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Contributors: A. Reder (CMCC), A. Essenfelder (CMCC), P. Mercogliano (CMCC), G. Rianna (CMCC), M. Raffa (CMCC), M. Mancini (CMCC), R. Padulano (CMCC), S. Bagli (GECOSISTEMA), P. Mazzoli (GECOSISTEMA)
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Table 7: Mean, median, and standard deviation carried out by merging for each city data derived from different return periods (data < 0.1 m are removed from the sample)
City | DEM | Mean (m) | Median (m) | St. Dev. (m) |
Amadora | EU-DEM | 0.68 | 0.46 | 0.70 |
Amersfoort | EU-DEM | 0.37 | 0.30 | 0.26 |
Antwerp | EU-DEM | 0.42 | 0.30 | 0.41 |
Athens | EU-DEM | 0.69 | 0.47 | 0.70 |
Bilbao | EU-DEM | 0.82 | 0.53 | 0.91 |
Birmingham | EU-DEM | 0.58 | 0.37 | 0.69 |
Brussels | EU-DEM | 0.58 | 0.40 | 0.53 |
Bucharest | EU-DEM | 0.47 | 0.36 | 0.44 |
Budapest | EU-DEM | 0.52 | 0.39 | 0.44 |
Frankfurt am Main | EU-DEM | 0.52 | 0.39 | 0.47 |
Koln | EU-DEM | 0.40 | 0.31 | 0.31 |
Koln | LiDAR | 0.32 | 0.21 | 0.34 |
London | EU-DEM | 0.45 | 0.32 | 0.45 |
Milan | EU-DEM | 0.43 | 0.34 | 0.34 |
Milan | LiDAR | 0.44 | 0.24 | 0.60 |
Pamplona | EU-DEM | 0.60 | 0.40 | 0.67 |
Pamplona | LiDAR | 0.41 | 0.27 | 0.41 |
Paris | EU-DEM | 0.49 | 0.35 | 0.47 |
Prague | EU-DEM | 0.66 | 0.42 | 0.76 |
Riga | EU-DEM | 0.39 | 0.30 | 0.31 |
Rimini | EU-DEM | 0.45 | 0.35 | 0.36 |
Stockholm | EU-DEM | 0.64 | 0.41 | 0.83 |
Vienna | EU-DEM | 0.52 | 0.34 | 0.61 |
Water Masks
- Description: Binary
- Units: Dimensionless
- Definition: Mask of flooded areas. The values are between 0 (not affected) and 1 (affected) and are function of hourly precipitation events with fixed return periods computed over 30-year (1989-2018) for 20 European cities
- Flag values for missing data: Not Expected
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Table 8: Mean, median, and standard deviation carried out by merging for each city data derived from different return periods (data < 0.1 €/m2 are removed from the sample)
City | DEM | Mean (€/m2) | Median (€/m2) | St. Dev. (€/m2) |
Amadora | EU-DEM | 64.03 | 31.92 | 100.88 |
Amersfoort | EU-DEM | 104.85 | 54.54 | 128.82 |
Antwerp | EU-DEM | 85.59 | 48.11 | 103.95 |
Athens | EU-DEM | 34.14 | 16.83 | 54.44 |
Bilbao | EU-DEM | 65.14 | 38.21 | 92.05 |
Birmingham | EU-DEM | 101.65 | 42.05 | 185.52 |
Brussels | EU-DEM | 124.92 | 63.85 | 179.38 |
Bucharest | EU-DEM | 26.29 | 11.72 | 38.05 |
Budapest | EU-DEM | 26.06 | 13.45 | 35.88 |
Frankfurt am Main | EU-DEM | 47.13 | 19.23 | 76.76 |
Koln | EU-DEM | 49.07 | 21.15 | 71.44 |
Koln | LiDAR | 37.52 | 17.74 | 53.17 |
London | EU-DEM | 95.90 | 44.47 | 142.31 |
Milan | EU-DEM | 33.64 | 17.48 | 49.59 |
Milan | LiDAR | 38.83 | 21.96 | 51.83 |
Pamplona | EU-DEM | 51.51 | 33.88 | 66.05 |
Pamplona | LiDAR | 47.73 | 40.44 | 36.65 |
Paris | EU-DEM | 43.91 | 21.56 | 64.49 |
Prague | EU-DEM | 29.49 | 13.67 | 49.97 |
Riga | EU-DEM | 20.83 | 10.49 | 28.71 |
Rimini | EU-DEM | 40.48 | 15.35 | 58.48 |
Stockholm | EU-DEM | 44.49 | 20.02 | 78.01 |
Vienna | EU-DEM | 39.34 | 20.59 | 61.61 |
Appendix III: Input Data Description
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Table 9: Overview of key characteristics of ERA5-2km Reanalysis
Data Description | |
Main Variables | Total Precipitation (mm) |
Domain | Europe (20 selected cities) (variable domain sizes) |
Horizontal resolution | 0.02° x 0.02° |
Temporal coverage | 1989-01-01 00:00/to/2018-12-31 23:00 |
Temporal resolution | Hourly |
Vertical coverage | Near surface |
Update frequency | None |
Model | Rockel et al., 2008 (DOI: 10.1127/0941-2948/2008/0309) |
Experiment | Evaluation |
Provider | Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC) |
References
Beersma, J., Versteeg, R., and Hakvoort, H.: Neerslagstatistieken voord korte duren, Tech. Rep., STOWA, Amersfoort, Netherlands, 58 pp., 2018.
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