Physics Instrumentation Center

Troitsk, Russia

Physics Instrumentation Center

Troitsk, Russia
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Nicolae D.,Romanian National Institute for Optoelectronics | Nemuc A.,Romanian National Institute for Optoelectronics | Muller D.,Leibniz Institute for Tropospheric Research | Muller D.,Gwangju Institute of Science and Technology | And 6 more authors.
Journal of Geophysical Research: Atmospheres | Year: 2013

This paper focuses on optical and microphysical properties of long-range transported biomass burning (BB) aerosols and their variation with atmospheric evolution (ageing), as observed by a multiwavelength Raman lidar, part of EARLINET (European Aerosol LIdar NETwork). Chemical analysis of the atmospheric aerosol was done using a colocated aerosol mass spectrometer (AMS). One relevant optical parameter for the ageing process is the Ångström exponent. In our study, we find that it decreases from 2 for fresh to 1.4-0.5 for aged smoke particles. The ratio of lidar (extinction-to-backscatter) ratios (LR 532/LR355) changes rapidly from values <1 for fresh to >1 for aged particles. The imaginary part of the refractive index is the most sensitive microphysical parameter. It decreases sharply from 0.05 to less than 0.01 for fresh and aged smoke particles, respectively. Singlescattering albedo (SSA) varies from 0.74 to 0.98 depending on aerosol age and source. The AMS was used to measure the marker ions of wood-burning particles during 2 days of measurements when the meteorological conditions favored the downward mixing of aerosols from lofted layers. Particle size distribution and particle effective radius from both AMS and lidar are similar, i.e., particle effective radii were approximately 0.27 μm for fresh BB aerosol particles. Microphysical aerosol properties from inversion of the lidar data agree with similar studies carried out in different regions on the globe. Our study shows that the Ångström exponent LR532/LR355 and the imaginary part of the refractive index can be used to clearly distinguish between fresh and aged smoke particles. © 2013. American Geophysical Union. All Rights Reserved.


Muller D.,Leibniz Institute for Tropospheric Research | Muller D.,Gwangju Institute of Science and Technology | Muller D.,University of Hertfordshire | Muller D.,Science Systems And Applications Inc. | And 6 more authors.
Applied Optics | Year: 2013

We present for the first time vertical profiles of microphysical properties of pure mineral dust (largely unaffected by any other aerosol types) on the basis of the inversion of optical data collected with multi-wavelength polarization Raman lidar. The data were taken during the Saharan Mineral Dust Experiment (SAMUM) in Morocco in 2006. We also investigated two cases of mixed dust-smoke plumes on the basis of data collected during the second SAMUM field campaign that took place in the Republic of Cape Verdein 2008. Following the experience of the Aerosol Robotic Network (AERONET), the dust is modeled as a mixture of spherical particles and randomly oriented spheroids. The retrieval is performed from the full set of lidar input data (three backscatter coefficients, two extinction coefficients, and one depolarization ratio) and from a reduced set of data in which we exclude the depolarization ratio. We find differences of the microphysical properties depending on what kind of optical data combination we use. For the case of pure mineral dust, the results from these two sets of optical data are consistent and confirm the validity of the spheroid particle model for data inversion. Our results indicate that in the case of pure mineral dust we do not need depolarization information in the inversion. For the mixture of dust and biomass burning, there seem to be more limitations in the retrieval accuracy of the various data products. The evaluation of the quality of our data products is done by comparing our lidar-derived data products (vertically resolved) to results from AERONET Sun photometer observations (column-averaged) carried out at the lidar field site. Our results for dust effective radius show agreement with the AERONET observations within the retrieval uncertainties. Regarding the complex refractive index a comparison is difficult, as AERONET provides this parameter as wavelength-dependent quantity. In contrast, our inversion algorithm provides this parameter as a wavelength-independent quantity. We also show some comparison to results from airborne in situ observation. A detailed comparison to in situ results will be left for a future contribution. © 2013 Optical Society of America.


Muller D.,Gwangju Institute of Science and Technology | Kolgotin A.,Physics Instrumentation Center | Mattis I.,Leibniz Institute for Tropospheric Research | Petzold A.,German Aerospace Center | Stohl A.,Norwegian Institute For Air Research
Applied Optics | Year: 2011

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 overWest/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. © 2011 Optical Society of America.


Veselovskii I.,Physics Instrumentation Center | Dubovik O.,Lille University of Science and Technology | Kolgotin A.,Physics Instrumentation Center | Korenskiy M.,Physics Instrumentation Center | And 4 more authors.
Atmospheric Measurement Techniques | Year: 2012

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 multi-wavelength 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 3β2 + 2α) 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. © 2012 Author(s). CC Attribution 3.0 License.


Kazadzis S.,Institute for Environmental Research and Sustainable Development IERSD | Veselovskii I.,Physics Instrumentation Center | Amiridis V.,National institute for astrophysics | Grobner J.,World Radiation Center | And 6 more authors.
Atmospheric Measurement Techniques | Year: 2014

Synchronized sun-photometric measurements from the AERONET-CIMEL (AErosol RObotic NETwork) and GAW-PFR (Global Atmospheric Watch-Precision Filter Radiometer) aerosol networks are used to compare retrievals of the aerosol optical depth (AOD), effective radius, and volume concentration during a high-temporal-resolution measurement campaign at the Athens site in the Mediterranean Basin from 14 to 22 July 2009. During this period, direct-sun AOD retrievals from both instruments exhibited small differences in the range 0.01-0.02. The AODs measured with CIMEL and PFR instruments were inverted to retrieve particle microphysical properties using the linear estimation (LE) technique. For low aerosol loads (AOD < 0.2), measurements of the effective radius by the PFR were found to be -20% to +30% different from CIMEL values for both direct-sun data and inversion data. At higher loads (AOD > 0.4), measurements of the effective radius by the PFR are consistently 20 % lower than CIMEL for both direct-sun and inversion data. Volume concentrations at low aerosol loads from the PFR are up to 80% higher than the CIMEL for direct-sun data but are up to 20% lower when derived from inversion data under these same conditions. At higher loads, the percentage difference in volume concentrations from the PFR and CIMEL is systematically negative, with inversion data predicting differences 30% lower than those obtained from direct-sun data. An assessment of the effect of errors in the AOD retrieval on the estimation of PFR bulk parameters was performed and demonstrates that it is possible to estimate the particle volume concentration and effective radius with an uncertainty < 65% when AOD < 0.2 and when input errors are as high as 10%. © Author(s) 2014. CC Attribution 3.0 License.


Di Girolamo P.,University of Basilicata | Summa D.,University of Basilicata | Bhawar R.,University of Basilicata | Di Iorio T.,University of Rome La Sapienza | And 4 more authors.
Atmospheric Environment | Year: 2012

The Raman lidar system BASIL was operational in Achern (Black Forest) between 25 May and 30 August 2007 in the framework of the Convective and Orographically-induced Precipitation Study (COPS). The system performed continuous measurements over a period of approx. 36h from 06:22 UTC on 1 August to 18:28 UTC on 2 August 2007, capturing the signature of a severe Saharan dust outbreak episode. The data clearly reveal the presence of two almost separate aerosol layers: a lower layer located between 1.5 and 3.5km above ground level (a.g.l.) and an upper layer extending between 3.0 and 6.0km a.g.l. The time evolution of the dust cloud is illustrated and discussed in the paper in terms of several optical parameters (particle backscatter ratio at 532 and 1064nm, the colour ratio and the backscatter Angström parameter).An inversion algorithm was used to retrieve particle size and microphysical parameters, i.e., mean and effective radius, number, surface area, volume concentration, and complex refractive index, as well as the parameters of a bimodal particle size distribution (PSD), from the multi-wavelength lidar data of particle backscattering, extinction and depolarization. The retrieval scheme employs Tikhonov's inversion with regularization and makes use of kernel functions for randomly oriented spheroids. Size and microphysical parameters of dust particles are estimated as a function of altitude at different times during the dust outbreak event. Retrieval results reveal the presence of a fine mode with radii of 0.1-0.2μm and a coarse mode with radii of 3-5μm both in the lower and upper dust layers, and the dominance in the upper dust layer of a coarse mode with radii of 4-5μm. Effective radius varies with altitude in the range 0.1-1.5μm, while volume concentration is found to not exceed 92μm 3cm -3. The real and imaginary part of the complex refractive index vary in the range 1.4-1.6 and 0.004-0.008, respectively. © 2012 Elsevier Ltd.


Veselovskii I.,Physics Instrumentation Center | Dubovik O.,Lille University of Science and Technology | Kolgotin A.,Physics Instrumentation Center | Lapyonok T.,Lille University of Science and Technology | And 5 more authors.
Journal of Geophysical Research: Atmospheres | Year: 2010

Multiwavelength (MW) Raman lidars have demonstrated their potential to profile particle parameters; however, until now, the physical models used in retrieval algorithms for processing MW lidar data have been predominantly based on the Mie theory. This approach is applicable to the modeling of light scattering by spherically symmetric particles only and does not adequately reproduce the scattering by generally nonspherical desert dust particles. Here we present an algorithm based on a model of randomly oriented spheroids for the inversion of multiwavelength lidar data. The aerosols are modeled as a mixture of two aerosol components: one composed only of spherical and the second composed of nonspherical particles. The nonspherical component is an ensemble of randomly oriented spheroids with size-independent shape distribution. This approach has been integrated into an algorithm retrieving aerosol properties from the observations with a Raman lidar based on a tripled Nd:YAG laser. Such a lidar provides three backscattering coefficients, two extinction coefficients, and the particle depolarization ratio at a single or multiple wavelengths. Simulations were performed for a bimodal particle size distribution typical of desert dust particles. The uncertainty of the retrieved particle surface, volume concentration, and effective radius for 10% measurement errors is estimated to be below 30%. We show that if the effect of particle nonsphericity is not accounted for, the errors in the retrieved aerosol parameters increase notably. The algorithm was tested with experimental data from a Saharan dust outbreak episode, measured with the BASIL multiwavelength Raman lidar in August 2007. The vertical profiles of particle parameters as well as the particle size distributions at different heights were retrieved. It was shown that the algorithm developed provided substantially reasonable results consistent with the available independent information about the observed aerosol event. Copyright © 2010 by the American Geophysical Union.


Haarig M.,Leibniz Institute for Tropospheric Research | Engelmann R.,Leibniz Institute for Tropospheric Research | Ansmann A.,Leibniz Institute for Tropospheric Research | Veselovskii I.,Physics Instrumentation Center | And 2 more authors.
Atmospheric Measurement Techniques | Year: 2016

For the first time, vertical profiles of the 1064 nm particle extinction coefficient obtained from Raman lidar observations at 1058 nm (nitrogen and oxygen rotational Raman backscatter) are presented. We applied the new technique in the framework of test measurements and performed several cirrus observations of particle backscatter and extinction coefficients, and corresponding extinctionto- backscatter ratios at the wavelengths of 355, 532, and 1064 nm. The cirrus backscatter coefficients were found to be equal for all three wavelengths keeping the retrieval uncertainties in mind. The multiple-scattering-corrected cirrus extinction coefficients at 355 nm were on average about 20-30% lower than the ones for 532 and 1064 nm. The cirrus-mean extinction-to-backscatter ratio (lidar ratio) was 31±5 sr (355 nm), 36±5 sr (532 nm), and 38±5 sr (1064 nm) in this single study. We further discussed the requirements needed to obtain aerosol extinction profiles in the lower troposphere at 1064 nm with good accuracy (20% relative uncertainty) and appropriate temporal and vertical resolution. © Author(s) 2016.


Suvorina A.,Physics Instrumentation Center | Veselovskii I.,Physics Instrumentation Center | Whiteman D.N.,NASA | Korenskiy M.,Physics Instrumentation Center
EPJ Web of Conferences | Year: 2016

Vibrational Raman scattering from nitrogen is commonly used in Mie-Raman lidars for evaluation of particle backscattering (β) and extinction (α) coefficients. However, vibrational scattering is characterized by significant frequency shift of the Raman component, so for the calculation of α and β the assumption about the extinction Ångstrom exponent is needed. Simulation results presented in this study demonstrate that ambiguity in the choice of this exponent can be the significant source of uncertainty in the calculation of backscattering coefficients when optically thick aerosol layers are considered. Examples of lidar measurements and optical data calculated for different values of Ångstrom exponent are given. © 2016 Owned by the authors, published by EDP Sciences.


Kolgotin A.,Physics Instrumentation Center | Korenskiy M.,Physics Instrumentation Center | Veselovskii I.,Physics Instrumentation Center | Whiteman D.N.,NASA
EPJ Web of Conferences | Year: 2016

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. © 2016 Owned by the authors, published by EDP Sciences.

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