EURADCLIM: The European climatological high-resolution gauge-adjusted radar rainfall dataset

Accurate precipitation information at high spatiotemporal resolutions is needed for many scientific domains and applications but is often lacking. This is also the case in Europe. While the EUMETNET OPERA ground-based weather radar composite provides strong coverage at the km scale (https://www.eumetnet.eu/activities/observations-programme/current-activities/opera/), weather radars generally underestimate precipitation by tens or even more than 50 percent. Moreover, many smaller areas suffer from severe overestimation due to non-meteorological echoes during dry weather (e.g., signal interference, or ground echoes caused by obstacles or refraction of the radar beam). In contrast, rain gauges often provide accurate local rainfall estimates, but their network densities are usually too sparse to capture the spatial rainfall variability, especially at the sub-daily time scale. The best of two worlds is combined if radar precipitation images are merged with rain gauge data.

This was addressed by the project EUropean RADar CLIMatology (EURADCLIM), which was funded by KNMI’s multi-annual strategic research programme. The main outcome is the climatological dataset EURADCLIM of 1-h and 24-h precipitation accumulations at a 2-km grid, which covers 78% of geographical Europe, currently for the period 2013 through 2022. The starting point is the OPERA gridded radar dataset of 15-min rainfall rates, which is based on data from approximately 141 radars. In EURADCLIM, methods are applied to further remove non-meteorological echoes from these images. Subsequently, the radar composites are merged with a pan-European rain gauge dataset from the European Climate Assessment & Dataset (ECA&D; https://www.ecad.eu/), containing data from potentially 8300 locations from National Meteorological and Hydrological Services. Descriptions of the used datasets, the methodology to derive EURADCLIM, and an evaluation showing its value and limitations have been published for version 1, which covers 2013 through 2020 (1). The usefulness of EURADCLIM for quantitative precipitation estimation is confirmed. Figure 1 shows an example of a precipitation climatology derived from EURADCLIM: the 10-year mean 1-h precipitation accumulation. The EURADCLIM 1-h and 24-h precipitation datasets are publicly available from the KNMI Data Platform (2,3). Tools are publicly available to accumulate and visualize EURADCLIM data and to perform climatological analyses (6). This helps end users to explore and analyze EURADCLIM. We expect to rerun EURADCLIM once a year over the entire period, using all available ECA&D rain gauge data, and extend it with one year of data. This will result in a new version.

EURADCLIM's strategic value encompasses:

- Much better reference for evaluation of weather prediction model output, Regional Climate Model simulations, satellite precipitation products (4), and opportunistic sensing data (e.g., from commercial microwave links between telephone towers or from personal weather stations). This also allows for improving quality control and retrieval algorithms.

- Better monitoring of (trends in) precipitation extremes and their spatial extent. This can contribute to improved understanding of the causes of these events.

- Better evaluation of extreme precipitation events and their impact (e.g., landslides, flooding). Specifically, EURADCLIM can be used as input for hydrological models in order to improve these models.

Within the project, the EURADCLIM version 1 dataset has been employed to validate satellite precipitation products for a variety of European climates (4). Moreover, a preliminary study has been performed on the relationship between extreme precipitation and dew point temperature for part of western Europe. In the framework of a MSc thesis, an exploratory analysis has been performed on merging OPERA radar accumulations with a satellite precipitation product. Such an approach could be relevant to increase the quality of radar precipitation datasets for regions lacking rain gauge data. Finally, a large crowdsourced rain gauge dataset has been merged with 1-h OPERA radar precipitation accumulations and its quality has been compared to that of EURADCLIM version 1. This shows the potential of personal weather station data for improving (real-time) radar precipitation products (5).

Figure 1: Map of mean hourly precipitation over the period 2013-2022 based on the EURADCLIM dataset. Map made with Natural Earth. Free vector and raster map data © naturalearthdata.com

Main output of the EURADCLIM project:

  1. Scientific manuscript (EURADCLIM version 1): Overeem, A., van den Besselaar, E., van der Schrier, G., Meirink, J. F., van der Plas, E., and Leijnse, H.: EURADCLIM: The European climatological high-resolution gauge-adjusted radar precipitation dataset, Earth Syst. Sci. Data, 15, 1441–1464, https://doi.org/10.5194/essd-15-1441-2023, 2023
  2. Dataset (EURADCLIM version 2): Overeem, A., van den Besselaar, E., van der Schrier, G., Meirink, J., van der Plas, E., and Leijnse, H.: EURADCLIM: The European climatological gauge-adjusted radar precipitation dataset (1-h accumulations), https://doi.org/10.21944/ymrk-mr24, https://dataplatform.knmi.nl/dataset/rad-opera-hourly-rainfall-accumulation-euradclim-2-0, 2024a.
  3. Dataset (EURADCLIM version 2): Overeem, A., van den Besselaar, E., van der Schrier, G., Meirink, J., van der Plas, E., and Leijnse, H.: EURADCLIM: The European climatological gauge-adjusted radar precipitation dataset (24-h accumulations), https://doi.org/10.21944/kcd7-3y59, https://dataplatform.knmi.nl/dataset/rad-opera-24h-rainfall-accumulation-euradclim-2-0, 2024b.
  4. Scientific manuscript: Van der Plas, E., Overeem, A., Meirink, J. F., Leijnse, H., and Bogerd, L.: Evaluation of IMERG and MSG-CPP precipitation estimates over Europe using EURADCLIM: a gauge-adjusted European composite radar dataset, Journal of Hydrometeorology, 25, 1177–1190, https://doi.org/10.1175/JHM-D-23-0184.1, 2024c.
  5. Scientific manuscript: Overeem, A., Leijnse, H., van der Schrier, G., van den Besselaar, E., Garcia-Marti, I., and de Vos, L. W.: Merging with crowdsourced rain gauge data improves pan-European radar precipitation estimates, Hydrol. Earth Syst. Sci., 28, 649–668, https://doi.org/10.5194/hess-28-649-2024, 2024.
  6. Overeem, A.: EURADCLIM-tools (v.1.0): Tools to accumulate and visualize OPERA & EURADCLIM radar data and to perform climatological analyses, Zenodo [code], https://doi.org/10.5281/zenodo.7473816, 2022.