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DISTurbS

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Dynamic Instabilities, Small-scale Turbulence and impacts on the Stratosphere (D...

Dynamic Instabilities, Small-scale Turbulence and impacts on the Stratosphere (DISTurbS) 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 str... ver más

31/08/2026

CNRS

212K€

Presupuesto del proyecto: 212K€

Líder del proyecto

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-05-17

HORIZON-MSCA-2023-PF-01-01: MSCA Postdoctoral Fellowships 2023 ExpectedOutcome:Project results are expected to contribute to the following outcomes:

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1 Participantes

CNRS

211.75K€ | Lider

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Duración del proyecto: 27 meses Fecha Inicio: 2024-05-17
Fecha Fin: 2026-08-31

Líder del proyecto

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 212K€

Descripción del proyecto 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.

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