EGU General Assembly 2020
© Author(s) 2020. This work is distributed underthe Creative Commons Attribution 4.0 License.
Object-based aviaton convection forecasts from global ensemble model
- Centre National de la Recherche Météorologique (CNRM)
In the framework of a single european sky and to improve Air Traffic Flow and Capacity
Management, involved actors need to share a common situational awareness of the airspace
conditions. These include the meteorological conditions with a focus on weather phenomena with a
strong impact on air traffic and network operations such as convection.
Within this framework, Météo-France is working to provide a new product of convection forecasts
based on ensemble prediction system (EPS) and global model, and is developing a similarity-based
method (Rottner et al., 2019) at Centre National de la Recherche Météorologique (CNRM).
The method aims to detect areas where meteorological conditions are homogeneous which are
called called objects. The latter are defined by a reference histogram representing the
meteorological phenomena to be detected and so are physically consistent. The similarity-based
method can be applied to each member of a EPS. The results can be summarized by a map that
contains the information predicted by all members of the ensemble. Thus, it provides spatialization
for local weather events. This method is currently tested to detect rainfall objects, however we can
apply this method to detect other event type, like convection. To discriminate the convection
characteristic within these rainfall objects, we use a diagnostic of cloud top pressure extracted from
global model outputs. Furthermore, to improve the convection forecast accuracy, the similarity-
based method can also be applied to several models to create a composite of convection forecast.
Météo-France will soon deliver a convection potential product to aeronautical users.
How to cite: Warnan, A.: Object-based aviaton convection forecasts from global ensemble model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6937, https://doi.org/10.5194/egusphere-egu2020-6937, 2020