Search Results
The automated multiwavelength Raman polarization and water-vapor lidar PollyXT: The neXT generation
2016, Engelmann, Ronny, Kanitz, Thomas, Baars, Holger, Heese, Birgit, Althausen, Dietrich, Skupin, Annett, Wandinger, Ulla, Komppula, Mika, Stachlewska, Iwona S., Amiridis, Vassilis, Marinou, Eleni, Mattis, Ina, Linné, Holger, Ansmann, Albert
The atmospheric science community demands autonomous and quality-assured vertically resolved measurements of aerosol and cloud properties. For this purpose, a portable lidar called Polly was developed at TROPOS in 2003. The lidar system was continuously improved with gained experience from the EARLINET community, involvement in worldwide field campaigns, and international institute collaborations within the last 10 years. Here we present recent changes of the setup of the portable multiwavelength Raman and polarization lidar PollyXT and discuss the improved capabilities of the system by means of a case study. The latest system developments include an additional near-range receiver unit for Raman measurements of the backscatter and extinction coefficient down to 120 m above ground, a water-vapor channel, and channels for simultaneous measurements of the particle linear depolarization ratio at 355 and 532 nm. Quality improvements were achieved by systematically following the EARLINET guidelines and the international PollyNET quality assurance developments. A modified ship radar ensures measurements in agreement with air-traffic safety regulations and allows for 24∕7 monitoring of the atmospheric state with PollyXT.
An overview of the first decade of PollyNET: An emerging network of automated Raman-polarization lidars for continuous aerosol profiling
2016, Baars, Holger, Kanitz, Thomas, Engelmann, Ronny, Althausen, Dietrich, Heese, Birgit, Komppula, Mika, Preißler, Jana, Tesche, Matthias, Ansmann, Albert, Wandinger, Ulla, Lim, Jae-Hyun, Ahn, Joon Young, Stachlewska, Iwona S., Amiridis, Vassilis, Marinou, Eleni, Seifert, Patric, Hofer, Julian, Skupin, Annett, Schneider, Florian, Bohlmann, Stephanie, Foth, Andreas, Bley, Sebastian, Pfüller, Anne, Giannakaki, Eleni, Lihavainen, Heikki, Viisanen, Yrjö, Hooda, Rakesh Kumar, Pereira, Sérgio Nepomuceno, Bortol, Daniele, Wagner, Frank, Mattis, Ina, Janicka, Lucja, Markowicz, Krzysztof M., Achtert, Peggy, Artaxo, Paulo, Pauliquevis, Theotonio, Souza, Rodrigo A.F., Sharma, Ved Prakesh, van Zyl, Pieter Gideon, Beukes, Johan Paul, Sun, Junying, Rohwer, Erich G., Deng, Ruru, Mamouri, Rodanthi-Elisavet, Zamorano, Felix
A global vertically resolved aerosol data set covering more than 10 years of observations at more than 20 measurement sites distributed from 63° N to 52° S and 72° W to 124° E has been achieved within the Raman and polarization lidar network PollyNET. This network consists of portable, remote-controlled multiwavelength-polarization-Raman lidars (Polly) for automated and continuous 24/7 observations of clouds and aerosols. PollyNET is an independent, voluntary, and scientific network. All Polly lidars feature a standardized instrument design with different capabilities ranging from single wavelength to multiwavelength systems, and now apply unified calibration, quality control, and data analysis. The observations are processed in near-real time without manual intervention, and are presented online at http://polly.tropos.de/. The paper gives an overview of the observations on four continents and two research vessels obtained with eight Polly systems. The specific aerosol types at these locations (mineral dust, smoke, dust-smoke and other dusty mixtures, urban haze, and volcanic ash) are identified by their Ångström exponent, lidar ratio, and depolarization ratio. The vertical aerosol distribution at the PollyNET locations is discussed on the basis of more than 55 000 automatically retrieved 30 min particle backscatter coefficient profiles at 532 nm as this operating wavelength is available for all Polly lidar systems. A seasonal analysis of measurements at selected sites revealed typical and extraordinary aerosol conditions as well as seasonal differences. These studies show the potential of PollyNET to support the establishment of a global aerosol climatology that covers the entire troposphere.
Relationship between temperature and apparent shape of pristine ice crystals derived from polarimetric cloud radar observations during the ACCEPT campaign
2016, Myagkov, Alexander, Seifert, Patric, Wandinger, Ulla, Bühl, Johannes, Engelmann, Ronny
This paper presents first quantitative estimations of apparent ice particle shape at the top of liquid-topped clouds. Analyzed ice particles were formed under mixed-phase conditions in the presence of supercooled water and in the temperature range from −20 to −3 °C. The estimation is based on polarizability ratios of ice particles measured by a Ka-band cloud radar MIRA-35 with hybrid polarimetric configuration. Polarizability ratio is a function of the geometrical axis ratio and the dielectric properties of the observed hydrometeors. For this study, 22 cases observed during the ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) field campaign were used. Polarizability ratios retrieved for cloud layers with the cloud-top temperatures of ∼ −5, ∼ −8, ∼ −15, and ∼ −20 °C were 1.6, 0.9, 0.6, and 0.9, respectively. Such values correspond to prolate, quasi-isotropic, oblate, and quasi-isotropic particles, respectively. Data from a free-fall chamber were used for the comparison. A good agreement of detected apparent shapes with well-known shape–temperature dependencies observed in laboratories was found. Polarizability ratios used for the analysis were estimated for areas located close to the cloud top, where aggregation and riming processes do not strongly affect ice particles. We concluded that, in microwave scattering models, ice particles detected in these areas can be assumed to have pristine shapes. It was also found that even slight variations of ambient conditions at the cloud top with temperatures warmer than ∼ −5 °C can lead to rapid changes of ice crystal shape.
Assessment of lidar depolarization uncertainty by means of a polarimetric lidar simulator
2016, Bravo-Aranda, Juan Antonio, Belegante, Livio, Freudenthaler, Volker, Alados-Arboledas, Lucas, Nicolae, Doina, Granados-Muñoz, María José, Guerrero-Rascado, Juan Luis, Amodeo, Aldo, D'Amico, Giusseppe, Engelmann, Ronny, Pappalardo, Gelsomina, Kokkalis, Panos, Mamouri, Rodanthy, Papayannis, Alex, Navas-Guzmán, Francisco, Olmo, Francisco José, Wandinger, Ulla, Amato, Francesco, Haeffelin, Martial
Lidar depolarization measurements distinguish between spherical and non-spherical aerosol particles based on the change of the polarization state between the emitted and received signal. The particle shape information in combination with other aerosol optical properties allows the characterization of different aerosol types and the retrieval of aerosol particle microphysical properties. Regarding the microphysical inversions, the lidar depolarization technique is becoming a key method since particle shape information can be used by algorithms based on spheres and spheroids, optimizing the retrieval procedure. Thus, the identification of the depolarization error sources and the quantification of their effects are crucial. This work presents a new tool to assess the systematic error of the volume linear depolarization ratio (δ), combining the Stokes–Müller formalism and the complete sampling of the error space using the lidar model presented in Freudenthaler (2016a). This tool is applied to a synthetic lidar system and to several EARLINET lidars with depolarization capabilities at 355 or 532 nm. The lidar systems show relative errors of δ larger than 100 % for δ values around molecular linear depolarization ratios (∼ 0.004 and up to ∼ 10 % for δ = 0.45). However, one system shows only relative errors of 25 and 0.22 % for δ = 0.004 and δ = 0.45, respectively, and gives an example of how a proper identification and reduction of the main error sources can drastically reduce the systematic errors of δ. In this regard, we provide some indications of how to reduce the systematic errors.