Aircraft icing: in-cloud measurements and sensitivity to physical parameterizations

The prediction of supercooled cloud drops in the atmosphere is a basic tool for aviation safety, owing to their contact with and instant freezing on sensitive locations of the aircraft. One of the main disadvantages for predicting atmospheric icing conditions is the acquisition of observational data...

ver descrição completa

Detalhes bibliográficos
Autores: Merino, A., García Ortega, E., Fernández González, S., Díaz Fernández, J., Quitián Hernández, L., Martín, M.L., López, L., Marcos, J.L., Valero Rodríguez, Francisco, Sánchez Roldán, José Luis
Formato: artículo
Fecha de publicación:2019
País:España
Recursos:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/13919
Acesso em linha:https://hdl.handle.net/20.500.14352/13919
Access Level:acceso abierto
Palavra-chave:52
Supercooled liquid water
Modeling system
Part I
Prediction
Forecasts
Precipitation
Microphysics
Simulation
Implementation
Environments
Física atmosférica
2501 Ciencias de la Atmósfera
Descrição
Resumo:The prediction of supercooled cloud drops in the atmosphere is a basic tool for aviation safety, owing to their contact with and instant freezing on sensitive locations of the aircraft. One of the main disadvantages for predicting atmospheric icing conditions is the acquisition of observational data. In this study, we used in‐cloud microphysics measurements taken during 10 flights of a C‐212 research aircraft under winter conditions, during which we encountered 37 regions containing supercooled liquid water. To investigate the capability of the Weather Research and Forecasting model to detect regions containing supercooled cloud drops, we propose a multiphysics ensemble approach. We used four microphysics and two planetary boundary layer schemes. The Morrison parameterization yielded superior results, whereas the planetary boundary layer schemes were essential in evaluating the presence of liquid water content. The Goddard microphysics scheme best detected the presence of ice water content but tended to underestimate liquid water content.