Potential of Polarization/Raman Lidar to Separate Fine Dust, Coarse Dust

Potential of Polarization/Raman Lidar to Separate Fine Dust, Coarse Dust

Atmos. Meas. Tech., 10, 3403–3427, 2017 https://doi.org/10.5194/amt-10-3403-2017 © Author(s) 2017. This work is distributed under the Creative Commons Attribution 3.0 License. Potential of polarization/Raman lidar to separate fine dust, coarse dust, maritime, and anthropogenic aerosol profiles Rodanthi-Elisavet Mamouri1,2 and Albert Ansmann3 1Cyprus University of Technology, Dep. of Civil Engineering and Geomatics, Limassol, Cyprus 2The Cyprus Institute, Energy, Environment, and Water Research Center, Nicosia, Cyprus 3Leibniz Institute for Tropospheric Research, Leipzig, Germany Correspondence to: Rodanthi-Elisavet Mamouri ([email protected]) Received: 26 April 2017 – Discussion started: 4 May 2017 Revised: 28 July 2017 – Accepted: 2 August 2017 – Published: 19 September 2017 Abstract. We applied the recently introduced polarization advantages in comparison to 355 and 1064 nm polarization lidar–photometer networking (POLIPHON) technique for lidar approaches and leads to the most robust and accurate the first time to triple-wavelength polarization lidar measure- POLIPHON products. ments at 355, 532, and 1064 nm. The lidar observations were performed at Barbados during the Saharan Aerosol Long- Range Transport and Aerosol-Cloud-Interaction Experiment (SALTRACE) in the summer of 2014. The POLIPHON 1 Introduction method comprises the traditional lidar technique to separate mineral dust and non-dust backscatter contributions and the Polarization lidar is a very powerful remote sensing tool for new, extended approach to separate even the fine and coarse aerosol and cloud research. The technique has been used for dust backscatter fractions. We show that the traditional and a long time to monitor and investigate cirrus cloud systems the advanced method are compatible and lead to a consis- (e.g., Sassen, 1991, 2005; Reichardt et al., 2002, 2008) and tent set of dust and non-dust profiles at simplified, less com- polar stratospheric cloud evolution (see, e.g., Browell et al., plex aerosol layering and mixing conditions as is the case 1990; Achtert and Tesche, 2014). The method is well suited over the remote tropical Atlantic. To derive dust mass con- to study heterogeneous ice formation in mixed-phased clouds centration profiles from the lidar observations, trustworthy (e.g., Sassen et al., 2003; Ansmann et al., 2005, 2008; Ans- extinction-to-volume conversion factors for fine, coarse, and mann et al., 2009a; Seifert et al., 2010, 2011) and liquid- total dust are needed and obtained from an updated, extended water cloud developments (e.g., Bissonnette, 2005; Dono- Aerosol Robotic Network sun photometer data analysis of van et al., 2015). Meanwhile, polarization lidars are inten- the correlation between the fine, coarse and total dust volume sively used to explore aerosol mixtures and to identify soil, concentration and the respective fine, coarse, and total dust desert, and volcanic dust (e.g., McNeil and Carswell, 1975; extinction coefficient for all three laser wavelengths. Con- Iwaska and Hayashida, 1981; Winker and Osborn, 1992; version factors (total volume to extinction) for pure marine Gobbi, 1998; Murayama et al., 1999, 2004; Cairo et al., aerosol conditions and continental anthropogenic aerosol sit- 1999; Gobbi et al., 2000; Sakai et al., 2003; Sassen et al., uations are presented in addition. As a new feature of the 2007; Freudenthaler et al., 2009; Ansmann et al., 2010; Ans- POLIPHON data analysis, the Raman lidar method for par- mann et al., 2011a; Groß et al., 2012; Miffre et al., 2012; ticle extinction profiling is used to identify the aerosol type Amiridis et al., 2013; Nisantzi et al., 2014). The technique (marine or anthropogenic) of the non-dust aerosol fraction. permits the discrimination of desert dust or volcanic dust The full POLIPHON methodology was successfully applied from other aerosols such as biomass-burning smoke, mar- to a SALTRACE case and the results are discussed. We con- itime particles, or urban haze (e.g., Sugimoto et al., 2003; clude that the 532 nm polarization lidar technique has many Shimizu et al., 2004; Nishizawa et al., 2007; Tesche et al., 2009a; Ansmann et al., 2012). Another fruitful field is related Published by Copernicus Publications on behalf of the European Geosciences Union. 3404 R.-E. Mamouri and A. Ansmann: Fine and coarse dust profiling to aerosol typing, which is based on combined data sets of the presented in this article, is that this technique does not need particle extinction-to-backscatter ratio (lidar ratio) measured a critical dust particle shape model in the data analysis, as with Raman lidar or high-spectral-resolution lidar (HSRL) required in alternative lidar–photometer retrieval schemes and the particle linear depolarization ratio obtained from po- (Chaikovsky et al., 2012; Lopatin et al., 2013; Torres et al., larization lidar observations (e.g., Burton et al., 2012, 2013; 2016). Another advantage is that the POLIPHON method is Groß et al., 2013, 2015; Illingworth et al., 2015). Recently, based on single-wavelength lidar observations, and as such we broadened the application spectrum of the polarization the method is likewise simple and robust and can be eas- lidar technique by introducing the POLIPHON (polariza- ily automatized and applied to continuously measured large tion lidar–photometer networking) method for estimating data sets. An important advantage is that the technique can be fine dust (particles with radius < 500 nm) and coarse dust used at cloudy conditions. The alternative lidar–photometer mass concentration profiles from single-wavelength polar- approaches need clear skies, which are often not given dur- ization lidar measurements (Mamouri and Ansmann, 2014). ing dust outbreak events. The robust POLIPHON method is Furthermore, we demonstrated that polarization lidars have thus well suited for environmental studies and aerosol–cloud the potential to contribute to vertical profiling of cloud con- interaction research. densation nucleus (CCN) and ice-nucleating particle (INP) In this article, we extend the methodology for fine and concentrations (Mamouri and Ansmann, 2015, 2016). coarse dust separation developed for 532 nm towards 355 and The retrieval of these higher level lidar products is driven 1064 nm lidar wavelengths. A dense set of high-quality ob- by the fact that state-of-the-art environmental (regional) and servational data obtained with a triple-wavelength polariza- global atmospheric models include aerosol schemes which tion lidar collected in the framework of the Saharan Aerosol simulate microphysical aerosol processes and life cycles of a Long-Range Transport and Aerosol-Cloud-Interaction Ex- variety of aerosol components and can be used to predict dust periment (SALTRACE) is available for this study (Haarig events and enable the simulation of CCN and INP profiles et al., 2017a). The importance of such a multi-wavelength ef- (Huneeus et al., 2011; Koffi et al., 2012, 2016; Mann et al., fort arises from the fact that NASA’s spaceborne polarization 2014; Kim et. al., 2014; Nickovic et al., 2016; Hande et al., lidar CALIOP (Cloud Aerosol Lidar with Orthogonal Polar- 2016). These models allow detailed dust climate impact stud- ization; Winker et al., 2009) is operated at 532 nm, whereas ies and forecasts of fine and coarse dust fractions and thus of ESA’s future spaceborne aerosol lidar ATLID (Atmospheric the fine dust contribution to the measured overall fine particle Lidar) will be operated at 355 nm (Illingworth et al., 2015), concentration (PM1, particles with diameters < 1 µm), which and to homogenize these different polarization lidar data sets is of great interest for environmental services (air-quality a good knowledge about the compatibility of 355 and 532 nm management), especially in areas close to deserts. It is im- retrieval schemes is required. In this article, we will discuss portant to quantify the natural impact of fine and coarse dust which of the available three lidar wavelengths is the optimum on recorded aerosol pollution levels measured as PM1, PM2:5 one and produces the most robust and accurate retrieval data (particle diameter < 2.5 µm), and PM10 (particle diameter sets when using the POLIPHON method. < 10 µm). However, dust modeling is associated with mod- Another favorable aspect to further explore the applica- erate to high uncertainties in the predictions and thus needs bility of the POLIPHON analysis scheme is that recently the to be accompanied by advanced dust profile observations. In results of a comprehensive laboratory study on particle linear a review article, Huneeus et al.(2011) emphasized the need depolarization ratios for a variety of soil and desert dust types for height-resolved observations of dust-size-characterizing were published (Järvinen et al., 2016). The most interesting parameters to support dust modeling. Kok et al.(2017) dis- point is that all measurements were performed as a function cussed in detail the consequences of a poorly modeled dust of dust particle size. In this way, for the first time, very de- size distribution (overestimation of the dust fine-mode frac- tailed information on fine dust depolarization ratios became tion) for the global energy balance through direct interaction available and can be used in the POLIPHON methodology of dust with radiation because fine and coarse dust fractions which was based before on a few laboratory measurements show significantly different radiative influences (Nabat et al., of fine- and coarse-dust-dominated linear depolarization ra- 2012; Ridley et al., 2016).

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