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International audience; Surface soil moisture content (SMC) is known to impact soil reflectance at all wavelengths of the solar spectrum. As a consequence, many semi-empirical methods aim at inferring SMC from soil reflectance, but very few rely on physically-based models. This article presents a multilayer radiative transfer model of soil reflectance called MARMIT (multilayer radiative transfer model of soil reflectance) as a function of SMC given on a mass basis and a method called MARMITforSMC to estimate it from soil reflectance spectra. This model depicts a wet soil as a dry soil covered with a thin film of water. It is used to assess SMC over seven independent laboratory datasets gathered from the literature. A learning phase is required to link the thickness of the water film with the SMC. For that purpose, a sigmoid function, the parameters of which are related to soil physical and chemical properties such as porosity, grain size and mineralogy composition, is fitted. SMC can be inferred with good accuracy (RMSE ≈ 3%) if the learning step is applied soil by soil. The link between SMC and water thickness actually depends on soil texture and chemical composition. If the soils are divided into classes and if the learning phase is applied to a class, the RMSE slightly increases up to 5%. Finally, MARMITforSMC provides lower RMSE than any other existing semi-empirical or physically-based method.

International audience; This work assesses the ability of equivalent-sphere models to reproduce the optical properties of soot aggregates relevant for lidar remote sensing, i.e. the backscattering and extinction cross sections. Lidar cross-sections are computed with a spectral discrete dipole approximation model over the visible-to-infrared (40 0-50 0 0 nm) spectrum and compared with equivalent-sphere approximations. It is shown that the equivalent-sphere approximation, applied to fractal aggregates, has a limited ability to calculate such cross-sections well. The approximation should thus be used with caution for the computation of broad-band lidar cross-sections, especially backscattering, at small and intermediate wavelengths (e.g. UV to visible).

International audience; Ceilometers are widely spread instruments mainly used for cloud base height determination. However, recent models are more sensitive to aerosols; hence, nowadays there is an increasing interest in these instruments to retrieve aerosol optical and microphysical properties.The high number of them distributed around the globe compared to the robust lidar systems and the fact that ceilometers work under unattended conditions are the main reasons behind this interest. In this paper a new methodology is proposed to retrieve aerosol vertical extinction and backscatter profiles from a Vaisala ceilometer CL51. This methodology is based in two parts: first, a signal pre-processing with a suppression of the dark current and background noises, and a correction of the water vapor absorption using near-real time temperature and absolute humidity (AH) profiles from a co-located Microwave radiometer (MWR). Then an iterative Klett-based algorithm that uses AERONET (AErosol RObotic NETwork) AOD (Aerosol Optical Depth) as an input to retrieve the extinction and backscatter profiles. The error analysis of the aerosol retrievals has been performed between MWR measurements and modelled radiosondes from HYSPLIT. The absolute errors found in temperature and AH are leading to errors in the pre-processed RCS signals up to 9%, and then in particle backscatter and particle extinction coefficients up to 2:2% and 25%, respectively.; Les ceilomètres sont des instruments très répandus, principalement utilisés pour déterminer la hauteur de la base des nuages. Cependant, des modèles récents sont plus sensibles aux aérosols ; c'est pourquoi, de nos jours, on s'intéresse de plus en plus à ces instruments pour mesurer des données optiques des aérosols et leurs propriétés microphysiques. Le nombre élevé de ces derniers, répartis dans le monde entier, par rapport aux systèmes lidar robustes et le fait que les plafonds fonctionnent dans des conditions non surveillées sont les principales raisons de cet intérêt. Dans ce document, une nouvelle méthodologie est proposée pour déterminer par inversion les profils d'extinction verticale et de rétrodiffusion des aérosols à partir d'un modèle CL51 de ceilomètre de Vaisala. Cette méthodologie est basée sur deux parties : premièrement, un prétraitement du signal avec une suppression du courant d'obscurité et du fond et une correction de l'absorption de la vapeur d'eau en utilisant des profils de température et d'humidité absolue (AH) en temps quasi réel d'un radiomètre à micro-ondes (MWR) colocalisé. Ensuite, un algorithme itératif basé sur Klett qui utilise AERONET (AErosol RObotic NETwork) AOD (Aerosol Optical Depth) comme entrée est appliquée pour récupérer les profils d'extinction et de rétrodiffusion. Les erreurs absolues trouvées dans la température et l'AH entraînent des erreurs dans les signaux RCS prétraités jusqu'à 9 %, puis dans les coefficients de rétrodiffusion et d'extinction des particules jusqu'à 2,2 % et 25 %, respectivement.

The modeling of radiative properties of soot particles can be addressed by a number of methods. Among them, the canonical Rayleigh-Debye-Gans (RDG) theory and the Superposition T-Matrix Method (STMM) are particularly well adapted to the task. Here, both RDG and STMM are used to model the radiative properties of two types of fractal aggregates indicative of soot relevant to lidar sensing. One type, a canonical aggregate with a chain-like morphology, corresponds to low-sooting flames and is well characterized by a single fractal dimension. The other type, a superaggregate, exhibits multiple fractal dimensions and is seen in heavily sooting flames. Radiative properties such as the differential scattering cross-section, total scattering cross-sections, backscattering cross-sections, and linear depolarization-ratio (LDR) are calculated for a range of wavelengths from 300 − 1100 nm while including the wavelength dependence of the soot refractive index. Of particular interest is that depolarization by a superaggregate is found to be approximately ten times larger than the depolarization by a canonical chain-like aggregate and both exhibit a power-law with wavelength. Results for specific wavelengths of interest to lidar (355, 532, and 1064 nm) are tabulated for lidar applications. Additionally, RDG theory yields fairly accurate results for modeling the radiative properties, including lidar relevant parameters such as backscattering cross-sections, only for canonical soot fractal aggregates.

International audience; A laboratory experiment is set up to study both surface and in-depth soil moisture content (SMC). For that purpose, an aquarium is filled successively with two soils, a clay loam and a sand. Reflectance spectra are acquired in the solar domain (400–2400 nm) on the soil surface using an ASD FieldSpec 3 HR spectroradiometer and in-depth through the aquarium glass wall using two hyperspectral cameras. Successive amounts of water ranging from low to heavy rainfall in a temperate region are uniformly poured into the aquarium. The MARMITforSMC method based on the MARMIT (MultilAyer Radiative Transfer Model for soIl reflecTance) model is applied to each reflectance spectrum to determine gravimetric SMC. In particular, vertical profiles of SMC are provided with unprecedented spatial accuracy (~0.287 mm). The results are compared with volumetric SMC measured by two time-domain reflectometry (TDR) sensors. The in-depth SMC image produced on the sand shows lower values within the first 2 cm (5%) than below (17%). In contrast, the SMC image produced on the clay loam shows evenly distributed values whatever the position in the aquarium, even 1 h after moistening. The difference in grain size between the soils explains this result.; Une expérience est montée en laboratoire pour étudier l’humidité (SMC) du sol à la fois en surface et en profondeur. Pour cela, un aquarium est successivement rempli avec deux sols, un limon argileux et un sable. Les spectres en réflectance sont acquis dans le domaine solaire (400-2400 nm) en utilisant un spectroradiomètre ASD FieldSpec 3 HR pour la surface et deux caméras hyperspectrales pour le profil derrière la paroi de l’aquarium. Des quantités successives d’eau, allant de la pluie faible à forte pour une région tempérée, sont versées uniformément dans l’aquarium. La méthode MARMITforSMC s’appuyant sur le modèle MARMIT (Modèle de Transfert Radiatif Multicouches pour la réflectance du sol) est appliquée à chaque spectre en réflectance pour déterminer l’humidité gravimétrique correspondante. Ceci permet en particulier d’obtenir des profils verticaux d’humidité avec une résolution spatiale sans précédent (0 ,287 mm). Les résultats sont comparés aux mesures d’humidité volumétrique obtenues à l’aide de sonde de réflectométrie dans le domaine temporel (TDR). Les cartes de profil d’humidité générées pour le sable montrent des valeurs plus faibles pour les 2 premiers centimètres (5 %) qu’au-delà (17 %). Par contre, les cartes de profil d’humidité générées pour le limon argileux montrent des valeurs homogènes quelle que soit la profondeur, même 1 heure après l’humidification. La différence de granulométrie des sols explique ces résultats.