Evaluation of the Lidar/Radiometer Inversion Code (LIRIC) to determine microphysical properties of volcanic and desert dust

© Author(s) 2013. This work is distributed under the Creative Commons Attribution 3.0 LicenseThe Lidar/Radiometer Inversion Code (LIRIC) combines the multiwavelength lidar technique with sun/sky photometry and allows us to retrieve vertical profiles of particle optical and microphysical properties separately for fine-mode and coarse-mode particles. After a brief presentation of the theoretical background, we evaluate the potential of LIRIC to retrieve the optical and microphysical properties of irregularly shaped dust particles. The method is applied to two very different aerosol scenarios: a strong Saharan dust outbreak towards central Europe and an Eyjafjallajökull volcanic dust event. LIRIC profiles of particle mass concentrations for the coarse-mode as well as for the non-spherical particle fraction are compared with results for the non-spherical particle fraction as obtained with the polarization-lidar- based POLIPHON method. Similar comparisons for fine-mode and spherical particle fractions are presented also. Acceptable agreement between the different dust mass concentration profiles is obtained. LIRIC profiles of optical properties such as particle backscatter coefficient, lidar ratio, Ångström exponent, and particle depolarization ratio are compared with direct Raman lidar observations. Systematic deviations between the LIRIC retrieval products and the Raman lidar measurements of the desert dust lidar ratio, depolarization ratio, and spectral dependencies of particle backscatter and lidar ratio point to the applied spheroidal-particle model as main source for these uncertainties in the LIRIC results.Peer reviewe

Retrieving global sources of aerosols from MODIS observations by inverting GOCART model

International audienceKnowledge of the global distribution of tropospheric aerosols is important for studying the effects of aerosols on global climate. Chemical transport models rely on archived meteorological fields, accounting for aerosol sources, transport and removal processes can simulate the global distribution of atmospheric aerosols. However, the accuracy of global aerosol modeling is limited. Uncertainty in location and strength of aerosol emission sources is a major factor in limiting modeling accuracy. This paper describes an effort to develop an algorithm for retrieving global sources of aerosol from satellite observations by inverting the GOCART aerosol transport model. To optimize inversion algorithm performance, the inversion was formulated as a generalized multi-term least-squares-type fitting. This concept uses the principles of statistical optimization and unites diverse retrieval techniques into a single flexible inversion procedure. It is particularly useful for choosing and refining a priori constraints in the retrieval algorithm. For example, it is demonstrated that a priori limitations on the partial derivatives of retrieved characteristics, which are widely used in atmospheric remote sensing, can also be useful in inverse modeling for constraining time and space variability of the retrieved global aerosol emissions. The similarities and differences with the standard "Kalman filter" inverse modeling approach and the "Phillips-Tikhonov-Twomey" constrained inversion widely used in remote sensing are discussed. In order to retain the originally high space and time resolution of the global model in the inversion of a long record of observations, the algorithm was expressed using adjoint operators in a form convenient for practical development of the inversion from codes implementing forward model simulations. The inversion algorithm was implemented using the GOCART aerosol transport model. The numerical tests we conducted showed successful retrievals of global aerosol emissions with a 2°×2.5° resolution by inverting the GOCART output. For achieving satisfactory retrieval from satellite sensors such as MODIS, the emissions were assumed constant within the 24 h diurnal cycle and aerosol differences in chemical composition were neglected. Such additional assumptions were needed to constrain the inversion due to limitations of satellite temporal coverage and sensitivity to aerosol parameters. As a result, the algorithm was defined for the retrieval of emission sources of fine and coarse mode aerosols from the MODIS fine and coarse mode aerosol optical thickness data respectively. Numerical tests showed that such assumptions are justifiable, taking into account the accuracy of the model and observations and that it provides valuable retrievals of the location and the strength of the aerosol emissions. The algorithm was applied to MODIS observations during two weeks in August 2000. The global placement of fine mode aerosol sources retrieved from inverting MODIS observations was coherent with available independent knowledge. This was particularly encouraging since the inverse method did not use any a priori information about the sources and it was initialized under a "zero aerosol emission" assumption. The retrieval reproduced the instantaneous global MODIS observations with a standard deviation in fitting of aerosol optical thickness of ~0.04. The optical thickness during high aerosol loading events was reproduced with a standard deviation of ~48%. Applications of the algorithm for the retrieval of coarse mode aerosol emissions were less successful, mainly due to the currently existing lack of MODIS data over high reflectance desert dust sources. Possibilities for enhancing the global satellite data inversion by using diverse a priori constraints on the retrieval are demonstrated. The potential and limitations of applying our approach for the retrieval of global aerosol sources from aerosol remote sensing are discussed

Retrieval of spatio-temporal distributions of particle parameters from multiwavelength lidar measurements using the linear estimation technique and comparison with AERONET

The results of the application of the linear estimation technique to multiwavelength Raman lidar measurements performed during the summer of 2011 in Greenbelt, MD, USA, are presented. We demonstrate that multiwavelength lidars are capable not only of providing vertical profiles of particle properties but also of revealing the spatio-temporal evolution of aerosol features. The nighttime 3β + 1α lidar measurements on 21 and 22 July were inverted to spatio-temporal distributions of particle microphysical parameters, such as volume, number density, effective radius and the complex refractive index. The particle volume and number density show strong variation during the night, while the effective radius remains approximately constant. The real part of the refractive index demonstrates a slight decreasing tendency in a region of enhanced extinction coefficient. The linear estimation retrievals are stable and provide time series of particle parameters as a function of height at 4 min resolution. AERONET observations are compared with multiwavelength lidar retrievals showing good agreement

Retrieving global aerosol sources from satellites using inverse modeling

International audienceUnderstanding aerosol effects on global climate requires knowing the global distribution of tropospheric aerosols. By accounting for aerosol sources, transports, and removal processes, chemical transport models simulate the global aerosol distribution using archived meteorological fields. We develop an algorithm for retrieving global aerosol sources from satellite observations of aerosol distribution by inverting the GOCART aerosol transport model. The inversion is based on a generalized, multi-term least-squares-type fitting, allowing flexible selection and refinement of a priori algorithm constraints. For example, limitations can be placed on retrieved quantity partial derivatives, to constrain global aerosol emission space and time variability in the results. Similarities and differences between commonly used inverse modeling and remote sensing techniques are analyzed. To retain the high space and time resolution of long-period, global observational records, the algorithm is expressed using adjoint operators. Successful global aerosol emission retrievals at 2°×2.5 resolution were obtained by inverting GOCART aerosol transport model output, assuming constant emissions over the diurnal cycle, and neglecting aerosol compositional differences. In addition, fine and coarse mode aerosol emission sources were inverted separately from MODIS fine and coarse mode aerosol optical thickness data, respectively. These assumptions are justified, based on observational coverage and accuracy limitations, producing valuable aerosol source locations and emission strengths. From two weeks of daily MODIS observations during August 2000, the global placement of fine mode aerosol sources agreed with available independent knowledge, even though the inverse method did not use any a priori information about aerosol sources, and was initialized with a "zero aerosol emission" assumption. Retrieving coarse mode aerosol emissions was less successful, mainly because MODIS aerosol data over highly reflecting desert dust sources is lacking. The broader implications of applying our approach are also discussed

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation

Remote sensing of soot carbon – Part 2: Understanding the absorption Ångström exponent

Recently, some authors have suggested that the absorption Ångström exponent (AAE) can be used to deduce the component aerosol absorption optical depths (AAODs) of carbonaceous aerosols in the AERONET database. This AAE approach presumes that AAE ≪ 1 for soot carbon, which contrasts the traditional small particle limit of AAE = 1 for soot carbon. Thus, we provide an overview of the AERONET retrieval, and we investigate how the microphysics of carbonaceous aerosols can be interpreted in the AERONET AAE product. We find that AAE ≪ 1 in the AERONET database requires large coarse mode fractions and/or imaginary refractive indices that increase with wavelength. Neither of these characteristics are consistent with the current definition of soot carbon, so we explore other possibilities for the cause of AAE ≪ 1. AAE is related to particle size, and coarse mode particles have a smaller AAE than fine mode particles for a given aerosol mixture of species. We also note that the mineral goethite has an imaginary refractive index that increases with wavelength, is very common in dust regions, and can easily contribute to AAE ≪ 1. We find that AAE ≪ 1 can not be caused by soot carbon, unless soot carbon has an imaginary refractive index that increases with wavelength throughout the visible and near-infrared spectrums. Finally, AAE is not a robust parameter for separating carbonaceous absorption from dust aerosol absorption in the AERONET database

Shortwave radiative forcing and efficiency of key aerosol types using AERONET data

The shortwave radiative forcing (Δ<i>F</i>) and the radiative forcing efficiency (Δ<i>F</i><sup>eff</sup>) of natural and anthropogenic aerosols have been analyzed using estimates of radiation both at the Top (TOA) and at the Bottom Of Atmosphere (BOA) modeled based on AERONET aerosol retrievals. Six main types of atmospheric aerosols have been compared (desert mineral dust, biomass burning, urban-industrial, continental background, oceanic and free troposphere) in similar observational conditions (i.e., for solar zenith angles between 55° and 65°) in order to compare the nearly same solar geometry. The instantaneous Δ<i>F</i> averages obtained vary from −122 ± 37 Wm<sup>−2</sup> (aerosol optical depth, AOD, at 0.55 μm, 0.85 ± 0.45) at the BOA for the mixture of desert mineral dust and biomass burning aerosols in West Africa and −42 ± 22 Wm<sup>−2</sup> (AOD = 0.9 ± 0.5) at the TOA for the pure mineral dust also in this region up to −6 ± 3 Wm<sup>−2</sup> and −4 ± 2 Wm<sup>−2</sup> (AOD = 0.03 ± 0.02) at the BOA and the TOA, respectively, for free troposphere conditions. This last result may be taken as reference on a global scale. Furthermore, we observe that the more absorbing aerosols are overall more efficient at the BOA in contrast to at the TOA, where they backscatter less solar energy into the space. The analysis of the radiative balance at the TOA shows that, together with the amount of aerosols and their absorptive capacity, it is essential to consider the surface albedo of the region on which they are. Thus, we document that in regions with high surface reflectivity (deserts and snow conditions) atmospheric aerosols lead to a warming of the Earth-atmosphere system

The Toroid Moment of Majorana Neutrino

If neutrino is the Majorana particle it can possess only one electromagnetic characteristic, the toroid dipole moment (anapole) in the static limit and nothing else. We have calculated the diagonal toroid moment (form factor) of the Majorana neutrino by the dispersion method in the one-loop approximation of the Standard Model and found it to be different from zero in the case of massive as well as massless neutrinos. All external particles are on the mass shells and there are no problems with the physical interpretation of the final result. Some manifestations of the toroid interactions of Majorana neutrinos, induced by their toroid moments, are also remarked.Comment: 22 pages, 1 table and 3 EPS-figures included, uses prd.sty, preprint.sty, aps.sty and epsfig.sty (RevTeX is used), major conceptual changes of E2-96-53 are include

The AMMA mulid network for aerosol characterization in West Africa

Three ground based portable low power consumption microlidars (MULID) have been built and deployed at three remote sites in Banizoumbou (Niger), Cinzana (Mali) and M'Bour (Senegal) in the framework of the African Monsoon Multidisciplinary Analyses (AMMA) project for the characterization of aerosols optical properties. A description of the instrument and a discussion of the data inversion method, including a careful analysis of measurement uncertainties (systematic and statistical errors) are presented. Some case studies of typical lidar profiles observed over the Banizoumbou site during 2006 are shown and discussed with respect to the AERONET 7-day back-trajectories and the biomass burning emissions from the Combustion Emission database for the AMMA campaign

Optical Properties of Aerosols from Long Term Ground-Based Aeronet Measurements

AERONET is an optical ground-based aerosol monitoring network and data archive supported by NASA's Earth Observing System and expanded by federation with many non-NASA institutions including AEROCAN (AERONET CANada) and PHOTON (PHOtometrie pour le Traiteinent Operatonnel de Normalisation Satellitaire). The network hardware consists of identical automatic sun-sky scanning spectral radiometers owned by national agencies and universities purchased for their own monitoring and research objectives. Data are transmitted hourly through the data collection system (DCS) on board the geostationary meteorological satellites GMS, GOES and METEOSAT and received in a common archive for daily processing utilizing a peer reviewed series of algorithms thus imposing a standardization and quality control of the product data base. Data from this collaboration provides globally distributed near real time observations of aerosol spectral optical depths, aerosol size distributions, and precipitable water in diverse aerosol regimes. Access to the AERONET data base has shifted from the interactive program 'demonstrat' (reserved for PI's) to the AERONET homepage allowing faster access and greater development for GIS object oriented retrievals and analysis with companion geocoded data sets from satellites, LIDAR and solar flux measurements for example. We feel that a significant yet under utilized component of the AERONET data base are inversion products made from hourly principal plane and almucanter measurements. The current inversions have been shown to retrieve aerosol volume size distributions. A significant enhancement to the inversion code has been developed and is presented in these proceedings