Home About HyMeX
Motivations
Science questions
Observation strategy
Modelling strategy
Target areas
Key documents
Organisation
International coordination
Working groups
Task teams
National contributions
Endorsements
Resources
Database
Data policy
Publications
Education and summer schools
Drifting balloons (BAMED)
SOP web page
Google maps data visualisation
Workshops Projects
ASICS-MED
MOBICLIMEX
MUSIC
IODA-MED
REMEMBER
FLOODSCALE
EXAEDRE
Offers Links Contacts
Science & Task teams
Science teams
Task teams
Implementation plan
Coordination
International Scientific Steering Committee (ISSC)
Executive Committee for Implementation and Science Coordination (EC-ISC)
Executive Committee - France (EC-Fr)
HyMeX France
HyMeX Italy
HyMeX Spain
Archive
by Osinski, R. and Bouttier, F.
Abstract:
An hourly initialized numerical weather prediction model, AROME-NWC, optimized for nowcasting purposes was used in this study to predict the probabilities of occurrence of convective aviation risks by generating an ensemble of time-lagged forecasts. The objective is the prediction of echotop and reflectivity maximum based on simulated 3D radar reflectivity columns. Forecasts were postprocessed using an upscaling of the model output fields in order to account for uncertainties in horizontal positions. Simulated radar reflectivities were bias corrected using a quantile-to-quantile mapping resulting in an improvement of the ensemble performance. A lagged-average-forecast ensemble was then constructed in order to blend mesoscale deterministic and ensemble forecasts, using numerical weather prediction systems that will soon be available in real time. The probabilities of reflectivities predicted by the ensemble are shown to have objective value at thresholds that are meaningful for air traffic control. Possible applications for aviation management purposes are discussed.
Reference:
Osinski, R. and Bouttier, F., 2018: Short-range probabilistic forecasting of convective risks for aviation based on a lagged-average-forecast ensemble approachMeteorological Applications, 25, 105-118.
Bibtex Entry:
@Article{Osinski2018,
  Title                    = {Short-range probabilistic forecasting of convective risks for aviation based on a lagged-average-forecast ensemble approach},
  Author                   = {Osinski, R. and Bouttier, F.},
  Journal                  = {Meteorological Applications},
  Year                     = {2018},

  Month                    = {January},
  Number                   = {1},
  Pages                    = {105-118},
  Volume                   = {25},

  Abstract                 = {An hourly initialized numerical weather prediction model, AROME-NWC, optimized for nowcasting purposes was used in this study to predict the probabilities of occurrence of convective aviation risks by generating an ensemble of time-lagged forecasts. The objective is the prediction of echotop and reflectivity maximum based on simulated 3D radar reflectivity columns. Forecasts were postprocessed using an upscaling of the model output fields in order to account for uncertainties in horizontal positions. Simulated radar reflectivities were bias corrected using a quantile-to-quantile mapping resulting in an improvement of the ensemble performance. A lagged-average-forecast ensemble was then constructed in order to blend mesoscale deterministic and ensemble forecasts, using numerical weather prediction systems that will soon be available in real time. The probabilities of reflectivities predicted by the ensemble are shown to have objective value at thresholds that are meaningful for air traffic control. Possible applications for aviation management purposes are discussed.},
  Copublication            = {2: 2 Fr},
  Doi                      = {10.1002/met.1674},
  ISSN                     = {1469-8080},
  Keywords                 = {aviation, convection, thunderstorm, nowcasting, mesoscale (ensemble) forecast, blending},
  Owner                    = {hymexw},
  Publisher                = {John Wiley \& Sons, Ltd},
  Timestamp                = {2018.03.08},
  Url                      = {http://dx.doi.org/10.1002/met.1674}
}