Wind kinetic energy climatology and effective resolution for the ERA5 reanalysis

ERA5 represents the state of the art for atmospheric reanalyses and is widely used in meteorological and climatological research. In this work, this dataset is evaluated using the wind kinetic energy spectrum. Seasonal climatologies are generated for 30 degrees latitudinal bands in the Northern Hemi...

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Detalhes bibliográficos
Autores: Bolgiani, Pedro, Calvo Sancho, C., Díaz Fernández, Javier, Quitián Hernández, Lara, Santos Muñoz, D., Farrán, J. I., González Alemán, Juan Jesús, Valero Rodríguez, Francisco, Martín, M. L., Sastre Marugán, Mariano
Tipo de documento: artigo
Data de publicação:2022
País:España
Recursos:Universidad Complutense de Madrid (UCM)
Repositório:Docta Complutense
Idioma:inglês
OAI Identifier:oai:docta.ucm.es:20.500.14352/71691
Acesso em linha:https://hdl.handle.net/20.500.14352/71691
Access Level:Acceso aberto
Palavra-chave:550.3
Wave-number spectra
Numerical weather prediction
Stratified turbulence
Convective systems
Upper troposphere
Temperature
Africa
Variability
Forecasts
Geofísica
2507 Geofísica
Descrição
Resumo:ERA5 represents the state of the art for atmospheric reanalyses and is widely used in meteorological and climatological research. In this work, this dataset is evaluated using the wind kinetic energy spectrum. Seasonal climatologies are generated for 30 degrees latitudinal bands in the Northern Hemisphere (periodic domain) and over the North Atlantic area (limited-area domain). The spectra are also assessed to determine the effective resolution of the reanalysis. The results present notable differences between the latitudinal domains, indicating that ERA5 is properly capturing the synoptic conditions. The seasonal variability is adequate too, being winter the most energetic, and summer the least energetic season. The limited area domain results introduce a larger energy density and range. Despite the good results for the synoptic scales, the reanalysis' spectra are not able to properly reproduce the dissipation rates at mesoscale. This is a source of uncertainties which needs to be taken into account when using the dataset. Finally, a cyclone tropical transition is presented as a case study. The spectrum generated shows a clear difference in energy density at every wavelength, as expected for a highly-energetic status of the atmosphere.