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Reference : UMR3589-FRACEA-002
Workplace : TOULOUSE
Date of publication : Monday, May 18, 2020
Scientific Responsible name : Xavier Ceamanos (CNRM) et Jean-Luc Attié (LA)
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 October 2020
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly
Description of the thesis topic
The actions of nature and man give rise to the injection of fine particles of different origins in the lower layers of the atmosphere. These particles, called aerosols, are of great importance in topics related to climate, numerical weather prediction, defense, the energy industry or air transport. For example, aerosols have an impact on the radiative balance of the earth due to their absorption and scattering of solar radiation incident on the earth. This extinction of radiation will be more or less important depending on the content and chemical composition of the particles, which can range from desert dust to carbon particles emanating from anthropogenic pollution or forest fires. For example, it is known that different types of aerosols can have a warming or cooling effect on the planet because of their different optical properties (Russell et al., 2002).
Uncertainties related to the spatial distribution and the impacts of the different classes of aerosols still exist today (Boucher et al., 2014). These uncertainties become especially important in the case of extreme events such as sandstorms, biomass fires or pollution episodes. These events are linked to strong impacts and are likely to evolve in the future. For example, the trends estimated today result in a decrease in dust storms (Evan et al., 2016) but an increase in biomass fires (Keywood et al., 2013), which would accelerate global warming.
In this context, there is today the need to detect, characterize and map the different types of aerosols at fine spatial and temporal scales. Passive spatial remote sensing operating in the visible and near infrared can provide this information through the use of inversion methods. These mathematical methods are often applied by considering predefined types of aerosols that group together average families of particles. However, the great heterogeneity of aerosols and the presence of mixtures of several types of particles can invalidate the use of these predefined types, which are defined by average optical properties.
During the past decade, the CNRM has developed expertise on the retrieval of the daily-averaged Aerosol Optical Thickness (AOD), which is closely related to aerosol content (Carrer et al., 2010 and 2014). The inversion method developed as part of this work was applied to the observations of the SEVIRI imager aboard the Meteosat Second Generation (MSG) satellite of the EUMETSAT agency. Currently, the CNRM is working on the retrieval at the frequency of SEVIRI (i.e. every 15 minutes) in order to have access to the diurnal cycle of the AOD. However, it is nowadays difficult to provide detailed information on other optical properties related to the chemical composition of these particles, whereas it is often necessary to correctly estimate the AOD.
The work to be conducted in this PhD aims to answer the following questions. Which information regarding aerosol composition can be determined from space? Is it possible to retrieve the optical properties that are related to the nature of aerosol particles (e.g., single scattering albedo or asymmetry parameter) and track their evolution in time and space? This study will be based on observations provided by the European geostationary platforms Meteosat, which allow aerosol tracking at a fine time scale. Initial work showing the potential of geostationary satellites for the restitution of aerosol properties other than AOD already exists (Yoshida et al., 2018, Luffarelli and Govaerts, 2019). One of the originalities of the proposed work is to rely on the current mission MSG to investigate the contribution of the future mission Meteosat Third Generation (MTG), which will be equipped with the FCI imager and which should make possible a better characterization of aerosols (Aoun, 2016, Descheemaecker et al., 2018).
Full details on the PhD topic can be found here: http://www.adum.fr/script/downloadfile.pl?ID=29832&type=78
CNRM (Université de Toulouse, Météo-France, CNRS), Toulouse, France
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