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http://hdl.handle.net/20.500.11765/15154
Comparison of the WRF and HARMONIE models ability for mountain wave warnings
Título : | Comparison of the WRF and HARMONIE models ability for mountain wave warnings |
Autor : | Díaz Fernández, Javier; Bolgiani, Pedro; Santos Muñoz, Daniel ; Quitián Hernández, Lara; Sastre, Mariano; Valero, Francisco; Farrán Martín, José Ignacio; González-Alemán, Juan Jesús ; Martín, María Luisa |
Palabras clave : | Mountain lee waves; Icing; Lenticular clouds; HARMONIE; WRF; Decision tree; Warning |
Fecha de publicación : | 2022 |
Editor: | Elsevier |
Citación : | Atmospheric Research. 2022, 265, 105890 |
Versión del editor: | https://doi.org/10.1016/j.atmosres.2021.105890 |
Resumen : | Mountain lee waves usually involve aircraft icing and turbulence events. These weather phenomena, in turn, are a threat to aviation safety. For this reason, mountain lee waves are an interesting subject of study for the scientific community. This paper analyses several mountain lee waves events in the south-east of the Guadarrama mountain range, near the Adolfo Suarez Madrid-Barajas airport (Spain), using the Weather Research and Forecasting (WRF) and the HARMONIE-AROME high-resolution numerical models. For this work, simulated brightness temperature from the optimum WRF parametrization schemes and from the HARMONIE are validated using satellite observations to evaluate the performance of the models in reproducing the lenticular clouds associated to mountain lee waves. The brightness temperature probability density shows interesting differences between both models. Following, a mountain wave characterization is performed simulating some atmospheric variables (wind direction, wind speed, atmospheric stability, liquid water content and temperature) in several grid points located in the leeward, windward and over the summit of the mountains. The characterization results are compared for both numerical models and a decision tree is developed for each to forecast and warn the mountain lee waves, lenticular clouds and icing events with a 24 to 48 h lead time. These warnings are validated using several skill scores, revealing similar results for both models. |
Patrocinador: | This work was partially supported by research projects: PID2019- 105306RB-I00, CGL2016-78702-C2-1-R and CGL2016-78702-C2-2-R (SAFEFLIGHT project), FEI-EU-17-16 and SPESMART AND SPESVALE (ECMWF Special Projects). J. Díaz-Fernández acknowledges the grant supported from the MINECO-FPI program (BES-2017). |
URI : | http://hdl.handle.net/20.500.11765/15154 |
ISSN : | 0169-8095 |
Colecciones: | Artículos científicos 2019-2022 |
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AR_Diaz_2022.pdf | 4,89 MB | Adobe PDF | Visualizar/Abrir |
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