The availability of reliable spatial and temporal data at proper spatial and temporal scale about extreme weather events represents a pivotal challenge for supporting Disaster Risk Reduction (DRR) policy and practice. In recent years several gridded observational datasets have been developed for Europe and for specific European countries; these products feature different temporal (from hourly to daily) and spatial (from ≃ 1 km to ≃ 10–20 km) resolutions, covering different time spans, and their reliability is strictly related to the density of station networks from which they derive.
A potential alternative solution to ensure homogeneity and continuity of data is represented by the use of climate reanalysis. In general, a climate reanalysis delivers a complete and consistent picture of the weather and climate of the past as close to reality as possible, by adopting a numerical weather prediction model to assimilate historical observations provided by different sources (satellite, in situ, etc) but not homogeneously distributed around the globe.
The data produced by the reanalysis are widely used and provide many kinds of information, not only about the atmosphere, such as temperature, wind and precipitation, but also about the ocean and the land surface.
Recently, the European Centre for Medium Range Weather Forecast (ECMWF) has released a new generation of reanalysis, acknowledged as ERA5, representing nowadays the most plausible description for current climate. It has a global coverage with a spatial resolution of ≃ 31 km and provide outputs at hourly scale since 1950 up to now. Such features make ERA5 suitable for a wide range of applications such as analyzing the past climate, monitoring climate change, research, education, policy making and business, in sectors such as renewable energy and agriculture. Despite the authoritative relevance of ERA5, its coarse resolution could prevent a reliable adoption for characterizing localized events (e. g., extreme precipitation) especially in complex areas (e.g., mountain or urban environments), confirming the need for highly localized data.
Based on this state-of-the-art, a study recently published on Weather and Climate Extremes led by the CMCC Foundation present a new hourly high-resolution (i.e., at ≃2.2 km) precipitation dataset, labelled as ERA5@2km, obtained by dynamically downscaling ERA5 reanalysis over 20 European cities for the recent past thirty years (1989–2018), with the ambition 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.
“The great added value of our reanalysis-based dataset”, explains Alfredo Reder, CMCC scientist at the REgional Models and Hydrogeological Impacts (REMHI) Research Division, “is the high resolution at 2 km reached that it’s particularly suitable in the view of deriving precipitation characteristics at city scale or at the event scale. ERA5 represents a good reference for general mean statistics (e.g., spatial pattern of annual precipitation, multi-year cycle of monthly precipitation); however, its coarser resolution tends to generate a smoothing of extreme precipitation. ERA5@2km overcomes this constraint by providing a reliable suite of extreme precipitation values for city analyses. A climate dataset such as ERA5@2km may also be a relevant tool to support adaptation strategies and risk assessment.”
“We are so proud of this result, requiring a considerable computational effort (almost two years of simulations)”, comments Paola Mercogliano, REMHI Division Director. “Our study demonstrated the importance of our very high-resolution reanalysis-based climate simulation, at the European level and for different climate conditions. Reanalysis (-based) datasets can indeed fill observational gaps, still existing in wide areas.”
The study evaluates the reliability of this new precipitation dataset for spatial patterns, trends, and extreme values. The evaluation is performed by making use of a set of available high-resolution observational datasets (comparable in terms of spatial and temporal resolution) for a subset of cities (i.e., London, Cologne, and Milan), analysing multiple features of interest such as mean spatial pattern of annual precipitation, multi-year cycle of monthly precipitation, multi-year cycle of hourly precipitation for summer season, and annual maximum hourly precipitation. “Such an evaluation”, adds Alfredo Reder, “provides a clearer understanding about the added value of very high-resolution dynamical downscaling reanalysis, such as ERA5@2km, in terms of localization and magnitude of precipitation events at urban scale confirming its potential importance for the assessment of extreme atmospheric events (such as heavy precipitations). The reliability and coherence of precipitation data provided by ERA5@2km at city scale were validated by the use of high-resolution observational precipitation datasets available over different areas at hourly scale; if our simulations were able to capture and describe the climate of the cities for which observational data were available, we can therefore imagine to apply our dataset even in areas outside the European Union, for which monitoring networks are still poor.”
“This study”, Paola Mercogliano concludes, “represents a first important step: model validation and the demonstration that ERA5@2km is able to understand and represent with great detail some features of the past climate, is the basis from which we will start to realize our scenarios and projections for understanding future climate change”.
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). The authors of this study are CMCC researchers A. Reder, M. Raffa, R. Padulano, G. Rianna, P. Mercogliano at REMHI – Regional Models and Geo-Hydrological Impacts Division.
For further information, read the integral version of the paper:
Reder A., Raffa M., Padulano R., Rianna G., Mercogliano P. Characterizing extreme values of precipitation at very high resolution: An experiment over twenty European cities, Weather and Climate Extremes, Volume 35, 2022. https://doi.org/10.1016/j.wace.2022.100407
Weather and Climate Extremes
Subject of Research
Characterizing extreme values of precipitation at very high resolution: An experiment over twenty European cities