EURADCLIM: The European climatological high-resolution gauge-adjusted radar precipitation dataset
- Royal Netherlands Meteorological Institute, Utrechtseweg 297, 3731 GA De Bilt, The Netherlands
- Royal Netherlands Meteorological Institute, Utrechtseweg 297, 3731 GA De Bilt, The Netherlands
Abstract. The European climatological high-resolution gauge-adjusted radar precipitation dataset, EURADCLIM, addresses the need for an accurate (sub-)daily precipitation product covering 78 % of Europe at high spatial resolution. A climatological dataset of 1-h and 24-h precipitation accumulations on a 2-km grid is derived for the period 2013 through 2020. The starting point is the European Meteorological Network (EUMETNET) Operational Program on the Exchange of weather RAdar Information (OPERA) gridded radar dataset of 15-min instantaneous surface rain rates, which is based on data from, on average, 138 ground-based weather radars. First, methods are applied to further remove non-meteorological echoes from these composites by applying two statistical methods and a satellite-based cloud type mask. Second, the radar composites are merged with the European Climate Assessment & Dataset (ECA&D) with potentially ~7700 rain gauges from National Meteorological and Hydrological Services (NMHS) in order to substantially improve its quality. Characteristics of the radar, rain gauge and satellite datasets are presented, as well as a detailed account of the applied algorithms. The clutter removal algorithms are effective, while removing few precipitation echoes. The usefulness of EURADCLIM for quantitative precipitation estimation (QPE) is confirmed by comparing against rain gauge accumulations employing scatter density plots, statistical metrics, and a spatial verification. These show a strong improvement with respect to the original OPERA product. The potential of EURADCLIM to derive pan-European precipitation climatologies and to evaluate extreme precipitation events is shown. Specific attention is given to remaining artefacts in and limitations of EURADCLIM. Finally, it is recommended to further improve EURADCLIM by applying algorithms to 3D instead of 2D radar data, and by obtaining more rain gauge data for the radar-gauge merging.The EURADCLIM 1-h and 24-h precipitation datasets are publicly available at https://doi.org/10.21944/7ypj-wn68 (Overeem et al., 2022a) and https://doi.org/10.21944/1a54-gg96 (Overeem et al., 2022b).
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Aart Overeem et al.
Status: final response (author comments only)
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RC1: 'Comment on essd-2022-334', Anonymous Referee #1, 09 Nov 2022
The manuscript presents a new precipitation dataset that covers most parts of Europe and is based on the OPERA gridded radar dataset. The algorithms for filtering non-meteorological echoes are described and evaluated as well as the adjustment to gauge data. Limitations of the dataset are discussed and ways to improve the climatological precipitation dataset are given.
The manuscript fits in the scope of ESSD, it is well written and clearly structured. The described new European radar climatology is unique, of high interest and importance for the community and allows for a variety of applications and studies. Â I recommend publishing the manuscript after taking the following (minor) suggestions and comments into account:
- 3, L.83-85: Does that mean, that in case of 10 minute temporal resolution the 10-min file from 10:10 UTC is used for the 10:15 UTC composite?
- 11, Eq.1: Why is Sw,g set to the value of T (0.25 mm) in case it is lower than T? In line 207 the authors say that 1-h radar-gauge pairs are only used for merging if the gauge precipitation exceeds 0.25 mm. Wouldn’t that mean that no factors should be computed in case Sw,g is lower than T?
- 12, L. 235-241: An example of the adjustment fields for v = 100000 and v = 0 would be beneficial to understand the influence of the mean-field bias and the local spatial adjustment.
- 20, Fig.8: It might be better to use the same colourbar for OPERA and EURADCLIM. Especially in the upper example the smaller range of precipitation values in the colourbar makes the EURADCLIM product look worse than the OPERA product. Maybe a logarithmic scale can help to compensate the different ranges of precipitation values.
- 22, Section 4.4: Have the authors compared their results to the corresponding national radar data sets? How similar are the extreme values in EURADCLIM and the national products?
- AC1: 'Reply on RC1', Aart Overeem, 12 Dec 2022
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RC2: 'Comment on essd-2022-334', Anonymous Referee #2, 15 Dec 2022
- AC2: 'Reply on RC2', Aart Overeem, 27 Jan 2023
Aart Overeem et al.
Data sets
EURADCLIM: The European climatological gauge-adjusted radar precipitation dataset (1-h accumulations) Aart Overeem, Else van den Besselaar, Gerard van der Schrier, Jan Fokke Meirink, Emiel van der Plas, Hidde Leijnse https://doi.org/10.21944/7ypj-wn68
EURADCLIM: The European climatological gauge-adjusted radar precipitation dataset (24-h accumulations) Aart Overeem, Else van den Besselaar, Gerard van der Schrier, Jan Fokke Meirink, Emiel van der Plas, Hidde Leijnse https://doi.org/10.21944/1a54-gg96
Model code and software
EURADCLIM-tools Aart Overeem https://github.com/overeem11/EURADCLIM-tools
Aart Overeem et al.
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