Descrizione del progetto
Decodificare la turbolenza nella troposfera e nella stratosfera per migliorare le previsioni climatiche
La troposfera superiore tropicale e la stratosfera inferiore (TUTLS) sono essenziali per la comprensione degli schemi meteorologici globali. Quest’area influenza la composizione stratosferica regolando il trasporto verticale di aerosol e gas traccia, nonché la formazione di sottili nubi di ghiaccio. La simulazione di questi processi è complessa e rende difficile per i modelli attuali rappresentare accuratamente la composizione della stratosfera inferiore. Finanziato dal programma di azioni Marie Sklodowska-Curie, il progetto DISTurbS utilizzerà diversi set di dati di osservazione provenienti da radiosonde ad alta risoluzione, aeromobili ad alta quota e palloni aerostatici a superpressione per studiare la turbolenza nella troposfera superiore tropicale e nella stratosfera inferiore. Le attività del progetto comprendono la quantificazione della frequenza di turbolenza e la valutazione del suo impatto sulle nubi di ghiaccio, sulle particelle di aerosol e sui gas traccia.
Obiettivo
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.
Campo scientifico
Parole chiave
Programma(i)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Meccanismo di finanziamento
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinatore
75794 Paris
Francia