Vertical profiles of pure dust and mixed smoke-dust plumes inferred from inversion of multiwavelength Raman/polarization lidar data and comparison to AERONET retrievals and in situ observations

Simulated depolarization ratios for dust and smoke at laser wavelengths: implications for lidar application

Polarization measurements have been widely used to detect aerosol properties by remote sensing in recent decades. To better understand the polarization characteristics of aerosols by lidar, the numerically exact T-matrix method was used to simulate the depolarization ratio (DR) of dust and smoke aerosols at typical laser wavelengths in this study. The results show that the DRs of dust and smoke aerosols have obviously different spectral dependences. Moreover, the ratio of DRs at two wavelengths has an obvious linear relationship with the microphysical properties of aerosols, including aspect ratio, effective radius and complex refractive index. At short wavelengths, we can use it to invert the absorption characteristics of particles, further improving the detection ability of lidar. Comparing the simulation results of different channels, DR, (color ratio) CR and (lidar ratio) LR have a good logarithmic fitting relationship at 532 nm and 1064 nm, which helps to classify the aerosol types. On this basis, a new inversion algorithm, "1β+1α+2δ", was presented. By this algorithm, the backscattering coefficient (β), extinction coefficient (α), DR (δ) at 532 nm and 1064 nm can be used to expand the range of inversion and compare lidar data with different configurations to obtain more extensive optical characteristics of aerosols. Our study enhances the application of laser remote sensing in aerosol observations more accurately.

Simulation and misalignment analysis of the gain ratio of a polarization Mie Raman lidar

The gain ratio is a critical parameter in a polarization Mie lidar. Calibrating the gain ratio is essential in aerosol classification studies. We developed a ray-tracing-based simulation method to investigate the impact of mounting errors on the gain ratio. In this method, a computational model for each element of the lidar was built, and Zemax was used to simulate the lidar receiver to obtain the optical gain ratio by theoretical calculations. This method can analyze the influence of each element's mounting errors and offer a theoretical foundation for the machining and mounting accuracy of the lidar design. The correctness of the model was verified by applying it to a single-wavelength polarization Mie Raman lidar.

Profiling Dust Mass Concentration in Northwest China Using a Joint Lidar and Sun-Photometer Setting

The satellite-based estimation of the dust mass concentration (DMC) is essential for accurately evaluating the global biogeochemical cycle of the dust aerosols. As for the uncertainties in estimating DMC caused by mixing dust and pollutants and assuming a fixed value for the mass extinction efficiency (MEE), a classic lidar-photometer method is employed to identify and separate the dust from pollutants, obtain the dust MEE, and evaluate the effect of the above uncertainties, during five dust field experiments in Northwest China. Our results show that this method is effective for continental aerosol mixtures consisting of dust and pollutants. It is also seen that the dust loading mainly occurred in the free troposphere (<6 km), with the average mass loading of 905 ± 635 µg m−2 trapped in the planetary boundary layer. The dust MEE ranges from 0.30 to 0.60 m2 g−1 and has a significantly negative relationship with the size of dust particles. With the assumption of the dust MEE of 0.37 (0.60) m2 g−1, the DMC is shown to be overestimated (underestimated) by 20–40% (15–30%). In other words, our results suggest that the change of MEE with the size of dust particles should be considered in the estimation of DMC.

On the use of light polarization to investigate the size, shape, and refractive index dependence of backscattering Ångström exponents

In this Letter, we exploit the polarization property of light to investigate the Ångström exponent describing the wavelength dependence of optical backscatter between two wavelengths. Where previous interpretation of Ångström exponent was that of a particle size indicator, the use of light polarization makes it possible to investigate the Ångström exponent dependence on the particle shape by separately retrieving the backscattering Ångström exponent of the spherical (s) and non-spherical (ns) particles contained in an atmospheric particle mixture $(p) = \{s, {\rm ns}\}$(p)={s,ns}. As an output, analytical solutions of the Maxwell's equations (Lorenz-Mie theory, spheroidal model) can then be applied to investigate the Ångström exponent dependence on the particle size and complex refractive index for each assigned shape. Interestingly, lidar-retrieved vertical profiles of backscattering Ångström exponents specific to $s$s- and ns-particles can be used by the optical community to evaluate a range of involved particle sizes and complex refractive indices for both particle shapes, $s$s and ns, as we remotely demonstrate on a case study dedicated to a dust nucleation event.

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.

Considerations about the Determination of the Depolarization Calibration Profile of a Two-Telescope Lidar and Its Implications for Volume Depolarization Ratio Retrieval

We propose a new method for calculating the volume depolarization ratio of light backscattered by the atmosphere and a lidar system that employs an auxiliary telescope to detect the depolarized component. It takes into account the possible error in the positioning of the polarizer used in the auxiliary telescope. The theory of operation is presented and then applied to a few cases for which the actual position of the polarizer is estimated, and the improvement of the volume depolarization ratio in the molecular region is quantified. In comparison to the method used before, i.e., without correction, the agreement between the volume depolarization ratio with correction and the theoretical value in the molecular region is improved by a factor of 2–2.5.

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.

Synergy of lidar and passive remote sensor data for retrieving profiles of microphysical properties of non-spherical particles

In this study we explore how the combination of 3 backscatter and 2 extinction lidar data with data that can be collected with ground-based and space-borne passive remote sensors, e.g. phase function coefficients which can be derived at various measurement wavelengths and scattering angles can result in improved profiles of particle microphysical properties. The algorithm is based on a light-scattering model that uses a mixture of spheres and randomly oriented spheroids.

An Architecture Providing Depolarization Ratio Capability for a Multi-Wavelength Raman Lidar: Implementation and First Measurements

A new architecture for the measurement of depolarization produced by atmospheric aerosols with a Raman lidar is presented. The system uses two different telescopes: one for depolarization measurements and another for total-power measurements. The system architecture and principle of operation are described. The first experimental results are also presented, corresponding to a collection of atmospheric conditions over the city of Barcelona.

Improved identification of the solution space of aerosol microphysical properties derived from the inversion of profiles of lidar optical data, part 1: theory

Multiwavelength Raman/high spectral resolution lidars that measure backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm can be used for the retrieval of particle microphysical parameters, such as effective and mean radius, number, surface-area and volume concentrations, and complex refractive index, from inversion algorithms. In this study, we carry out a correlation analysis in order to investigate the degree of dependence that may exist between the optical data taken with lidar and the underlying microphysical parameters. We also investigate if the correlation properties identified in our study can be used as a priori or a posteriori constraints for our inversion scheme so that the inversion results can be improved. We made the simplifying assumption of error-free optical data in order to find out what correlations exist in the best case situation. Clearly, for practical applications, erroneous data need to be considered too. On the basis of simulations with synthetic optical data, we find the following results, which hold true for arbitrary particle size distributions, i.e., regardless of the modality or the shape of the size distribution function: surface-area concentrations and extinction coefficients are linearly correlated with a correlation coefficient above 0.99. We also find a correlation coefficient above 0.99 for the extinction coefficient versus (1) the ratio of the volume concentration to effective radius and (2) the product of the number concentration times the sum of the squares of the mean radius and standard deviation of the investigated particle size distributions. Besides that, we find that for particles of any mode fraction of the particle size distribution, the complex refractive index is uniquely defined by extinction- and backscatter-related Ångström exponents, lidar ratios at two wavelengths, and an effective radius.

Vertically resolved separation of dust and other aerosol types by a new lidar depolarization method

This paper developed a new retrieval framework of external mixing of the dust and non-dust aerosol to predict the lidar ratio of the external mixing aerosols and to separate the contributions of non-spherical aerosols by using different depolarization ratios among dust, sea salt, smoke, and polluted aerosols. The detailed sensitivity tests and case study with the new method showed that reliable dust information could be retrieved even without prior information about the non-dust aerosol types. This new method is suitable for global dust retrievals with satellite observations, which is critical for better understanding global dust transportation and for model improvements.

Optical, size and mass properties of mixed type aerosols in Greece and Romania as observed by synergy of lidar and sunphotometers in combination with model simulations: a case study

A coordinated experimental campaign aiming to study the aerosol optical, size and mass properties was organized in September 2012, in selected sites in Greece and Romania. It was based on the synergy of lidar and sunphotometers. In this paper we focus on a specific campaign period (23-24 September), where mixed type aerosols (Saharan dust, biomass burning and continental) were confined from the Planetary Boundary Layer (PBL) up to 4-4.5 km height. Hourly mean linear depolarization and lidar ratio values were measured inside the dust layers, ranging from 13 to 29 and from 44 to 65sr, respectively, depending on their mixing status and the corresponding air mass pathways over Greece and Romania. During this event the columnar Aerosol Optical Depth (AOD) values ranged from 0.13 to 0.26 at 532 nm. The Lidar/Radiometer Inversion Code (LIRIC) and the Polarization Lidar Photometer Networking (POLIPHON) codes were used and inter-compared with regards to the retrieved aerosol (fine and coarse spherical/spheroid) mass concentrations, showing that LIRIC generally overestimates the aerosol mass concentrations, in the case of spherical particles. For non-spherical particles the difference in the retrieved mass concentration profiles from these two codes remained smaller than ±20%. POLIPHON retrievals showed that the non-spherical particles reached concentrations of the order of 100-140 μg/m(3) over Romania compared to 50-75 μg/m(3) over Greece. Finally, the Dust Regional Atmospheric Model (DREAM) model was used to simulate the dust concentrations over the South-Eastern Europe.