Modeling a Spheroidal Particle Ensemble and Inversion by Generalized Runge-Kutta Regularizers from Limited Data

Extracting information about the shape or size of non-spherical aerosol particles from limited optical radar data is a well-known inverse ill-posed problem. The purpose of the study is to figure out a robust and stable regularization method including an appropriate parameter choice rule to address the latter problem. First, we briefly review common regularization methods and investigate a new iterative family of generalized Runge–Kutta filter regularizers. Next, we model a spheroidal particle ensemble and test with it different regularization methods experimenting with artificial data pertaining to several atmospheric scenarios. We found that one method of the newly introduced generalized family combined with the L-curve method performs better compared to traditional methods

Vertical Profiles of Aerosol Optical and Microphysical Properties During a Rare Case of Long-range Transport of Mixed Biomass Burning-polluted Dust Aerosols from the Russian Federation-kazakhstan to Athens, Greece

Multi-wavelength aerosol Raman lidar measurements with elastic depolarization at 532 nm were combined with sun photometry during the HYGRA-CD campaign over Athens, Greece, on May-June 2014. We retrieved the aerosol optical [3 aerosol backscatter profiles (baer) at 355-532-1064 nm, 2 aerosol extinction (aaer) profiles at 355-532 nm and the aerosol linear depolarization ratio (δ) at 532 nm] and microphysical properties [effective radius (reff), complex refractive index (m), single scattering albedo (ω)]. We present a case study of a long distance transport (~3.500-4.000 km) of biomass burning particles mixed with dust from the Russian Federation-Kazakhstan regions arriving over Athens on 21-23 May 2014 (1.7-3.5 km height). On 23 May, between 2-2.75 km we measured mean lidar ratios (LR) of 35 sr (355 nm) and 42 sr (532 nm), while the mean Ångström exponent (AE) aerosol backscatter-related values (355nm/532nm and 532nm/1064nm) were 2.05 and 1.22, respectively; the mean value of δ at 532 nm was measured to be 9%. For that day the retrieved mean aerosol microphysical properties at 2-2.75 km height were: reff=0.26 μm (fine mode), reff=2.15 μm (coarse mode), m=1.36+0.00024i, ω=0.999 (355 nm, fine mode), ω=0.992(355 nm, coarse mode), ω=0.997 (532 nm, fine mode), and ω=0.980 (532 nm, coarse mode)

EARLINET observations of Saharan dust intrusions over the northern Mediterranean region (2014--2017): properties and impact on radiative forcing

Remote sensing measurements of aerosols using depolarization Raman lidar systems from four EARLINET (European Aerosol Research Lidar Network) stations are used for a comprehensive analysis of Saharan dust events over the Mediterranean basin in the period 2014–2017. In this period, 51 dust events regarding the geometrical, optical and microphysical properties of dust were selected, classified and assessed according to their radiative forcing effect on the atmosphere. From west to east, the stations of Granada, Potenza, Athens and Limassol were selected as representative Mediterranean cities regularly affected by Saharan dust intrusions. Emphasis was given on lidar measurements in the visible (532 nm) and specifically on the consistency of the particle linear depolarization ratio (δp532), the extinction-to-backscatter lidar ratio (LR532) and the aerosol optical thickness (AOT532) within the observed dust layers. We found mean δp532 values of 0.24±0.05, 0.26±0.06, 0.28±0.05 and 0.28±0.04, mean LR532 values of 52±8, 51±9, 52±9 and 49±6 sr and mean AOT532 values of 0.40±0.31, 0.11±0.07, 0.12±0.10 and 0.32±0.17, for Granada, Potenza, Athens and Limassol, respectively. The mean layer thickness values were found to range from ∼ 1700 to ∼ 3400 m a.s.l. Additionally, based also on a previous aerosol type classification scheme provided by airborne High Spectral Resolution Lidar (HSRL) observations and on air mass backward trajectory analysis, a clustering analysis was performed in order to identify the mixing state of the dusty layers over the studied area. Furthermore, a synergy of lidar measurements and modeling was used to analyze the solar and thermal radiative forcing of airborne dust in detail. In total, a cooling behavior in the solar range and a significantly lower heating behavior in the thermal range was estimated. Depending on the dust optical and geometrical properties, the load intensity and the solar zenith angle (SZA), the estimated solar radiative forcing values range from −59 to −22 W m−2 at the surface and from −24 to −1 W m−2 at the top of the atmosphere (TOA). Similarly, in the thermal spectral range these values range from +2 to +4 W m−2 for the surface and from +1 to +3 W m−2 for the TOA. Finally, the radiative forcing seems to be inversely proportional to the dust mixing ratio, since higher absolute values are estimated for less mixed dust layers

Retrieval of Dust Microphysical Properties

An intense mineral dust event from the Saharan desert was observed over the Island of Barbados after a long-range transport over the Atlantic Ocean during SALTRACE Campaign in June 2014. We analyze data from a multi-wavelength Raman-lidar system of Leibniz Institute for Tropospheric Research (TROPOS) called BERTHA (Back- scatter Extinction lidar Ratio Temperature Humidity profiling Apparatus) to derive the aerosol microphysical properties of the inspected layer via regularization using the software SphInX (Spheroidal Inversion eXperiments). These parameters were found to be within credible ranges

Application of an Algorithm For the Retrieval of the Aerosol Microphysical Properties Using Inverse Scattering Mathematical Techniques

125 σ.Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Φυσική και Τεχνολογικές Εφαρμογές”Εφαρμογή αλγορίθμου για τον προσδιορισμό των μικροφυσικών ιδιοτήτων των σωματιδίων με χρήση μαθηματικών τεχνικών αντίστροφης σκέδασηςApplication of an algorithm for the retrival of the microphysical properties of aerosol particles using inverse mathematical scaterring techniquesΣτέφανος Σ. Σαμαρά

Combined sphere-spheroid particle model for the retrieval of the microphysical aerosol parameters via regularized inversion of lidar data

In this work we propose a two-step advancement of the Mie spherical-particle model accounting for particle non-sphericity. First, a naturally two-dimensional (2D) generalized model (GM) is made, which further triggers analogous 2D re-definitions of microphysical parameters. We consider a spheroidal-particle approach where the size distribution is additionally dependent on aspect ratio. Second, we incorporate the notion of a sphere-spheroid particle mixture (PM) weighted by a non-sphericity percentage. The efficiency of these two models is investigated running synthetic data retrievals with two different regularization methods to account for the inherent instability of the inversion procedure. Our preliminary studies show that a retrieval with the PM model improves the fitting errors and the microphysical parameter retrieval and it has at least the same efficiency as the GM. While the general trend of the initial size distributions is captured in our numerical experiments, the reconstructions are subject to artifacts. Finally, our approach is applied to a measurement case yielding acceptable results

Combined sphere-spheroid particle model for the retrieval of the microphysical aerosol parameters via regularized inversion of lidar data

In this work we propose a two-step advancement of the Mie spherical-particle model accounting for particle non-sphericity. First, a naturally two-dimensional (2D) generalized model (GM) is made, which further triggers analogous 2D re-definitions of microphysical parameters. We consider a spheroidal-particle approach where the size distribution is additionally dependent on aspect ratio. Second, we incorporate the notion of a sphere-spheroid particle mixture (PM) weighted by a non-sphericity percentage. The efficiency of these two models is investigated running synthetic data retrievals with two different regularization methods to account for the inherent instability of the inversion procedure. Our preliminary studies show that a retrieval with the PM model improves the fitting errors and the microphysical parameter retrieval and it has at least the same efficiency as the GM. While the general trend of the initial size distributions is captured in our numerical experiments, the reconstructions are subject to artifacts. Finally, our approach is applied to a measurement case yielding acceptable results