Classification of ice crystal shapes in midlatitude ice clouds from three years of lidar observations over the SIRTA observatory

This paper presents a study of ice crystal shapes in midlatitude ice clouds inferred from a technique based on the comparison of ray-tracing simulations with lidar depolarization ratio measured at 532 nm. This technique is applied to three years of lidar depolarization ratio observations from the SIRTA (Site Instrumental de Recherche par Télédétection Atmosphérique) observatory in Palaiseau, France, amounting to 322 different days of ice cloud observations. Particles in clouds are classified in three major groups : plates, columns, and irregular shapes with aspect ratios close to unity. Retrieved shapes are correlated with radiosounding observations from a close-by meteorological station: temperature, relative humidity, wind speed and direction

Multifractal characteristics of optical turbulence measured through a single beam holographic process

We have previously shown that azopolymer thin films exposed to coherent light that has travelled through a turbulent medium produces a surface relief grating containing information about the intensity of the turbulence; for instance, a relation between the refractive index structure constant C2 as a function of the surface parameters was obtained. In this work, we show that these films capture much more information about the turbulence dynamics. Multifractal detrended fluctuation and fractal dimension analysis from images of the surface roughness produced by the light on the azopolymer reveals scaling properties related to those of the optical turbulence.Comment: 8 pages, 5 figure

Electroactive mixed self-assembled monolayers: A numerical overview of phase segregations

Article de revue (Article scientifique dans une revue à comité de lecture)International audienceWe propose a modelling of phase segregations, inspired by image filtering, and dedicated to electrochemical systems. This original approach is compared to previous experimental results and enhanced with the concepts of 2D segregation and site percolation threshold.</p

Impact of the transport of aerosols from the free troposphere towards the boundary layer on the air quality in the Paris area

International audienceWe propose a quantification of the downward transport of aerosols from the free troposphere (FT) to the planetary boundary layer (PBL). Aerosols are originally released at the surface as a consequence of anthropogenic activities, biomass burning, soil mobilization, etc. After being vertically transported into the FT, they are exposed to the long-range transport (LRT) and may subside to impact, in turn, surface air pollution in remote places. Using 5400 h of routine Lidar observations conducted at the SIRTA observatory in the Paris area (France), we identified 154 free tropospheric aerosol layers continuously monitored during their downward transport into the local PBL. One of these events—associated to a Saharan dust outbreak—is thoroughly documented in a case study. And a climatological analysis of surface PM10 levels recorded at air quality monitoring stations allows the impact of FT to PBL transport of aerosols to be quantified. This source is found to be significant for 15 out of the 16 stations, with average PM10 concentrations 2.14 μg m -3 (i.e. 12%) above climatological values after the injection of free tropospheric aerosols into the PBL

STRAT: an automated algorithm to retrieve the vertical structure of the atmosphere from single channel lidar data

International audienceToday several lidar networks around the world provide large data sets that are extremely valuable for aerosol and cloud research. Retrieval of atmospheric constituent properties from lidar profiles requires detailed analysis of spatial and temporal variations of the signal. This paper presents an algorithm called STRAT (STRucture of the ATmosphere) designed to retrieve the vertical distribution of cloud and aerosol layers in the boundary layer and through the free troposphere and to identify near particle free regions of the ver tical profile and the range at which the lidar signal becomes too attenuated for exploitation, from a single lidar channel. The paper describes each detection method used in the STRAT algorithm and its application to a tropospheric backscatter lidar operated at the SIRTA obser vatory, in Palaiseau, 20 km south of Paris, France. STRAT retrievals are compared to other means of layer detection and classification; retrieval performances and uncertainties are discussed

Stratus-Fog Formation and Dissipation: A 6-Day Case Study

15th international symposium for the advancement of boundary-layer remote sensing (ISARS), 28-30 June 2010, Paris, FranceInternational audienceA suite of active and passive remote sensing instruments and in-situ sensors deployed at the SIRTA Observatory (Instrumented Site for Atmospheric Remote Sensing Research), near Paris, France, for a period of six months (October 2006-March 2007) document simultaneously radiative, microphysical and dynamic processes driving the continental-fog life cycle. The study focuses on a 6-day period between 23 and 29 December 2006 characterized by several stratus-cloud lowering and lifting events and almost 18 h of visibility below 1 km. Conceptual models and different possible scenarios are presented here to explain the formation, the development and the dissipation phases of three major stratus-fog events and to quantify the impact of each driving process. For example, slowly evolving large-scale conditions characterized by a slow continuous cloud-base lowering, followed by a rapid transient period conductive to fog formation and dissipation, are observed for cases 1 and 3. During this stable period, continuous cloud-top radiative cooling (≈ -160 Wm-2) induces a progressive and slow lowering of the cloud base: larger droplets at cloud top (cloud reflectivity approximately equals to -20 dBZ) induce slow droplet fall to and beyond cloud base (Doppler velocity ≈ -0.1 ms-1), cooling the sub-cloud layer by evaporation and lowering the saturation level to 100 m (case 1) or to the surface (cases 2 and 3). Suddenly, a significant increase in Doppler velocity magnitude ≈ -0.6 ms-1 and of turbulent kinetic energy dissipation rate around 10-3 m2s-3 occurs at cloud base (case 1). These larger cloud droplets reach the surface leading to fog formation over 1.5 h. The Doppler velocity continues to increase over the entire cloud depth with a maximum value of around -1 ms-1 due to the collection of fog droplets by the drizzle drops with high collection efficiency. As particles become larger, they fall to the ground and lead to fog dissipation. Hence, falling particles play a major role in both the formation and also in the dissipation of the fog. These roles co-exist and the balance is driven by the characteristics of the falling particles, such as the concentration of drizzle drops, the size distribution of drizzle drops compared to fog droplets, Doppler velocity and thermodynamic state close to the surface

Impact of conditional sampling and instrumental limitations on the statistics of cloud properties derived from cloud radar and lidar at SIRTA

International audienceClouds represent the largest uncertainty in future climate projections. As a result, unbiased long-term vertically-resolved cloud observations must be collected and analyzed in order to produce regional cloud climatologies. In the present study, we use model outputs to evaluate the impact of conditional temporal sampling and instrumental effects on the 2-year statistics of frequency of cloud occurrence and cloud fraction. We then quantify the radiative significance of the ice clouds undetected by cloud radars. We find that in order to evaluate the representation of all types of clouds in operational models both a cloud radar and a lidar must be used. The cloud radar alone can do a reasonable job at describing cloud properties up to 8–9 km, however the lidar is mandatory to detect most of the high-altitude clouds above 9 km. The sampling should be regular but not necessarily continuous, and should not be driven by meteorological conditions. This result applies to all sites having a lidar without a radome. It is finally suggested that a cloud radar of around ?60 dBZ sensitivity at 1 km range would be required to detect almost all radiatively-significant ice clouds

An original self-assembly using a tetrathiafulvalene-based molecular clip for the recognition of fullerene C 60

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The ability of MM5 to simulate ice clouds : systematic comparison between simulated and measured fluxes and lidar/radar profiles at the SIRTA atmospheric observatory.

The ability of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) to simulate midlatitude ice clouds is evaluated. Model outputs are compared to long-term meteorological measurements by active (radar and lidar) and passive (infrared and visible fluxes) remote sensing collected at an atmospheric observatory near Paris, France. The goal is to understand which of four microphysical schemes is best suited to simulate midlatitude ice clouds. The methodology consists of simulating instrument observables from the model outputs without any profile inversion, which allows the authors to use fewer assumptions on microphysical and optical properties of ice particles. Among the four schemes compared in the current study, the best observation-to-simulations scores are obtained with Reisner et al. provided that the particles' sedimentation velocity from Heymsfield and Donner is used instead of that originally proposed. For this last scheme, the model gives results close to the measurements for clouds with medium optical depth of typically 1 to 3, whatever the season. In this configuration, MM5 simulates the presence of midlatitude ice clouds in more than 65% of the authors' selection of observed cloud cases. In 35% of the cases, the simulated clouds are too persistent whatever the microphysical scheme and tend to produce too much solid water (ice and snow) and not enough liquid water