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

Linear Estimation of Particle Bulk Parameters from Multi-Wavelength Lidar Measurements

An algorithm for linear estimation of aerosol bulk properties such as particle volume, effective radius and complex refractive index from multiwavelength lidar measurements is presented. The approach uses the fact that the total aerosol concentration can well be approximated as a linear combination of aerosol characteristics measured by multiwavelength lidar. Therefore, the aerosol concentration can be estimated from lidar measurements without the need to derive the size distribution, which entails more sophisticated procedures. The definition of the coefficients required for the linear estimates is based on an expansion of the particle size distribution in terms of the measurement kernels. Once the coefficients are established, the approach permits fast retrieval of aerosol bulk properties when compared with the full regularization technique. In addition, the straightforward estimation of bulk properties stabilizes the inversion making it more resistant to noise in the optical data. Numerical tests demonstrate that for data sets containing three aerosol backscattering and two extinction coefficients (so called 3 + 2 ) the uncertainties in the retrieval of particle volume and surface area are below 45% when input data random uncertainties are below 20 %. Moreover, using linear estimates allows reliable retrievals even when the number of input data is reduced. To evaluate the approach, the results obtained using this technique are compared with those based on the previously developed full inversion scheme that relies on the regularization procedure. Both techniques were applied to the data measured by multiwavelength lidar at NASA/GSFC. The results obtained with both methods using the same observations are in good agreement. At the same time, the high speed of the retrieval using linear estimates makes the method preferable for generating aerosol information from extended lidar observations. To demonstrate the efficiency of the method, an extended time series of observations acquired in Turkey in May 2010 was processed using the linear estimates technique permitting, for what we believe to be the first time, temporal-height distributions of particle parameters

Effects of systematic and random errors on the retrieval of particle microphysical properties from multiwavelength lidar measurements using inversion with regularization

In this work we study the effects of systematic and random errors on the inversion of multiwavelength (MW) lidar data using the well-known regularization technique to obtain vertically resolved aerosol microphysical properties. The software implementation used here was developed at the Physics Instrumentation Center (PIC) in Troitsk (Russia) in conjunction with the NASA/Goddard Space Flight Center. Its applicability to Raman lidar systems based on backscattering measurements at three wavelengths (355, 532 and 1064 nm) and extinction measurements at two wavelengths (355 and 532 nm) has been demonstrated widely. The systematic error sensitivity is quantified by first determining the retrieved parameters for a given set of optical input data consistent with three different sets of aerosol physical parameters. Then each optical input is perturbed by varying amounts and the inversion is repeated. Using bimodal aerosol size distributions, we find a generally linear dependence of the retrieved errors in the microphysical properties on the induced systematic errors in the optical data. For the retrievals of effective radius, number/surface/volume concentrations and fine-mode radius and volume, we find that these results are not significantly affected by the range of the constraints used in inversions. But significant sensitivity was found to the allowed range of the imaginary part of the particle refractive index. Our results also indicate that there exists an additive property for the deviations induced by the biases present in the individual optical data. This property permits the results here to be used to predict deviations in retrieved parameters when multiple input optical data are biased simultaneously as well as to study the influence of random errors on the retrievals. The above results are applied to questions regarding lidar design, in particular for the spaceborne multiwavelength lidar under consideration for the upcoming ACE mission.This work was supported by the NASA/Goddard Space Flight Center, the Spanish Ministry of Science and Technology through projects CGL2010-18782 and CSD2007-00067, the Andalusian Regional Government through projects P10-RNM-6299 and P08-RNM-3568, the EU through ACTRIS project (EU INFRA-2010-1.1.16-262254) and the Postdoctoral Program of the University of Granada

Retrieval of optical and physical properties of African dust from multiwavelength Raman lidar measurements during the SHADOW campaign in Senegal

West Africa and the adjacent oceanic regions are very important locations for studying dust properties and their influence on weather and climate. The SHADOW (study of SaHAran Dust Over West Africa) campaign is performing a multiscale and multilaboratory study of aerosol properties and dynamics using a set of in situ and remote sensing instruments at an observation site located at the IRD (Institute for Research and Development) in Mbour, Senegal (14° N, 17° W). In this paper, we present the results of lidar measurements performed during the first phase of SHADOW (study of SaHAran Dust Over West Africa) which occurred in March–April 2015. The multiwavelength Mie–Raman lidar acquired 3<i>β</i> + 2<i>α</i> + 1<i>δ</i> measurements during this period. This set of measurements has permitted particle-intensive properties, such as extinction and backscattering Ångström exponents (BAE) for 355/532 nm wavelengths' corresponding lidar ratios and depolarization ratio at 532 nm, to be determined. The mean values of dust lidar ratios during the observation period were about 53 sr at both 532 and 355 nm, which agrees with the values observed during the SAMUM-1 and SAMUM-2 campaigns held in Morocco and Cabo Verde in 2006 and 2008. The mean value of the particle depolarization ratio at 532 nm was 30 ± 4.5 %; however, during strong dust episodes this ratio increased to 35 ± 5 %, which is also in agreement with the results of the SAMUM campaigns. The backscattering Ångström exponent during the dust episodes decreased to ∼ −0.7, while the extinction Ångström exponent, though negative, was greater than −0.2. Low values of BAE can likely be explained by an increase in the imaginary part of the dust refractive index at 355 nm compared to 532 nm. The dust extinction and backscattering coefficients at multiple wavelengths were inverted to the particle microphysics using the regularization algorithm and the model of randomly oriented spheroids. The analysis performed has demonstrated that the spectral dependence of the imaginary part of the dust refractive index may significantly influence the inversion results and should be taken into account

Mie–Raman–fluorescence lidar observations of aerosols during pollen season in the north of France

International audienceAbstract. The multiwavelength Mie–Raman–fluorescence lidar of the University of Lille has the capability to measure three aerosol backscattering coefficients, two extinction coefficients and three linear depolarization ratios, together with fluorescence backscattering at 466 nm. It was used to characterize aerosols during the pollen season in the north of France for the period March–June 2020. The results of observations demonstrate that the presence of pollen grains in aerosol mixture leads to an increase in the depolarization ratio. Moreover, the depolarization ratio exhibits a strong spectral dependence increasing with wavelength, which is expected for the mixture containing fine background aerosols with low depolarization and strongly depolarizing pollen grains. A high depolarization ratio correlates with the enhancement of the fluorescence backscattering, corroborating the presence of pollen grains. Obtained results demonstrate that simultaneous measurements of particle depolarization and fluorescence allows for the separation of dust, smoke particles and aerosol mixtures containing the pollen grains

Direct Estimation of Fine and Coarse Mode Particle Parameters from Multiwavelength Lidar Measurements

An approach for the direct estimation (DE) of particle parameters in the fine and coarse mode from multiwavelength lidar measurements is presented. Particle size distributions in both modes are approximated by rectangular functions, so the particle density is estimated directly without solving the inverse problem. The numerical simulation demonstrates that the particle volume in both modes can be estimated from 3β+2α lidar measurements with uncertainty of ~25% for a wide range of size distributions. The technique developed was applied to the observations of NASA GSFC Raman lidar. Comparison of the results obtained with DE and regularization approach applied to the same set of data demonstrates agreement between these two techniques

Comparison of aerosol properties retrieved using GARRLiC, LIRIC, and Raman algorithms applied to multi-wavelength lidar and sun/sky-photometer data

Aerosol particles are important and highly variable components of the terrestrial atmosphere, and they affect both air quality and climate. In order to evaluate their multiple impacts, the most important requirement is to precisely measure their characteristics. Remote sensing technologies such as lidar (light detection and ranging) and sun/sky photometers are powerful tools for determining aerosol optical and microphysical properties. In our work, we applied several methods to joint or separate lidar and sun/sky-photometer data to retrieve aerosol properties. The Raman technique and inversion with regularization use only lidar data. The LIRIC (LIdar-Radiometer Inversion Code) and recently developed GARRLiC (Generalized Aerosol Retrieval from Radiometer and Lidar Combined data) inversion methods use joint lidar and sun/sky-photometer data. This paper presents a comparison and discussion of aerosol optical properties (extinction coefficient profiles and lidar ratios) and microphysical properties (volume concentrations, complex refractive index values, and effective radius values) retrieved using the aforementioned methods. The comparison showed inconsistencies in the retrieved lidar ratios. However, other aerosol properties were found to be generally in close agreement with the AERONET (AErosol RObotic NETwork) products. In future studies, more cases should be analysed in order to clearly define the peculiarities in our results

Characterization of forest fire smoke event near Washington, DC in summer 2013 with multi-wavelength lidar

The multi-wavelength lidar technique was applied to the study of a smoke event near Washington, DC on 26–28 August 2013. Satellite observations combined with transport model predictions imply that the smoke plume originated mainly from Wyoming/Idaho forest fires and its transportation to Washington, DC took approximately 5 days. The NASA Goddard Space Flight Center (GSFC) multi-wavelength Mie–Raman lidar was used to measure the smoke particle intensive parameters such as extinction and backscatter Ångström exponents together with lidar ratios at 355 and 532 nm wavelengths. For interpretation of the observed vertical profiles of the backscatter Ångström exponents &gamma;_&beta; at 355–532 and 532–1064 nm, numerical simulation was performed. The results indicate that, for fine-mode dominant aerosols, the Ångström exponents &gamma;_&beta;(355–532) and &gamma;_&beta;(532–1064) have essentially different dependence on the particle size and refractive index. Inversion of 3 &beta; + 2 &alpha; lidar observations on 27–28 August provided vertical variation of the particle volume, effective radius and the real part of the refractive index through the planetary boundary layer (PBL) and the smoke layer. The particle effective radius decreased with height from approximately 0.27 μm inside the PBL to 0.15 μm in the smoke layer, which was situated above the PBL. Simultaneously the real part of the refractive index in the smoke layer increased to <i>m</i>_R &approx; 1.5. The retrievals demonstrate also that the fine mode is predominant in the particle size distribution, and that the decrease of the effective radius with height is due to a shift of the fine mode toward smaller radii

Comparison of aerosol properties retrieved using GARRLiC, LIRIC, and Raman algorithms applied to multi-wavelength lidar and sun/sky-photometer data

Aerosol particles are important and highly variable components of the terrestrial atmosphere, and they affect both air quality and climate. In order to evaluate their multiple impacts, the most important requirement is to precisely measure their characteristics. Remote sensing technologies such as lidar (light detection and ranging) and sun/sky photometers are powerful tools for determining aerosol optical and microphysical properties. In our work, we applied several methods to joint or separate lidar and sun/sky-photometer data to retrieve aerosol properties. The Raman technique and inversion with regularization use only lidar data. The LIRIC (LIdar-Radiometer Inversion Code) and recently developed GARRLiC (Generalized Aerosol Retrieval from Radiometer and Lidar Combined data) inversion methods use joint lidar and sun/sky-photometer data. This paper presents a comparison and discussion of aerosol optical properties (extinction coefficient profiles and lidar ratios) and microphysical properties (volume concentrations, complex refractive index values, and effective radius values) retrieved using the aforementioned methods. The comparison showed inconsistencies in the retrieved lidar ratios. However, other aerosol properties were found to be generally in close agreement with the AERONET (AErosol RObotic NETwork) products. In future studies, more cases should be analysed in order to clearly define the peculiarities in our results

High temporal resolution estimates of columnar aerosol microphysical parameters from spectrum of aerosol optical depth by linear estimation: application to long-term AERONET and star-photometry measurements

This work deals with the applicability of the linear estimation technique (LE) to invert spectral measurements of aerosol optical depth (AOD) provided by AERONET CIMEL sun photometers. The inversion of particle properties using only direct-sun AODs allows the evaluation of parameters such as effective radius (reff) and columnar volume aerosol content (V) with significantly better temporal resolution than the operational AERONET algorithm which requires both direct sun and sky radiance measurements. Sensitivity studies performed demonstrate that the constraints on the range of the inversion are very important to minimize the uncertainties, and therefore estimates of reff can be obtained with uncertainties less than 30 % and of V with uncertainties below 40 %. The LE technique is applied to data acquired at five AERONET sites influenced by different aerosol types and the retrievals are compared with the results of the operational AERONET code. Good agreement between the two techniques is obtained when the fine mode predominates, while for coarse mode cases the LE results systematically underestimate both reff and V. The highest differences are found for cases where no mode predominates. To minimize these biases, correction functions are developed using the multi-year database of observations at selected sites, where the AERONET retrieval is used as the reference. The derived corrections are tested using data from 18 other AERONET stations offering a range of aerosol types. After correction, the LE retrievals provide better agreement with AERONET for all the sites considered. Finally, the LE approach developed here is applied to AERONET and star-photometry measurements in the city of Granada (Spain) to obtain day-to-night time evolution of columnar aerosol microphysical properties.This work was supported by the NASA Atmospheric Composition Program and by the NASA Aerosols, Clouds, Ecosystems mission. Support has also been provided by the Spanish Ministry of Science and Technology through projects CGL2010-18782 and CSD2007-00067, by the Andalusian Regional Government through projects P10-RNM-6299 and P08-RNM-3568, by the EU through ACTRIS project (EU INFRA-2010-1.1.16-262254), and by the Postdoctoral Program of the University of Granada. The authors would like to express their gratitude to the NOAA Air Resources Laboratory and Naval Research Laboratory for the HYSPLIT model