Etude par modélisation et assimilation de données d'un capteur infrarouge géostationnaire pour la qualité de l'air

L'objectif de cette thèse porte sur la définition d'un capteur géostationnaire infrarouge pour l'observation de la composition chimique de la basse troposphère et l'évaluation de la valeur ajoutée de cet instrument afin de caractériser la variabilité de la moyenne et basse troposphère des principaux polluants et d'améliorer l'observation et les prévisions de la qualité de l'air. Nous nous sommes intéressés à deux polluants importants: l'ozone troposphérique en raison de son impact sur la santé humaine, les écosystèmes et le climat, et le monoxyde de carbone (CO) qui est un traceur de pollution nous renseignant sur les sources d'émissions et les processus de transport. Dans un premier temps, une évaluation d'un schéma linéaire pour la chimie du CO a été effectuée sur une période d'un an et demi en comparaison avec un schéma chimique détaillé (RACMOBUS) et différents types d'observations troposphériques et stratosphériques (satellitaires, aéroportées). L'intérêt principal de ce schéma est son faible coût en temps de calcul qui permet une assimilation sur de longues périodes de jeux de données de CO. L'assimilation de données MOPITT (Measurements Of Pollution In The Troposphere) dans ce schéma a d'ailleurs permis d'évaluer la valeur ajoutée de données d'observations infrarouges à l'échelle globale. Ensuite, les caractéristiques optimales du capteur géostationnaire infrarouge ont été définies en réalisant des études d'inversion de spectres atmosphériques pour sonder l'ozone et le CO pour la qualité de l'air, le but étant d'avoir un capteur techniquement et économiquement faisable, capable de sonder la basse troposphère. Le contenu en information de cet instrument a été comparé, en période estivale, à l'information apportée par un autre instrument infrarouge géostationnaire similaire à MTG-IRS (Meteosat Third Generation - Infrared Sounder), optimisé pour la mesure de la vapeur d'eau et de la température mais capable d'avoir une information sur la composition chimique de l'atmosphère. Enfin dans une dernière partie, la valeur ajoutée de ces deux instruments dans le modèle de qualité de l'air MOCAGE, a été quantifiée en utilisant des expériences de simulation de système d'observations sur une période de deux mois d'été (juillet - août 2009). La capacité de ces deux instruments à corriger différentes sources d'erreurs (les forçages atmosphériques, les émissions, l'état initial et les trois paramètres réunis) qui affectent les prévisions et simulations de qualité de l'air, a été quantifiées. Au final, l'instrument que nous avons défini s'avère effectivement capable d'apporter une contrainte efficace sur les champs d'ozone et de CO dans la moyenne et basse troposphère.The objective of this thesis is to define a geostationary infrared sensor to observe the atmospheric composition of the lowermost troposphere. We evaluate the potential added value of such an instrument at characterizing the variability of the main pollutants and improving air quality observations and forecasts. We focus on two air quality key pollutants: tropospheric ozone, because of its impact on human health, ecosystems and climate; carbon monoxide (CO), which is a tracer of pollutants emissions. Firstly, an evaluation of a linear scheme for the CO chemistry during one year and a half has been performed in comparison with a detailed chemical scheme (RACMOBUS) and different tropospheric and stratospheric observations (satellite and aircraft data). The advantage of such a scheme is its low computational cost which allows data assimilation of CO during long periods. Assimilation of CO data from the Measurements Of Pollution In The Troposphere (MOPITT) instrument allows us to evaluate the information brought by such infrared observations at the global scale. Secondly, the optimal configuration of a new infrared geostationary sensor has been defined using retrieval studies of atmospheric spectra with the objectives to contribute to the monitoring of ozone and CO for air quality purposes; our constraint also set the ground for a sensor with technically feasible and affordable characteristics. For reference, the information content of this instrument has been compared during summer to the information content from another infrared geostationary instrument similar to MTG-IRS (Meteosat Third Generation - Infrared Sounder), optimized to monitor water vapour and temperature but with monitoring atmospheric composition as Lastly, the potential added value of both instruments for air quality prognoses has been compared using observing system simulation experiments (OSSEs) over two summer months (July - August 2009). The skill of the two instruments to correct different error sources (atmospheric forcing, emission, initial state and the three conditions together) affecting air quality simulations and forecasts, has been characterised. In the end, it is concluded that the instrument configuration proposed is effectively able to bring a constraint on ozone and CO fields in the mid-to-low troposphere

THE USE OF GLOBAL SENSITIVITY ANALYSIS FOR ASSESSING CAPABILITY OF THE MTG/FCI INSTRUMENT TO DETECT AEROSOLS

International audienceThe Flexible Combined Imager (FCI) is an instrument to be borne by the future geostationary meteorological satellite Meteosat Third Generation (MTG). A numerical simulator was set up to provide simulated outputs of the instrument. It includes top-of-atmosphere scene of upwelling spectral radiance obtained by a radiative transfer model in the clear atmosphere, and the transfer function of the FCI. The sensitivity of the sensor outputs to aerosol properties is studied by varying the inputs defining the scenes and their illumination. The Global Sensitivity Analysis (GSA) with the Sobol' decomposition is applied to the outputs of the simulator, yielding a ranking of the inputs with respect to their influence on the FCI numerical outputs. The results are presented for all visible and near infrared channels of the FCI for desert type of aerosols according to the OPAC database. The study highlights the most relevant channels for aerosol detection and characterization and gives assessment of the different sources of uncertainties in aerosol retrieval with such channels

Contribution of the MTG/IRS radiance assimilation in the characterization of the atmospheric chemical composition

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Preliminary study of the FCI instrument capability to detect dust aerosols

International audienceThe Flexible Combined Imager (FCI) is an instrument on the future geostationary meteorological satellite Meteosat Third Generation (MTG). This communication presents preliminary results on its capability in measuring and characterizing the optical properties of the aerosols, their load, and nature. A numerical simulator has been built that includes top-of-atmosphere scene simulation obtained by a radiative transfer model in the clear atmosphere, and the transfer function of the FCI (spectral response, SNR…) to provide simulated outputs of the instrument. Changes of inputs depicting the atmosphere and the ground yield a series of FCI outputs that are analyzed by means of global sensitivity analysis to assess the sensitivity of FCI to changing aerosol properties

Contribution of the MTG/IRS radiance assimilation in the characterization of the atmospheric chemical composition

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Contribution of the Meteosat Third Generation (MTG) / InfraRed Sounder (IRS) radiance assimilation in the characterization of the atmospheric chemical composition

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An OSSE estimation of the capacity of FCI to improve aerosols forecast, by assimilating observations of aerosols optical thickness in MOCAGE CTM: Preliminary results

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Monitoring aerosols over Europe: an assessment of the potential benefit of assimilating the VIS04 measurements from the future MTG/FCI geostationary imager

International audienceThe study assesses the possible benefit of assimilating aerosol optical depth (AOD) from the future space-borne sensor FCI (Flexible Combined Imager) for air quality monitoring in Europe. An observing system simulation experiment (OSSE) was designed and applied over a 4-month period, which includes a severe-pollution episode. The study focuses on the FCI channel centred at 444 nm, which is the shortest wavelength of FCI. A nature run (NR) and four different control runs of the MOCAGE chemistry transport model were designed and evaluated to guarantee the robust-ness of the OSSE results. The synthetic AOD observations from the NR were disturbed by errors that are typical of the FCI. The variance of the FCI AOD at 444 nm was deduced from a global sensitivity analysis that took into account the aerosol type, surface reflectance and different atmospheric optical properties. The experiments show a general benefit to all statistical indicators of the assimilation of the FCI AOD at 444 nm for aerosol concentrations at the surface over Europe, and also a positive impact during the severe-pollution event. The simulations with data assimilation reproduced spatial and temporal patterns of PM 10 concentrations at the surface better than those without assimilation all along the simulations and especially during the pollution event. The advantage of assimilating AODs from a geostationary platform over a low Earth orbit satellite has also been quantified. This work demonstrates the capability of data from the future FCI sensor to bring added value to the MOCAGE aerosol simulations , and in general, to other chemistry transport models