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- ItemLidar-Radiometer Inversion Code (LIRIC) for the retrieval of vertical aerosol properties from combined lidar/radiometer data: Development and distribution in EARLINET(München : European Geopyhsical Union, 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, XuanThis 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.
- ItemCalibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data(München : European Geopyhsical Union, 2018) Dai, Guangyao; Althausen, Dietrich; Hofer, Julian; Engelmann, Ronny; Seifert, Patric; Bühl, Johannes; Mamouri, Rodanthi-Elisavet; Wu, Songhua; Ansmann, AlbertWe 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 %.
- ItemPotential of polarization lidar to provide profiles of CCN-and INP-relevant aerosol parameters(München : European Geopyhsical Union, 2016) Mamouri, Rodanthi-Elisavet; Ansmann, AlbertWe 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.