EMO-1: an improved version of the high-resolution multi-variable gridded meteorological dataset for Europe

Earth System Science Data Discussions

Abstract

Abstract. High-quality, gridded meteorological datasets are essential for continental-scale hydrological modelling. This paper introduces EMO-1, an advanced version of the European Meteorological Observations (EMO) dataset, developed to support the operational European Flood Awareness System (EFAS) of the Copernicus Emergency Management Service. EMO-1 provides daily and 6-hourly meteorological fields across Europe at a high spatial resolution of 1 arc-minute (~1.5 km) covering the period from 1990 to 2024. The dataset represents a substantial upgrade over its predecessor, EMO-5, integrating observations from 47 data providers and increasing significantly the number of stations used for interpolation. It harmonizes heterogeneous data from in-situ stations and integrates "virtual stations" from high-resolution regional grids and ERA5-Land to minimize data gaps in regions with very low station density. The dataset covers eight variables: daily and 6-hourly total precipitation, minimum and maximum air temperature, 6-hourly average air temperature, daily mean wind speed, solar radiation, and water vapor pressure. A rigorous, two-tier quality control system is applied to filter erroneous observations before processing. For interpolation EMO-1 uses an open-source implementation of the Angular Distance Weighting (ADW) scheme. Cross-validation results demonstrate that ADW maintains interpolation skill comparable to other deterministic methods while offering superior computational efficiency and reproducibility. EMO-1 prioritizes station density and timeliness to serve operational forecasting needs, although the resulting spatial-temporal heterogeneity makes it less suitable for long-term trend analysis. The dataset is openly available under a Creative Commons Attribution 4.0 license via the Joint Research Centre Data Catalogue, with foreseen annual updates and accessible open-source interpolation software to foster transparency and community collaboration.

Authors 12

1. Peter Salamon corresponding

   Joint Research Centre

   Affiliation as printed

   Joint Research Centre (Ispra, Italy)

2. Tim R. Sperzel

   Deutscher Wetterdienst

   Affiliation as printed

   Deutscher Wetterdienst, Offenbach am Main, Germany

3. Goncalo Ramos Gomes
   Affiliation as printed

   WTP (Westpole Italy), Milan, Italy

4. Marco Radke-Fretz Aachen Kisters AG

   Kisters (Germany)

   Affiliation as printed

   KISTERS AG, Aachen, Germany

5. Carina-Denise Lemke
   Affiliation as printed

   City of Regensburg, Regensburg, Germany

6. Carlo Russo
   Affiliation as printed

   UniSystems, Milan, Italy

7. Christoph Schweim Aachen Kisters AG

   Kisters (Germany)

   Affiliation as printed

   KISTERS AG, Aachen, Germany

8. Ervin Zsótér

   European Centre for Medium-Range Weather Forecasts

   Affiliation as printed

   European Center for Medium-Range Weather Forecasts, Reading, UK

9. Alessandro Dosio

   Joint Research Centre

   Affiliation as printed

   European Commission – Joint Research Centre, Ispra, Italy

10. Mariapina Vomero

    University of Tasmania · Institute for Marine and Antarctic Studies

    Affiliation as printed

    Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia

11. Markus Ziese

    Deutscher Wetterdienst

    Affiliation as printed

    Deutscher Wetterdienst, Offenbach am Main, Germany

12. Stefania Grimaldi

    Joint Research Centre

    Affiliation as printed

    European Commission – Joint Research Centre, Ispra, Italy