Power utilities are increasingly emphasizing the need for high-resolution reanalysis datasets to develop resilience plans for protecting and managing infrastructure against extreme weather events. In response, Ricerca Sul Sistema Energetico (RSE) S.p.A. created the new MEteorological Reanalysis Italian DAtaset (MERIDA) High-RESolution (HRES) reanalysis, a 4-km resolution dataset with explicit convection specifically designed for Italy. This dataset, publicly available from 1986 to the present, has been evaluated and compared with the previously developed MERIDA reanalysis dataset (7-km resolution over Italy) and ERA5, the global reanalysis driver. The validation is conducted across different scales (i.e., from climatology to single extreme events) and for multiple variables (i.e., 2-meter temperature, daily total precipitation, and 10-meter wind speed). Specific cases, such as a convective storm in July 2016 in northern Italy near Bergamo and the more synoptically driven Vaia storm in October 2018, are analyzed to illustrate the dataset's potential in capturing precipitation and wind extremes. Additionally, the Arbus wildfire event in Sardinia is examined to showcase a multivariable application for assessing fire weather hazards. Through performance maps and statistical analyses, the ability of MERIDA HRES to represent both long-term statistics and extreme events is highlighted. Despite a consistent cold temperature bias across Italy, with higher peaks over mountainous regions, the performance of precipitation and wind outperforms that of both MERIDA and ERA5 in all analyzed cases. These findings demonstrate the significant potential of this product for multiple applications in Italy.

MERIDA HRES: A new high‐resolution reanalysis dataset for Italy / F. Viterbo, S. Sperati, B. Vitali, F. D'Amico, F. Cavalleri, R. Bonanno, M. Lacavalla. - In: METEOROLOGICAL APPLICATIONS. - ISSN 1350-4827. - 31:6(2024 Nov 08), pp. e70011.1-e70011.26. [10.1002/met.70011]

MERIDA HRES: A new high‐resolution reanalysis dataset for Italy

F. Cavalleri;
2024

Abstract

Power utilities are increasingly emphasizing the need for high-resolution reanalysis datasets to develop resilience plans for protecting and managing infrastructure against extreme weather events. In response, Ricerca Sul Sistema Energetico (RSE) S.p.A. created the new MEteorological Reanalysis Italian DAtaset (MERIDA) High-RESolution (HRES) reanalysis, a 4-km resolution dataset with explicit convection specifically designed for Italy. This dataset, publicly available from 1986 to the present, has been evaluated and compared with the previously developed MERIDA reanalysis dataset (7-km resolution over Italy) and ERA5, the global reanalysis driver. The validation is conducted across different scales (i.e., from climatology to single extreme events) and for multiple variables (i.e., 2-meter temperature, daily total precipitation, and 10-meter wind speed). Specific cases, such as a convective storm in July 2016 in northern Italy near Bergamo and the more synoptically driven Vaia storm in October 2018, are analyzed to illustrate the dataset's potential in capturing precipitation and wind extremes. Additionally, the Arbus wildfire event in Sardinia is examined to showcase a multivariable application for assessing fire weather hazards. Through performance maps and statistical analyses, the ability of MERIDA HRES to represent both long-term statistics and extreme events is highlighted. Despite a consistent cold temperature bias across Italy, with higher peaks over mountainous regions, the performance of precipitation and wind outperforms that of both MERIDA and ERA5 in all analyzed cases. These findings demonstrate the significant potential of this product for multiple applications in Italy.
extreme events; Italy; power system resilience; reanalyses validation; regional reanalyses; WRF;
Settore GEOS-04/C - Oceanografia, meteorologia e climatologia
8-nov-2024
https://doi.org/10.1002/met.70011
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1117549
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