Information content of multiwavelength lidar data with respect to microphysical particle properties derived from eigenvalue analysis

Automated, unsupervised inversion of multiwavelength lidar data with TiARA: assessment of retrieval performance of microphysical parameters using simulated data

We evaluate the retrieval performance of the automated, unsupervised inversion algorithm, Tikhonov Advanced Regularization Algorithm (TiARA), which is used for the autonomous retrieval of microphysical parameters of anthropogenic and natural pollution particles. TiARA (version 1.0) has been developed in the past 10 years and builds on the legacy of a data-operator-controlled inversion algorithm used since 1998 for the analysis of data from multiwavelength Raman lidar. The development of TiARA has been driven by the need to analyze in (near) real time large volumes of data collected with NASA Langley Research Center's high-spectral-resolution lidar (HSRL-2). HSRL-2 was envisioned as part of the NASA Aerosols-Clouds-Ecosystems mission in response to the National Academy of Sciences (NAS) Decadal Study mission recommendations 2007. TiARA could thus also serve as an inversion algorithm in the context of a future space-borne lidar. We summarize key properties of TiARA on the basis of simulations with monomodal logarithmic-normal particle size distributions that cover particle radii from approximately 0.05 μm to 10 μm. The real and imaginary parts of the complex refractive index cover the range from non-absorbing to highly light-absorbing pollutants. Our simulations include up to 25% measurement uncertainty. The goal of our study is to provide guidance with respect to technical features of future space-borne lidars, if such lidars will be used for retrievals of microphysical data products, absorption coefficients, and single-scattering albedo. We investigate the impact of two different measurement-error models on the quality of the data products. We also obtain for the first time, to the best of our knowledge, a statistical view on systematic and statistical uncertainties, if a large volume of data is processed. Effective radius is retrieved to 50% accuracy for 58% of cases with an imaginary part up to 0.01i and up to 100% of cases with an imaginary part of 0.05i. Similarly, volume concentration, surface-area concentration, and number concentrations are retrieved to 50% accuracy in 56%-100% of cases, 99%-100% of cases, and 54%-87% of cases, respectively, depending on the imaginary part. The numbers represent measurement uncertainties of up to 15%. If we target 20% retrieval accuracy, the numbers of cases that fall within that threshold are 36%-76% for effective radius, 36%-73% for volume concentration, 98%-100% for surface-area concentration, and 37%-61% for number concentration. That range of numbers again represents a spread in results for different values of the imaginary part. At present, we obtain an accuracy of (on average) 0.1 for the real part. A case study from the ORCALES field campaign is used to illustrate data products obtained with TiARA.

Improved identification of the solution space of aerosol microphysical properties derived from the inversion of profiles of lidar optical data, part 3: case studies

We conclude our series of publications on the development of the gradient correlation method (GCM), which can be used for an improved stabilization of the solution space of particle microphysical parameters derived from measurements with multiwavelength Raman and high-spectral-resolution lidar (3 backscatter +2 extinction coefficients). We show results of three cases studies. The data were taken with a ground-based multiwavelength Raman lidar during the Saharan Mineral Dust Experiment in the Cape Verde Islands (North Atlantic). These cases describe mixtures of dust with smoke. For our data analysis we separated the contribution of smoke to the total signal and only used these optical profiles for the test of GCM. The results show a significant stabilization of the solution space of the particle microphysical parameter retrieval on the particle radius domain from 0.03 to 10 μm, the real part of the complex refractive index domain from 1.3 to 1.8, and the imaginary part from 0 to 0.1. This new method will be included in the Tikhonov Advanced Regularization Algorithm, which is a fully automated, unsupervised algorithm that is used for the analysis of data collected with the worldwide first airborne 3 backscatter +2 extinction high-spectral-resolution lidar developed by NASA Langley Research Center.

Characterization of smoke and dust episode over West Africa: comparison of MERRA-2 modeling with multiwavelength Mie-Raman lidar observations

Observations of multiwavelength Mie-Raman lidar taken during the SHADOW field campaign are used to analyze a smoke-dust episode over West Africa on 24-27 December 2015. For the case considered, the dust layer extended from the ground up to approximately 2000 m while the elevated smoke layer occurred in the 2500-4000 m range. The profiles of lidar measured backscattering, extinction coefficients, and depolarization ratios are compared with the vertical distribution of aerosol parameters provided by the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The MERRA-2 model simulated the correct location of the near-surface dust and elevated smoke layers. The values of modeled and observed aerosol extinction coefficients at both 355 and 532 nm are also rather close. In particular, for the episode reported, the mean value of difference between the measured and modeled extinction coefficients at 355 nm is 0.01 km^-1 with SD of 0.042 km^-1. The model predicts significant concentration of dust particles inside the elevated smoke layer, which is supported by an increased depolarization ratio of 15 % observed in the center of this layer. The modeled at 355 nm the lidar ratio of 65 sr in the near-surface dust layer is close to the observed value (70 ± 10) sr. At 532 nm, however, the simulated lidar ratio (about 40 sr) is lower than measurements (55 ± 8 sr). The results presented demonstrate that the lidar and model data are complimentary and the synergy of observations and models is a key to improve the aerosols characterization.

Earlinet database: new design and new products for a wider use of aerosol lidar data

The EARLINET database is facing a complete reshaping to meet the wide request for more intuitive products and to face the even wider request related to the new initiatives such as Copernicus, the European Earth observation programme. The new design has been carried out in continuity with the past, to take advantage from long-term database. In particular, the new structure will provide information suitable for synergy with other instruments, near real time (NRT) applications, validation and process studies and climate applications.

Retrieval of the particle size distribution function from the data of lidar sensing under the assumption of known refractive index

This paper presents a method to retrieve the particle size distribution function from the data of vertical lidar sensing. We have used 462 data models obtained at the Zvenigorod AERONET site obtained in 2011-2012. For each laser shot, we considered both fine (with particle sizes in a range from 0.05 to 0.6 μm) and coarse aerosol fractions (from 0.6 to 10 μm), with emphasize on the coarse fraction. Our suggested method is a modification of the Tikhonov method. The Tikhonov method is not optimal for coarse particles because its stabilizer does not and cannot account for the presence of the coarse mode, i.e., existence of more than one maximum of the size distribution function. The components of the matrix Wu-1 located in quadrants II and IV are sensitive to the change of these parameters. Neglecting this fact will lead again to arbitrary estimates of the contribution of the coarse particles even for exact values on the main diagonal and the two diagonals adjacent to it. Our method allows the coarse fraction up to 2.5 μm to be determined unambiguously. For larger particles (>2.5  μm) we recommend using the available sets of the coefficients, but with the level of values to be determined.

Forest fire smoke layers observed in the free troposphere over Portugal with a multiwavelength Raman lidar: optical and microphysical properties

Vertically resolved optical and microphysical properties of biomass burning aerosols, measured in 2011 with a multiwavelength Raman lidar, are presented. The transportation time, within 1-2 days (or less), pointed towards the presence of relatively fresh smoke particles over the site. Some strong layers aloft were observed with particle backscatter and extinction coefficients (at 355 nm) greater than 5 Mm⁻¹ sr⁻¹ and close to 300 Mm⁻¹, respectively. The particle intensive optical properties showed features different from the ones reported for aged smoke, but rather consistent with fresh smoke. The Ångström exponents were generally high, mainly above 1.4, indicating a dominating accumulation mode. Weak depolarization values, as shown by the small depolarization ratio of 5% or lower, were measured. Furthermore, the lidar ratio presented no clear wavelength dependency. The inversion of the lidar signals provided a set of microphysical properties including particle effective radius below 0.2 μm, which is less than values previously observed for aged smoke particles. Real and imaginary parts of refractive index of about 1.5-1.6 and 0.02i, respectively, were derived. The single scattering albedo was in the range between 0.85 and 0.93; these last two quantities indicate the nonnegligible absorbing characteristics of the observed particles.

Simultaneous retrieval of the complex refractive indices of the core and shell of coated aerosol particles from extinction measurements using simulated annealing

Simultaneously retrieving the complex refractive indices of the core and shell of coated aerosol particles given the measured extinction efficiency as a function of particle dimensions (core diameter and coated diameter) is much more difficult than retrieving the complex refractive index of homogeneous aerosol particles. Not only must the minimization be performed over a four-parameter space, making it less efficient, but in addition the absolute value of the difference between the measured extinction and the calculated extinction does not have an easily distinguished global minimum. Rather, there are a number of local minima to which almost all conventional retrieval algorithms converge. In this work, we develop a new (to our knowledge) retrieval algorithm that employs the numerical method known as simulated annealing with an innovative "temperature" schedule. This study is limited only to spherical particles with a concentric shell and to cases in which the diameter of both the core and the coated particle are known. We find that when the top ranking particle sizes according to their information content are combined from separate experiments to make up the particle size distribution, the simulated annealing retrieval algorithm is quite robust and by far superior to a greedy random perturbation approach often used.

Raman and fluorescent scattering matrix of spherical microparticles

In this paper, we have investigated the main properties of the Raman and fluorescent matrix of scattering by microspheres using the matrix scattering formalism. The coherent and incoherent inelastic scattering of incident light by a microsphere is described by the Stokes parameters. We demonstrate the main symmetry properties of the coherent and incoherent Raman and fluorescent scattering matrices. Numerical results are presented to illustrate the Raman scattering efficiency, cross-phase coefficient, and some other parameters of scattering by microspheres.

Vertical profiles of microphysical particle properties derived from inversion with two-dimensional regularization of multiwavelength Raman lidar data: experiment

Inversion with two-dimensional (2-D) regularization is a new methodology that can be used for the retrieval of profiles of microphysical properties, e.g., effective radius and complex refractive index of atmospheric particles from complete (or sections) of profiles of optical particle properties. The optical profiles are acquired with multiwavelength Raman lidar. Previous simulations with synthetic data have shown advantages in terms of retrieval accuracy compared to our so-called classical one-dimensional (1-D) regularization, which is a method mostly used in the European Aerosol Research Lidar Network (EARLINET). The 1-D regularization suffers from flaws such as retrieval accuracy, speed, and ability for error analysis. In this contribution, we test for the first time the performance of the new 2-D regularization algorithm on the basis of experimental data. We measured with lidar an aged biomass-burning plume over West/Central Europe. For comparison, we use particle in situ data taken in the smoke plume during research aircraft flights upwind of the lidar. We find good agreement for effective radius and volume, surface-area, and number concentrations. The retrieved complex refractive index on average is lower than what we find from the in situ observations. Accordingly, the single-scattering albedo that we obtain from the inversion is higher than what we obtain from the aircraft data. In view of the difficult measurement situation, i.e., the large spatial and temporal distances between aircraft and lidar measurements, this test of our new inversion methodology is satisfactory.

Particle size distribution retrieval from multiwavelength lidar signals for droplet aerosol

A method of retrieval of the aerosol particle size distribution (APSD) from multiwavelength lidar signals is presented. Assumed distribution (usually a bimodal combination of lognormal functions) with a few free parameters is directly substituted into the lidar equations. The minimization technique allows one to find the parameters that provide the best fit of the assumed APSD by comparison of theoretically generated and experimental signals. Prior knowledge of the lidar ratio is not required. The approach was tested on a typical synthetic APSD consisting of spherical droplets. Comparison of lidar measurements with results from a condensation particle counter was also performed. For signals registered at 3-5 wavelengths from the UV to the near IR a satisfactory retrieval of synthetic APSD is possible for the particles within the 100-3000 nm range.

Information content of data measured with a multiple-field-of-view lidar

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.