Ability of the WRF-ARW and HARMONIE-AROME models to detect turbulence related to mountain waves over Central Iberia

Aircraft turbulence is one of the most dangerous meteorological phenomena that can affect aviation safety. This study is focused on the turbulence associated to mountain lee waves in the vicinity of Adolfo Suárez Madrid-Barajas airport (Spain). Sixty-eight mountain lee waves events are selected to s...

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Detalles Bibliográficos
Autores: Díaz Fernández, Javier, Bolgiani, P., Sastre Marugán, Mariano, Santos-Muñoz, D., Valero Rodríguez, Francisco, Farrán, J.I., Martín, M.L.
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/71537
Acceso en línea:https://hdl.handle.net/20.500.14352/71537
Access Level:acceso abierto
Palabra clave:550.3
Central Iberian Zone
Decision trees
Turbulence
Weather forecasting
Aviation safety
Barajas airport
Eddy dissipation rate
HARMONIE-AROME
Lee waves
Meteorological phenomena
Mountain wave
Numerical weather prediction models
Weather research and forecasting
WRF-ARW
aircraft
airport
climate prediction
dissipation
eddy
turbulence
Landforms
Aeronáutica
Geofísica
Meteorología (Física)
3301 Ingeniería y Tecnología Aeronáuticas
2507 Geofísica
Descripción
Sumario:Aircraft turbulence is one of the most dangerous meteorological phenomena that can affect aviation safety. This study is focused on the turbulence associated to mountain lee waves in the vicinity of Adolfo Suárez Madrid-Barajas airport (Spain). Sixty-eight mountain lee waves events are selected to simulate the turbulence with the Weather Research and Forecasting (WRF-ARW) and the HARMONIE-AROME numerical weather prediction models. To study and characterize the turbulence associated, the vertical wind speeds are selected as an important variable and the Eddy Dissipation Rate is estimated. Both models have properly simulated the turbulence and the clear air turbulence, obtaining higher values of turbulence intensity by WRF-ARW than HARMONIE-AROME in the mountain lee waves events. Finally, these results are used to enhance a mountain wave warning decision tree, including the turbulence warning which is validated through several turbulence reports.