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Under single scattering conditions, water droplets clouds do not depolarize the backscattered light. However, backscattered light from multiple scattering will be depolarized. The level of depolarization is a function of the droplets size and of the cloud extinction coefficient value and its profile; it has also a strong dependency on the lidar field-of-view (FOV) and azimuth angle [1]-[3]. It has been demonstrated in [4] that the multiple scattering cross polarization signal can be reduced to a second order scattering one using the azimuthal dependency of the cross polarization. In this paper we present how the multiple scattering cross polarization can be reduced to a second order scattering and how this signal is related to the droplet particle size. Monte Carlo simulations for clouds at different ranges and effective radius sizes are performed and compared with the results obtained with an analytical model.

The relation between the accumulated single scattering factor and the layer accumulated depolarization ratio appears to be independent of the geometry of the measurements and contains information on the optical depth and thus on the extinction coefficient. A simple equation is developed to retrieve the extinction coefficient from the total integrated signal and the integrated depolarization ratio measurements. The results compare well with Klett and Weinman lidar inversion techniques. The results from the measurements of the integrated depolarization ratio can be used to set the far end initial extinction coefficient value required for Klett and Weinman lidar inversion or can be used directly. [c] 2010 Optical Society of America OCIS codes: 010.3640, 290.4210.

Recently, an empirical relationship between the layer integrated backscattered light and the layer accumulated depolarization ratio has been established for linear polarization for the case of water droplet clouds. This is a powerful relation, allowing calibration of space lidar and correction of the lidar signal for multiple scattering effects. The relationship is strongly based on Monte Carlo simulations with some experimental evidence. We support the empirical relationship with strong experimental data and then show experimentally and via second order scattering theoretical calculations that a modified relationship can be obtained for circular polarization. Also, we demonstrate that other empirical relationships exist between the layer accumulated linear and circular depolarization ratios and the layer integrated backscattered light for submicrometer particles and nonspherical particles. OCIS codes: 010.3640, 280.1350, 290.4020, 290.4210, 290.5820, 290.5855.

A field trial involving 50 separate releases of inert aerosol (kaolin) was conducted to determine the concentration distribution within aerosol puffs resulting from near-instantaneous releases. Atmospheric conditions during the trial fell within Pasquill stability classes A and B (very and moderately unstable, respectively). Aerosol concentration measurements were made using a scanning lidar system operating at 1.06 Rm. Artificial neural network (ANN) models were developed using the data to predict concentration distributions, given a number of meteorological parameters. The ANN predictions were compared to those from traditional Gaussian puff models, and provided better predictions than the Gaussian model parameterizations examined. The ANN models were also used to develop Gaussian fitting parameters to replace traditional Pasquill and Slade dispersion coefficients. The ANN-derived dispersion coefficients provided better predictions of measured puff concentration distributions than either the Pasquill or Slade parameterizations, though the full multi-input ANN models provided even better predictions than the Gaussian puff model using ANN-derived dispersion coefficients. Key words: puff dispersion, neural network modeling, Gaussian puff model. Un essai sur le terrain portant sur la relache de 50 bouffees d'aerosols inertes (kaolin) a ete effectue dans le but de determiner la distribution de la concentration a l'interieur des bouffees resultant de la quasi-instantaneite de la relache. Les conditions atmospheriques pendant les essais etaient selon le model de stability de Pasquil comprissent entre la classe A et B (soit : de tres a moderement instable respectivement). Les mesures de concentrations ont ete effectuees a l'aide d'un lidar a balayage operant a 1,06 µm. Des modeles de reseau de neurones artificielles (RNA) ont ete developpees en utilisant les donnees pour predire les distributions de concentrations pour un nombre de parameters atmospheriques. Les predictions des RNA ont ete compaees avec celles du modele traditionnel de bouffees gaussiennes. Les predictions des RNA ont fournit de meilleures predictions que le modele de parametrisation gaussien. Les modeles RNA ont ete egalement utilises pour developper des parameters de lissage gaussien dans le but de remplacer les parameters traditionnelles des coefficients de dispersion etablit par Pasquill et Slade. Les coefficients de dispersion derives des modeles RNA fournissent de meilleures predictions de la distribution de la concentration des bouffees que les parametrisations de Pasquill et Slade, quoique les modeles RNA a multiple entree completes fournissent meme de meilleurs prediction que le modele de bouffee gaussienne qui utilise les coefficients derives des modeles RNA. Mots-cles : bouffee dispersion, modelisation reseau de neurones, model Gaussien de bouffee. [Traduit par la Redaction], Introduction For a continuously released plume, a time-average of concentration measurements at a given point provides a practical and useful estimate of ensemble mean concentrations (Csanady 1973). However, for transient [...]

A simple relationship is established between the linear and the circular depolarization ratios averaged over the azimuth angle of clouds made of spherical particles. The relationship is validated theoretically using double-scattering calculations; in the framework, the measurements are performed with a multiple-field-of-view lidar (MFOV) lidar. The relationship is also validated using data obtained with MFOV lidar equipped with linear and circular polarization measurement capabilities. The experimental data support theoretical results for small optical depths. At higher optical depths and large fields of view, the contribution of multiple scatterings is important; experimental data suggest that the relationship established between the linear and circular depolarization stays valid as long as the main depolarization mechanism comes from one scattering (most likely a backscattering a few degrees away from 180[degrees]). OCIS codes: 010.3640, 280.1350, 290.4020, 290.4210, 290.5820, 290.5855.

Diffractive target plates are used to emulate aerosols of known size and concentration. These target plates are used to validate and determine the sensitivity of a multiple-field-of-view lidar signal inversion technique based on double-scattering measurement to retrieve the particle size and the concentration of small optical depth clouds. We estimate that nighttime and daytime quantification (size and concentration) is possible for optical depths as low as 0.005 and 0.016, respectively. The recovery technique limiting factors are the shot noise, the laser features, the optical lens quality, the background illumination level, the background aerosol fluctuations, and the noise introduced by the lidar detector, a gated intensified camera (camera G-ICCD). OCIS codes: 030.4280, 040.1520, 280.1100, 280.3640, 290.4210, 290.5820.

A multiple-field-of-view (MFOV) lidar is used to characterize size and optical depth of low concentration of bioaerosol clouds. The concept relies on the measurement of the forward scattered light by using the background aerosols at various distances at the back of a subvisible cloud. It also relies on the subtraction of the background aerosol forward scattering contribution and on the partial attenuation of the first-order backscattering. The validity of the concept developed to retrieve the effective diameter and the optical depth of low concentration bioaerosol clouds with good precision is demonstrated using simulation results and experimental MFOV lidar measurements. Calculations are also done to show that the method presented can be extended to small optical depth cloud retrieval. OCIS codes: 030.4280, 040.1520, 110.4280, 280.1100, 280.3640, 290.4210.

The Undique imaging Monte Carlo simulator (Undique hereafter) was developed to reproduce the behavior of 3D imaging devices. This paper describes its high fidelity imaging algorithm.

Under single scattering conditions, water droplets clouds do not depolarize the backscattered light. However, backscattered light from multiple scattering will be depolarized. The level of depolarization is a function of the droplets size, the cloud extinction coefficient value and profile; it has also an important dependency on the lidar field-of-view (FOV). The use of depolarization information to retrieve cloud microphysical properties, using Multiple-FOV has been the object of studies, [1], [2]. Recently the use of the depolarization, at a single FOV, has been studied for cloud with linear liquid water content profiles, [3], [4]. In this paper we present the mechanism leading to depolarization and identify the FOV values for which the information on particle size is high. Also Monte Carlo simulations for cloud with constant and ramp up profiles are presented. The degree of linear depolarization as a function of cloud penetration is significantly different for both cloud profiles. This suggests that the use of the degree of linear depolarization at a single FOV should be used with caution to determine clouds micro-physical parameters.

Lidars with multiple fields of view (MFOVs) are promising tools for gaining information on cloud particle size. We perform a study of the information content of MFOV lidar data with the use of eigenvalue analysis. The approach we have developed permits an understanding of the main features of MFOV lidars and provides a way to relate the accuracy of particle size estimation with the measurement uncertainty and the scattering geometry such as the cloud-base height and the lidar sounding depth. Second-order scattering computations are performed for an extended range of particle sizes and for a wide range of lidar fields of view (FOVs). The results obtained allow us to specify the areas of possible applications of these lidars in cloud studies. Comparison of results obtained with polarized and cross-polarized scattered components demonstrate that the cross-polarized signal should provide a more stable retrieval and is preferable when double scattering is highly dominant. Our analysis allows for the estimation of the optimal number of FOVs in the system and their angular distribution, so this work can be a useful tool for practical MFOV lidar design. OCIS codes: 280.0280, 280.1100, 280.3640, 290.4210.

Recent developments in the search for a practical method of exploiting the multiple-scattering contributions to lidar returns are consolidated in a robust retrieval algorithm. The theoretical basis is the small-angle diffusion approximation. This implies that the algorithm is limited to media of sufficient optical thickness to generate measurable multiple scattering and to geometries for which the receiver's footprint diameter is less than the scattering mean free path. The primary retrieval products are the range-resolved extinction coefficient and the effective particle diameter from which secondary products such as the particle volume mixing ratio and the extinction at other wavelengths can be calculated. We recall briefly earlier validation tests and present new data and analysis that demonstrate and quantify the solutions' accuracy. The results show that systematic lidar probings with the proposed multiple-scattering technique can provide valuable physical information on cloud formation and evolution. OCIS codes: 280.3640, 280.1310, 290.4210, 290.1090, 010.3640.

High-energy femtosecond laser pulses propagating in the atmosphere undergo self-focusing resulting in the appearance of the phenomenon of filamentation. We observed an extra-attenuation of such (terawatt) femtosecond laser pulses propagating in the atmosphere when compared with long pulses (200 ps) with the same energy. This is because, in contrast to the linear propagation of the long pulse, the input femtosecond laser pulse is attenuated owing to either absorption through multiphoton ionization/tunnel ionization or to scattering on the laser-induced plasma; self-phase-modulation and self-steepening further convert partially the energy initially contained in the fundamental bandwidth into the broad side bands of the laser, becoming eventually a white-light laser pulse (supercontinuum). The experimental data allow us to extract an effective extra-attenuation coefficient for an exponential decay of the input pulse energy with the propagation distance. Such a coefficient allows us to estimate an upper bound of the filament length under the experimental conditions used. More generally, our observation leads to a new technique to remotely detect light filaments in the atmosphere. OCIS codes: 010.1300, 010.1310, 010.3640, 190.4180, 190.5940, 190.7110, 350.5400.

We measure with a gated intensified CCD camera the cross-polarized backscattered light from a linearly polarized laser beam penetrating a cloud made of spherical particles. In accordance with previously published results we observe a clear azimuthal pattern in the recorded images. We show that the pattern is symmetrical, that it originates from second-order scattering, and that higher-order scattering causes blurring that increases with optical depth. We also find that the contrast in the symmetrical features can be related to measurement of the optical depth. Moreover, when the blurring contributions are identified and subtracted, the resulting pattern provides a pure second-order scattering measurement that can be used for retrieval of droplet size. OCIS codes: 280.3640, 260.5430, 290.4210, 290.1090, 290.1310.

In atmospheric sensing, one application that has demonstrated several impressive successes over the last two decades is the light detection and ranging (LIDAR). Elastic LIDAR has shown an important capability in providing aerosol density and spatial distribution from a standoff position. However, it provides limited information on the material composition of the aerosol component. On the other hand, inelastic L1DARs (including laser-induced fluorescence and Raman LIDARs) measure the spectrally distributed returned signal that may contain important clues about the nature of the scatterers. In order to investigate the capability of these LIDARs in characterizing bioaerosols from a standoff position, Defence Research & Development Canada initiated a three-year program in spring 1999, named SINBAHD (Standoff Integrated Bioaerosol Active Hyperspectral Detection). The aim of the program was to investigate the sensitivity and discrimination capabilities of an inelastic LIDAR based on the intensified range-gated spectral detection of laser-induced fluorescence. An exploratory prototype based on this technique has shown sensitivity of a few living bioaerosol particles per liter of air for a range of 1.4 km at night. Furthermore, based on spectral signatures measured during open-air releases, good discrimination capabilities were obtained between Bacillius subtilis var globiggi (BG) and Erwinia herbicola (EH). These results agree well with a performance model using Raman returns from atmospheric nitrogen as a calibration tool. Index Terms--Bioaerosol, fluorescence, intensified charge-coupled device (ICCD), laser-induced fluorescence (LIF), light detection and ranging (LIDAR), Raman, spectroscopy.