CMCC FOUNDATION – EUROPEAN CENTER ON CLIMATE CHANGE
The availability of reliable spatial and temporal data at appropriate spatial and temporal scales on extreme weather events represents an important challenge for supporting policy and practice. disaster risk reduction (DRR). In recent years, some grid observation dataset has been developed for Europe and for specific European countries; These products have temporal (hourly to daily) and spatial (from 1 km to 10–20 km) resolutions, covering different time intervals and their reliability. closely related to the station network density they receive.
A potential alternative to ensure the uniformity and continuity of the data represented by the use of climate analysis. In general, one climate reanalysis yields a complete and consistent picture of past weather and climate as close to reality as possible, by applying numerical weather forecasting models to assimilate historical observations provided by different sources (satellite, on-site, etc.) but not uniformly distributed globally.
The data generated by the reanalysis is widely used and provides a wide range of information, not only about the atmosphere, such as temperature, wind, and precipitation, but also about the oceans and land surfaces.
Recently, the European Center for Medium Range Weather Forecasts (ECMWF) released a new generation of reanalysis, acknowledged as ERA5, represents the current best possible description for the current climate. It has global coverage with spatial resolution of ≃31 km and provides hourly scale output since 1950 to present. Such features make the ERA5 suitable for many applications such as past climate analysis, climate change monitoring, research, education, policy making and business, in areas such as energy and energy. renewables and agriculture. Despite ERA5’s authoritative relevance, its raw resolution may preclude reliable application for characterizing localized events (e.g., extreme rainfall), in particular is in complex areas (e.g. mountain or urban environments), confirming the need for highly localized data.
Based on this modern, research recently published above Extreme weather and climate led by the CMCC Foundation presented a new hourly high resolution (ie, at ≃2.2 km) precipitation dataset, labeled as ERA5 @ 2km, obtained by re-analyzing the dynamic rate reduction ERA5 across 20 European cities over the last thirty years (1989–2018), with the ambition to assist the Disaster Risk Reduction (DRR) community to participate in assess flood risk by providing the basis for city-scale impact analysis, under extreme hourly rainfall conditions.
“Excellent added value of our data set based on our reanalysis”, explains Alfredo Reder, CMCC scientist at the Research Laboratory of REgional Modeling and Hydrogeological Impacts (REMHI), “having a high resolution of up to 2 km is particularly relevant from the perspective of urban-scale precipitation characterization.” street or event size. ERA5 represents a good reference for general average statistics (e.g. spatial patterns of annual precipitation, multi-year cycles of monthly precipitation); however, its coarser resolution tends to produce intense precipitation. ERA5 @ 2km overcomes this limitation by providing a reliable set of extreme precipitation values for city analyses. A climate dataset such as ERA5 @ 2km could also be a suitable tool to support adaptation strategies and risk assessment”.
“We are very proud of this result, which requires a considerable computational effort (nearly two years of simulation)”, comments Paola Mercogliano, Director of the REMHI Division. “Our study demonstrated the importance of climate simulations based on our very high resolution reanalysis, at the European level and for different climate conditions. Reanalytical (base-based) datasets can indeed fill in the observational gap, which still exists in large areas. ”
The study evaluates the reliability of this new precipitation dataset for spatial patterns, trends and extreme values. The evaluation is performed using a set of available high resolution observational datasets (comparable in spatial and temporal resolution) for a subset of cities (e.g.: London, Cologne and Milan), analyzing many features of interest such as the spatially modeled average of annual precipitation, multiyear cycle of monthly precipitation, multiyear cycle of hourly precipitation for summer and annual maximum hourly precipitation. Alfredo Reder adds: “Such assessment”, “provides a clearer understanding of the added value of very high resolution dynamic downscaling analysis, such as ERA5 @ 2km, about The localization and magnitude of precipitation events at the urban scale confirm its potential importance for assessing extreme atmospheric events (such as heavy rainfall). The reliability and consistency of the precipitation data provided by ERA5 @ 2km at the city scale was confirmed using the high resolution observed precipitation datasets available across the regions. different areas on an hourly scale; if our simulations can capture and describe the climates of the cities for which observational data are available, then we can envision to apply our dataset even in regions areas outside the European Union, where surveillance networks are still poor. “
“This study,” concludes Paola Mercogliano, “represents an important first step: validating the model and demonstrating that the ERA5 @ 2km can understand and represent in great detail a number of features of climate over time past, is the basis for us to begin to realize our scenarios and forecasts to understand future climate change”.
The downscaling was carried out under the Contract by Fondazione CMCC to support the Sector Information System on “Disaster Risk Reduction” (see https://climate.copernicus.eu/pluvial-flood-risk-assessment-urban-areas) of the Copernican Climate Change Service (C3S). The authors of this study are CMCC researchers A. Reder, M. Raffa, R. Padulano, G. Rianna, P. Mercogliano at REMHI – Division of Geo-hydrological Impacts and Area Modeling.
For more information, read the integrated version of the article:
Reder A., Raffa M., Padulano R., Rianna G., Mercogliano P. Characterizing extreme values of precipitation at very high resolution: An experiment on twenty European cities., Extreme weather and climateEpisode 35, 2022. https://doi.org/10.1016/j.wace.2022.100407
JOURNEYS
Extreme weather and climate
DOI
RESEARCH SUBJECTS
Do not apply
ARTICLE TITLE
Characterizing extreme values of precipitation at very high resolution: An experiment on twenty European cities.
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