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.     

Theory of inversion with two-dimensional regularization: profiles of microphysical particle properties derived from multiwavelength lidar measurements

We present the theory of inversion with two-dimensional regularization. We use this novel method to retrieve profiles of microphysical properties of atmospheric particles from profiles of optical properties acquired with multiwavelength Raman lidar. This technique is the first attempt to the best of our knowledge, toward an operational inversion algorithm, which is strongly needed in view of multiwavelength Raman lidar networks. The new algorithm has several advantages over the inversion with so-called classical one-dimensional regularization. Extensive data postprocessing procedures, which are needed to obtain a sensible physical solution space with the classical approach, are reduced. Data analysis, which strongly depends on the experience of the operator, is put on a more objective basis. Thus, we strongly increase unsupervised data analysis. First results from simulation studies show that the new methodology in many cases outperforms our old methodology regarding accuracy of retrieved particle effective radius, and number, surface-area, and volume concentration. The real and the imaginary parts of the complex refractive index can be estimated with at least as equal accuracy as with our old method of inversion with one-dimensional regularization. However, our results on retrieval accuracy still have to be verified in a much larger simulation study.     

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.     

Retrieval of aerosol properties from combined multiwavelength lidar and sunphotometer measurements

Simulation studies were carried out with regard to the feasibility of using combined observations from sunphotometer (SPM) and lidar for microphysical characterization of aerosol particles, i.e., the retrieval of effective radius, volume, and surface-area concentrations. It was shown that for single, homogeneous aerosol layers, the aerosol parameters can be retrieved with an average accuracy of 30% for a wide range of particle size distributions. Based on the simulations, an instrument combination consisting of a lidar that measures particle backscattering at 355 and 1574 nm, and a SPM that measures at three to four channels in the range from 340 to 1020 nm is a promising tool for aerosol characterization. The inversion algorithm has been tested for a set of experimental data. The comparison with the particle size distribution parameters, measured with in situ instrumentation at the lidar site, showed good agreement.     

Determination of stratospheric aerosol microphysical properties from independent extinction and backscattering measurements with a Raman lidar

An algorithm that permits the retrieval of profiles of particle mass and surface-area concentrations in the stratospheric aerosol layer from independently measured aerosol (particle and Rayleigh) and molecule (Raman or Rayleigh) backscatter signals is developed. The determination is based on simultaneously obtained particle extinction and backscatter profiles and on relations between optical and microphysical properties found from Mie-scattering calculations for realistic stratospheric particle size distributions. The size distributions were measured with particle counters released on balloons from Laramie, Wyoming, between June 1991 and April 1994. Mass and surface-area concentrations can be retrieved with relative errors of 10-20% and 20-40%, respectively, with a laser wavelength of 355 nm and with errors of 20-30% and 30-60%, respectively, with a laser wavelength of 308 nm. Lidar measurements taken within the first three years after the eruption of Mt. Pinatubo in June 1991 are shown. Surface-area concentrations around 20 μm(2) cm(-3) and mass concentrations of 3 to 6 μg m(-3) were found until spring 1993.     

Tropospheric aerosol optical properties derived from lidar, sun photometer, and optical particle counter measurements

Tropospheric aerosols have been observed for the period from November 1990 to April 1992 with a lidar, a sun photometer, and an optical particle counter. Variations of aerosol optical thickness derived from the lidar and the sun photometer data and measurements are presented. The simultaneous measurements of these instruments also allowed us to estimate the extinction-to-backscatter ratio (S(1)), which ranged from 20 to 70. Comparison of optical thicknesses derived from both instruments clearly shows the effect of Mt. Pinatubo's eruption and the temporal variation of optical thickness in the stratosphere over 12 km. The possible range of the complex refractive index for the columnar mean aerosols can be deduced from the probable range of S(1) derived by the use of an S(1) diagram as a function of complex refractive index (m). The imaginary part of m can be estimated provided that the real part of m is known.     

Principal component analysis applied to multiwavelength lidar aerosol backscatter and extinction measurements

The use of powerful Raman backscatter lidars enables one to measure the stratospheric aerosol extinction profile independently of the backscatter, thereby obtaining additional information to aid in retrieving the physical characteristics of the sampled aerosol. We used principal component analysis to construct a self-consistent method for the retrieval of aerosol bulk physical and optical properties from multiwavelength elastic and/or inelastic Raman backscatter lidar signals. The procedure is applied to synthetic and actual lidar signals. We found that aerosol surface area and volume can be usefully estimated and that the use of Raman-derived extinction data leads to a notable improvement in the accuracy of the estimations.     

Inversion of multiwavelength Raman lidar data for retrieval of bimodal aerosol size distribution

We report on the feasibility of deriving microphysical parameters of bimodal particle size distributions from Mie-Raman lidar based on a triple Nd:YAG laser. Such an instrument provides backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm. The inversion method employed is Tikhonov's inversion with regularization. Special attention has been paid to extend the particle size range for which this inversion scheme works to approximately 10 microm, which makes this algorithm applicable to large particles, e.g., investigations concerning the hygroscopic growth of aerosols. Simulations showed that surface area, volume concentration, and effective radius are derived to an accuracy of approximately 50% for a variety of bimodal particle size distributions. For particle size distributions with an effective radius of < 1 microm the real part of the complex refractive index was retrieved to an accuracy of +/- 0.05, the imaginary part was retrieved to 50% uncertainty. Simulations dealing with a mode-dependent complex refractive index showed that an average complex refractive index is derived that lies between the values for the two individual modes. Thus it becomes possible to investigate external mixtures of particle size distributions, which, for example, might be present along continental rims along which anthropogenic pollution mixes with marine aerosols. Measurement cases obtained from the Institute for Tropospheric Research six-wavelength aerosol lidar observations during the Indian Ocean Experiment were used to test the capabilities of the algorithm for experimental data sets. A benchmark test was attempted for the case representing anthropogenic aerosols between a broken cloud deck. A strong contribution of particle volume in the coarse mode of the particle size distribution was found.     

Inversion with regularization for the retrieval of tropospheric aerosol parameters from multiwavelength lidar sounding

We present an inversion algorithm for the retrieval of particle size distribution parameters, i.e., mean (effective) radius, number, surface area, and volume concentration, and complex refractive index from multiwavelength lidar data. In contrast to the classical Tikhonov method, which accepts only that solution for which the discrepancy reaches its global minimum, in our algorithm we perform the averaging of solutions in the vicinity of this minimum. This averaging stabilizes the underlying ill-posed inverse problem, particularly with respect to the retrieval of number concentration. Results show that, for typical tropospheric particles and 10% error in the optical data, the mean radius could be retrieved to better than 20% from a lidar on the basis of a Nd:YAG laser, which provides a combination of backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm. The accuracy is improved if the lidar is also equipped with a hydrogen Raman shifter. In this case two additional backscatter coefficients at 416 and 683 nm are available. The combination of two extinction coefficients and five backscatter coefficients then allows one to retrieve not only averaged aerosol parameters but also the size distribution function. There was acceptable agreement between physical particle properties obtained from the evaluation of multiwavelength lidar data taken during the Lindenberg Aerosol Characterization Experiment in 1998 (LACE 98) and in situ data, which were taken aboard aircraft.     

Microphysical particle parameters from extinction and backscatter lidar data by inversion with regularization: experiment

We present effective radius, volume, surface-area, and number concentrations as well as mean complex refractive index of tropospheric particle size distributions based on lidar measurements at six wavelengths. The parameters are derived by means of an inversion algorithm that has been specifically designed for the inversion of available optical data sets. The data were taken on 20 June and on 20 July 1997 during the Aerosol Characterization Experiment ACE 2 (North Atlantic/Portugal) and on 9 August 1998 during the Lindenberg Aerosol Characterization Experiment LACE 98 (Lindenberg/Germany). Measurements on 20 June 1997 were taken in a clean-marine boundary layer, and a large value of 0.64 mum for the effective radius, a low value of 1.45 for the real part, and a negligible imaginary part of the complex refractive index were found. The single-scatter albedo was 0.98 at 532 nm. It was derived from the particle parameters with Mie-scattering calculations. In contrast, the particles were less than 0.2 mum in effective radius in a continental-polluted aerosol layer on 20 July 1997. The real part of the complex refractive index was ~1.6; the imaginary part showed values near 0.03i. The single-scatter albedo was 0.84. On 9 August 1998 an elevated particle layer located from 3000 to 6000 m was observed, which had originated from an area of biomass burning in northwestern Canada. Here the effective radius was ~0.24 mum, the real part of the complex refractive index was above 1.6, the imaginary part was ~0.04i, and the single-scatter albedo was 0.81. Excellent agreement has been found with results based on sunphotometer and in situ measurements that were performed during the field campaigns.     

Microphysical particle parameters from extinction and backscatter lidar data by inversion with regularization: theory

A method is proposed that permits one to retrieve physical parameters of tropospheric particle size distributions, e.g., effective radius, volume, surface-area, and number concentrations, as well as the mean complex refractive index on a routine basis from backscatter and extinction coefficients at multiple wavelengths. The optical data in terms of vertical profiles are derived from multiple-wavelength lidar measurements at 355, 400, 532, 710, 800, and 1064 nm for backscatter data and 355 and 532 nm for extinction data. The algorithm is based on the concept of inversion with regularization. Regularization is performed by generalized cross-validation. This method does not require knowledge of the shape of the particle size distribution and can handle measurement errors of the order of 20%. It is shown that at least two extinction data are necessary to retrieve the particle parameters to an acceptable accuracy. Simulations with monomodal and bimodal logarithmic-normal size distributions show that it is possible to derive effective radius, volume, and surface-area concentrations to an accuracy of +/-50%, the real part of the complex refractive index to +/-0.05, and the imaginary part to +/-50%. Number concentrations may have errors larger than +/-50%.     

Microphysical particle parameters from extinction and backscatter lidar data by inversion with regularization: simulation

A sensitivity study with an inversion scheme that permits one to retrieve physical parameters of tropospheric particle size distributions, e.g., effective radius, volume, surface-area, and number concentrations, as well as the mean complex refractive index from backscatter and extinction coefficients at multiple wavelengths is presented. The optical data for the analysis are derived from Mie-scattering calculations for monomodal and bimodal logarithmic-normal distributions in the particle size range between 0.01 and 10 microm. The complex refractive index is taken between 1.33 and 1.8 in the real part and between 0 and 0.1 in the imaginary part. The choice of these parameters takes account of properties of optically active atmospheric particles. The wavelengths were chosen at 355, 400, 532, 710, 800, and 1064 nm for the backscatter and at 355 and 532 nm for the extinction data, which are the available wavelengths of the two lidar systems at the Institute for Tropospheric Research. Cases of erroneous optical data of the order of as much as 20%, an unknown refractive index, which may also be wavelength and size dependent, as well as the a priori unknown modality of the particle size distribution were considered. It is shown that both extinction channels are necessary for determining the above-mentioned parameters within reasonable limits, i.e., effective radius, surface-area, and volume concentrations to an accuracy of +/-50%, the real part of the complex refractive index to +/-0.1, and the imaginary part to +/-50%. The number concentration may have errors larger than 50%. The overall performance of the inversion scheme permits the evaluation of experimental data on a routine basis.     

Extension of the graphical technique for estimation of particle size distribution parameters for the consistent intercomparison of diverse sets of multiwavelength lidar derived optical coefficients

In applying the graphical technique to the estimation of the particle size distribution (PSD) parameters, determination of proper bounds surrounding the solution space for a particular confidence level is essential to the consistent intercomparison of diverse multiwavelength lidar optical data sets. The graphical technique utilizes ratios of backscatter and/or extinction coefficients, and it is shown that if the correlation between ratios is not taken into account in calculating the error bounds, the solution space will be overestimated, resulting in relatively larger discrepancies for a larger number of optical coefficients. A method for correcting the bounds, to account for the correlation is developed for various numbers of wavelengths. These improved bounds are then applied, for the case of a monomodal lognormal PSD, with an assumed refractive index, to assess the role additional Raman extinction channels play in improving retrieval capability of a typical three-channel backscatter lidar (1064, 532, and 355 nm) under varying noise levels. Applying the same formalism to underlying bimodal distributions of coarse and fine particles can result in false monomodal solutions. However, when both Raman optical extinction channels are available, no solution is obtained. This can potentially serve as a quick and simple method, prior to a more complex regularization analysis, to differentiate between cases in which the fine mode is dominant versus the cases in which the contribution from the coarse mode is significant.     

High-efficiency aerosol scatterometer that uses an integrating sphere for the calibration of multiwavelength lidar data

For the purpose of calibrating multiwavelength lidar data, we developed a scatterometer to measure the aerosol scattering coefficient at the ground level. The system is based on an integrating sphere, cw lasers (532 and 633 nm), and a controlled flow of the ambient air, including aerosol particles. The simulation study and experimental results indicate that the detection efficiency of this instrument is approximately 10%-40% better than that of an integrating nephelometer, because of the wider acceptance angle of the scattered light. The scattering coefficients measured at the two wavelengths, as well as the resulting value of the angstrom exponent, show good correlation with the results simultaneously measured with an integrating nephelometer and an optical particle counter.     

Synergetic technique combining elastic backscatter lidar data and sunphotometer AERONET inversion for retrieval by layer of aerosol optical and microphysical properties

We present a so-called lidar and almucantar (LidAlm) algorithm that combines information provided by standard elastic backscatter lidar (i.e., calibrated attenuated backscatter coefficient profile at one or two wavelengths) and sunphotometer AERONET inversion of almucantar like measurements (i.e., column-integrated aerosol size distribution and refractive index). The purpose of the LidAlm technique is to characterize the atmospheric column by its different aerosol layers. These layers may be distinct or partially mixed, and they may contain different aerosol species (e.g., urban, desert, or biomass burning aerosols). The LidAlm synergetic technique provides the extinction and backscatter coefficient profiles, particle size distributions, and backscatter-to-extinction ratios for each aerosol layer. We present the LidAlm procedure and sensitivity studies. The applications are illustrated with examples of actual atmospheric conditions encountered in the Paris area.     

Retrieval of physical particle properties from lidar observations of extinction and backscatter at multiple wavelengths

Tropospheric height profiles of five particle backscatter coefficients between 355 and 800 nm and particle extinction coefficients at 355 and 532 nm measured with a multiple-wavelength backscatter lidar and a dual-wavelength Raman lidar are presented. From these data microphysical particle parameters are determined by a specifically designed inversion algorithm.     

Iterative method for the inversion of multiwavelength lidar signals to determine aerosol size distribution

Two iterative methods of inverting lidar backscatter signals to determine altitude profiles of aerosol extinction and altitude-resolved aerosol size distribution (ASD) are presented. The first method is for inverting two-wavelength lidar signals in which the shape of the ASD is assumed to be of power-law type, and the second method is for inverting multiwavelength lidar signals without assuming any a priori analytical form of ASD. An arbitrary value of the aerosol extinction-to-backscatter ratio (S(1)) is assumed initially to invert the lidar signals, and the ASD determined by use of the spectral dependence of the retrieved aerosol extinction coefficients is used to improve the value of S(1) iteratively. The methods are tested for different forms of altitude-dependent ASD's by use of simulated lidar-backscatter-signal profiles. The effect of random noise on the lidar backscatter signals is also studied.     

Hybrid regularization method for the ill-posed inversion of multiwavelength lidar data in the retrieval of aerosol size distributions

A specially developed method is proposed to retrieve the particle volume distribution, the mean refractive index, and other important physical parameters, e.g., the effective radius, volume, surface area, and number concentrations of tropospheric and stratospheric aerosols, from optical data by use of multiple wavelengths. This algorithm requires neither a priori knowledge of the analytical shape of the distribution nor an initial guess of the distribution. As a result, even bimodal and multimodal distributions can be retrieved without any advance knowledge of the number of modes. The nonlinear ill-posed inversion is achieved by means of a hybrid method combining regularization by discretization, variable higher-order B-spline functions and a truncated singular-value decomposition. The method can be used to handle different lidar devices that work with various values and numbers of wavelengths. It is shown, to my knowledge for the first time, that only one extinction and three backscatter coefficients are sufficient for the solution. Moreover, measurement errors up to 20% are allowed. This result could be achieved by a judicious fusion of different properties of three suitable regularization parameters. Finally, numerical results with an additional unknown refractive index show the possibility of successfully recovering both unknowns simultaneously from the lidar data: the aerosol volume distribution and the refractive index.