Articles | Volume 12, issue 7
Atmos. Meas. Tech., 12, 3921–3941, 2019
https://doi.org/10.5194/amt-12-3921-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 12, 3921–3941, 2019
https://doi.org/10.5194/amt-12-3921-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article 17 Jul 2019
Research article | 17 Jul 2019
Inversion of multiangular polarimetric measurements over open and coastal ocean waters: a joint retrieval algorithm for aerosol and water-leaving radiance properties
Meng Gao et al.
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Meng Gao, Bryan A. Franz, Kirk Knobelspiesse, Peng-Wang Zhai, Vanderlei Martins, Sharon Burton, Brian Cairns, Richard Ferrare, Joel Gales, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Brent McBride, Anin Puthukkudy, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 14, 4083–4110, https://doi.org/10.5194/amt-14-4083-2021, https://doi.org/10.5194/amt-14-4083-2021, 2021
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Multi-angle polarimetric measurements can retrieve accurate aerosol properties over complex atmosphere and ocean systems; however, most retrieval algorithms require high computational costs. We propose a deep neural network (NN) forward model to represent the radiative transfer simulation of coupled atmosphere and ocean systems and then conduct simultaneous aerosol and ocean color retrievals on AirHARP measurements. The computational acceleration is 103 times with CPU or 104 times with GPU.
Kirk Knobelspiesse, Amir Ibrahim, Bryan Franz, Sean Bailey, Robert Levy, Ziauddin Ahmad, Joel Gales, Meng Gao, Michael Garay, Samuel Anderson, and Olga Kalashnikova
Atmos. Meas. Tech., 14, 3233–3252, https://doi.org/10.5194/amt-14-3233-2021, https://doi.org/10.5194/amt-14-3233-2021, 2021
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We assessed atmospheric aerosol and ocean surface wind speed remote sensing capability with NASA's Multi-angle Imaging SpectroRadiometer (MISR), using synthetic data and a Bayesian inference technique called generalized nonlinear retrieval analysis (GENRA). We found success using three aerosol parameters plus wind speed. This shows that MISR can perform an atmospheric correction for the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same spacecraft (Terra).
Kirk Knobelspiesse, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, Anthony Cook, Antonio Di Noia, Bastiaan van Diedenhoven, David J. Diner, Richard Ferrare, Guangliang Fu, Meng Gao, Michael Garay, Johnathan Hair, David Harper, Gerard van Harten, Otto Hasekamp, Mark Helmlinger, Chris Hostetler, Olga Kalashnikova, Andrew Kupchock, Karla Longo De Freitas, Hal Maring, J. Vanderlei Martins, Brent McBride, Matthew McGill, Ken Norlin, Anin Puthukkudy, Brian Rheingans, Jeroen Rietjens, Felix C. Seidel, Arlindo da Silva, Martijn Smit, Snorre Stamnes, Qian Tan, Sebastian Val, Andrzej Wasilewski, Feng Xu, Xiaoguang Xu, and John Yorks
Earth Syst. Sci. Data, 12, 2183–2208, https://doi.org/10.5194/essd-12-2183-2020, https://doi.org/10.5194/essd-12-2183-2020, 2020
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The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign is a resource for the next generation of spaceborne multi-angle polarimeter (MAP) and lidar missions. Conducted in the fall of 2017 from the Armstrong Flight Research Center in Palmdale, California, four MAP instruments and two lidars were flown on the high-altitude ER-2 aircraft over a variety of scene types and ground assets. Data are freely available to the public and useful for algorithm development and testing.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Kirk Knobelspiesse, Amir Ibrahim, Brian Cairns, Susanne E. Craig, Guangliang Fu, Otto Hasekamp, Yongxiang Hu, and P. Jeremy Werdell
Atmos. Meas. Tech., 13, 3939–3956, https://doi.org/10.5194/amt-13-3939-2020, https://doi.org/10.5194/amt-13-3939-2020, 2020
Yaping Zhou, Yuekui Yang, Meng Gao, and Peng-Wang Zhai
Atmos. Meas. Tech., 13, 1575–1591, https://doi.org/10.5194/amt-13-1575-2020, https://doi.org/10.5194/amt-13-1575-2020, 2020
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Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and the bright and cold surfaces; the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) has very limited channels. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios for cloud detection over snow and ice surfaces.
Guangliang Fu, Otto Hasekamp, Jeroen Rietjens, Martijn Smit, Antonio Di Noia, Brian Cairns, Andrzej Wasilewski, David Diner, Felix Seidel, Feng Xu, Kirk Knobelspiesse, Meng Gao, Arlindo da Silva, Sharon Burton, Chris Hostetler, John Hair, and Richard Ferrare
Atmos. Meas. Tech., 13, 553–573, https://doi.org/10.5194/amt-13-553-2020, https://doi.org/10.5194/amt-13-553-2020, 2020
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In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON (the Netherlands Institute for Space Research). We perform aerosol retrievals from different multi-angle polarimeters employed during the ACEPOL campaign and evaluate them against ground-based AERONET measurements and High Spectral Resolution Lidar-2 (HSRL-2) measurements.
David Painemal, Douglas Spangenberg, William L. Smith Jr., Patrick Minnis, Brian Cairns, Richard H. Moore, Ewan Crosbie, Claire Robinson, Kenneth L. Thornhill, Edward L. Winstead, and Luke Ziemba
Atmos. Meas. Tech., 14, 6633–6646, https://doi.org/10.5194/amt-14-6633-2021, https://doi.org/10.5194/amt-14-6633-2021, 2021
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Cloud properties derived from satellite sensors are critical for the global monitoring of climate. This study evaluates satellite-based cloud properties over the North Atlantic using airborne data collected during NAAMES. Satellite observations of droplet size and cloud optical depth tend to compare well with NAAMES data. The analysis indicates that the satellite pixel resolution and the specific viewing geometry need to be taken into account in research applications.
Meng Gao, Bryan A. Franz, Kirk Knobelspiesse, Peng-Wang Zhai, Vanderlei Martins, Sharon Burton, Brian Cairns, Richard Ferrare, Joel Gales, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Brent McBride, Anin Puthukkudy, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 14, 4083–4110, https://doi.org/10.5194/amt-14-4083-2021, https://doi.org/10.5194/amt-14-4083-2021, 2021
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Multi-angle polarimetric measurements can retrieve accurate aerosol properties over complex atmosphere and ocean systems; however, most retrieval algorithms require high computational costs. We propose a deep neural network (NN) forward model to represent the radiative transfer simulation of coupled atmosphere and ocean systems and then conduct simultaneous aerosol and ocean color retrievals on AirHARP measurements. The computational acceleration is 103 times with CPU or 104 times with GPU.
Kirk Knobelspiesse, Amir Ibrahim, Bryan Franz, Sean Bailey, Robert Levy, Ziauddin Ahmad, Joel Gales, Meng Gao, Michael Garay, Samuel Anderson, and Olga Kalashnikova
Atmos. Meas. Tech., 14, 3233–3252, https://doi.org/10.5194/amt-14-3233-2021, https://doi.org/10.5194/amt-14-3233-2021, 2021
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We assessed atmospheric aerosol and ocean surface wind speed remote sensing capability with NASA's Multi-angle Imaging SpectroRadiometer (MISR), using synthetic data and a Bayesian inference technique called generalized nonlinear retrieval analysis (GENRA). We found success using three aerosol parameters plus wind speed. This shows that MISR can perform an atmospheric correction for the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same spacecraft (Terra).
Andrew M. Dzambo, Tristan L'Ecuyer, Kenneth Sinclair, Bastiaan van Diedenhoven, Siddhant Gupta, Greg McFarquhar, Joseph R. O'Brien, Brian Cairns, Andrzej P. Wasilewski, and Mikhail Alexandrov
Atmos. Chem. Phys., 21, 5513–5532, https://doi.org/10.5194/acp-21-5513-2021, https://doi.org/10.5194/acp-21-5513-2021, 2021
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This work highlights a new algorithm using data collected from the 2016–2018 NASA ORACLES field campaign. This algorithm synthesizes cloud and rain measurements to attain estimates of cloud and precipitation properties over the southeast Atlantic Ocean. Estimates produced by this algorithm compare well against in situ estimates. Increased rain fractions and rain rates are found in regions of atmospheric instability. This dataset can be used to explore aerosol–cloud–precipitation interactions.
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
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Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
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Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Adeyemi A. Adebiyi, Paquita Zuidema, Ian Chang, Sharon P. Burton, and Brian Cairns
Atmos. Chem. Phys., 20, 11025–11043, https://doi.org/10.5194/acp-20-11025-2020, https://doi.org/10.5194/acp-20-11025-2020, 2020
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Over the southeast Atlantic, interactions between the low-level clouds and the overlying smoke aerosols have previously been highlighted, but no study has yet focused on the presence of the mid-level clouds that complicate the aerosol–cloud interactions. Here we show that these optically thin super-cooled mid-level clouds are relatively common, and they frequently occur at the top of the smoke layer between August and October with significant radiative impacts on the low-level clouds.
Kirk Knobelspiesse, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, Anthony Cook, Antonio Di Noia, Bastiaan van Diedenhoven, David J. Diner, Richard Ferrare, Guangliang Fu, Meng Gao, Michael Garay, Johnathan Hair, David Harper, Gerard van Harten, Otto Hasekamp, Mark Helmlinger, Chris Hostetler, Olga Kalashnikova, Andrew Kupchock, Karla Longo De Freitas, Hal Maring, J. Vanderlei Martins, Brent McBride, Matthew McGill, Ken Norlin, Anin Puthukkudy, Brian Rheingans, Jeroen Rietjens, Felix C. Seidel, Arlindo da Silva, Martijn Smit, Snorre Stamnes, Qian Tan, Sebastian Val, Andrzej Wasilewski, Feng Xu, Xiaoguang Xu, and John Yorks
Earth Syst. Sci. Data, 12, 2183–2208, https://doi.org/10.5194/essd-12-2183-2020, https://doi.org/10.5194/essd-12-2183-2020, 2020
Short summary
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The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign is a resource for the next generation of spaceborne multi-angle polarimeter (MAP) and lidar missions. Conducted in the fall of 2017 from the Armstrong Flight Research Center in Palmdale, California, four MAP instruments and two lidars were flown on the high-altitude ER-2 aircraft over a variety of scene types and ground assets. Data are freely available to the public and useful for algorithm development and testing.
Melody A. Avery, Robert A. Ryan, Brian J. Getzewich, Mark A. Vaughan, David M. Winker, Yongxiang Hu, Anne Garnier, Jacques Pelon, and Carolus A. Verhappen
Atmos. Meas. Tech., 13, 4539–4563, https://doi.org/10.5194/amt-13-4539-2020, https://doi.org/10.5194/amt-13-4539-2020, 2020
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CALIOP data users will find more cloud layers detected in V4, with edges that extend further than in V3, for an increase in total atmospheric cloud volume of 6 %–9 % for high-confidence cloud phases and 1 %–2 % for all cloudy bins, including cloud fringes and unknown cloud phases. In V4 there are many fewer cloud layers identified as horizontally oriented ice, particularly in the 3° off-nadir view. Depolarization at 532 nm is the predominant parameter determining cloud thermodynamic phase.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Kirk Knobelspiesse, Amir Ibrahim, Brian Cairns, Susanne E. Craig, Guangliang Fu, Otto Hasekamp, Yongxiang Hu, and P. Jeremy Werdell
Atmos. Meas. Tech., 13, 3939–3956, https://doi.org/10.5194/amt-13-3939-2020, https://doi.org/10.5194/amt-13-3939-2020, 2020
Daniel J. Miller, Michal Segal-Rozenhaimer, Kirk Knobelspiesse, Jens Redemann, Brian Cairns, Mikhail Alexandrov, Bastiaan van Diedenhoven, and Andrzej Wasilewski
Atmos. Meas. Tech., 13, 3447–3470, https://doi.org/10.5194/amt-13-3447-2020, https://doi.org/10.5194/amt-13-3447-2020, 2020
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A neural network (NN) is developed and used to retrieve cloud microphysical properties from multiangular and multispectral polarimetric remote sensing observations. The NN is applied to research scanning polarimeter (RSP) observations obtained during the ORACLES field campaign and compared to other co-located remote sensing retrievals of cloud effective radius and optical thickness. A NN approach can advance more complex iterative search retrieval algorithms by providing a quick initial guess.
Kimberly A. Casey, Cecile S. Rousseaux, Watson W. Gregg, Emmanuel Boss, Alison P. Chase, Susanne E. Craig, Colleen B. Mouw, Rick A. Reynolds, Dariusz Stramski, Steven G. Ackleson, Annick Bricaud, Blake Schaeffer, Marlon R. Lewis, and Stéphane Maritorena
Earth Syst. Sci. Data, 12, 1123–1139, https://doi.org/10.5194/essd-12-1123-2020, https://doi.org/10.5194/essd-12-1123-2020, 2020
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An increase in spectral resolution in forthcoming remote-sensing missions will improve our ability to understand and characterize aquatic ecosystems. We organize and provide a global compilation of high spectral resolution inherent and apparent optical property data from polar, midlatitude, and equatorial open-ocean, estuary, coastal, and inland waters. The data are intended to aid in development of remote-sensing data product algorithms and to perform calibration and validation activities.
Yaping Zhou, Yuekui Yang, Meng Gao, and Peng-Wang Zhai
Atmos. Meas. Tech., 13, 1575–1591, https://doi.org/10.5194/amt-13-1575-2020, https://doi.org/10.5194/amt-13-1575-2020, 2020
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Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and the bright and cold surfaces; the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) has very limited channels. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios for cloud detection over snow and ice surfaces.
Guangliang Fu, Otto Hasekamp, Jeroen Rietjens, Martijn Smit, Antonio Di Noia, Brian Cairns, Andrzej Wasilewski, David Diner, Felix Seidel, Feng Xu, Kirk Knobelspiesse, Meng Gao, Arlindo da Silva, Sharon Burton, Chris Hostetler, John Hair, and Richard Ferrare
Atmos. Meas. Tech., 13, 553–573, https://doi.org/10.5194/amt-13-553-2020, https://doi.org/10.5194/amt-13-553-2020, 2020
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In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON (the Netherlands Institute for Space Research). We perform aerosol retrievals from different multi-angle polarimeters employed during the ACEPOL campaign and evaluate them against ground-based AERONET measurements and High Spectral Resolution Lidar-2 (HSRL-2) measurements.
Wenbo Sun, Yongxiang Hu, Rosemary R. Baize, Gorden Videen, Sungsoo S. Kim, Young-Jun Choi, Kyungin Kang, Chae Kyung Sim, Minsup Jeong, Ali Omar, Snorre A. Stamnes, David G. MacDonnell, and Evgenij Zubko
Atmos. Chem. Phys., 19, 15583–15586, https://doi.org/10.5194/acp-19-15583-2019, https://doi.org/10.5194/acp-19-15583-2019, 2019
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Dusts have a significant impact on climate and environment. Detecting dust using satellite instruments is generally conducted by measuring at multiple observation angles due to the uncertainty of the surface reflection. This report shows that the degree of polarization of reflected light can be used for retrieving the optical depth of dust at backscatter angles only, regardless of surface conditions. This simple method is suitable for surveying dust aerosols over oceans with low-cost satellites.
Andrew M. Sayer and Kirk D. Knobelspiesse
Atmos. Chem. Phys., 19, 15023–15048, https://doi.org/10.5194/acp-19-15023-2019, https://doi.org/10.5194/acp-19-15023-2019, 2019
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Data about the Earth are routinely obtained from satellite observations, model simulations, and ground-based or other measurements. These are at different space and timescales, and it is common to average them to reduce gaps and increase ease of use. The question of how the data should be averaged depends on the underlying distribution of the quantity. This study presents a method for determining how to appropriately aggregate data and applies it to data sets about atmospheric aerosol levels.
Kristina Pistone, Jens Redemann, Sarah Doherty, Paquita Zuidema, Sharon Burton, Brian Cairns, Sabrina Cochrane, Richard Ferrare, Connor Flynn, Steffen Freitag, Steven G. Howell, Meloë Kacenelenbogen, Samuel LeBlanc, Xu Liu, K. Sebastian Schmidt, Arthur J. Sedlacek III, Michal Segal-Rozenhaimer, Yohei Shinozuka, Snorre Stamnes, Bastiaan van Diedenhoven, Gerard Van Harten, and Feng Xu
Atmos. Chem. Phys., 19, 9181–9208, https://doi.org/10.5194/acp-19-9181-2019, https://doi.org/10.5194/acp-19-9181-2019, 2019
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Understanding how smoke particles interact with sunlight is important in calculating their effects on climate, since some smoke is more scattering (cooling) and some is more absorbing (heating). Knowing this proportion is important for both satellite observations and climate models. We measured smoke properties in a recent aircraft-based field campaign off the west coast of Africa and present a comparison of these properties as measured using the six different, independent techniques available.
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Malcolm Taberner, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Yngve Borsheim, Astrid Bracher, Vittorio Brando, Elisabetta Canuti, Francisco Chavez, Andrés Cianca, Hervé Claustre, Lesley Clementson, Richard Crout, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Richard Gould, Stanford B. Hooker, Mati Kahru, Milton Kampel, Holger Klein, Susanne Kratzer, Raphael Kudela, Jesus Ledesma, Hubert Loisel, Patricia Matrai, David McKee, Brian G. Mitchell, Tiffany Moisan, Frank Muller-Karger, Leonie O'Dowd, Michael Ondrusek, Trevor Platt, Alex J. Poulton, Michel Repecaud, Thomas Schroeder, Timothy Smyth, Denise Smythe-Wright, Heidi M. Sosik, Michael Twardowski, Vincenzo Vellucci, Kenneth Voss, Jeremy Werdell, Marcel Wernand, Simon Wright, and Giuseppe Zibordi
Earth Syst. Sci. Data, 11, 1037–1068, https://doi.org/10.5194/essd-11-1037-2019, https://doi.org/10.5194/essd-11-1037-2019, 2019
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A compiled set of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the compilation of global bio-optical in situ data (spanning from 1997 to 2018) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Shan Zeng, Mark Vaughan, Zhaoyan Liu, Charles Trepte, Jayanta Kar, Ali Omar, David Winker, Patricia Lucker, Yongxiang Hu, Brian Getzewich, and Melody Avery
Atmos. Meas. Tech., 12, 2261–2285, https://doi.org/10.5194/amt-12-2261-2019, https://doi.org/10.5194/amt-12-2261-2019, 2019
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We use a fuzzy k-means (FKM) classifier to assess the ability of the CALIPSO cloud–aerosol discrimination (CAD) algorithm to correctly distinguish between clouds and aerosols detected in the CALIPSO lidar backscatter signals. FKM is an unsupervised learning algorithm, so the classifications it derives are wholly independent from those reported by the CAD scheme. For a full month of measurements, the two techniques agree in ~ 95 % of all cases, providing strong evidence for CAD correctness.
Meloë S. Kacenelenbogen, Mark A. Vaughan, Jens Redemann, Stuart A. Young, Zhaoyan Liu, Yongxiang Hu, Ali H. Omar, Samuel LeBlanc, Yohei Shinozuka, John Livingston, Qin Zhang, and Kathleen A. Powell
Atmos. Chem. Phys., 19, 4933–4962, https://doi.org/10.5194/acp-19-4933-2019, https://doi.org/10.5194/acp-19-4933-2019, 2019
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Significant efforts are required to estimate the direct radiative effects of aerosols above clouds (DAREcloudy). We have used a combination of passive and active A-Train satellite sensors and derive mainly positive global and regional DAREcloudy values (e.g., global seasonal values between 0.13 and 0.26 W m-2). Despite differences in methods and sensors, the DAREcloudy values in this study are generally higher than previously reported. We discuss the primary reasons for these higher estimates.
Mark Vaughan, Anne Garnier, Damien Josset, Melody Avery, Kam-Pui Lee, Zhaoyan Liu, William Hunt, Jacques Pelon, Yongxiang Hu, Sharon Burton, Johnathan Hair, Jason L. Tackett, Brian Getzewich, Jayanta Kar, and Sharon Rodier
Atmos. Meas. Tech., 12, 51–82, https://doi.org/10.5194/amt-12-51-2019, https://doi.org/10.5194/amt-12-51-2019, 2019
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The version 4 (V4) release of the CALIPSO data products includes substantial improvements to the calibration of the CALIOP 1064 nm channel. In this paper we review the fundamentals of 1064 nm lidar calibration, explain the motivations for the changes made to the algorithm, and describe the mechanics of the V4 calibration technique. Internal consistency checks and comparisons to collocated high spectral resolution lidar measurements show the V4 1064 nm calibration coefficients to within ~ 3 %.
Man-Hae Kim, Ali H. Omar, Jason L. Tackett, Mark A. Vaughan, David M. Winker, Charles R. Trepte, Yongxiang Hu, Zhaoyan Liu, Lamont R. Poole, Michael C. Pitts, Jayanta Kar, and Brian E. Magill
Atmos. Meas. Tech., 11, 6107–6135, https://doi.org/10.5194/amt-11-6107-2018, https://doi.org/10.5194/amt-11-6107-2018, 2018
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This paper discusses recent advances made in distinguishing among different aerosols species detected in the CALIPSO lidar measurements. A new classification algorithm now classifies four different aerosol types in the stratosphere, and the number of aerosol types recognized in the troposphere has increased from six to seven. The lidar ratios characterizing each type have been updated and the effects of these changes on CALIPSO retrievals of aerosol optical depth are examined in detail.
Daniel J. Miller, Zhibo Zhang, Steven Platnick, Andrew S. Ackerman, Frank Werner, Celine Cornet, and Kirk Knobelspiesse
Atmos. Meas. Tech., 11, 3689–3715, https://doi.org/10.5194/amt-11-3689-2018, https://doi.org/10.5194/amt-11-3689-2018, 2018
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Prior satellite comparisons of bispectral and polarimetric cloud droplet size retrievals exhibited systematic biases. However, similar airborne instrument retrievals have been found to be quite similar to one another. This study explains this discrepancy in terms of differing sensitivity to vertical profile, as well as spatial and angular resolution. This is accomplished by using a satellite retrieval simulator – an LES cloud model coupled to radiative transfer and cloud retrieval algorithms.
Xiaomei Lu, Yongxiang Hu, Yuekui Yang, Mark Vaughan, Zhaoyan Liu, Sharon Rodier, William Hunt, Kathy Powell, Patricia Lucker, and Charles Trepte
Atmos. Meas. Tech., 11, 3281–3296, https://doi.org/10.5194/amt-11-3281-2018, https://doi.org/10.5194/amt-11-3281-2018, 2018
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This paper presents an innovative retrieval method that translates the CALIOP land surface laser pulse returns into the surface bidirectional reflectance. The surface bidirectional reflectances retrieved from CALIOP measurements contribute complementary data for existing MODIS standard data products and could be used to detect and monitor seasonal surface reflectance changes in high latitude regions where passive MODIS measurements are limited.
Antonio Di Noia, Otto P. Hasekamp, Lianghai Wu, Bastiaan van Diedenhoven, Brian Cairns, and John E. Yorks
Atmos. Meas. Tech., 10, 4235–4252, https://doi.org/10.5194/amt-10-4235-2017, https://doi.org/10.5194/amt-10-4235-2017, 2017
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In this paper an algorithm for the retrieval of aerosol properties from NASA Research Scanning Polarimeter (RSP) data is presented. An artificial neural network is used to produce a first estimate of the aerosol properties, which is then improved using an iterative retrieval scheme based on Phillips–Tikhonov regularization. Using the neural network retrievals as a first guess for the Phillips–Tikhonov improved the retrieval convergence, confirming results previously found on ground-based data.
Kenneth Sinclair, Bastiaan van Diedenhoven, Brian Cairns, John Yorks, Andrzej Wasilewski, and Matthew McGill
Atmos. Meas. Tech., 10, 2361–2375, https://doi.org/10.5194/amt-10-2361-2017, https://doi.org/10.5194/amt-10-2361-2017, 2017
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We present a multi-angular contrast approach to retrieve cloud top height (CTH) using photogrammetry. We demonstrate the method’s ability to retrieve heights of multiple cloud layers within single footprints, using the multiple views available for each footprint. This paper provides an in-depth description and performance analysis of the CTH retrieval technique and the retrieved cloud heights are evaluated using collocated data from the Cloud Physics Lidar.
Sharon P. Burton, Eduard Chemyakin, Xu Liu, Kirk Knobelspiesse, Snorre Stamnes, Patricia Sawamura, Richard H. Moore, Chris A. Hostetler, and Richard A. Ferrare
Atmos. Meas. Tech., 9, 5555–5574, https://doi.org/10.5194/amt-9-5555-2016, https://doi.org/10.5194/amt-9-5555-2016, 2016
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Retrievals of aerosol microphysics exist for ground-based, airborne, and future space-borne lidar measurements. We investigate the information content of a lidar measurement system, using only a forward model but no explicit inversion. The simplified aerosol used here is applicable as a best case for all retrievals in the absence of additional constraints. We report (1) information content of the measurements; (2) uncertainties on the retrieved parameters; and (3) sources of compensating errors.
Feng Xu, Oleg Dubovik, Peng-Wang Zhai, David J. Diner, Olga V. Kalashnikova, Felix C. Seidel, Pavel Litvinov, Andrii Bovchaliuk, Michael J. Garay, Gerard van Harten, and Anthony B. Davis
Atmos. Meas. Tech., 9, 2877–2907, https://doi.org/10.5194/amt-9-2877-2016, https://doi.org/10.5194/amt-9-2877-2016, 2016
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We developed an algorithm for aerosol and water-leaving radiance retrieval in a simultaneous way.
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Malcolm Taberner, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Vittorio Brando, Elisabetta Canuti, Francisco Chavez, Hervé Claustre, Richard Crout, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Richard Gould, Stanford Hooker, Mati Kahru, Holger Klein, Susanne Kratzer, Hubert Loisel, David McKee, Brian G. Mitchell, Tiffany Moisan, Frank Muller-Karger, Leonie O'Dowd, Michael Ondrusek, Alex J. Poulton, Michel Repecaud, Timothy Smyth, Heidi M. Sosik, Michael Twardowski, Kenneth Voss, Jeremy Werdell, Marcel Wernand, and Giuseppe Zibordi
Earth Syst. Sci. Data, 8, 235–252, https://doi.org/10.5194/essd-8-235-2016, https://doi.org/10.5194/essd-8-235-2016, 2016
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A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite data records. Here we describe the compilation of global bio-optical in situ data (spanning from 1997 to 2012) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Joel McCorkel, Brian Cairns, and Andrzej Wasilewski
Atmos. Meas. Tech., 9, 955–962, https://doi.org/10.5194/amt-9-955-2016, https://doi.org/10.5194/amt-9-955-2016, 2016
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The transfer and maintenance of international radiometric standards to satellite remote-sensing instruments is a labor-intensive and costly one. The goal is to provide specific examples for calibration implementation for a potential instrument mission and, with this, advance debate on the roles that the various satellite calibration techniques play in providing the best radiometric standards for Earth-observing sensors.
B. Nechad, K. Ruddick, T. Schroeder, K. Oubelkheir, D. Blondeau-Patissier, N. Cherukuru, V. Brando, A. Dekker, L. Clementson, A. C. Banks, S. Maritorena, P. J. Werdell, C. Sá, V. Brotas, I. Caballero de Frutos, Y.-H. Ahn, S. Salama, G. Tilstone, V. Martinez-Vicente, D. Foley, M. McKibben, J. Nahorniak, T. Peterson, A. Siliò-Calzada, R. Röttgers, Z. Lee, M. Peters, and C. Brockmann
Earth Syst. Sci. Data, 7, 319–348, https://doi.org/10.5194/essd-7-319-2015, https://doi.org/10.5194/essd-7-319-2015, 2015
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The CoastColour Round Robin (CCRR) project (European Space Agency) was designed to set up the first database for remote-sensing algorithm testing and accuracy assessment of water quality parameter retrieval in coastal waters, from satellite imagery. This paper analyses the CCRR database, which includes in situ bio-geochemical and optical measurements in various water types, match-up reflectance products from the MEdium Resolution Imaging Spectrometer (MERIS), and radiative transfer simulations.
W. Sun, R. R. Baize, G. Videen, Y. Hu, and Q. Fu
Atmos. Chem. Phys., 15, 11909–11918, https://doi.org/10.5194/acp-15-11909-2015, https://doi.org/10.5194/acp-15-11909-2015, 2015
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A method is reported for retrieving super-thin cloud optical depth with polarized light. It is found that near-backscatter p-polarized light is sensitive to clouds, but not to ocean conditions. Near-backscatter p-polarized intensity linearly relates to super-thin cloud optical depth. Based on these findings, super-thin cloud optical depth can be retrieved with little effect from surface reflection.
M. Ottaviani, B. van Diedenhoven, and B. Cairns
The Cryosphere, 9, 1933–1942, https://doi.org/10.5194/tc-9-1933-2015, https://doi.org/10.5194/tc-9-1933-2015, 2015
W. Sun, R. R. Baize, C. Lukashin, and Y. Hu
Atmos. Chem. Phys., 15, 7725–7734, https://doi.org/10.5194/acp-15-7725-2015, https://doi.org/10.5194/acp-15-7725-2015, 2015
L. Wu, O. Hasekamp, B. van Diedenhoven, and B. Cairns
Atmos. Meas. Tech., 8, 2625–2638, https://doi.org/10.5194/amt-8-2625-2015, https://doi.org/10.5194/amt-8-2625-2015, 2015
Z. Liu, D. Winker, A. Omar, M. Vaughan, J. Kar, C. Trepte, Y. Hu, and G. Schuster
Atmos. Chem. Phys., 15, 1265–1288, https://doi.org/10.5194/acp-15-1265-2015, https://doi.org/10.5194/acp-15-1265-2015, 2015
A. Lyapustin, Y. Wang, X. Xiong, G. Meister, S. Platnick, R. Levy, B. Franz, S. Korkin, T. Hilker, J. Tucker, F. Hall, P. Sellers, A. Wu, and A. Angal
Atmos. Meas. Tech., 7, 4353–4365, https://doi.org/10.5194/amt-7-4353-2014, https://doi.org/10.5194/amt-7-4353-2014, 2014
S. Zeng, J. Riedi, C. R. Trepte, D. M. Winker, and Y.-X. Hu
Atmos. Chem. Phys., 14, 7125–7134, https://doi.org/10.5194/acp-14-7125-2014, https://doi.org/10.5194/acp-14-7125-2014, 2014
S. Rodier, Y. Hu, and M. Vaughan
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-4681-2013, https://doi.org/10.5194/tcd-7-4681-2013, 2013
Revised manuscript has not been submitted
B. van Diedenhoven, B. Cairns, A. M. Fridlind, A. S. Ackerman, and T. J. Garrett
Atmos. Chem. Phys., 13, 3185–3203, https://doi.org/10.5194/acp-13-3185-2013, https://doi.org/10.5194/acp-13-3185-2013, 2013
Related subject area
Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Mass concentration estimates of long-range-transported Canadian biomass burning aerosols from a multi-wavelength Raman polarization lidar and a ceilometer in Finland
Retrievals of dust-related particle mass and ice-nucleating particle concentration profiles with ground-based polarization lidar and sun photometer over a megacity in central China
Introducing the MISR level 2 near real-time aerosol product
Estimation of PM2.5 concentration in China using linear hybrid machine learning model
Species correlation measurements in turbulent flare plumes: considerations for field measurements
Retrieval of aerosol microphysical properties from atmospheric lidar sounding: an investigation using synthetic measurements and data from the ACEPOL campaign
Integration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaigns
Deriving boundary layer height from aerosol lidar using machine learning: KABL and ADABL algorithms
Inferring the absorption properties of organic aerosol in biomass burning plumes from remote optical observations
Efficient multi-angle polarimetric inversion of aerosols and ocean color powered by a deep neural network forward model
Quantitative comparison of measured and simulated O4 absorptions for one day with extremely low aerosol load over the tropical Atlantic
Methodology to obtain highly resolved SO2 vertical profiles for representation of volcanic emissions in climate models
A Dark Target research aerosol algorithm for MODIS observations over eastern China: increasing coverage while maintaining accuracy at high aerosol loading
Optimal use of the Prede POM sky radiometer for aerosol, water vapor, and ozone retrievals
Analysis of simultaneous aerosol and ocean glint retrieval using multi-angle observations
Model-enforced post-process correction of satellite aerosol retrievals
Explicit and consistent aerosol correction for visible wavelength satellite cloud and nitrogen dioxide retrievals based on optical properties from a global aerosol analysis
Reducing cloud contamination in aerosol optical depth (AOD) measurements
Synergy processing of diverse ground-based remote sensing and in situ data using the GRASP algorithm: applications to radiometer, lidar and radiosonde observations
Retrieval of stratospheric aerosol size distribution parameters using satellite solar occultation measurements at three wavelengths
Relative sky radiance from multi-exposure all-sky camera images
An uncertainty-based protocol for the setup and measurement of soot–black carbon emissions from gas flares using sky-LOSA
A new measurement approach for validating satellite-based above-cloud aerosol optical depth
OMPS LP Version 2.0 multi-wavelength aerosol extinction coefficient retrieval algorithm
Simulated reflectance above snow constrained by airborne measurements of solar radiation: implications for the snow grain morphology in the Arctic
ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set
Integrated System for Atmospheric Boundary Layer Height Estimation (ISABLE) using a ceilometer and microwave radiometer
Effects of clouds on the UV Absorbing Aerosol Index from TROPOMI
Correction of a lunar-irradiance model for aerosol optical depth retrieval and comparison with a star photometer
Improving GOES Advanced Baseline Imager (ABI) aerosol optical depth (AOD) retrievals using an empirical bias correction algorithm
Stratospheric aerosol extinction profiles from SCIAMACHY solar occultation
A feasibility study to use machine learning as an inversion algorithm for aerosol profile and property retrieval from multi-axis differential absorption spectroscopy measurements
Leveraging spatial textures, through machine learning, to identify aerosols and distinct cloud types from multispectral observations
Retrieval of aerosol properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) observations during ACEPOL 2017
Aerosol optical properties as observed from an ultralight aircraft over the Strait of Gibraltar
Evaluation of a method for converting Stratospheric Aerosol and Gas Experiment (SAGE) extinction coefficients to backscatter coefficients for intercomparison with lidar observations
Inversion of multiangular polarimetric measurements from the ACEPOL campaign: an application of improving aerosol property and hyperspectral ocean color retrievals
Improved water vapour retrieval from AMSU-B and MHS in the Arctic
The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2
Issues related to the retrieval of stratospheric-aerosol particle size information based on optical measurements
A new lidar inversion method using a surface reference target applied to the backscattering coefficient and lidar ratio retrievals of a fog-oil plume at short range
A multi-axis differential optical absorption spectroscopy aerosol profile retrieval algorithm for high-altitude measurements: application to measurements at Schneefernerhaus (UFS), Germany
The potential of elastic and polarization lidars to retrieve extinction profiles
Introducing the 4.4 km spatial resolution Multi-Angle Imaging SpectroRadiometer (MISR) aerosol product
Retrieval of gridded aerosol direct radiative forcing based on multiplatform datasets
Assessing the stability of surface lights for use in retrievals of nocturnal atmospheric parameters
A neural network radiative transfer model approach applied to the Tropospheric Monitoring Instrument aerosol height algorithm
Applying the Dark Target aerosol algorithm with Advanced Himawari Imager observations during the KORUS-AQ field campaign
Above-cloud aerosol radiative effects based on ORACLES 2016 and ORACLES 2017 aircraft experiments
The role of aerosol layer height in quantifying aerosol absorption from ultraviolet satellite observations
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.
Thomas Rieutord, Sylvain Aubert, and Tiago Machado
Atmos. Meas. Tech., 14, 4335–4353, https://doi.org/10.5194/amt-14-4335-2021, https://doi.org/10.5194/amt-14-4335-2021, 2021
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This article describes two methods to estimate the height of the very first layer of the atmosphere. It is measured with aerosol lidars, and the two new methods are based on machine learning. Both are open source and available under free licenses. A sensitivity analysis and a 2-year evaluation against meteorological balloons were carried out. One method has a good agreement with balloons but is limited by training, and the other has less good agreement with balloons but is more flexible.
Igor B. Konovalov, Nikolai A. Golovushkin, Matthias Beekmann, Mikhail V. Panchenko, and Meinrat O. Andreae
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-151, https://doi.org/10.5194/amt-2021-151, 2021
Revised manuscript accepted for AMT
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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.
Meng Gao, Bryan A. Franz, Kirk Knobelspiesse, Peng-Wang Zhai, Vanderlei Martins, Sharon Burton, Brian Cairns, Richard Ferrare, Joel Gales, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Brent McBride, Anin Puthukkudy, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 14, 4083–4110, https://doi.org/10.5194/amt-14-4083-2021, https://doi.org/10.5194/amt-14-4083-2021, 2021
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Multi-angle polarimetric measurements can retrieve accurate aerosol properties over complex atmosphere and ocean systems; however, most retrieval algorithms require high computational costs. We propose a deep neural network (NN) forward model to represent the radiative transfer simulation of coupled atmosphere and ocean systems and then conduct simultaneous aerosol and ocean color retrievals on AirHARP measurements. The computational acceleration is 103 times with CPU or 104 times with GPU.
Thomas Wagner, Steffen Dörner, Steffen Beirle, Sebastian Donner, and Stefan Kinne
Atmos. Meas. Tech., 14, 3871–3893, https://doi.org/10.5194/amt-14-3871-2021, https://doi.org/10.5194/amt-14-3871-2021, 2021
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We compare measured and simulated O4 absorptions for conditions of extremely low aerosol optical depth, for which the uncertainties related to imperfect knowledge of aerosol properties do not significantly affect the comparison results. The simulations underestimate the measurements by 15 % to 20 %. Even if no aerosols are considered, the simulated O4 absorptions are systematically lower than the measurements. Our results indicate a fundamental inconsistency between simulations and measurements.
Oscar S. Sandvik, Johan Friberg, Moa K. Sporre, and Bengt G. Martinsson
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-94, https://doi.org/10.5194/amt-2021-94, 2021
Revised manuscript accepted for AMT
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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 two weeks after an eruption with air trajectory analyses. The profile agrees with a published high-resolution aerosol profile when most of the SO2 is converted to sulphate aerosol. The detailed resolution of the SO2 profile is unprecedented compared to other methods.
Yingxi R. Shi, Robert C. Levy, Leiku Yang, Lorraine A. Remer, Shana Mattoo, and Oleg Dubovik
Atmos. Meas. Tech., 14, 3449–3468, https://doi.org/10.5194/amt-14-3449-2021, https://doi.org/10.5194/amt-14-3449-2021, 2021
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Due to fast industrialization and development, China has been experiencing haze pollution episodes with both high frequencies and severity over the last 3 decades. This study improves the accuracy and data coverage of measured aerosol from satellites, which help quantify, characterize, and understand the impact of the haze phenomena over the entire East Asia region.
Rei Kudo, Henri Diémoz, Victor Estellés, Monica Campanelli, Masahiro Momoi, Franco Marenco, Claire L. Ryder, Osamu Ijima, Akihiro Uchiyama, Kouichi Nakashima, Akihiro Yamazaki, Ryoji Nagasawa, Nozomu Ohkawara, and Haruma Ishida
Atmos. Meas. Tech., 14, 3395–3426, https://doi.org/10.5194/amt-14-3395-2021, https://doi.org/10.5194/amt-14-3395-2021, 2021
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A new method, Skyrad pack MRI version 2, was developed to retrieve aerosol physical and optical properties, water vapor, and ozone column concentrations from the sky radiometer, a filter radiometer deployed in the SKYNET international network. Our method showed good performance in a radiative closure study using surface solar irradiances from the Baseline Surface Radiation Network and a comparison using aircraft in situ measurements of Saharan dust events during the SAVEX-D 2015 campaign.
Kirk Knobelspiesse, Amir Ibrahim, Bryan Franz, Sean Bailey, Robert Levy, Ziauddin Ahmad, Joel Gales, Meng Gao, Michael Garay, Samuel Anderson, and Olga Kalashnikova
Atmos. Meas. Tech., 14, 3233–3252, https://doi.org/10.5194/amt-14-3233-2021, https://doi.org/10.5194/amt-14-3233-2021, 2021
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We assessed atmospheric aerosol and ocean surface wind speed remote sensing capability with NASA's Multi-angle Imaging SpectroRadiometer (MISR), using synthetic data and a Bayesian inference technique called generalized nonlinear retrieval analysis (GENRA). We found success using three aerosol parameters plus wind speed. This shows that MISR can perform an atmospheric correction for the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same spacecraft (Terra).
Antti Lipponen, Ville Kolehmainen, Pekka Kolmonen, Antti Kukkurainen, Tero Mielonen, Neus Sabater, Larisa Sogacheva, Timo H. Virtanen, and Antti Arola
Atmos. Meas. Tech., 14, 2981–2992, https://doi.org/10.5194/amt-14-2981-2021, https://doi.org/10.5194/amt-14-2981-2021, 2021
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We have developed a new computational method to post-process-correct the satellite aerosol retrievals. The proposed method combines the conventional satellite aerosol retrievals relying on physics-based models and machine learning. The results show significantly improved accuracy in the aerosol data over the operational satellite data products. The correction can be applied to the existing satellite aerosol datasets with no need to fully reprocess the much larger original radiance data.
Alexander Vasilkov, Nickolay Krotkov, Eun-Su Yang, Lok Lamsal, Joanna Joiner, Patricia Castellanos, Zachary Fasnacht, and Robert Spurr
Atmos. Meas. Tech., 14, 2857–2871, https://doi.org/10.5194/amt-14-2857-2021, https://doi.org/10.5194/amt-14-2857-2021, 2021
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To explicitly account for aerosol effects in the OMI cloud and nitrogen dioxide algorithms, we use a model of aerosol optical properties from a global aerosol assimilation system and radiative transfer computations. Accounting for anisotropic reflection of Earth's surface is an important feature of the approach. Comparisons of the cloud and tropospheric nitrogen dioxide retrievals with implicit and explicit aerosol corrections are carried out for a selected area with high pollution.
Verena Schenzinger and Axel Kreuter
Atmos. Meas. Tech., 14, 2787–2798, https://doi.org/10.5194/amt-14-2787-2021, https://doi.org/10.5194/amt-14-2787-2021, 2021
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When measuring the aerosol optical depth of the atmosphere, clouds in front of the sun lead to erroneously high values. Therefore, measurements that are potentially affected by clouds need to be removed from the dataset by an automatic process. As the currently used algorithm cannot reliably identify thin clouds, we developed a new one based on a method borrowed from machine learning. Tests with 10 years of data show improved performance of the new routine and therefore higher data quality.
Anton Lopatin, Oleg Dubovik, David Fuertes, Georgiy Stenchikov, Tatyana Lapyonok, Igor Veselovskii, Frank G. Wienhold, Illia Shevchenko, Qiaoyun Hu, and Sagar Parajuli
Atmos. Meas. Tech., 14, 2575–2614, https://doi.org/10.5194/amt-14-2575-2021, https://doi.org/10.5194/amt-14-2575-2021, 2021
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The article presents novelties in characterizing fine particles suspended in the air by means of combining various measurements that observe light propagation in atmosphere. Several non-coincident observations (some of which require sunlight, while others work only at night) could be united under the assumption that aerosol properties do not change drastically at nighttime. It also proposes how to describe particles' composition in a simplified manner that uses new types of observations.
Felix Wrana, Christian von Savigny, Jacob Zalach, and Larry W. Thomason
Atmos. Meas. Tech., 14, 2345–2357, https://doi.org/10.5194/amt-14-2345-2021, https://doi.org/10.5194/amt-14-2345-2021, 2021
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In this paper, we describe a new method for calculating the size of naturally occurring droplets (aerosols) made mostly of sulfuric acid and water that can be found roughly at 20 km altitude in the atmosphere. We use data from the instrument SAGE III/ISS that is mounted on the International Space Station. We show that our method works well, and that the size parameters we calculate are reasonable and can be a valuable addition for a better understanding of aerosols and their effect on climate.
Juan C. Antuña-Sánchez, Roberto Román, Victoria E. Cachorro, Carlos Toledano, César López, Ramiro González, David Mateos, Abel Calle, and Ángel M. de Frutos
Atmos. Meas. Tech., 14, 2201–2217, https://doi.org/10.5194/amt-14-2201-2021, https://doi.org/10.5194/amt-14-2201-2021, 2021
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This paper presents a new technique to exploit the potential of all-sky cameras. The sky radiance at three effective wavelengths is calculated and compared with alternative measurements and simulated data. The proposed method will be useful for the retrieval of aerosol and cloud properties.
Bradley M. Conrad and Matthew R. Johnson
Atmos. Meas. Tech., 14, 1573–1591, https://doi.org/10.5194/amt-14-1573-2021, https://doi.org/10.5194/amt-14-1573-2021, 2021
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A general uncertainty analysis (GUA) is performed for the sky-LOSA technique used to remotely measure soot emissions from gas flares. GUA data are compiled in an open-source software tool to help sky-LOSA users select critical setup and acquisition parameters while giving quantitative visual feedback on anticipated uncertainties for a specific measurement. The software tool enables easy acquisition of optimal measurement data, significantly increasing the accessibility of the sky-LOSA technique.
Charles K. Gatebe, Hiren Jethva, Ritesh Gautam, Rajesh Poudyal, and Tamás Várnai
Atmos. Meas. Tech., 14, 1405–1423, https://doi.org/10.5194/amt-14-1405-2021, https://doi.org/10.5194/amt-14-1405-2021, 2021
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The retrieval of aerosol parameters from passive satellite instruments in cloudy scenes is very challenging, partly because clouds and cloud-related processes significantly modify the aerosol properties and the 3D radiative effects. This study shows simultaneous retrieval of above-cloud aerosol optical depth and aerosol-corrected cloud optical depth from airborne measurements, thereby demonstrating a novel approach for assessing satellite retrievals of aerosols above clouds.
Ghassan Taha, Robert Loughman, Tong Zhu, Larry Thomason, Jayanta Kar, Landon Rieger, and Adam Bourassa
Atmos. Meas. Tech., 14, 1015–1036, https://doi.org/10.5194/amt-14-1015-2021, https://doi.org/10.5194/amt-14-1015-2021, 2021
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This work describes the newly released OMPS LP aerosol extinction profile multi-wavelength Version 2.0 algorithm and dataset. It is shown that the V2.0 aerosols exhibit significant improvements in OMPS LP retrieval performance in the Southern Hemisphere and at lower altitudes. The new product is compared to the SAGE III/ISS, OSIRIS and CALIPSO missions and shown to be of good quality and suitable for scientific studies.
Soheila Jafariserajehlou, Vladimir V. Rozanov, Marco Vountas, Charles K. Gatebe, and John P. Burrows
Atmos. Meas. Tech., 14, 369–389, https://doi.org/10.5194/amt-14-369-2021, https://doi.org/10.5194/amt-14-369-2021, 2021
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In this work, we study retrieval of snow grain morphologies and their impact on the reflectance in a coupled snow–atmosphere system. We present a sensitivity study to highlight the importance of having adequate information about snow and atmosphere. A novel two-stage algorithm for retrieving the size and shape of snow grains is presented. The reflectance simulation results are compared to that of airborne measurements; high correlations of 0.98 at IR and 0.88–0.98 at VIS are achieved.
Antonis Gkikas, Emmanouil Proestakis, Vassilis Amiridis, Stelios Kazadzis, Enza Di Tomaso, Alexandra Tsekeri, Eleni Marinou, Nikos Hatzianastassiou, and Carlos Pérez García-Pando
Atmos. Meas. Tech., 14, 309–334, https://doi.org/10.5194/amt-14-309-2021, https://doi.org/10.5194/amt-14-309-2021, 2021
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We present the development of the MIDAS (ModIs Dust AeroSol) data set, providing daily dust optical depth (DOD; 550 nm) at a global scale and fine spatial resolution (0.1° x 0.1°) over a 15-year period (2003–2017). It has been developed via the synergy of MODIS-Aqua and MERRA-2 data, while CALIOP and AERONET retrievals are used for its assessment. MIDAS upgrades existing dust observational capabilities, and it is suitable for dust climatological studies, model evaluation, and data assimilation.
Jae-Sik Min, Moon-Soo Park, Jung-Hoon Chae, and Minsoo Kang
Atmos. Meas. Tech., 13, 6965–6987, https://doi.org/10.5194/amt-13-6965-2020, https://doi.org/10.5194/amt-13-6965-2020, 2020
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An algorithm for an integrated system for ABLH estimation (ISABLE) was developed and applied to the vertical profile data obtained by a ceilometer and a microwave radiometer in Seoul city, Korea. The ISABLE algorithm finds an optimal ABLH through the post-processing including k-means clustering and density-based spatial clustering of applications with noise (DBSCAN) techniques. The ISABLE ABLH exhibited better performance than those obtained by most conventional methods.
Maurits L. Kooreman, Piet Stammes, Victor Trees, Maarten Sneep, L. Gijsbert Tilstra, Martin de Graaf, Deborah C. Stein Zweers, Ping Wang, Olaf N. E. Tuinder, and J. Pepijn Veefkind
Atmos. Meas. Tech., 13, 6407–6426, https://doi.org/10.5194/amt-13-6407-2020, https://doi.org/10.5194/amt-13-6407-2020, 2020
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We investigated the influence of clouds on the Absorbing Aerosol Index (AAI), an indicator of the presence of small particles in the atmosphere. Clouds produce artifacts in AAI calculations on the individual measurement (7 km) scale, which was not seen with previous instruments, as well as on large (1000+ km) scales. To reduce these artefacts, we used three different AAI calculation techniques of varying complexity. We find that the AAI artifacts are reduced when using more complex techniques.
Roberto Román, Ramiro González, Carlos Toledano, África Barreto, Daniel Pérez-Ramírez, Jose A. Benavent-Oltra, Francisco J. Olmo, Victoria E. Cachorro, Lucas Alados-Arboledas, and Ángel M. de Frutos
Atmos. Meas. Tech., 13, 6293–6310, https://doi.org/10.5194/amt-13-6293-2020, https://doi.org/10.5194/amt-13-6293-2020, 2020
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Atmospheric-aerosol and gaseous properties can be derived at night-time if the lunar irradiance at the ground is measured. To this end, the knowledge of lunar irradiance at the top of the atmosphere is necessary. This extraterrestrial lunar irradiance is usually calculated by models since it varies with several geometric factors mainly depending on time and location. This paper proposes a correction to the most used lunar-irradiance model to be applied for atmospheric-aerosol characterization.
Hai Zhang, Shobha Kondragunta, Istvan Laszlo, and Mi Zhou
Atmos. Meas. Tech., 13, 5955–5975, https://doi.org/10.5194/amt-13-5955-2020, https://doi.org/10.5194/amt-13-5955-2020, 2020
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Geostationary Operational Environmental Satellites (GOES) retrieve high temporal resolution aerosol optical depth, which is a measure of the aerosol quantity within the atmospheric column. This work introduces an algorithm that improves the accuracy of the aerosol optical depth retrievals from GOES. The resulting data product can be used in monitoring the air quality and climate change research.
Stefan Noël, Klaus Bramstedt, Alexei Rozanov, Elizaveta Malinina, Heinrich Bovensmann, and John P. Burrows
Atmos. Meas. Tech., 13, 5643–5666, https://doi.org/10.5194/amt-13-5643-2020, https://doi.org/10.5194/amt-13-5643-2020, 2020
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A new approach to derive stratospheric aerosol extinction profiles from SCIAMACHY solar occultation measurements based on an onion-peeling method is presented. The resulting extinctions at 452, 525 and 750 nm compare well with other limb and occultation data from, e.g. SAGE and SCIAMACHY, but show small oscillating features which vanish in monthly anomalies. Major volcanic eruptions, polar stratospheric clouds and influences of the quasi-biennial oscillation can be identified in the time series.
Yun Dong, Elena Spinei, and Anuj Karpatne
Atmos. Meas. Tech., 13, 5537–5550, https://doi.org/10.5194/amt-13-5537-2020, https://doi.org/10.5194/amt-13-5537-2020, 2020
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This paper is about a feasibility study of applying a machine learning technique to derive aerosol properties from a single MAX-DOAS sky scan, which detects sky-scattered UV–visible photons at multiple elevation angles. Evaluation of retrieved aerosol properties shows good performance of the ML algorithm, suggesting several advantages of a ML-based inversion algorithm such as fast data inversion, simple implementation and the ability to extract information not available using other algorithms.
Willem J. Marais, Robert E. Holz, Jeffrey S. Reid, and Rebecca M. Willett
Atmos. Meas. Tech., 13, 5459–5480, https://doi.org/10.5194/amt-13-5459-2020, https://doi.org/10.5194/amt-13-5459-2020, 2020
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Space agencies use moderate-resolution satellite imagery to study how smoke, dust, pollution (aerosols) and cloud types impact the Earth's climate; these space agencies include NASA, ESA and the China Meteorological Administration. We demonstrate in this paper that an algorithm with convolutional neural networks can greatly enhance the automated detection of aerosols and cloud types from satellite imagery. Our algorithm is an improvement on current aerosol and cloud detection algorithms.
Anin Puthukkudy, J. Vanderlei Martins, Lorraine A. Remer, Xiaoguang Xu, Oleg Dubovik, Pavel Litvinov, Brent McBride, Sharon Burton, and Henrique M. J. Barbosa
Atmos. Meas. Tech., 13, 5207–5236, https://doi.org/10.5194/amt-13-5207-2020, https://doi.org/10.5194/amt-13-5207-2020, 2020
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In this work, we report the demonstration and validation of the aerosol properties retrieved using AirHARP and GRASP for data from the NASA ACEPOL campaign 2017. These results serve as a proxy for the scale and detail of aerosol retrievals that are anticipated from future space mission data, as HARP CubeSat (mission begins 2020) and HARP2 (aboard the NASA PACE mission with the launch in 2023) are near duplicates of AirHARP and are expected to provide the same level of aerosol characterization.
Patrick Chazette
Atmos. Meas. Tech., 13, 4461–4477, https://doi.org/10.5194/amt-13-4461-2020, https://doi.org/10.5194/amt-13-4461-2020, 2020
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By coupling lidar on board a ULA and ground-based lidar measurements, this paper highlights aerosol transport over the Strait of Gibraltar. It shows that the lidar-derived aerosol optical properties can be different from what is commonly accepted. It presents unprecedented vertical profiles over this region and relates them to the origin of air masses. The results are based on ground, airborne, and spaceborne observations, as well as multiple retro-trajectory analyses.
Travis N. Knepp, Larry Thomason, Marilee Roell, Robert Damadeo, Kevin Leavor, Thierry Leblanc, Fernando Chouza, Sergey Khaykin, Sophie Godin-Beekmann, and David Flittner
Atmos. Meas. Tech., 13, 4261–4276, https://doi.org/10.5194/amt-13-4261-2020, https://doi.org/10.5194/amt-13-4261-2020, 2020
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Two common measurements that represent atmospheric aerosol loading are the backscatter and extinction coefficients. Measuring backscatter and extinction coefficients requires different viewing geometries and fundamentally different instrument systems. Further, these coefficients are not directly comparable. We present an algorithm to convert SAGE-observed extinction coefficients to backscatter coefficients for intercomparison with lidar backscatter products, followed by evaluation of the method.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Kirk Knobelspiesse, Amir Ibrahim, Brian Cairns, Susanne E. Craig, Guangliang Fu, Otto Hasekamp, Yongxiang Hu, and P. Jeremy Werdell
Atmos. Meas. Tech., 13, 3939–3956, https://doi.org/10.5194/amt-13-3939-2020, https://doi.org/10.5194/amt-13-3939-2020, 2020
Arantxa M. Triana-Gómez, Georg Heygster, Christian Melsheimer, Gunnar Spreen, Monia Negusini, and Boyan H. Petkov
Atmos. Meas. Tech., 13, 3697–3715, https://doi.org/10.5194/amt-13-3697-2020, https://doi.org/10.5194/amt-13-3697-2020, 2020
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In the Arctic, in situ measurements are sparse and standard remote sensing retrieval methods have problems. We present advances in a retrieval algorithm for vertically integrated water vapour tuned for polar regions. In addition to the initial sensor used (AMSU-B), we can now also use data from the successor instrument (MHS). Additionally, certain artefacts are now filtered out. Comparison with radiosondes shows the overall good performance of the updated algorithm.
Alexander Sinyuk, Brent N. Holben, Thomas F. Eck, David M. Giles, Ilya Slutsker, Sergey Korkin, Joel S. Schafer, Alexander Smirnov, Mikhail Sorokin, and Alexei Lyapustin
Atmos. Meas. Tech., 13, 3375–3411, https://doi.org/10.5194/amt-13-3375-2020, https://doi.org/10.5194/amt-13-3375-2020, 2020
Christian von Savigny and Christoph G. Hoffmann
Atmos. Meas. Tech., 13, 1909–1920, https://doi.org/10.5194/amt-13-1909-2020, https://doi.org/10.5194/amt-13-1909-2020, 2020
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Stratospheric sulfate aerosols increase the Earth's planetary albedo and can lead to significant surface cooling, for example in the aftermath of volcanic eruptions. Their particle size distribution, important for physical and chemical effects of these aerosols, is still not fully understood. The present paper proposes an explanation for systematic differences in aerosol particle size retrieved from measurements made in different measurement geometries and reported in earlier studies.
Florian Gaudfrin, Olivier Pujol, Romain Ceolato, Guillaume Huss, and Nicolas Riviere
Atmos. Meas. Tech., 13, 1921–1935, https://doi.org/10.5194/amt-13-1921-2020, https://doi.org/10.5194/amt-13-1921-2020, 2020
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A new elastic lidar inversion equation is presented. It is based on the backscattering signal from a surface reference target rather than that from a volumetric layer of reference as is usually done. The method presented can be used in the case of airborne elastic lidar measurements or when the lidar–target line is horizontal. Also, a new algorithm is described to retrieve the lidar ratio and the backscattering coefficient of an aerosol plume without any a priori assumptions about the plume.
Zhuoru Wang, Ka Lok Chan, Klaus-Peter Heue, Adrian Doicu, Thomas Wagner, Robert Holla, and Matthias Wiegner
Atmos. Meas. Tech., 13, 1835–1866, https://doi.org/10.5194/amt-13-1835-2020, https://doi.org/10.5194/amt-13-1835-2020, 2020
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We present a new aerosol profile retrieval algorithm for MAX-DOAS measurements at high-altitude sites and applied to the MAX-DOAS measurements at UFS. The retrieval algorithm is based on a O4 DSCD lookup table which is dedicated to high-altitude MAX-DOAS measurements. The comparison of retrieved aerosol optical depths (AODs) to sun photometer observations shows good agreement with a correlation coefficient (R) of 0.733 and 0.798 at 360 and 477 nm, respectively.
Elina Giannakaki, Panos Kokkalis, Eleni Marinou, Nikolaos S. Bartsotas, Vassilis Amiridis, Albert Ansmann, and Mika Komppula
Atmos. Meas. Tech., 13, 893–905, https://doi.org/10.5194/amt-13-893-2020, https://doi.org/10.5194/amt-13-893-2020, 2020
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A new method, called ElEx, is proposed for the estimation of extinction coefficient lidar profiles using only the information provided by the elastic and polarization channels of a lidar system. The method is applicable to lidar measurements both during daytime and nighttime under well-defined aerosol mixtures. Comparisons with both Raman lidar profiles during nightime and sun photometer daytime aerosol optical depth observations demonstrate the potential of the ElEx methodology.
Michael J. Garay, Marcin L. Witek, Ralph A. Kahn, Felix C. Seidel, James A. Limbacher, Michael A. Bull, David J. Diner, Earl G. Hansen, Olga V. Kalashnikova, Huikyo Lee, Abigail M. Nastan, and Yan Yu
Atmos. Meas. Tech., 13, 593–628, https://doi.org/10.5194/amt-13-593-2020, https://doi.org/10.5194/amt-13-593-2020, 2020
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The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been operational since early 2000, creating an extensive data set of global Earth observations. Here we introduce the latest version (V23) of the MISR aerosol products, which is reported on a 4.4 km spatial grid and contains retrieved aerosol optical depth and aerosol particle property information derived over both land and water. The changes implemented in V23 have significant impacts on the data product and its interpretation.
Yanyu Wang, Rui Lyu, Xin Xie, Ze Meng, Meijin Huang, Junshi Wu, Haizhen Mu, Qiu-Run Yu, Qianshan He, and Tiantao Cheng
Atmos. Meas. Tech., 13, 575–592, https://doi.org/10.5194/amt-13-575-2020, https://doi.org/10.5194/amt-13-575-2020, 2020
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A satellite-based method for clear-sky aerosol direct radiative forcing (ADRF) retrieval and spatiotemporal characteristics of ADRF in eastern China were displayed during 2000–2016. Our analysis shows aerosols have a strong cooling effect at the surface, and the changes of ADRF are closely related to the changes of AOD with the development of economic growth and rapid urbanization in eastern China.
Jeremy E. Solbrig, Steven D. Miller, Jianglong Zhang, Lewis Grasso, and Anton Kliewer
Atmos. Meas. Tech., 13, 165–190, https://doi.org/10.5194/amt-13-165-2020, https://doi.org/10.5194/amt-13-165-2020, 2020
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New satellite sensors are able to view visible light, such as that emitted by cities, at night. It may be possible to use the light from cities to assess the amount of particulate matter in the atmosphere and the thickness of clouds. To do this we must understand how light emitted from the Earth's surface changes with time and viewing conditions. This study takes a step towards understanding the characteristics of light emitted by cities and its stability in time.
Swadhin Nanda, Martin de Graaf, J. Pepijn Veefkind, Mark ter Linden, Maarten Sneep, Johan de Haan, and Pieternel F. Levelt
Atmos. Meas. Tech., 12, 6619–6634, https://doi.org/10.5194/amt-12-6619-2019, https://doi.org/10.5194/amt-12-6619-2019, 2019
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This paper discusses a neural network forward model used by the operational aerosol layer height (ALH) retrieval algorithm for the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Sentinel-5 Precursor satellite mission. This model replaces online radiative transfer calculations within the oxygen A-band, improving the speed of the algorithm by 3 orders of magnitude. With this advancement in the algorithm's speed, TROPOMI is set to deliver the ALH product operationally.
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine A. Remer, Robert E. Holz, and Andrew K. Heidinger
Atmos. Meas. Tech., 12, 6557–6577, https://doi.org/10.5194/amt-12-6557-2019, https://doi.org/10.5194/amt-12-6557-2019, 2019
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Aerosol optical depth (AOD) from a geostationary satellite has been retrieved, and validated and diurnal cycles of aerosols are discussed over the eastern hemisphere and a 2-month period of May–June 2016. The new AOD product matches well with AERONET as well as with the standard MODIS product. Future work to make this algorithm operational will need to re-examine masking including snow masks, re-evaluate assumed aerosol models for geosynchronous geometry and address the surface characterization.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Meloë Kacenelenbogen, Michal Segal Rozenhaimer, Yohei Shinozuka, Connor Flynn, Steven Platnick, Kerry Meyer, Rich Ferrare, Sharon Burton, Chris Hostetler, Steven Howell, Steffen Freitag, Amie Dobracki, and Sarah Doherty
Atmos. Meas. Tech., 12, 6505–6528, https://doi.org/10.5194/amt-12-6505-2019, https://doi.org/10.5194/amt-12-6505-2019, 2019
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For two cases from the NASA ORACLES experiments, we retrieve aerosol and cloud properties and calculate a direct aerosol radiative effect (DARE). We investigate the relationship between DARE and the cloud albedo by specifying the albedo for which DARE transitions from a cooling to warming radiative effect. Our new aerosol retrieval algorithm is successful despite complexities associated with scenes that contain aerosols above clouds and decreases the uncertainty on retrieved aerosol parameters.
Jiyunting Sun, Pepijn Veefkind, Swadhin Nanda, Peter van Velthoven, and Pieternel Levelt
Atmos. Meas. Tech., 12, 6319–6340, https://doi.org/10.5194/amt-12-6319-2019, https://doi.org/10.5194/amt-12-6319-2019, 2019
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Single scattering albedo (SSA) is critical for reducing uncertainties in radiative forcing assessment. This paper presents two methods to retrieve SSA from satellite observations of the near-UV absorbing aerosol index (UVAI). The first is physically based radiative transfer simulations; the second is a statistically based machine learning algorithm. The result of the latter is encouraging. Both methods show that the ALH is necessary to quantitatively interpret aerosol absorption from UVAI.
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