MERIDA HRES: A new high‐resolution reanalysis dataset for Italy.
| Title: | MERIDA HRES: A new high‐resolution reanalysis dataset for Italy. |
|---|---|
| Authors: | Viterbo, Francesca, Sperati, Simone, Vitali, Bruno, D'Amico, Filippo, Cavalleri, Francesco, Bonanno, Riccardo, Lacavalla, Matteo |
| Source: | Meteorological Applications; Nov/Dec2024, Vol. 31 Issue 6, p1-26, 26p |
| Subject Terms: | EXTREME weather, WEATHER hazards, THUNDERSTORMS, FIRE weather, COLD (Temperature) |
| 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. [ABSTRACT FROM AUTHOR] |
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| Database: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: MERIDA HRES: A new high‐resolution reanalysis dataset for Italy. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Viterbo%2C+Francesca%22">Viterbo, Francesca</searchLink><br /><searchLink fieldCode="AR" term="%22Sperati%2C+Simone%22">Sperati, Simone</searchLink><br /><searchLink fieldCode="AR" term="%22Vitali%2C+Bruno%22">Vitali, Bruno</searchLink><br /><searchLink fieldCode="AR" term="%22D'Amico%2C+Filippo%22">D'Amico, Filippo</searchLink><br /><searchLink fieldCode="AR" term="%22Cavalleri%2C+Francesco%22">Cavalleri, Francesco</searchLink><br /><searchLink fieldCode="AR" term="%22Bonanno%2C+Riccardo%22">Bonanno, Riccardo</searchLink><br /><searchLink fieldCode="AR" term="%22Lacavalla%2C+Matteo%22">Lacavalla, Matteo</searchLink> – Name: TitleSource Label: Source Group: Src Data: Meteorological Applications; Nov/Dec2024, Vol. 31 Issue 6, p1-26, 26p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22EXTREME+weather%22">EXTREME weather</searchLink><br /><searchLink fieldCode="DE" term="%22WEATHER+hazards%22">WEATHER hazards</searchLink><br /><searchLink fieldCode="DE" term="%22THUNDERSTORMS%22">THUNDERSTORMS</searchLink><br /><searchLink fieldCode="DE" term="%22FIRE+weather%22">FIRE weather</searchLink><br /><searchLink fieldCode="DE" term="%22COLD+%28Temperature%29%22">COLD (Temperature)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Meteorological Applications is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/met.70011 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 26 StartPage: 1 Subjects: – SubjectFull: EXTREME weather Type: general – SubjectFull: WEATHER hazards Type: general – SubjectFull: THUNDERSTORMS Type: general – SubjectFull: FIRE weather Type: general – SubjectFull: COLD (Temperature) Type: general Titles: – TitleFull: MERIDA HRES: A new high‐resolution reanalysis dataset for Italy. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Viterbo, Francesca – PersonEntity: Name: NameFull: Sperati, Simone – PersonEntity: Name: NameFull: Vitali, Bruno – PersonEntity: Name: NameFull: D'Amico, Filippo – PersonEntity: Name: NameFull: Cavalleri, Francesco – PersonEntity: Name: NameFull: Bonanno, Riccardo – PersonEntity: Name: NameFull: Lacavalla, Matteo IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov/Dec2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 13504827 Numbering: – Type: volume Value: 31 – Type: issue Value: 6 Titles: – TitleFull: Meteorological Applications Type: main |
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