Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11765/14730
Towards nowcasting in Europe in 2030
Title: Towards nowcasting in Europe in 2030
Authors: Bojinski, StephanBlaauboer, DickCalbet, XavierDe Coning, EstelleDebie, FransMontmerle, ThibautNietosvaara, VesaNorman, KatieBañón Peregrín, Luis María ORCID RESEARCHERID Autor AEMETSchmid, FranziskaStrelec Mahovic, NatasaWapler, Kathrin
Keywords: European Weather Cloud; High-resolution NWP; Meteosat Third Generation; Nowcasting; Probabilistic forecasts; Seamless prediction
Issue Date: 2023
Publisher: Wiley Open Access; Royal Meteorological Society
Citation: Meteorological Applications. 2023, 30(4), e2124
Publisher version: https://doi.org/10.1002/met.2124
Abstract: The increasing impact of severe weather over Europe on lives and weathersensitive economies can be mitigated by accurate 0–6 h forecasts (nowcasts), supporting a vital ‘last line of defence’ for civil protection and many other applications. Recognizing lack of skill in some complex situations, often at convective and local sub-kilometre scales and associated with rare events, we identify seven recommendations with the aim to improve nowcasting in Europe by the national meteorological and hydrological services (NMHSs) by 2030. These recommendations are based on a review of user needs, the state of the observing system, techniques based on observations and high-resolution numerical weather models, as well as tools, data and infrastructure supporting the nowcasting community in Europe. Denser and more accurate observations are necessary particularly in the boundary layer to better characterize the ingredients of severe storms. A key driver for improvement is next-generation European satellite data becoming available as of 2023. Seamless ensemble prediction methods to produce enhanced weather forecasts with 0–24 h lead times and probabilistic products require further development. Such products need to be understood and interpreted by skilled forecasters operating in an evolving forecasting context.
URI: http://hdl.handle.net/20.500.11765/14730
ISSN: 1350-4827
1469-8080
Appears in Collections:Artículos científicos 2023-2026


Files in This Item:
  File Description SizeFormat 
MA_Bojinski_2023.pdf
17,71 MBAdobe PDFThumbnail
View/Open
Show full item record



Items in Arcimis are protected by Creative Commons License, unless otherwise indicated.

Arcimis Repository
Nota Legal Contacto y sugerencias