Description du projet
Décoder la turbulence dans la troposphère et la stratosphère pour améliorer les prévisions climatiques
La haute troposphère et la basse stratosphère tropicales (TUTLS) sont essentielles à la compréhension des phénomènes météorologiques mondiaux. Cette zone influence la composition de la stratosphère en régulant le transport vertical des aérosols et des gaz à l’état de traces, ainsi que la formation de minces nuages de glace. La simulation de ces processus est complexe, ce qui fait que les modèles actuels ont du mal à représenter avec précision la composition de la basse stratosphère. Financé par le programme Actions Marie Sklodowska-Curie, le projet DISTurbS utilisera divers ensembles de données d’observation provenant de radiosondes à haute résolution, d’avions à haute altitude et de ballons à superpression pour étudier la turbulence de TUTLS. Les activités du projet comprennent la quantification de la fréquence de la turbulence et l’évaluation de son impact sur les nuages de glace, les particules d’aérosol et les gaz à l’état de traces.
Objectif
The tropical upper troposphere and lower stratosphere (TUTLS) plays a critical role in the climate system as the gateway to the global stratosphere. Within this region, tropical upwelling, wave activity, and turbulence control stratospheric composition by modulating the vertical transport of aerosol and trace gases, and the formation of thin ice clouds, which are a net sink of water vapor. This complex interplay between dynamics and chemistry is challenging to simulate, and as a result, atmospheric models struggle to represent the composition of the lower stratosphere in the current and future climate.
The proposed work uses diverse observational datasets collected by high-resolution radiosondes, high-altitude research aircraft, and superpressure balloons to understand the role of turbulence in this system, and to apply that knowledge to the improvement of atmospheric models. The work is divided into four parts: 1) quantifying the frequency of TUTLS turbulence and characterizing its variability, 2) investigating the effect of TUTLS turbulence on ice clouds, aerosol, and trace gases, 3) evaluating TUTLS turbulence in two different types of atmospheric models, and 4) developing a data-driven parameterization of TUTLS turbulence using machine learning.
I will carry out my fellowship at Laboratoire de Météorologie Dynamique (LMD), in Palaiseau, France, under the supervision of Dr. Aurélien Podglajen. My experience with machine learning complements the host's expertise in the theory and measurement of turbulence, and familiarity with the datasets used for this work, facilitating a two-way transfer of knowledge. I will acquire new technical skills in observations and modelling, broaden my physical understanding of the atmosphere, contribute to the planning and execution of a large field campaign, and work with an international network of collaborators, which will critically support my professional ambition of leading my own research group.
Champ scientifique
Mots‑clés
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Régime de financement
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinateur
75794 Paris
France