skilful rainfall forecasts can improve farming strategies in rain-fed agricultural production. In Indonesia, large-scale modes of climate variability have strong relationships with the seasonal rainfall. This makes them natural candidates for use as potential predictors in a statistical post-processing application. It is not known whether using climate indices as additional predictors in the statistical post-processing of ECMWF Seasonal Forecast System 5 (SEAS5) precipitation can improve skill. Lead author Dian Nur Ratri says "Indices of El NiƱo and the Indian Ocean Dipole are not needed as extra predictors to improve monthly precipitation forecasts for the first lead month in Java - Indonesia, except for September. However, for longer lead times in September and October, advanced statistical models that use only the climate indices are as skilful as models that use bias-corrected precipitation as the inputs".
  • A figure showing that some WOW-NL stations recorded much more rainfall than the AWS station in Maastricht

    Insights about extreme precipitation in Limburg from crowdsourced data

    Weather observations are the cornerstone of climatological and meteorological services. Crowdsourced data can complement the existing official KNMI network by providing observations with both a high spatial and temporal resolution. We examine precipitation on July 13th and 14th measured by the WOW-NL network to show how the acquisition of crowdsourced measurements can help KNMI to better understand extreme events.

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About KNMI

The Royal Netherlands Meteorological Institute (KNMI)

Is the dutch national weather service. Primary tasks of KNMI are weather forecasting, and monitoring of weather, climate and seismic activity. KNMI is also the national research and information centre for meteorology, climate, air quality, and seismology