Retrieval of aerosol extinction coefficient profiles from Raman lidar data by inversion method

Pornsawad, Pornsarp; D’Amico, Giuseppe; Böckmann, Christine; Amodeo, Aldo; Pappalardo, Gelsomina

doi:10.1364/ao.51.002035

Cited by 14 publications

(23 citation statements)

References 27 publications

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“…The introduction of Veselovskii et al (2002) provides a good review of early attempts and the methodology. Shcherbakov (2007) and Pornsawad et al (2012) demonstrated that such methods return solely positive extinction and can produce more accurate products than the Ansmann method but use Tikhonov smoothing within the retrieval, which generates significant errors where there are substantial gradients. Though the formulation of that technique resembles that of optimal estimation, they differ in their interpretation.…”

Section: Existing Lidar Analysesmentioning

confidence: 99%

Retrieval of aerosol backscatter, extinction, and lidar ratio from Raman lidar with optimal estimation

et al. 2014

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Abstract.Optimal estimation retrieval is a form of nonlinear regression which determines the most probable circumstances that produced a given observation, weighted against any prior knowledge of the system. This paper applies the technique to the estimation of aerosol backscatter and extinction (or lidar ratio) from two-channel Raman lidar observations. It produces results from simulated and real data consistent with existing Raman lidar analyses and additionally returns a more rigorous estimate of its uncertainties while automatically selecting an appropriate resolution without the imposition of artificial constraints. Backscatter is retrieved at the instrument's native resolution with an uncertainty between 2 and 20 %. Extinction is less well constrained, retrieved at a resolution of 0.1-1 km depending on the quality of the data. The uncertainty in extinction is > 15 %, in part due to the consideration of short 1 min integrations, but is comparable to fair estimates of the error when using the standard Raman lidar technique.The retrieval is then applied to several hours of observation on 19 April 2010 of ash from the Eyjafjallajökull eruption. A depolarising ash layer is found with a lidar ratio of 20-30 sr, much lower values than observed by previous studies. This potentially indicates a growth of the particles after 12-24 h within the planetary boundary layer. A lower concentration of ash within a residual layer exhibited a backscatter of 10 Mm −1 sr −1 and lidar ratio of 40 sr.

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Section: Existing Lidar Analysesmentioning

confidence: 99%

Retrieval of aerosol backscatter, extinction, and lidar ratio from Raman lidar with optimal estimation

et al. 2014

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“…This particle mass profiling (PMAP) polarization lidar photometer networking (POLIPHON) method can be regarded as one of the basic techniques for detailed height-resolved profiling of optical and microphysical properties of atmospheric particles. Polarization lidars equipped not only with elastic backscatter channels but also with nitrogen Raman channels increase the potential of such a monitoring site by independently measuring vertical profiles of particle backscatter and extinction coefficients (Ansmann et al, 1992;Ansmann and Müller, 2005;Shcherbakov, 2007;Samoilova and Balin, 2008;Pornsawad et al, 2012) and by providing direct observations on the relationship between backscatter and extinction (lidar ratio) for desert dust, volcanic dust, and for layers with mixtures of dust and fine-mode particles (Mattis et al, 2002Pappalardo et al, 2004;Müller et al, 2007;Wang et al, 2008;Tesche et al, 2009aTesche et al, , 2011aWiegner et al, 2011Wiegner et al, , 2012Groß et al, 2011bGroß et al, , 2012Mona et al, 2012;Papayannis et al, 2012;Sicard et al, 2012).…”

mentioning

confidence: 99%

Profiling of fine and coarse particle mass: case studies of Saharan dust and Eyjafjallajökull/Grimsvötn volcanic plumes

et al. 2012

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Abstract. The polarization lidar photometer networking (POLIPHON) method introduced to separate coarse-mode and fine-mode particle properties of Eyjafjallajökull volcanic aerosols in 2010 is extended to cover Saharan dust events as well. Furthermore, new volcanic dust observations performed after the Grimsvötn volcanic eruptions in 2011 are presented. The retrieval of particle mass concentrations requires mass-specific extinction coefficients. Therefore, a review of recently published mass-specific extinction coefficients for Saharan dust and volcanic dust is given. Case studies of four different scenarios corroborate the applicability of the profiling technique: (a) Saharan dust outbreak to central Europe, (b) Saharan dust plume mixed with biomass-burning smoke over Cape Verde, and volcanic aerosol layers originating from (c) the Eyjafjallajökull eruptions in 2010 and (d) the Grimsvötn eruptions in 2011. Strong differences in the vertical aerosol layering, aerosol mixing, and optical properties are observed for the different volcanic events.

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“…Finally it is worth mentioning that, within the lidar community, other approaches rooted in the numerical derivative problem have been proved to be effective, and there are other methods providing alternative and reasonable ERes definitions (Leblanc et al, 2012;Pornsawad et al, 2012;Trickl, 2010;Shcherbakov, 2007;Eisele and Trickl, 2005;VDIVerein Deutscher Ingenieure, 1999). For this reason a more exhaustive comparison with other approaches to the evaluation of the ERes will be likely done in future in the frame of EARLINET activities.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, this procedure, also known as the "step function" method, has been already tested in the frame of the first EAR-LINET algorithm intercomparison . There are alternative approaches to estimate the ERes such as the analysis of the smoothing effect on the full width at half maximum (FWHM) of a finite impulse (Leblanc et al, 2012), the response to a Heaviside step function (VDIVerein Deutscher Ingenieure, 1999; Eisele and Trickl, 2005;Vogelmann andTrickl, 2008, Trickl, 2010), or the application of the regularization theory to lidar data processing (Pornsawad et al, 2012;Shcherbakov, 2007). However, for SG filters, the "step function" method apparently shows some ambiguous results as can be seen in the examples reported in Fig.…”

Section: The Effective Resolution: the Rayleigh Criterionmentioning

confidence: 99%

“…The primary aim of this paper is to study the problem of the effective resolution (ERes) estimation for lidar products using a different approach with respect to those already presented in the literature (Godin at al., 1999;Beyerle and McDermid, 1999;Shcherbakov, 2007;Trickl, 2010;Leblanc et al, 2012;Pornsawad et al, 2012). A parametric study of several smoothing filters is performed, and the results provide recommendations on the optimization of lidar signal processing.…”

Section: Introductionmentioning

confidence: 99%

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Effective resolution concepts for lidar observations

et al. 2015

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Abstract. Since its establishment in 2000, EARLINET (European Aerosol Research Lidar NETwork) has provided, through its database, quantitative aerosol properties, such as aerosol backscatter and aerosol extinction coefficients, the latter only for stations able to retrieve it independently (from Raman or high-spectral-resolution lidars). These coefficients are stored in terms of vertical profiles, and the EARLINET database also includes the details of the range resolution of the vertical profiles. In fact, the algorithms used in the lidar data analysis often alter the spectral content of the data, mainly acting as low-pass filters to reduce the high-frequency noise. Data filtering is described by the digital signal processing (DSP) theory as a convolution sum: each filtered signal output at a given range is the result of a linear combination of several signal input data samples (relative to different ranges from the lidar receiver), and this could be seen as a loss of range resolution of the output signal. Low-pass filtering always introduces distortions in the lidar profile shape. Thus, both the removal of high frequency, i.e., the removal of details up to a certain spatial extension, and the spatial distortion produce a reduction of the range resolution.This paper discusses the determination of the effective resolution (ERes) of the vertical profiles of aerosol properties retrieved from lidar data. Large attention has been dedicated to providing an assessment of the impact of low-pass filtering on the effective range resolution in the retrieval procedure.

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Retrieval of aerosol extinction coefficient profiles from Raman lidar data by inversion method

Cited by 14 publications

References 27 publications

Retrieval of aerosol backscatter, extinction, and lidar ratio from Raman lidar with optimal estimation

Retrieval of aerosol backscatter, extinction, and lidar ratio from Raman lidar with optimal estimation

Profiling of fine and coarse particle mass: case studies of Saharan dust and Eyjafjallajökull/Grimsvötn volcanic plumes

Effective resolution concepts for lidar observations

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