Articles | Volume 14, issue 7
https://doi.org/10.5194/essd-14-3249-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-3249-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
EMO-5: a high-resolution multi-variable gridded meteorological dataset for Europe
Vera Thiemig
Joint Research Centre, European Commission, Ispra, 21027, Italy
Goncalo N. Gomes
Joint Research Centre, European Commission, Ispra, 21027, Italy
Jon O. Skøien
Joint Research Centre, European Commission, Ispra, 21027, Italy
Markus Ziese
Global Precipitation Climatology Centre, Deutscher Wetterdienst,
Offenbach, 63067, Germany
Armin Rauthe-Schöch
Global Precipitation Climatology Centre, Deutscher Wetterdienst,
Offenbach, 63067, Germany
Elke Rustemeier
Global Precipitation Climatology Centre, Deutscher Wetterdienst,
Offenbach, 63067, Germany
Kira Rehfeldt
Global Precipitation Climatology Centre, Deutscher Wetterdienst,
Offenbach, 63067, Germany
Jakub P. Walawender
Global Precipitation Climatology Centre, Deutscher Wetterdienst,
Offenbach, 63067, Germany
Faculty of Geography, Philipps University of Marburg, Marburg, 35032,
Germany
Christine Kolbe
Global Precipitation Climatology Centre, Deutscher Wetterdienst,
Offenbach, 63067, Germany
Faculty of Geography, Philipps University of Marburg, Marburg, 35032,
Germany
Damien Pichon
Kisters France SAS, Rueil-Malmaison, 92500, France
Christoph Schweim
Kisters AG, Aachen, 52076, Germany
Joint Research Centre, European Commission, Ispra, 21027, Italy
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The study proposes a new framework, named FLEXTH, to estimate flood water depth and improve satellite-based flood monitoring using topographical data. FLEXTH is readily available as a computer code, offering a practical and scalable solution for estimating flood depth quickly and systematically over large areas. The methodology can reduce the impacts of floods and enhance emergency response efforts, particularly where resources are limited.
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CEMS_SurfaceFields_2022 dataset is a new set of high-resolution maps for land type (e.g. lake, forest), soil properties and population water needs at approximately 2 and 6 km at the Equator, covering Europe and the globe (excluding Antarctica). We describe what and how new high-resolution information can be used to create the dataset. The paper suggests that the dataset can be used as input for river, weather or other models, as well as for statistical descriptions of the region of interest.
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In August and September 2022, millions of people were impacted by a severe flood event in Pakistan. Since many roads and other infrastructure were destroyed, satellite data were the only way of providing large-scale information on the flood's impact. Based on the flood mapping algorithm developed at Technische Universität Wien (TU Wien), we mapped an area of 30 492 km2 that was flooded at least once during the study's time period. This affected area matches about the total area of Belgium.
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Real-time river discharge forecasts and reforecasts from the Global Flood Awareness System (GloFAS) have been made publicly available, together with an evaluation of forecast skill at the global scale. Results show that GloFAS is skillful in over 93 % of catchments in the short (1–3 d) and medium range (5–15 d) and skillful in over 80 % of catchments in the extended lead time (16–30 d). Skill is summarised in a new layer on the GloFAS Web Map Viewer to aid decision-making.
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Short summary
EMO-5 is a free and open European high-resolution (5 km), sub-daily, multi-variable (precipitation, temperatures, wind speed, solar radiation, vapour pressure), multi-decadal meteorological dataset based on quality-controlled observations coming from almost 30 000 stations across Europe, and is produced in near real-time. EMO-5 (v1) covers the time period from 1990 to 2019. In this paper, we have provided insight into the source data, the applied methods, and the quality assessment of EMO-5.
EMO-5 is a free and open European high-resolution (5 km), sub-daily, multi-variable...
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