EMO-5: a high-resolution multi-variable gridded meteorological dataset for Europe

• Published in: Earth system science data Vol. 14; no. 7; pp. 3249 - 3272
• Main Authors: Thiemig, Vera, Gomes, Goncalo N, Skøien, Jon O, Ziese, Markus, Rauthe-Schöch, Armin, Rustemeier, Elke, Rehfeldt, Kira, Walawender, Jakub P, Kolbe, Christine, Pichon, Damien, Schweim, Christoph, Salamon, Peter
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 15-07-2022; Copernicus Publications
• Subjects: Data collection; Datasets; Ground stations; Heavy precipitation; High resolution; Hydrologic data; Hydrology; Interpolation; Interpolation methods; Mean temperatures; Meteorological observations; Precipitation; Precipitation data; Quality control; Radiation; Real time; Resolution; Solar radiation; Spatial discrimination; Spatial resolution; Temperature data; Transparency (optical); Uncertainty; Vapor pressure; Vapour pressure; Variables; Water vapor; Water vapour; Weather; Weather stations; Wind speed; Poland; Europe; Spain
• DOI: 10.5194/essd-14-3249-2022
• EISSN: 1866-3516
• ISSN: 1866-3516; 1866-3508

In this paper we present EMO-5 (“European Meteorological Observations”, spatial resolution of 5 km), a European high-resolution, (sub-)daily, multi-variable
meteorological dataset built on historical and real-time observations
obtained by integrating data from 18 964 ground weather stations, four
high-resolution regional observational grids (i.e. CombiPrecip, ZAMG – INCA,
EURO4M-APGD, and CarpatClim), and one global reanalysis
(ERA-Interim/Land). EMO-5 includes the following at daily resolution: total precipitation,
temperatures (minimum and maximum), wind speed, solar radiation, and water
vapour pressure. In addition, EMO-5 also makes available 6-hourly
precipitation and mean temperature data. The raw observations from the ground
weather stations underwent a set of quality controls before SPHEREMAP and
Yamamoto interpolation methods were applied in order to estimate for each
5×5 km grid cell the variable value and its affiliated uncertainty,
respectively. The quality of the EMO-5 precipitation data was evaluated
through (1) comparison with two regional high-resolution datasets (i.e.
seNorge2 and seNorge2018), (2) analysis of 15 heavy precipitation events,
and (3) examination of the interpolation uncertainty. Results show that
EMO-5 successfully captured 80 % of the heavy precipitation events, and
that it is of comparable quality to a regional high-resolution dataset. The
availability of the uncertainty fields increases the transparency of the
dataset and hence the possible usage. EMO-5 (version 1) covers the time
period from 1990 to 2019, with a near real-time release of the latest
gridded observations foreseen with version 2. As a product of Copernicus,
the EU's Earth Observation Programme, the EMO-5 dataset is free and open, and
can be accessed at https://doi.org/10.2905/0BD84BE4-CEC8-4180-97A6-8B3ADAAC4D26 (Thiemig et
al., 2020).