Articles | Volume 12, issue 7
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.
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
| 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
SSAI, NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
JCET, Physics Department, University of Maryland,
Baltimore County, Baltimore, MD 21250, USA
Peng-Wang Zhai
CORRESPONDING AUTHOR
JCET, Physics Department, University of Maryland,
Baltimore County, Baltimore, MD 21250, USA
Bryan A. Franz
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Yongxiang Hu
MS 475 NASA Langley Research Center, Hampton, VA 23681-2199, USA
Kirk Knobelspiesse
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
P. Jeremy Werdell
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Amir Ibrahim
SSAI, NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Brian Cairns
NASA Goddard Institute for Space Studies, New York, NY 10025, USA
Alison Chase
School of Marine Sciences, University of Maine, Orono, ME 04469, USA
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The strong variability in the chemistry of atmospheric particulate matter affects the amount of water aerosols absorb and their effect on climate. We present a remote sensing method to determine the amount of water in particulate matter. Its application to airborne instruments indicates that the observed aerosols have rather low water contents and low fractions of soluble particles. Future satellites will be able to yield global aerosol water uptake data.
Santiago Gassó and Kirk D. Knobelspiesse
Atmos. Chem. Phys., 22, 13581–13605, https://doi.org/10.5194/acp-22-13581-2022, https://doi.org/10.5194/acp-22-13581-2022, 2022
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Atmospheric particles interact with light resulting in observable optical polarization. Thus, we can learn about their composition from space. New satellite sensor technology measures full polarization of reflected sunlight. This paper considers circular polarization, an overlooked category of polarization with distinctive features that could bring new insights. We review existing literature and make novel computations to consider this previously underappreciated category of polarization.
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
Short summary
Short summary
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.
Dongwei Fu, Larry Di Girolamo, Robert M. Rauber, Greg M. McFarquhar, Stephen W. Nesbitt, Jesse Loveridge, Yulan Hong, Bastiaan van Diedenhoven, Brian Cairns, Mikhail D. Alexandrov, Paul Lawson, Sarah Woods, Simone Tanelli, Sebastian Schmidt, Chris Hostetler, and Amy Jo Scarino
Atmos. Chem. Phys., 22, 8259–8285, https://doi.org/10.5194/acp-22-8259-2022, https://doi.org/10.5194/acp-22-8259-2022, 2022
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Satellite-retrieved cloud microphysics are widely used in climate research because of their central role in water and energy cycles. Here, we provide the first detailed investigation of retrieved cloud drop sizes from in situ and various satellite and airborne remote sensing techniques applied to real cumulus cloud fields. We conclude that the most widely used passive remote sensing method employed in climate research produces high biases of 6–8 µm (60 %–80 %) caused by 3-D radiative effects.
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
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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
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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
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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.
Kirk Knobelspiesse and Sreeja Nag
Atmos. Meas. Tech., 11, 3935–3954, https://doi.org/10.5194/amt-11-3935-2018, https://doi.org/10.5194/amt-11-3935-2018, 2018
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We test if small satellites flying in formation can be used for multi-angle aerosol remote sensing. So far, this has only been done with multiple views on one satellite. Single-view angle satellites flying in formation are a technically feasible alternative, although with different geometries. Using Bayesian information content analysis, we find such satellites equally capable. For aerosol remote sensing, the number of viewing angles is the most important.
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
Characterization of stratospheric particle size distribution uncertainties using SAGE II and SAGE III/ISS extinction spectra
Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager
Aerosol and cloud data processing and optical property retrieval algorithms for the spaceborne ACDL/DQ-1
Derivation of depolarization ratios of aerosol fluorescence and water vapor Raman backscatters from lidar measurements
Long-term aerosol particle depolarization ratio measurements with HALO Photonics Doppler lidar
HETEAC-Flex: an optimal estimation method for aerosol typing based on lidar-derived intensive optical properties
MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm
Multi-section reference value for the analysis of horizontally scanning aerosol lidar observations
Retrieval of aerosol optical depth over the Arctic cryosphere during spring and summer using satellite observations
Innovative aerosol hygroscopic growth study from Mie-Raman-Fluorescence lidar and Microwave Radiometer synergy
Quantifying particulate matter optical properties and flow rate in industrial stack plumes from the PRISMA hyperspectral imager
A near-global multiyear climate data record of the fine-mode and coarse-mode components of atmospheric pure-dust
Aerosol retrieval over snow using the RemoTAP algorithm
Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign
Simultaneous retrieval of aerosol and ocean properties from PACE HARP2 with uncertainty assessment using cascading neural network radiative transfer models
Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–20 Australian bushfires
An iterative algorithm to simultaneously retrieve aerosol extinction and effective radius profiles using the CALIOP lidar
Linear polarization signatures of atmospheric dust with the SolPol direct-sun polarimeter
Retrieval of aerosol properties from zenith sky radiance measurements
Cloud Detection from Multi-Angular Polarimetric Satellite Measurements using a Neural Network Ensemble Approach
An ensemble method for improving the estimation of planetary boundary layer height from radiosonde data
Detection and analysis of Lhù'ààn Mân' (Kluane Lake) dust plumes using passive and active ground-based remote sensing supported by physical surface measurements
Cloud top heights and aerosol layer properties from EarthCARE lidar observations: the A-CTH and A-ALD products
Influence of electromagnetic interference on the evaluation of lidar-derived aerosol properties from Ny-Ålesund, Svalbard
Global 3-D distribution of aerosol composition by synergistic use of CALIOP and MODIS observations
Multi-wavelength dataset of aerosol extinction profiles retrieved from GOMOS stellar occultation measurements
Retrieving UV-VIS Spectral Single-scattering Albedo of Absorbing Aerosols above Clouds from Synergy of ORACLES Airborne and A-train Sensors
Stratospheric aerosol characteristics from SCIAMACHY limb observations: 2-parameter retrieval
Evaluation of Calibration Performance of a Low-cost Particulate Matter Sensor Using Colocated and Distant NO2
Aerosol optical depth retrieval from the EarthCARE Multi-Spectral Imager: the M-AOT product
Evaluating the effects of columnar NO2 on the accuracy of aerosol optical properties retrievals
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
HETEAC – the Hybrid End-To-End Aerosol Classification model for EarthCARE
DeLiAn – a growing collection of depolarization ratio, lidar ratio and Ångström exponent for different aerosol types and mixtures from ground-based lidar observations
Deep-Pathfinder: A boundary layer height detection algorithm based on image segmentation
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
Ground-based remote sensing of aerosol properties using high-resolution infrared emission and lidar observations in the High Arctic
The CALIPSO version 4.5 stratospheric aerosol subtyping algorithm
Volcanic cloud detection using Sentinel-3 satellite data by means of neural networks: the Raikoke 2019 eruption test case
The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water
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
Travis N. Knepp, Mahesh Kovilakam, Larry Thomason, and Stephen J. Miller
Atmos. Meas. Tech., 17, 2025–2054, https://doi.org/10.5194/amt-17-2025-2024, https://doi.org/10.5194/amt-17-2025-2024, 2024
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An algorithm is presented to derive a new SAGE III/ISS (Stratospheric Aerosol and Gas Experiment III on the International Space Station) Level-2 product: the size distribution of stratospheric particles. This is a significant improvement over previous techniques in that we now provide uncertainty estimates for all inferred parameters. We also evaluated the stability of this method in retrieving bimodal distribution parameters. We present a special application to the 2022 eruption of Hunga Tonga.
Mijin Kim, Robert C. Levy, Lorraine A. Remer, Shana Mattoo, and Pawan Gupta
Atmos. Meas. Tech., 17, 1913–1939, https://doi.org/10.5194/amt-17-1913-2024, https://doi.org/10.5194/amt-17-1913-2024, 2024
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The study focused on evaluating and modifying the surface reflectance parameterization (SRP) of the Dark Target (DT) algorithm for geostationary observation. When using the DT SRP with the ABIs sensor on GOES-R, artificial diurnal signatures were present in AOD retrieval. To overcome this issue, a new SRP was developed, incorporating solar zenith angle and land cover type. The revised SRP resulted in improved AOD retrieval, demonstrating reduced bias around local noon.
Guangyao Dai, Songhua Wu, Wenrui Long, Jiqiao Liu, Yuan Xie, Kangwen Sun, Fanqian Meng, Xiaoquan Song, Zhongwei Huang, and Weibiao Chen
Atmos. Meas. Tech., 17, 1879–1890, https://doi.org/10.5194/amt-17-1879-2024, https://doi.org/10.5194/amt-17-1879-2024, 2024
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An overview is given of the main algorithms applied to derive the aerosol and cloud optical property product of the Aerosol and Carbon Detection Lidar (ACDL), which is capable of globally profiling aerosol and cloud optical properties with high accuracy. The paper demonstrates the observational capabilities of ACDL for aerosol and cloud vertical structure and global distribution through two optical property product measurement cases and global aerosol optical depth profile observations.
Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, William Boissiere, Mikhail Korenskiy, Nikita Kasianik, Sergey Khaykyn, and Robin Miri
Atmos. Meas. Tech., 17, 1023–1036, https://doi.org/10.5194/amt-17-1023-2024, https://doi.org/10.5194/amt-17-1023-2024, 2024
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Measurements of transported smoke layers were performed with a lidar in Lille and a five-channel fluorescence lidar in Moscow. Results show the peak of fluorescence in the boundary layer is at 438 nm, while in the smoke layer it shifts to longer wavelengths. The fluorescence depolarization is 45 % to 55 %. The depolarization ratio of the water vapor channel is low (2 ± 0.5 %) in the absence of fluorescence and can be used to evaluate the contribution of fluorescence to water vapor signal.
Viet Le, Hannah Lobo, Ewan J. O'Connor, and Ville Vakkari
Atmos. Meas. Tech., 17, 921–941, https://doi.org/10.5194/amt-17-921-2024, https://doi.org/10.5194/amt-17-921-2024, 2024
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This study offers a long-term overview of aerosol particle depolarization ratio at the wavelength of 1565 nm obtained from vertical profiling measurements by Halo Doppler lidars during 4 years at four different locations across Finland. Our observations support the long-term usage of Halo Doppler lidar depolarization ratio such as the detection of aerosols that may pose a safety risk for aviation. Long-range Saharan dust transport and pollen transport are also showcased here.
Athena Augusta Floutsi, Holger Baars, and Ulla Wandinger
Atmos. Meas. Tech., 17, 693–714, https://doi.org/10.5194/amt-17-693-2024, https://doi.org/10.5194/amt-17-693-2024, 2024
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We introduce an aerosol-typing scheme (HETEAC-Flex) based on lidar-derived intensive optical properties and applicable to ground-based and spaceborne lidars. HETEAC-Flex utilizes the optimal estimation method and enables the identification of up to four different aerosol components, as well as the determination of their contribution to the aerosol mixture in terms of relative volume. The aerosol components represent common aerosol types such as dust, sea salt, smoke and pollution.
James A. Limbacher, Ralph A. Kahn, Mariel D. Friberg, Jaehwa Lee, Tyler Summers, and Hai Zhang
Atmos. Meas. Tech., 17, 471–498, https://doi.org/10.5194/amt-17-471-2024, https://doi.org/10.5194/amt-17-471-2024, 2024
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We present the new Multi-Angle Geostationary Aerosol Retrieval Algorithm (MAGARA) that fuses observations from GOES-16 and GOES-17 to retrieve information about aerosol loading (at 10–15 min cadence) and aerosol particle properties (daily), all at pixel-level resolution. We present MAGARA results for three case studies: the 2018 California Camp Fire, the 2019 Williams Flats Fire, and the 2019 Kincade Fire. We also compare MAGARA aerosol loading and particle properties with AERONET.
Juseon Shin, Gahyeong Kim, Dukhyeon Kim, Matthias Tesche, Gahyeon Park, and Youngmin Noh
Atmos. Meas. Tech., 17, 397–406, https://doi.org/10.5194/amt-17-397-2024, https://doi.org/10.5194/amt-17-397-2024, 2024
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We introduce the multi-section method, a novel approach for stable extinction coefficient retrievals in horizontally scanning aerosol lidar measurements, in this study. Our method effectively removes signal–noise-induced irregular peaks and derives a reference extinction coefficient, αref, from multiple scans, resulting in a strong correlation (>0.74) with PM2.5 mass concentrations. Case studies demonstrate its utility in retrieving spatio-temporal aerosol distributions and PM2.5 concentrations.
Basudev Swain, Marco Vountas, Adrien Deroubaix, Luca Lelli, Yanick Ziegler, Soheila Jafariserajehlou, Sachin S. Gunthe, Andreas Herber, Christoph Ritter, Hartmut Bösch, and John P. Burrows
Atmos. Meas. Tech., 17, 359–375, https://doi.org/10.5194/amt-17-359-2024, https://doi.org/10.5194/amt-17-359-2024, 2024
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Aerosols are suspensions of particles dispersed in the air. In this study, we use a novel retrieval of satellite data to investigate an optical property of aerosols, the aerosol optical depth, in the high Arctic to assess their direct and indirect roles in climate change. This study demonstrates that the presented approach shows good quality and very promising potential.
Robin Miri, Olivier Pujol, Qiaoyun Hu, Philippe Goloub, Igor Veselovskii, Thierry Podvin, and Fabrice Ducos
EGUsphere, https://doi.org/10.5194/egusphere-2024-84, https://doi.org/10.5194/egusphere-2024-84, 2024
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This paper focuses on the use of fluorescence to study aerosols with lidar. An innovative method for automatic aerosol classification, along with an investigation into aerosol hygroscopic growth fluorescence are presented. The paper presents case studies to showcase the effectiveness and potential of the proposed approach. These advancements will contribute to better understand the interactions between aerosols and water, with future work expected to be dedicated to aerosol-cloud interaction.
Gabriel Calassou, Pierre-Yves Foucher, and Jean-François Léon
Atmos. Meas. Tech., 17, 57–71, https://doi.org/10.5194/amt-17-57-2024, https://doi.org/10.5194/amt-17-57-2024, 2024
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We propose analyzing the aerosol composition of plumes emitted by different industrial stacks using PRISMA satellite hyperspectral observations. Three industrial sites have been observed: a coal-fired power plant in South Africa, a steel plant in China, and gas flaring at an oil extraction site in Algeria. Aerosol optical thickness and particle radius are retrieved within the plumes. The mass flow rate of particulate matter is estimated in the plume using the integrated mass enhancement method.
Emmanouil Proestakis, Antonis Gkikas, Thanasis Georgiou, Anna Kampouri, Eleni Drakaki, Claire Ryder, Franco Marenco, Eleni Marinou, and Vassilis Amiridis
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-262, https://doi.org/10.5194/amt-2023-262, 2024
Revised manuscript accepted for AMT
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A new four-dimensional, multiyear, and near-global climate data record of the fine-mode (submicrometer in terms of diameter) and coarse-mode (supermicrometer in terms of diameter) components of atmospheric pure-dust, is presented. The dataset is considered unique with respect to a wide range of potential applications, including climatological, time-series, trend analysis over extensive geographical domains and temporal periods, validation of atmospheric dust models and datasets, and air quality.
Zihan Zhang, Guangliang Fu, and Otto Hasekamp
Atmos. Meas. Tech., 16, 6051–6063, https://doi.org/10.5194/amt-16-6051-2023, https://doi.org/10.5194/amt-16-6051-2023, 2023
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In order to conduct accurate aerosol retrieval over snow, the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) algorithm is extended with a bi-directional reflection distribution function for snow surfaces. The experiments with both synthetic and real data show that the extended RemoTAP maintains capability for snow-free pixels and has obvious advantages in accuracy and the fraction of successful retrievals for retrieval over snow, especially over surfaces with snow cover > 75 %.
Alexandra Tsekeri, Anna Gialitaki, Marco Di Paolantonio, Davide Dionisi, Gian Luigi Liberti, Alnilam Fernandes, Artur Szkop, Aleksander Pietruczuk, Daniel Pérez-Ramírez, Maria J. Granados Muñoz, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Diego Bermejo Pantaleón, Juan Antonio Bravo-Aranda, Anna Kampouri, Eleni Marinou, Vassilis Amiridis, Michael Sicard, Adolfo Comerón, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Salvatore Romano, Maria Rita Perrone, Xiaoxia Shang, Mika Komppula, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Diofantos Hadjimitsis, Francisco Navas-Guzmán, Alexander Haefele, Dominika Szczepanik, Artur Tomczak, Iwona S. Stachlewska, Livio Belegante, Doina Nicolae, Kalliopi Artemis Voudouri, Dimitris Balis, Athena A. Floutsi, Holger Baars, Linda Miladi, Nicolas Pascal, Oleg Dubovik, and Anton Lopatin
Atmos. Meas. Tech., 16, 6025–6050, https://doi.org/10.5194/amt-16-6025-2023, https://doi.org/10.5194/amt-16-6025-2023, 2023
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EARLINET/ACTRIS organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. The work presented herein focuses on deriving a common methodology for applying a synergistic retrieval that utilizes the network's ground-based passive and active remote sensing measurements and deriving the aerosols from anthropogenic activities over Europe.
Meng Gao, Bryan A. Franz, Peng-Wang Zhai, Kirk Knobelspiesse, Andrew M. Sayer, Xiaoguang Xu, J. Vanderlei Martins, Brian Cairns, Patricia Castellanos, Guangliang Fu, Neranga Hannadige, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Frederick Patt, Anin Puthukkudy, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 5863–5881, https://doi.org/10.5194/amt-16-5863-2023, https://doi.org/10.5194/amt-16-5863-2023, 2023
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This study evaluated the retrievability and uncertainty of aerosol and ocean properties from PACE's HARP2 instrument using enhanced neural network models with the FastMAPOL algorithm. A cascading retrieval method is developed to improve retrieval performance. A global set of simulated HARP2 data is generated and used for uncertainty evaluations. The performance assessment demonstrates that the FastMAPOL algorithm is a viable approach for operational application to HARP2 data after PACE launch.
Daniel Jamie Victor Robbins, Caroline Poulsen, Steven Siems, Simon Proud, Andrew Prata, Roy Grainger, and Adam Povey
EGUsphere, https://doi.org/10.5194/egusphere-2023-2179, https://doi.org/10.5194/egusphere-2023-2179, 2023
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Extreme wildfire events, which are becoming more common with climate change, produce smoke plumes which are not captured by current operational satellite products due to their very high optical thicknesses. We have developed a novel aerosol retrieval for the the Advanced Himawari Imager to study these plumes in full, finding very high values of optical thickness not seen in other operational satellite products and suggesting these plumes have been missed in previous studies.
Liang Chang, Jing Li, Jingjing Ren, Changrui Xiong, and Lu Zhang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-223, https://doi.org/10.5194/amt-2023-223, 2023
Revised manuscript accepted for AMT
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We described a modified lidar inversion algorithm to retrieve aerosol extinction and size distribution simultaneously from two wavelengths elastic lidar measurements. Its major advantage is that the lidar ratio of each layer is determined iteratively by the lidar ratio-AE look-up table. The algorithm was applied to the Raman lidar and CALIOP measurements. The retrieved results by our method are in good agreement with by Raman method.
Vasiliki Daskalopoulou, Panagiotis I. Raptis, Alexandra Tsekeri, Vassilis Amiridis, Stelios Kazadzis, Zbigniew Ulanowski, Vassilis Charmandaris, Konstantinos Tassis, and William Martin
Atmos. Meas. Tech., 16, 4529–4550, https://doi.org/10.5194/amt-16-4529-2023, https://doi.org/10.5194/amt-16-4529-2023, 2023
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Atmospheric dust particles may present a preferential alignment due to their shape on long range transport. Since dust is abundant and plays a key role to global climate, the elusive observation of orientation will be a game changer to existing measurement techniques and the representation of particles in climate models. We utilize a specifically designed instrument, SolPol, and target the Sun from the ground for large polarization values under dusty conditions, a clear sign of orientation.
Sara Herrero-Anta, Roberto Román, David Mateos, Ramiro González, Juan Carlos Antuña-Sánchez, Marcos Herreras-Giralda, Antonio Fernando Almansa, Daniel González-Fernández, Celia Herrero del Barrio, Carlos Toledano, Victoria E. Cachorro, and Ángel M. de Frutos
Atmos. Meas. Tech., 16, 4423–4443, https://doi.org/10.5194/amt-16-4423-2023, https://doi.org/10.5194/amt-16-4423-2023, 2023
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This paper shows the potential of a simple radiometer like the ZEN-R52 as a possible alternative for aerosol property retrieval in remote areas. A calibration method based on radiative transfer simulations together with an inversion methodology using the GRASP code is proposed here. The results demonstrate that this methodology is useful for the retrieval of aerosol extensive properties like aerosol optical depth (AOD) and aerosol volume concentration for total, fine and coarse modes.
Zihao Yuan, Guangliang Fu, Bastiaan van Diedenhoven, Hai Xiang Lin, Jan Willem Erisman, and Otto P. Hasekamp
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-145, https://doi.org/10.5194/amt-2023-145, 2023
Revised manuscript accepted for AMT
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Currently, aerosol properties from spaceborne Multi-Angle Polarimeter (MAP) instruments can only be retrieved in cloud-free areas, or for areas where an aerosol layer is located above a cloud. Therefore, it is important to be able to identify cloud-free pixels for which an aerosol retrieval algorithm can provide meaningful output. The developed Neural Network cloud screening demonstrates that cloud masking for MAP aerosol retrieval can be based on the MAP measurements themselves.
Xi Chen, Ting Yang, Zifa Wang, Futing Wang, and Haibo Wang
Atmos. Meas. Tech., 16, 4289–4302, https://doi.org/10.5194/amt-16-4289-2023, https://doi.org/10.5194/amt-16-4289-2023, 2023
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Uncertainties remain great in the planetary boundary layer height (PBLH) determination from radiosonde, especially during the transition period of different PBL regimes. We combine seven existing methods along with statistical modification on gradient-based methods. We find that the ensemble method can eliminate the overestimation of PBLH and reduce the inconsistency between individual methods. The ensemble method improves the effectiveness of PBLH determination to 62.6 %.
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., 16, 4115–4135, https://doi.org/10.5194/amt-16-4115-2023, https://doi.org/10.5194/amt-16-4115-2023, 2023
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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 insights into how satellite RS could be used to analyze Arctic-wide dust transport. This helps modelers 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.
Ulla Wandinger, Moritz Haarig, Holger Baars, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 4031–4052, https://doi.org/10.5194/amt-16-4031-2023, https://doi.org/10.5194/amt-16-4031-2023, 2023
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We introduce the algorithms that have been developed to derive cloud top height and aerosol layer products from observations with the Atmospheric Lidar (ATLID) onboard the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE). The products provide information on the uppermost cloud and geometrical and optical properties of aerosol layers in an atmospheric column. They can be used individually but also serve as input for algorithms that combine observations with EarthCARE’s lidar and imager.
Tim Poguntke and Christoph Ritter
Atmos. Meas. Tech., 16, 4009–4014, https://doi.org/10.5194/amt-16-4009-2023, https://doi.org/10.5194/amt-16-4009-2023, 2023
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In this work we analyze the impact of electromagnetic interference on an aerosol lidar. We found that aging transient recorders may produce a noise with fixed frequency that can be removed a posteriori.
Rei Kudo, Akiko Higurashi, Eiji Oikawa, Masahiro Fujikawa, Hiroshi Ishimoto, and Tomoaki Nishizawa
Atmos. Meas. Tech., 16, 3835–3863, https://doi.org/10.5194/amt-16-3835-2023, https://doi.org/10.5194/amt-16-3835-2023, 2023
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A synergistic retrieval method of aerosol components (water-soluble, light-absorbing, dust, and sea salt particles) from CALIOP and MODIS observations was developed. The total global 3-D distributions and those for each component showed good consistency with the CALIOP and MODIS official products and previous studies. The shortwave direct radiative effects of each component at the top and bottom of the atmosphere and for the heating rate were also consistent with previous studies.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Didier Fussen, Christine Bingen, Filip Vanhellemont, Nina Mateshvili, Alexei Rozanov, and Christine Pohl
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-179, https://doi.org/10.5194/amt-2023-179, 2023
Revised manuscript accepted for AMT
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We have developed the new multi-wavelength dataset of aerosol extinction profiles, which are retrieved from the averaged transmittance spectra by the Global Ozone Monitoring by Occultation of Stars instrument on board Envisat. The retrieved aerosol extinction profiles are provided in the altitude range 10–40 km at 400, 440, 452, 470, 500, 525, 550, 672 and 750 nm, for the period 2002–2012. FMI-GOMOSaero aerosol profiles have improved quality; they are in good agreement with other datasets.
Hiren Jethva, Omar Torres, Richard Ferrare, Sharon Burton, Anthony Cook, David Harper, Chris Hostetler, Jens Redemann, Vinay Kayetha, Samuel LeBlanc, Kristina Pistone, Logan Mitchell, and Connor Flynn
EGUsphere, https://doi.org/10.5194/egusphere-2023-1717, https://doi.org/10.5194/egusphere-2023-1717, 2023
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We introduce a novel synergy algorithm applied to ORALCES airborne measurements of above-cloud aerosol optical depth and UV-VIS satellite observations from OMI and MODIS to retrieve spectral aerosol single-scattering albedo of lofted layers of carbonaceous smoke aerosols over clouds. The development of the proposed aerosol-cloud algorithm implies a possible synergy of CALIOP lidar and OMI-MODIS passive sensors to deduce a global product of ACAOD and SSA.
Christine Pohl, Felix Wrana, Alexei Rozanov, Terry Deshler, Elizaveta Malinina, Christian von Savigny, Landon A. Rieger, Adam E. Bourassa, and John P. Burrows
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-156, https://doi.org/10.5194/amt-2023-156, 2023
Revised manuscript accepted for AMT
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The knowledge of stratospheric aerosol characteristics is important to understand the chemical and climate aerosol feedbacks. Two particle size distribution parameters, the aerosol extinction coefficient, and the effective radius are retrieved from SCIAMACHY limb observations. The aerosol characteristics show good agreement with independent data sets from balloon-borne and satellite observations. This data set expands the limited knowledge of stratospheric aerosol characteristics.
Kabseok Ko, Seokheon Cho, and Ramesh R. Rao
EGUsphere, https://doi.org/10.5194/egusphere-2023-1344, https://doi.org/10.5194/egusphere-2023-1344, 2023
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We studied the effect of NO2, temperature, and humidity on calibration performances of low-cost particulate matter sensors, particularly PurpleAir PA-II. We showed that NO2 data obtained from reliable instruments colocated with sensors could improve the calibration of PM2.5. Due to the impractical of colocating reliable NO2 instruments with sensors, we propose using distant NO2 data for calibration. We showed that distant NO2 data can improve calibration performance when highly correlated.
Nicole Docter, Rene Preusker, Florian Filipitsch, Lena Kritten, Franziska Schmidt, and Jürgen Fischer
Atmos. Meas. Tech., 16, 3437–3457, https://doi.org/10.5194/amt-16-3437-2023, https://doi.org/10.5194/amt-16-3437-2023, 2023
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We describe the stand-alone retrieval algorithm used to derive aerosol properties relying on measurements of the Multi-Spectral Imager (MSI) aboard the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite. This aerosol data product will be available as M-AOT after the launch of EarthCARE. Additionally, we applied the algorithm to simulated EarthCARE MSI and Moderate Resolution Imaging Spectroradiometer (MODIS) data for prelaunch algorithm verification.
Theano Drosoglou, Ioannis-Panagiotis Raptis, Massimo Valeri, Stefano Casadio, Francesca Barnaba, Marcos Herreras-Giralda, Anton Lopatin, Oleg Dubovik, Gabriele Brizzi, Fabrizio Niro, Monica Campanelli, and Stelios Kazadzis
Atmos. Meas. Tech., 16, 2989–3014, https://doi.org/10.5194/amt-16-2989-2023, https://doi.org/10.5194/amt-16-2989-2023, 2023
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Aerosol optical properties derived from sun photometers depend on the optical depth of trace gases absorbing solar radiation at specific spectral ranges. Various networks use satellite-based climatologies to account for this or neglect their effect. In this work, we evaluate the effect of NO2 absorption in aerosol retrievals from AERONET and SKYNET over two stations in Rome, Italy, with relatively high NO2 spatiotemporal variations, using NO2 data from the Pandora network and the TROPOMI sensor.
Adolfo Comerón, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Michaël Sicard, Federico Dios, Cristina Gil-Díaz, Daniel Camilo Fortunato dos Santos Oliveira, and Francesc Rocadenbosch
Atmos. Meas. Tech., 16, 3015–3025, https://doi.org/10.5194/amt-16-3015-2023, https://doi.org/10.5194/amt-16-3015-2023, 2023
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We derive an explicit (i.e., non-iterative) formula for the retrieval of the overlap function in an aerosol lidar with both elastic and Raman N2 and/or O2 channels used for independent measurements of aerosol backscatter and extinction coefficients. The formula requires only the measured, range-corrected elastic and the corresponding Raman signals, plus an assumed lidar ratio. We assess the influence of the lidar ratio error in the overlap function retrieval and present retrieval examples.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
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The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Mahesh Kovilakam, Larry Thomason, and Travis Knepp
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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The paper describes SAGE III/ISS aerosol/cloud categorization and its implications on Global Space-based Stratospheric Aerosol Climatology (GloSSAC). The presence of data from the SAGE type of multi-wavelength measurements is important in GloSSAC. The new aerosol/cloud categorization method described in this paper will help retain more measurements, particularly in the lower stratosphere during and following a volcanic event and other processes.
Minseok Kim, Jhoon Kim, Hyunkwang Lim, Seoyoung Lee, Yeseul Cho, Huidong Yeo, and Sang-Woo Kim
Atmos. Meas. Tech., 16, 2673–2690, https://doi.org/10.5194/amt-16-2673-2023, https://doi.org/10.5194/amt-16-2673-2023, 2023
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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.
Jasper S. Wijnands, Arnoud Apituley, Diego Alves Gouveia, and Jan Willem Noteboom
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-80, https://doi.org/10.5194/amt-2023-80, 2023
Revised manuscript accepted for AMT
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The mixing of air in the lower atmosphere influences the concentration of air pollutants and greenhouse gases. Our study developed a new method, Deep-Pathfinder, to estimate mixing layer height. Deep-Pathfinder analyses imagery with aerosol observations using artificial intelligence techniques for computer vision. Compared to existing methods, it improves temporal consistency, resolution and can be used in real-time, which is valuable for aviation, weather forecasting and air quality monitoring.
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.
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