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Lidar-Radiometer Inversion Code (LIRIC) for the retrieval of vertical aerosol properties from combined lidar/radiometer data: Development and distribution in EARLINET

2016, Chaikovsky, Anatoli, Dubovik, Oleg, Holben, Brent, Bril, Andrey, Goloub, Philippe, Tanré, Didier, Pappalardo, Gelsomina, Wandinger, Ulla, Chaikovskaya, Ludmila, Denisov, Sergey, Grudo, Jan, Lopatin, Anton, Karol, Yana, Lapyonok, Tatsiana, Amiridis, Vassilis, Ansmann, Albert, Apituley, Arnoud, Allados-Arboledas, Lucas, Binietoglou, Ioannis, Boselli, Antonella, D'Amico, Giuseppe, Freudenthaler, Volker, Giles, David, Granados-Muñoz, María José, Kokkalis, Panayotis, Nicolae, Doina, Oshchepkov, Sergey, Papayannis, Alex, Perrone, Maria Rita, Pietruczuk, Alexander, Rocadenbosch, Francesc, Sicard, Michaël, Slutsker, Ilya, Talianu, Camelia, De Tomasi, Ferdinando, Tsekeri, Alexandra, Wagner, Janet, Wang, Xuan

This paper presents a detailed description of LIRIC (LIdar-Radiometer Inversion Code) algorithm for simultaneous processing of coincident lidar and radiometric (sun photometric) observations for the retrieval of the aerosol concentration vertical profiles. As the lidar/radiometric input data we use measurements from European Aerosol Research Lidar Network (EARLINET) lidars and collocated sun-photometers of Aerosol Robotic Network (AERONET). The LIRIC data processing provides sequential inversion of the combined lidar and radiometric data. The algorithm starts with the estimations of column-integrated aerosol parameters from radiometric measurements followed by the retrieval of height dependent concentrations of fine and coarse aerosols from lidar signals using integrated column characteristics of aerosol layer as a priori constraints. The use of polarized lidar observations allows us to discriminate between spherical and non-spherical particles of the coarse aerosol mode. The LIRIC software package was implemented and tested at a number of EARLINET stations. Intercomparison of the LIRIC-based aerosol retrievals was performed for the observations by seven EARLINET lidars in Leipzig, Germany on 25 May 2009. We found close agreement between the aerosol parameters derived from different lidars that supports high robustness of the LIRIC algorithm. The sensitivity of the retrieval results to the possible reduction of the available observation data is also discussed.

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Potential of polarization lidar to provide profiles of CCN-and INP-relevant aerosol parameters

2016, Mamouri, Rodanthi-Elisavet, Ansmann, Albert

We investigate the potential of polarization lidar to provide vertical profiles of aerosol parameters from which cloud condensation nucleus (CCN) and ice nucleating particle (INP) number concentrations can be estimated. We show that height profiles of particle number concentrations n50, dry considering dry aerosol particles with radius  > 50 nm (reservoir of CCN in the case of marine and continental non-desert aerosols), n100, dry (particles with dry radius  >  100 nm, reservoir of desert dust CCN), and of n250, dry (particles with dry radius  >  250 nm, reservoir of favorable INP), as well as profiles of the particle surface area concentration sdry (used in INP parameterizations) can be retrieved from lidar-derived aerosol extinction coefficients σ with relative uncertainties of a factor of 1.5–2 in the case of n50, dry and n100, dry and of about 25–50 % in the case of n250, dry and sdry. Of key importance is the potential of polarization lidar to distinguish and separate the optical properties of desert aerosols from non-desert aerosol such as continental and marine particles. We investigate the relationship between σ, measured at ambient atmospheric conditions, and n50, dry for marine and continental aerosols, n100, dry for desert dust particles, and n250, dry and sdry for three aerosol types (desert, non-desert continental, marine) and for the main lidar wavelengths of 355, 532, and 1064 nm. Our study is based on multiyear Aerosol Robotic Network (AERONET) photometer observations of aerosol optical thickness and column-integrated particle size distribution at Leipzig, Germany, and Limassol, Cyprus, which cover all realistic aerosol mixtures. We further include AERONET data from field campaigns in Morocco, Cabo Verde, and Barbados, which provide pure dust and pure marine aerosol scenarios. By means of a simple CCN parameterization (with n50, dry or n100, dry as input) and available INP parameterization schemes (with n250, dry and sdry as input) we finally compute profiles of the CCN-relevant particle number concentration nCCN and the INP number concentration nINP. We apply the method to a lidar observation of a heavy dust outbreak crossing Cyprus and a case dominated by continental aerosol pollution.

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Calibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data

2018, Dai, Guangyao, Althausen, Dietrich, Hofer, Julian, Engelmann, Ronny, Seifert, Patric, Bühl, Johannes, Mamouri, Rodanthi-Elisavet, Wu, Songhua, Ansmann, Albert

We present a practical method to continuously calibrate Raman lidar observations of water vapor mixing ratio profiles. The water vapor profile measured with the multiwavelength polarization Raman lidar PollyXT is calibrated by means of co-located AErosol RObotic NETwork (AERONET) sun photometer observations and Global Data Assimilation System (GDAS) temperature and pressure profiles. This method is applied to lidar observations conducted during the Cyprus Cloud Aerosol and Rain Experiment (CyCARE) in Limassol, Cyprus. We use the GDAS temperature and pressure profiles to retrieve the water vapor density. In the next step, the precipitable water vapor from the lidar observations is used for the calibration of the lidar measurements with the sun photometer measurements. The retrieved calibrated water vapor mixing ratio from the lidar measurements has a relative uncertainty of 11 % in which the error is mainly caused by the error of the sun photometer measurements. During CyCARE, nine measurement cases with cloud-free and stable meteorological conditions are selected to calculate the precipitable water vapor from the lidar and the sun photometer observations. The ratio of these two precipitable water vapor values yields the water vapor calibration constant. The calibration constant for the PollyXT Raman lidar is 6.56 g kg−1 ± 0.72 g kg−1 (with a statistical uncertainty of 0.08 g kg−1 and an instrumental uncertainty of 0.72 g kg−1). To check the quality of the water vapor calibration, the water vapor mixing ratio profiles from the simultaneous nighttime observations with Raman lidar and Vaisala radiosonde sounding are compared. The correlation of the water vapor mixing ratios from these two instruments is determined by using all of the 19 simultaneous nighttime measurements during CyCARE. Excellent agreement with the slope of 1.01 and the R2 of 0.99 is found. One example is presented to demonstrate the full potential of a well-calibrated Raman lidar. The relative humidity profiles from lidar, GDAS (simulation) and radiosonde are compared, too. It is found that the combination of water vapor mixing ratio and GDAS temperature profiles allow us to derive relative humidity profiles with the relative uncertainty of 10–20 %.

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Vertical aerosol distribution in the southern hemispheric midlatitudes as observed with lidar in Punta Arenas, Chile (53.2° and 70.9° W), during ALPACA

2019, Foth, Andreas, Kanitz, Thomas, Engelmann, Ronny, Baars, Holger, Radenz, Martin, Seifert, Patric, Barja, Boris, Fromm, Michael, Kalesse, Heike, Ansmann, Albert

Within this publication, lidar observations of the vertical aerosol distribution above Punta Arenas, Chile (53.2 S and 70.9 W), which have been performed with the Raman lidar PollyXT from December 2009 to April 2010, are presented. Pristine marine aerosol conditions related to the prevailing westerly circulation dominated the measurements. Lofted aerosol layers could only be observed eight times during the whole measurement period. Two case studies are presented showing long-range transport of smoke from biomass burning in Australia and regionally transported dust from the Patagonian Desert, respectively. The aerosol sources are identified by trajectory analyses with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and FLEXible PARTicle dispersion model (FLEXPART). However, seven of the eight analysed cases with lofted layers show an aerosol optical thickness of less than 0.05. From the lidar observations, a mean planetary boundary layer (PBL) top height of 1150 350m was determined. An analysis of particle backscatter coefficients confirms that the majority of the aerosol is attributed to the PBL, while the free troposphere is characterized by a very low background aerosol concentration. The ground-based lidar observations at 532 and 1064 nm are supplemented by the Aerosol Robotic Network (AERONET) Sun photometers and the space-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The averaged aerosol optical thickness (AOT) determined by CALIOP was 0:02 0:01 in Punta Arenas from 2009 to 2010. © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.

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Extreme levels of Canadian wildfire smoke in the stratosphere over central Europe on 21-22 August 2017

2018, Ansmann, Albert, Baars, Holger, Chudnovsky, Alexandra, Mattis, Ina, Veselovskii, Igor, Haarig, Moritz, Seifert, Patric, Engelmann, Ronny, Wandinger, Ulla

Light extinction coefficients of 500 Mm1, about 20 times higher than after the Pinatubo volcanic eruptions in 1991, were observed by European Aerosol Research Lidar Network (EARLINET) lidars in the stratosphere over central Europe on 21-22 August 2017. Pronounced smoke layers with a 1-2 km vertical extent were found 2-5 km above the local tropopause. Optically dense layers of Canadian wildfire smoke reached central Europe 10 days after their injection into the upper troposphere and lower stratosphere which was caused by rather strong pyrocumulonimbus activity over western Canada. The smoke-related aerosol optical thickness (AOT) identified by lidar was close to 1.0 at 532 nm over Leipzig during the noon hours on 22 August 2017. Smoke particles were found throughout the free troposphere (AOT of 0.3) and in the pronounced 2 km thick stratospheric smoke layer at an altitude of 14-16 km (AOT of 0.6). The lidar observations indicated peak mass concentrations of 70-100 μgm-3 in the stratosphere. In addition to the lidar profiles, we analyzed Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power (FRP) over Canada, and the distribution of MODIS AOT and Ozone Monitoring Instrument (OMI) aerosol index across the North Atlantic. These instruments showed a similar pattern and a clear link between the western Canadian fires and the aerosol load over Europe. In this paper, we also present Aerosol Robotic Network (AERONET) sun photometer observations, compare photometer and lidar-derived AOT, and discuss an obvious bias (the smoke AOT is too low) in the photometer observations. Finally, we compare the strength of this recordbreaking smoke event (in terms of the particle extinction coefficient and AOT) with major and moderate volcanic events observed over the northern midlatitudes.