On the characterization of mountain waves and the development of a warning method for aviation safety using WRF forecast
[EN] Mountain wave and icing episodes are adverse meteorological conditions that can affect aviation safety and air traffic management in the vicinity of airports. This study presents a mountain wave characterization performed for the winter months from 2001 to 2010 in the center of the Iberian Peni...
| Autores: | , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universidad de León |
| Repositorio: | BULERIA. Repositorio Institucional de la Universidad de León |
| OAI Identifier: | oai:buleria.unileon.es:10612/23919 |
| Acceso en línea: | https://www.sciencedirect.com/science/article/pii/S0169809521001721 https://hdl.handle.net/10612/23919 |
| Access Level: | acceso abierto |
| Palabra clave: | Física Meteorología Mountain waves Icing Wave clouds WRF model Warning method Decision tree 2501.12 Turbulencia Atmosférica 2501.06 Dinámica Atmosférica 3327.01 Líneas Aéreas y Control del Trafico Aéreo |
| Sumario: | [EN] Mountain wave and icing episodes are adverse meteorological conditions that can affect aviation safety and air traffic management in the vicinity of airports. This study presents a mountain wave characterization performed for the winter months from 2001 to 2010 in the center of the Iberian Peninsula, close to an important orographic barrier and next to the busiest Spanish airport. Sixty-eight episodes were simulated using the Weather Research and Forecasting model (WRF). Five simulated atmospheric variables (wind direction, wind speed, atmospheric stability, liquid water content and temperature) were evaluated in several grid points at 2800 meters above sea level in leeward, windward and over the summit of the mountains. Based on the percentiles and thresholds obtained from the characterization, a decision tree was developed with the aim to forecast and warn the occurrence of mountain waves, wave clouds and icing events. The decision tree and the three warning methods were validated against satellite images. The results show satisfactory scores, with a percentage correct of detection above 70% for the three warnings |
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