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Caractérisation in situ des propriétés microphysiques et optiques des nuages : Contribution à l'amélioration des modèles de transfert radiatif et des méthodes d'inversion satellitales

Abstract : Microphysical and optical properties of cloud particles are known to be a primordial source of information for the understanding of light interactions in the atmosphere system through radiative and chemical processes, hence of the cloud feedback on terrestrial climate. However, given the complexity and variability of cloud's microphysical and structural properties, the representation of the coupling between microphysical and radiative processes remains limited in climate models. In order to reduce uncertainties in these models, there is an urgent need to develop accurate microphysical parameterizations that will lead to more realistic cloud radiative behavior. Therefore, the reliable modeling of radiative processes in a cloudy atmosphere requires well- documented observations of clouds' optical and microphysical properties at different spatial scales. This study lies within this framework presenting an accurate characterization of cloud's optical and microphysical properties in different thermodynamic phases using in situ measurements. The use of the information provided by the synergy between high-resolution scale airborne measurements will thereby enable the improvement and the validation of global scale satellite retrieval algorithms. As a first step, the relationship between clouds' microphysical and optical properties was investigated considering an hybrid microphysical model based on a combination of spherical water droplets and hexagonal ice crystals of variable aspect ratio. Even though this approach might not be correct from a microphysical point of view, it was shown that this hybrid model was able to model optical properties in agreement with in situ measurements for different types of clouds relative to their particle-phase composition. Secondly, a database including a large set of in situ microphysical and optical measurements performed by different airborne instruments in a wide variety of meteorological conditions was constructed. A principal component analysis (PCA) of the in situ angular scattering coefficients measurements performed by the LaMP's airborne "Polar Nephelometer" was implemented in order to assess a representative set of single scattering characteristics for different groups of clouds. This analysis enables one to gather the measurements as a function of their "optical signing", revealing the variability of clouds' microphysical properties inside the database. Then, classification of the revealed patterns in the principal component space was achieved by using a neural network (multilayer perceptron) which has the advantage of involving all the information carried by the angular scattering coefficients measurements. Consequently, the complementary nature of the PCA and neural network allowed us to classify the data set into three specific groups of clouds relative to their particle phase composition (liquid-water droplets, mixed-phase and solid-ice particles). This cloud classification was then validated by the discrimination of the cloud water phase on the basis of the ratio of bulk microphysical parameters derived from direct microphysical PMS (FSSP-100 and 2D-C) probe measurements. The next step was performed by extracting three average angular scattering coefficients, established for scattering angles ranging from 15° to 155° at a wavelength of 0.8 µm, describing the representative single scattering properties of the three types of clouds. The interpretation of these typical phase functions, using an inversion technique based on the physical modeling of light scattering processes computed by the hybrid model, showed that the information contained in the scattering measurements is sufficient to restore component composition and particle volume distributions for the three types of clouds. This statement was supported by rather good agreement of the inversion results (the retrieved particle distributions) with the particle size composition obtained by the collocated independent FSSP and 2D-C measurements for each selected clouds. However, the results established by these analyses do not account for the complete set of clouds' optical parameters needed for the direct and inverse modeling of radiative transfer. Consequently, the information contained in the average angular scattering coefficients, measured at 0.8 µm for near uniformly positioned scattering angles from 15° to 155°, was exported to the forward and backward scattering directions and then projected to two other wavelengths in the near infra red region (1.6 µm and 3.7 µm) which are valuable for radiative transfer modeling. Accordingly, the hybrid direct model was applied to the retrieved particle volume distributions to compute representative angular scattering coefficients documented between 0° and 180° for wavelengths 0.8µm, 1.6µm and 3.7µm. This process was implemented for the three types of clouds as well as for cirrus cloud whose radiative effect is subject to high uncertainties in the scientific community. Thus, a complete set of average microphysical and optical parameters was established for four types of clouds and allowed us to construct representative look-up tables which can directly be input in cloud parameter retrieval algorithm used in passive remote sensing techniques.
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Submitted on : Tuesday, December 16, 2003 - 2:27:25 PM
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Olivier Jourdan. Caractérisation in situ des propriétés microphysiques et optiques des nuages : Contribution à l'amélioration des modèles de transfert radiatif et des méthodes d'inversion satellitales. Océan, Atmosphère. Université Blaise Pascal - Clermont-Ferrand II, 2003. Français. ⟨tel-00003911v2⟩

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