Articles | Volume 8, issue 3
https://doi.org/10.5194/amt-8-1593-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-8-1593-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
27 Mar 2015
Research article |
| 27 Mar 2015
The impact of the microphysical properties of aerosol on the atmospheric correction of hyperspectral data in coastal waters
Institute for Atmospheric Pollution Research (IIA), Italian National Research Council (CNR), Via Research Area of Rome 1, Via Salaria Km 29 300, 00016 Monterotondo Scalo, Rome, Italy
Institute for Atmospheric Pollution Research (IIA), Italian National Research Council (CNR), Via Research Area of Rome 1, Via Salaria Km 29 300, 00016 Monterotondo Scalo, Rome, Italy
F. Braga
Institute of Marine Sciences (ISMAR), Italian National Research Council (CNR), Arsenale Tesa 104, Castello 2737/F, 30122 Venice, Italy
M. Bresciani
Institute for Electromagnetic Sensing of the Environment (IREA), Italian National Research Council (CNR), Via Bassini 13, 20133 Milan, Italy
C. Giardino
Institute for Electromagnetic Sensing of the Environment (IREA), Italian National Research Council (CNR), Via Bassini 13, 20133 Milan, Italy
L. Alberotanza
Institute of Marine Sciences (ISMAR), Italian National Research Council (CNR), Arsenale Tesa 104, Castello 2737/F, 30122 Venice, Italy
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Related subject area
Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Aerosol optical depth retrieval from the EarthCARE Multi-Spectral Imager: the M-AOT product
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An explicit formulation for the retrieval of the overlap function in an elastic and Raman aerosol lidar
The classification of atmospheric hydrometeors and aerosols from the EarthCARE radar and lidar: the A-TC, C-TC and AC-TC products
SAGE III/ISS aerosol/cloud categorization and its impact on GloSSAC
Exploring geometrical stereoscopic aerosol top height retrieval from geostationary satellite imagery in East Asia
Sensitivity studies of nighttime top-of-atmosphere radiances from artificial light sources using a 3-D radiative transfer model for nighttime aerosol retrievals
Instantaneous aerosol and surface retrieval using satellites in geostationary orbit (iAERUS-GEO) – estimation of 15 min aerosol optical depth from MSG/SEVIRI and evaluation with reference data
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DeLiAn – a growing collection of depolarization ratio, lidar ratio and Ångström exponent for different aerosol types and mixtures from ground-based lidar observations
Analysis of Lhù’ààn Mân’ (Kluane Lake) dust plumes using passive and active ground-based remote sensing supported by physical surface measurements
Global 3-D distribution of aerosol composition by synergistic use of CALIOP and MODIS observations
The impact and estimation of uncertainty correlation for multi-angle polarimetric remote sensing of aerosols and ocean color
POLIPHON conversion factors for retrieving dust-related cloud condensation nuclei and ice-nucleating particle concentration profiles at oceanic sites
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Algorithm for vertical distribution of boundary layer aerosol components in remote-sensing data
Atmospheric visibility inferred from continuous-wave Doppler wind lidar
Identification of smoke and sulfuric acid aerosol in SAGE III/ISS extinction spectra
Combining Mie–Raman and fluorescence observations: a step forward in aerosol classification with lidar technology
Effective uncertainty quantification for multi-angle polarimetric aerosol remote sensing over ocean
Employing relaxed smoothness constraints on imaginary part of refractive index in AERONET aerosol retrieval algorithm
Observation of bioaerosol transport using wideband integrated bioaerosol sensor and coherent Doppler lidar
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Atmos. Meas. Tech., 16, 2709–2731, https://doi.org/10.5194/amt-16-2709-2023, https://doi.org/10.5194/amt-16-2709-2023, 2023
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Minseok Kim, Jhoon Kim, Hyunkwang Lim, Seoyoung Lee, Yeseul Cho, Huidong Yeo, and Sang-Woo Kim
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Aerosol height information is important when seeking an understanding of the vertical structure of the aerosol layer and long-range transport. In this study, a geometrical aerosol top height (ATH) retrieval using a parallax of two geostationary satellites is investigated. With sufficient longitudinal separation between the two satellites, a decent ATH product could be retrieved.
Jianglong Zhang, Jeffrey S. Reid, Steven D. Miller, Miguel Román, Zhuosen Wang, Robert J. D. Spurr, and Shawn Jaker
Atmos. Meas. Tech., 16, 2531–2546, https://doi.org/10.5194/amt-16-2531-2023, https://doi.org/10.5194/amt-16-2531-2023, 2023
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We adapted the spherical harmonics discrete ordinate method 3-dimentional radiative transfer model (3-D RTM) and developed a nighttime 3-D RTM capability for simulating top-of-atmosphere radiances from artificial light sources for aerosol retrievals. Our study suggests that both aerosol optical depth and aerosol plume height can be effectively retrieved using nighttime observations over artificial light sources, through the newly developed radiative transfer modeling capability.
Xavier Ceamanos, Bruno Six, Suman Moparthy, Dominique Carrer, Adèle Georgeot, Josef Gasteiger, Jérôme Riedi, Jean-Luc Attié, Alexei Lyapustin, and Iosif Katsev
Atmos. Meas. Tech., 16, 2575–2599, https://doi.org/10.5194/amt-16-2575-2023, https://doi.org/10.5194/amt-16-2575-2023, 2023
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A new algorithm to retrieve the diurnal evolution of aerosol optical depth over land and ocean from geostationary meteorological satellites is proposed and successfully evaluated with reference ground-based and satellite data. The high-temporal-resolution aerosol observations that are obtained from the EUMETSAT Meteosat Second Generation mission are unprecedented and open the door to studies that cannot be conducted with the once-a-day observations available from low-Earth-orbit satellites.
Ulla Wandinger, Athena Augusta Floutsi, Holger Baars, Moritz Haarig, Albert Ansmann, Anja Hünerbein, Nicole Docter, David Donovan, Gerd-Jan van Zadelhoff, Shannon Mason, and Jason Cole
Atmos. Meas. Tech., 16, 2485–2510, https://doi.org/10.5194/amt-16-2485-2023, https://doi.org/10.5194/amt-16-2485-2023, 2023
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We introduce an aerosol classification model that has been developed for the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE). The model provides a consistent description of microphysical, optical, and radiative properties of common aerosol types such as dust, sea salt, pollution, and smoke. It is used for aerosol classification and assessment of radiation effects based on the synergy of active and passive observations with lidar, imager, and radiometer of the multi-instrument platform.
Athena Augusta Floutsi, Holger Baars, Ronny Engelmann, Dietrich Althausen, Albert Ansmann, Stephanie Bohlmann, Birgit Heese, Julian Hofer, Thomas Kanitz, Moritz Haarig, Kevin Ohneiser, Martin Radenz, Patric Seifert, Annett Skupin, Zhenping Yin, Sabur F. Abdullaev, Mika Komppula, Maria Filioglou, Elina Giannakaki, Iwona S. Stachlewska, Lucja Janicka, Daniele Bortoli, Eleni Marinou, Vassilis Amiridis, Anna Gialitaki, Rodanthi-Elisavet Mamouri, Boris Barja, and Ulla Wandinger
Atmos. Meas. Tech., 16, 2353–2379, https://doi.org/10.5194/amt-16-2353-2023, https://doi.org/10.5194/amt-16-2353-2023, 2023
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DeLiAn is a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarization lidar measurements and currently covers two wavelengths, 355 and 532 nm, for 13 aerosol categories ranging from basic aerosol types to mixtures.
Seyed Ali Sayedain, Norman T. O’Neill, James King, Patrick L. Hayes, Daniel Bellamy, Richard Washington, Sebastian Engelstaedter, Andy Vicente-Luis, Jill Bachelder, and Malo Bernhard
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-67, https://doi.org/10.5194/amt-2023-67, 2023
Revised manuscript accepted for AMT
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We used (columnar) ground-based remote sensing (RS) tools and surface measurements to characterize local (drainage-basin) dust plumes at a site in the Yukon. Plume height, particle size, and column to surface ratios enabled insight into how satellite RS could be used to analyze Arctic-wide dust transport. This helps modellers refine dust impacts in their climate change simulations. It is an important step since local dust is a key source of dust deposition on snow in the sensitive Arctic region.
Rei Kudo, Akiko Higurashi, Eiji Oikawa, Masahiro Fujikawa, Hiroshi Ishimoto, and Tomoaki Nishizawa
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-59, https://doi.org/10.5194/amt-2023-59, 2023
Revised manuscript accepted for AMT
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We developed a synergistic retrieval method of aerosol composition using CALIOP and MODIS data and analyzed the observations in 2010. The results showed the global distributions of water-soluble, light-absorbing, dust, and sea salt particles. The comparisons of the results with the CALIPSO, MODIS, and AERONET standard products showed good consistency Furthermore, we evaluated the impacts of each components on the radiative fluxes at the top and bottom of atmospheres and the heating rate.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Brian Cairns, Xiaoguang Xu, and J. Vanderlei Martins
Atmos. Meas. Tech., 16, 2067–2087, https://doi.org/10.5194/amt-16-2067-2023, https://doi.org/10.5194/amt-16-2067-2023, 2023
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Multi-angle polarimetric measurements have been shown to greatly improve the remote sensing capability of aerosols and help atmospheric correction for ocean color retrievals. However, the uncertainty correlations among different measurement angles have not been well characterized. In this work, we provided a practical framework to evaluate the impact of the angular uncertainty correlation in retrieval results and a method to directly estimate correlation strength from retrieval residuals.
Yun He, Zhenping Yin, Albert Ansmann, Fuchao Liu, Longlong Wang, Dongzhe Jing, and Huijia Shen
Atmos. Meas. Tech., 16, 1951–1970, https://doi.org/10.5194/amt-16-1951-2023, https://doi.org/10.5194/amt-16-1951-2023, 2023
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With the AERONET database, this study derives dust-related conversion factors at oceanic sites used in the POLIPHON method, which can convert lidar-retrieved dust extinction to ice-nucleating particle (INP)- and cloud condensation nuclei (CCN)-relevant parameters. The particle linear depolarization ratio in the AERONET aerosol inversion product is used to identify dust data points. The derived conversion factors can be applied to inverse 3-D global distributions of dust-related INPCs and CCNCs.
Denghui Ji, Mathias Palm, Christoph Ritter, Philipp Richter, Xiaoyu Sun, Matthias Buschmann, and Justus Notholt
Atmos. Meas. Tech., 16, 1865–1879, https://doi.org/10.5194/amt-16-1865-2023, https://doi.org/10.5194/amt-16-1865-2023, 2023
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To measuring aerosol components, a Fourier transform infrared spectrometer (FTIS) and a lidar are operated in Ny-Ålesund, Spitsbergen (78° N, 11° E). Using the FTIS, a retrieval algorithm is developed for dust, sea salt, black carbon, and sulfate. The distribution of aerosols or clouds is provided by lidar and used as an indicator for aerosol or cloud retrieval with the FTS. Thus, a two-instrument joint-observation scheme is designed and is used on the data measured from 2019 to the present.
Jason L. Tackett, Jayanta Kar, Mark A. Vaughan, Brian J. Getzewich, Man-Hae Kim, Jean-Paul Vernier, Ali H. Omar, Brian E. Magill, Michael C. Pitts, and David M. Winker
Atmos. Meas. Tech., 16, 745–768, https://doi.org/10.5194/amt-16-745-2023, https://doi.org/10.5194/amt-16-745-2023, 2023
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The accurate identification of aerosol types in the stratosphere is important to characterize their impacts on the Earth climate system. The space-borne lidar on board CALIPSO is well-posed to identify aerosols in the stratosphere from volcanic eruptions and major wildfire events. This paper describes improvements implemented in the version 4.5 CALIPSO data release to more accurately discriminate between volcanic ash, sulfate, and smoke within the stratosphere.
Ilaria Petracca, Davide De Santis, Matteo Picchiani, Stefano Corradini, Lorenzo Guerrieri, Fred Prata, Luca Merucci, Dario Stelitano, Fabio Del Frate, Giorgia Salvucci, and Giovanni Schiavon
Atmos. Meas. Tech., 15, 7195–7210, https://doi.org/10.5194/amt-15-7195-2022, https://doi.org/10.5194/amt-15-7195-2022, 2022
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The authors propose a near-real-time procedure for the detection of volcanic clouds by means of Sentinel-3 satellite data and neural networks. The algorithm results in an automatic image classification where ashy pixels are distinguished from other surfaces with remarkable accuracy. The model is considerably faster if compared to other approaches which are time consuming, case specific, and not automatic. The algorithm can be significantly helpful for emergency management during eruption events.
James A. Limbacher, Ralph A. Kahn, and Jaehwa Lee
Atmos. Meas. Tech., 15, 6865–6887, https://doi.org/10.5194/amt-15-6865-2022, https://doi.org/10.5194/amt-15-6865-2022, 2022
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Launched in December 1999, NASA’s Multi-angle Imaging SpectroRadiometer (MISR) has given researchers qualitative constraints on aerosol particle properties for the past 22 years. Here, we present a new MISR research aerosol retrieval algorithm (RA) that utilizes over-land surface reflectance data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) to address limitations of the MISR operational aerosol retrieval algorithm and improve retrievals of aerosol particle properties.
Futing Wang, Ting Yang, Zifa Wang, Haibo Wang, Xi Chen, Yele Sun, Jianjun Li, Guigang Tang, and Wenxuan Chai
Atmos. Meas. Tech., 15, 6127–6144, https://doi.org/10.5194/amt-15-6127-2022, https://doi.org/10.5194/amt-15-6127-2022, 2022
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We develop a new algorithm to get the vertical mass concentration profiles of fine aerosol components based on the synergy of ground-based remote sensing for the first time. The comparisons with in situ observations and chemistry transport models validate the performance of the algorithm. Uncertainties caused by input parameters are also assessed in this paper. We expected that the algorithm can provide a new idea for lidar inversion and promote the development of aerosol component profiles.
Manuel Queißer, Michael Harris, and Steven Knoop
Atmos. Meas. Tech., 15, 5527–5544, https://doi.org/10.5194/amt-15-5527-2022, https://doi.org/10.5194/amt-15-5527-2022, 2022
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Visibility is how well we can see something. Visibility sensors, such as employed in meteorological observatories and airports, measure at a point at the instrument location, which may not be representative of visibilities further away, e.g. near the sea surface during sea spray. Light detecting and ranging (lidar) can measure visibility further away. We find wind lidar to be a viable tool to measure visibility with low accuracy, which could suffice for safety-uncritical applications.
Travis N. Knepp, Larry Thomason, Mahesh Kovilakam, Jason Tackett, Jayanta Kar, Robert Damadeo, and David Flittner
Atmos. Meas. Tech., 15, 5235–5260, https://doi.org/10.5194/amt-15-5235-2022, https://doi.org/10.5194/amt-15-5235-2022, 2022
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We used aerosol profiles from the SAGE III/ISS instrument to develop an aerosol classification method that was tested on four case-study events (two volcanic, two fire) and supported with CALIOP aerosol products. The method worked well in identifying smoke and volcanic aerosol in the stratosphere for these events. Raikoke is presented as a demonstration of the limitations of this method.
Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Boris Barchunov, and Mikhail Korenskii
Atmos. Meas. Tech., 15, 4881–4900, https://doi.org/10.5194/amt-15-4881-2022, https://doi.org/10.5194/amt-15-4881-2022, 2022
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An approach to reveal variability in aerosol type at a high spatiotemporal resolution, by combining fluorescence and Mie–Raman lidar data, is presented. We applied this new classification scheme to lidar data obtained by LOA, University of Lille, in 2020–2021. It is demonstrated that the separation of the main particle types, such as smoke, dust, pollen, and urban, can be performed with a height resolution of 60 m and temporal resolution better than 10 min for the current lidar configuration.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 15, 4859–4879, https://doi.org/10.5194/amt-15-4859-2022, https://doi.org/10.5194/amt-15-4859-2022, 2022
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In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
Alexander Sinyuk, Brent N. Holben, Thomas F. Eck, David M. Giles, Ilya Slutsker, Oleg Dubovik, Joel S. Schafer, Alexander Smirnov, and Mikhail Sorokin
Atmos. Meas. Tech., 15, 4135–4151, https://doi.org/10.5194/amt-15-4135-2022, https://doi.org/10.5194/amt-15-4135-2022, 2022
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This paper describes modification of smoothness constraints on the imaginary part of the refractive index employed in the AERONET aerosol retrieval algorithm. This modification is termed relaxed due to the weaker strength of this new smoothness constraint. Applying the modified version of the smoothness constraint results in a significant reduction of retrieved light absorption by brown-carbon-containing aerosols.
Dawei Tang, Tianwen Wei, Jinlong Yuan, Haiyun Xia, and Xiankang Dou
Atmos. Meas. Tech., 15, 2819–2838, https://doi.org/10.5194/amt-15-2819-2022, https://doi.org/10.5194/amt-15-2819-2022, 2022
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During 11–20 March 2020, three aerosol transport events were investigated by a lidar system and an online bioaerosol detection system in Hefei, China.
Observation results reveal that the events not only contributed to high particulate matter pollution but also to the transport of external bioaerosols, resulting in changes in the fraction of fluorescent biological aerosol particles.
This detection method improved the time resolution and provided more parameters for aerosol detection.
Liqiao Lei, Timothy A. Berkoff, Guillaume Gronoff, Jia Su, Amin R. Nehrir, Yonghua Wu, Fred Moshary, and Shi Kuang
Atmos. Meas. Tech., 15, 2465–2478, https://doi.org/10.5194/amt-15-2465-2022, https://doi.org/10.5194/amt-15-2465-2022, 2022
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Aerosol extinction in the UVB (280–315 nm) is difficult to retrieve using simple lidar techniques due to the lack of lidar ratios at those wavelengths. The 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City region provided the opportunity to characterize the lidar ratio for UVB aerosol retrieval for the Langley Mobile Ozone Lidar (LMOL). A 292 nm aerosol product comparison between the NASA Langley High Altitude Lidar Observatory (HALO) and LMOL was also carried out.
Jan-Lukas Tirpitz, Udo Frieß, Robert Spurr, and Ulrich Platt
Atmos. Meas. Tech., 15, 2077–2098, https://doi.org/10.5194/amt-15-2077-2022, https://doi.org/10.5194/amt-15-2077-2022, 2022
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MAX-DOAS is a widely used measurement technique for the remote detection of atmospheric aerosol and trace gases. It relies on the analysis of ultra-violet and visible radiation spectra of skylight. To date, information contained in the skylight's polarisation state has not been utilised. On the basis of synthetic data, we carried out sensitivity analyses to assess the potential of polarimetry for MAX-DOAS applications.
Thibault Vaillant de Guélis, Gérard Ancellet, Anne Garnier, Laurent C.-Labonnote, Jacques Pelon, Mark A. Vaughan, Zhaoyan Liu, and David M. Winker
Atmos. Meas. Tech., 15, 1931–1956, https://doi.org/10.5194/amt-15-1931-2022, https://doi.org/10.5194/amt-15-1931-2022, 2022
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A new IIR-based cloud and aerosol discrimination (CAD) algorithm is developed using the IIR brightness temperature differences for cloud and aerosol features confidently identified by the CALIOP version 4 CAD algorithm. IIR classifications agree with the majority of V4 cloud identifications, reduce the ambiguity in a notable fraction of
not confidentV4 cloud classifications, and correct a few V4 misclassifications of cloud layers identified as dense dust or elevated smoke layers by CALIOP.
Marco Di Paolantonio, Davide Dionisi, and Gian Luigi Liberti
Atmos. Meas. Tech., 15, 1217–1231, https://doi.org/10.5194/amt-15-1217-2022, https://doi.org/10.5194/amt-15-1217-2022, 2022
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A procedure for the characterization of the lidar transmitter–receiver geometry was developed. This characterization is currently implemented in the Rome RMR lidar to optimize the telescope/beam alignment, retrieve the overlap function, and estimate the absolute and relative tilt of the laser beam. This procedure can be potentially used to complement the standard EARLINET quality assurance tests.
Monica Campanelli, Henri Diémoz, Anna Maria Siani, Alcide di Sarra, Anna Maria Iannarelli, Rei Kudo, Gabriele Fasano, Giampietro Casasanta, Luca Tofful, Marco Cacciani, Paolo Sanò, and Stefano Dietrich
Atmos. Meas. Tech., 15, 1171–1183, https://doi.org/10.5194/amt-15-1171-2022, https://doi.org/10.5194/amt-15-1171-2022, 2022
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The aerosol optical depth (AOD) characteristics in an urban area of Rome were retrieved over a period of 11 years (2010–2020) to determine, for the first time, their effect on the incoming ultraviolet (UV) solar radiation. The surface forcing efficiency shows that the AOD is the primary parameter affecting the surface irradiance in Rome, and it is found to be greater for smaller zenith angles and for larger and more absorbing particles in the UV range (such as, e.g., mineral dust).
Jean-Claude Roger, Eric Vermote, Sergii Skakun, Emilie Murphy, Oleg Dubovik, Natacha Kalecinski, Bruno Korgo, and Brent Holben
Atmos. Meas. Tech., 15, 1123–1144, https://doi.org/10.5194/amt-15-1123-2022, https://doi.org/10.5194/amt-15-1123-2022, 2022
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From measurements of the sky performed by AERONET, we determined the microphysical properties of the atmospheric particles (aerosols) for each AERONET site. We used the aerosol optical thickness and its variation over the visible spectrum. This allows us to determine an aerosol model useful for (but not only) the validation of the surface reflectance satellite-derived product. The impact of the aerosol model uncertainties on the surface reflectance validation has been found to be 1 % to 3 %.
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, Ja-Ho Koo, Seoyoung Lee, Minah Bae, Soontae Kim, Hong Liao, and Daniel J. Jacob
Atmos. Meas. Tech., 15, 1075–1091, https://doi.org/10.5194/amt-15-1075-2022, https://doi.org/10.5194/amt-15-1075-2022, 2022
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This paper uses a machine learning algorithm to infer high-resolution maps of particulate air quality in eastern China, Japan, and the Korean peninsula, using data from a geostationary satellite along with meteorology. We then perform an extensive evaluation of this inferred air quality and use it to diagnose trends in the region. We hope this paper and the associated data will be valuable to other scientists interested in epidemiology, air quality, remote sensing, and machine learning.
Antti Lipponen, Jaakko Reinvall, Arttu Väisänen, Henri Taskinen, Timo Lähivaara, Larisa Sogacheva, Pekka Kolmonen, Kari Lehtinen, Antti Arola, and Ville Kolehmainen
Atmos. Meas. Tech., 15, 895–914, https://doi.org/10.5194/amt-15-895-2022, https://doi.org/10.5194/amt-15-895-2022, 2022
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We have developed a machine-learning-based model that can be used to correct the Sentinel-3 satellite-based aerosol parameter data of the Synergy data product. The strength of the model is that the original satellite data processing does not have to be carried out again but the correction can be carried out with the data already available. We show that the correction significantly improves the accuracy of the satellite aerosol parameters.
Vinay Kayetha, Omar Torres, and Hiren Jethva
Atmos. Meas. Tech., 15, 845–877, https://doi.org/10.5194/amt-15-845-2022, https://doi.org/10.5194/amt-15-845-2022, 2022
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Existing measurements of spectral aerosol absorption are limited, particularly in the UV region. We use the synergy of satellite and ground measurements to derive spectral single scattering albedo of aerosols from the UV–visible spectrum. The resulting spectral SSAs are used to investigate seasonality in absorption for carbonaceous, dust, and urban aerosols. Regional aerosol absorption models that could be used to make reliable assumptions in satellite remote sensing of aerosols are derived.
Goutam Choudhury and Matthias Tesche
Atmos. Meas. Tech., 15, 639–654, https://doi.org/10.5194/amt-15-639-2022, https://doi.org/10.5194/amt-15-639-2022, 2022
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Aerosols are tiny particles suspended in the atmosphere. A fraction of these particles can form clouds and are called cloud condensation nuclei (CCN). Measurements of such aerosol particles are necessary to study the aerosol–cloud interactions and reduce the uncertainty in our future climate predictions. We present a novel methodology to estimate global 3D CCN concentrations from the CALIPSO satellite measurements. The final data set will be used to study the aerosol–cloud interactions.
Hiroshi Ishimoto, Masahiro Hayashi, and Yuzo Mano
Atmos. Meas. Tech., 15, 435–458, https://doi.org/10.5194/amt-15-435-2022, https://doi.org/10.5194/amt-15-435-2022, 2022
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Using data from the Infrared Atmospheric Sounding Interferometer (IASI) measurements of volcanic ash clouds (VACs) and radiative transfer calculations, we attempt to simulate the measured brightness temperature spectra (BTS) of volcanic ash aerosols in the infrared region. In particular, the dependence on the ash refractive index (RI) model is investigated.
Roberto Román, Juan C. Antuña-Sánchez, Victoria E. Cachorro, Carlos Toledano, Benjamín Torres, David Mateos, David Fuertes, César López, Ramiro González, Tatyana Lapionok, Marcos Herreras-Giralda, Oleg Dubovik, and Ángel M. de Frutos
Atmos. Meas. Tech., 15, 407–433, https://doi.org/10.5194/amt-15-407-2022, https://doi.org/10.5194/amt-15-407-2022, 2022
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An all-sky camera is used to obtain the relative sky radiance, and this radiance is used as input in an inversion code to obtain aerosol properties. This paper is really interesting because it pushes forward the use and capability of sky cameras for more advanced science purposes. Enhanced aerosol properties can be retrieved with accuracy using only an all-sky camera, but synergy with other instruments providing aerosol optical depth could even increase the power of these low-cost instruments.
Frithjof Ehlers, Thomas Flament, Alain Dabas, Dimitri Trapon, Adrien Lacour, Holger Baars, and Anne Grete Straume-Lindner
Atmos. Meas. Tech., 15, 185–203, https://doi.org/10.5194/amt-15-185-2022, https://doi.org/10.5194/amt-15-185-2022, 2022
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The Aeolus satellite observes the Earth and can vertically detect any kind of particles (aerosols or clouds) in the atmosphere below it. These observations are typically very noisy, which needs to be accounted for. This work dampens the noise in Aeolus' aerosol and cloud data, which are provided publicly by the ESA, so that the scientific community can make better use of it. This makes the data potentially more useful for weather prediction and climate research.
Alberto Sorrentino, Alessia Sannino, Nicola Spinelli, Michele Piana, Antonella Boselli, Valentino Tontodonato, Pasquale Castellano, and Xuan Wang
Atmos. Meas. Tech., 15, 149–164, https://doi.org/10.5194/amt-15-149-2022, https://doi.org/10.5194/amt-15-149-2022, 2022
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We present a novel approach that can be used to obtain microphysical properties of atmospheric aerosol, up to several kilometers in the atmosphere, from lidar measurements taken from the ground. Our approach provides accurate reconstructions under many different experimental conditions. Our results can contribute to the expansion of the use of remote sensing techniques for air quality monitoring and atmospheric science in general.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Michal Segal Rozenhaimer, Meloë Kacenelenbogen, Yohei Shinozuka, Connor Flynn, Rich Ferrare, Sharon Burton, Chris Hostetler, Marc Mallet, and Paquita Zuidema
Atmos. Meas. Tech., 15, 61–77, https://doi.org/10.5194/amt-15-61-2022, https://doi.org/10.5194/amt-15-61-2022, 2022
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This work presents heating rates derived from aircraft observations from the 2016 and 2017 field campaigns of ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS). We separate the total heating rates into aerosol and gas (primarily water vapor) absorption and explore some of the co-variability of heating rate profiles and their primary drivers, leading to the development of a new concept: the heating rate efficiency (HRE; the heating rate per unit aerosol extinction).
Thomas Flament, Dimitri Trapon, Adrien Lacour, Alain Dabas, Frithjof Ehlers, and Dorit Huber
Atmos. Meas. Tech., 14, 7851–7871, https://doi.org/10.5194/amt-14-7851-2021, https://doi.org/10.5194/amt-14-7851-2021, 2021
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This paper presents the main algorithms of the Aeolus Level 2 aerosol optical properties product. The processing chain was developed under contract with ESA.
We show that the ALADIN instrument, although primarily designed to retrieve atmospheric winds, is also able to provide valuable information about aerosol and cloud optical properties. The algorithms are detailed, and validation on simulated and real examples is shown.
Oscar S. Sandvik, Johan Friberg, Moa K. Sporre, and Bengt G. Martinsson
Atmos. Meas. Tech., 14, 7153–7165, https://doi.org/10.5194/amt-14-7153-2021, https://doi.org/10.5194/amt-14-7153-2021, 2021
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A method to form SO2 profiles in the stratosphere with high vertical resolution following volcanic eruptions is introduced. The method combines space-based high-resolution vertical aerosol profiles and SO2 measurements the first 2 weeks after an eruption with air mass trajectory analyses. The SO2 is located at higher altitude than in most previous studies. The detailed resolution of the SO2 profile is unprecedented compared to other methods.
Igor B. Konovalov, Nikolai A. Golovushkin, Matthias Beekmann, Mikhail V. Panchenko, and Meinrat O. Andreae
Atmos. Meas. Tech., 14, 6647–6673, https://doi.org/10.5194/amt-14-6647-2021, https://doi.org/10.5194/amt-14-6647-2021, 2021
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The absorption of solar light by organic matter, known as brown carbon (BrC), contributes significantly to the radiative budget of the Earth’s atmosphere, but its representation in atmospheric models is uncertain. This paper advances a methodology to constrain model parameters characterizing BrC absorption of atmospheric aerosol originating from biomass burning with the available remote ground-based observations of atmospheric aerosol.
Xiaoxia Shang, Tero Mielonen, Antti Lipponen, Elina Giannakaki, Ari Leskinen, Virginie Buchard, Anton S. Darmenov, Antti Kukkurainen, Antti Arola, Ewan O'Connor, Anne Hirsikko, and Mika Komppula
Atmos. Meas. Tech., 14, 6159–6179, https://doi.org/10.5194/amt-14-6159-2021, https://doi.org/10.5194/amt-14-6159-2021, 2021
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The long-range-transported smoke particles from a Canadian wildfire event were observed with a multi-wavelength Raman polarization lidar and a ceilometer over Kuopio, Finland, in June 2019. The optical properties and the mass concentration estimations were reported for such aged smoke aerosols over northern Europe.
Yun He, Yunfei Zhang, Fuchao Liu, Zhenping Yin, Yang Yi, Yifan Zhan, and Fan Yi
Atmos. Meas. Tech., 14, 5939–5954, https://doi.org/10.5194/amt-14-5939-2021, https://doi.org/10.5194/amt-14-5939-2021, 2021
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The POLIPHON method can retrieve the height profiles of dust-related particle mass and ice-nucleating particle (INP) concentrations. Applying a dust case data set screening scheme based on the lidar-derived depolarization ratio (rather than Ångström exponent for 440–870 nm and AOD at 532 nm), the mixed-dust-related conversion factors are retrieved from sun photometer observations over Wuhan, China. This method may potentially be extended to regions influenced by mixed dust.
Marcin L. Witek, Michael J. Garay, David J. Diner, Michael A. Bull, Felix C. Seidel, Abigail M. Nastan, and Earl G. Hansen
Atmos. Meas. Tech., 14, 5577–5591, https://doi.org/10.5194/amt-14-5577-2021, https://doi.org/10.5194/amt-14-5577-2021, 2021
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This article documents the development and testing of a new near real-time (NRT) aerosol product from the MISR instrument on NASA’s Terra platform. The NRT product capitalizes on the unique attributes of the MISR retrieval approach, which leads to a high-quality and reliable aerosol data product. Several modifications are described that allow for rapid product generation within a 3 h window following acquisition. Implications for the product quality and consistency are discussed.
Zhihao Song, Bin Chen, Yue Huang, Li Dong, and Tingting Yang
Atmos. Meas. Tech., 14, 5333–5347, https://doi.org/10.5194/amt-14-5333-2021, https://doi.org/10.5194/amt-14-5333-2021, 2021
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The linear hybrid machine learning model achieves the expected target well. The overall inversion accuracy (R2) of the model is 0.84, and the RMSE is 12.92 µg m−3. R2 was above 0.7 in more than 70 % of the sites, whereas RMSE and mean absolute error were below 20 and 15 µg m−3, respectively. There was severe pollution in winter with an average PM2.5 concentration of 62.10 µg m−3. However, there was only slight pollution in summer with an average PM2.5 concentration of 47.39 µg m−3.
Scott P. Seymour and Matthew R. Johnson
Atmos. Meas. Tech., 14, 5179–5197, https://doi.org/10.5194/amt-14-5179-2021, https://doi.org/10.5194/amt-14-5179-2021, 2021
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Field measurements of gas flare emissions often assume that combustion species are spatially and temporally correlated in the plume. By measuring black carbon (BC) and water vapour in turbulent lab-scale flare plumes, this study shows that the well-correlated species assumption is not universally valid and that field measurements may be subject to large added uncertainty. Further analysis suggests that this uncertainty is easily avoided, and initial guidance is provided on sampling protocols.
William G. K. McLean, Guangliang Fu, Sharon P. Burton, and Otto P. Hasekamp
Atmos. Meas. Tech., 14, 4755–4771, https://doi.org/10.5194/amt-14-4755-2021, https://doi.org/10.5194/amt-14-4755-2021, 2021
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In this study, we present results from aerosol retrievals using both synthetic and real lidar datasets, including measurements from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, a combined initiative between NASA and SRON (the Netherlands Institute for Space Research). Aerosol microphysical retrievals were performed using the High Spectral Resolution Lidar-2 (HSRL-2) setup, alongside several others, with the ACEPOL retrievals also compared to polarimeter retrievals.
Hyunkwang Lim, Sujung Go, Jhoon Kim, Myungje Choi, Seoyoung Lee, Chang-Keun Song, and Yasuko Kasai
Atmos. Meas. Tech., 14, 4575–4592, https://doi.org/10.5194/amt-14-4575-2021, https://doi.org/10.5194/amt-14-4575-2021, 2021
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Aerosol property observations by satellites from geostationary Earth orbit (GEO) in particular have advantages of frequent sampling better than 1 h in addition to broader spatial coverage. This study provides data fusion products of aerosol optical properties from four different algorithms for two different GEO satellites: GOCI and AHI. The fused aerosol products adopted ensemble-mean and maximum-likelihood estimation methods. The data fusion provides improved results with better accuracy.
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