Characterizing extreme values of precipitation at very high resolution: An experiment over twenty European cities

• DOI: 10.1016/j.wace.2022.100407
• Publication Date: 2022-01-20T10:36:10Z
• Authors: A. Reder; M. Raffa; R. Padulano; G. Rianna; P. Mercogliano
• Keywords: ERA5 reanalysis; Dynamical downscaling, Climate reanalysis, ERA5 reanalysis, Convection permitting scale, IDF curves, Sub-daily extreme rainfall, Disaster risk reduction; 0207 environmental engineering; IDF curves; Sub-daily extreme rainfall; 02 engineering and technology; Dynamical downscaling; Convection permitting scale; 13. Climate action; Meteorology. Climatology; 11. Sustainability; Disaster risk reduction; QC851-999; Climate reanalysis

The paper presents a new hourly high-resolution (i.e., at 0.02°, ≃2.2 km) precipitation dataset, labelled as ERA5@2km, obtained by dynamically downscaling ERA5 reanalysis at convection permitting scale (CPS) over 20 European cities for the recent past thirty years (1989–2018). The downscaling activity is performed within the framework of the Contract implemented by Fondazione CMCC to support Sectoral Information System about “Disaster Risk Reduction” (see https://climate.copernicus.eu/pluvial-flood-risk-assessment-urban-areas) of Copernicus Climate Change Service (C3S). Specifically, such an additional precipitation dataset is developed to provide precipitation data for estimating expected precipitations at fixed return periods used as input for pluvial flooding risk analysis where hazard (inundated areas, water levels) and risk (estimated damages) are assessed. The ambition is to support the Disaster Risk Reduction (DRR) community involved in pluvial flood risk assessment by providing a basis for impact analysis at city scale, in terms of extreme hourly precipitation, that matches with the expected spatial and temporal requirements. In this work, ERA5@2km precipitation dataset is introduced for the first time and its reliability and coherence are evaluated as for spatial patterns and trends as for extreme values against a set of available high-resolution observational datasets (comparable in terms of spatial and temporal resolution). Such an evaluation provides a clearer understanding about the added value of very high-resolution (VHR) dynamical downscaling reanalysis in terms of localization and magnitude of precipitation events at urban scale, confirming a general and relevant added value of this new configuration for the assessment of extreme atmospheric events (such as heavy precipitations).