Articles | Volume 16, issue 8
https://doi.org/10.5194/amt-16-2067-2023
© Author(s) 2023. 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-16-2067-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Apr 2023
Research article |
| 19 Apr 2023
The impact and estimation of uncertainty correlation for multi-angle polarimetric remote sensing of aerosols and ocean color
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Science Systems and Applications, Inc., Greenbelt, MD 20706, USA
Kirk Knobelspiesse
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Bryan A. Franz
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Peng-Wang Zhai
Physics Department, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
Brian Cairns
NASA Goddard Institute for Space Studies, New York, NY 10025, USA
Xiaoguang Xu
Physics Department, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
J. Vanderlei Martins
Physics Department, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
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We evaluated the impact of three ocean optical models with different numbers of free parameters on the performance of an aerosol and ocean color remote sensing algorithm using the multi-angle polarimeter (MAP) measurements. It was demonstrated that the 3 and 7-parameter bio-optical models can be used to accurately represent both open and coastal waters, whereas the 1-parameter model does have smaller retrieval uncertainty over open waters.
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In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
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Santiago Gassó and Kirk D. Knobelspiesse
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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
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In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
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
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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
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
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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
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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.
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.
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.
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.
Yi Wang, Jun Wang, Xiaoguang Xu, Daven K. Henze, Zhen Qu, and Kai Yang
Atmos. Chem. Phys., 20, 6631–6650, https://doi.org/10.5194/acp-20-6631-2020, https://doi.org/10.5194/acp-20-6631-2020, 2020
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The use of OMPS satellite observations to inverse-model SO2 and NO2 emissions is presented through the GEOS-Chem adjoint modeling framework. The work is illustrated over China. The robustness of the results is studied through separate and joint inversions of SO2 and NO2 and the consideration of NH3 uncertainty. Independent validation is performed with OMI SO2 and NO2 data. It is shown that simultaneous inversion of NO2 and SO2 from OMPS provides an effective way to rapidly update emissions.
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.
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.
Steven D. Miller, Louie D. Grasso, Qijing Bian, Sonia M. Kreidenweis, Jack F. Dostalek, Jeremy E. Solbrig, Jennifer Bukowski, Susan C. van den Heever, Yi Wang, Xiaoguang Xu, Jun Wang, Annette L. Walker, Ting-Chi Wu, Milija Zupanski, Christine Chiu, and Jeffrey S. Reid
Atmos. Meas. Tech., 12, 5101–5118, https://doi.org/10.5194/amt-12-5101-2019, https://doi.org/10.5194/amt-12-5101-2019, 2019
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Satellite–based detection of lofted mineral via infrared–window channels, well established in the literature, faces significant challenges in the presence of atmospheric moisture. Here, we consider a case featuring the juxtaposition of two dust plumes embedded within dry and moist air masses. The case is considered from the vantage points of numerical modeling, multi–sensor observations, and radiative transfer theory arriving at a new method for mitigating the water vapor masking effect.
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.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Yongxiang Hu, Kirk Knobelspiesse, P. Jeremy Werdell, Amir Ibrahim, Brian Cairns, and Alison Chase
Atmos. Meas. Tech., 12, 3921–3941, https://doi.org/10.5194/amt-12-3921-2019, https://doi.org/10.5194/amt-12-3921-2019, 2019
Xiaoguang Xu, Jun Wang, Yi Wang, Jing Zeng, Omar Torres, Jeffrey S. Reid, Steven D. Miller, J. Vanderlei Martins, and Lorraine A. Remer
Atmos. Meas. Tech., 12, 3269–3288, https://doi.org/10.5194/amt-12-3269-2019, https://doi.org/10.5194/amt-12-3269-2019, 2019
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Detecting aerosol layer height from space is challenging. The traditional method relies on active sensors such as lidar that provide the detailed vertical structure of the aerosol profile but is costly with limited spatial coverage (more than 1 year is needed for global coverage). Here we developed a passive remote sensing technique that uses backscattered sunlight to retrieve smoke aerosol layer height over both water and vegetated surfaces from a sensor 1.5 million kilometers from the Earth.
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.
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.
Shouguo Ding, Jun Wang, and Xiaoguang Xu
Atmos. Meas. Tech., 9, 2077–2092, https://doi.org/10.5194/amt-9-2077-2016, https://doi.org/10.5194/amt-9-2077-2016, 2016
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Knowledge on the vertical distribution of aerosols in the atmospheric is important for studying aerosol impacts on air quality and climate change. The polarization measurements in O2 A and B bands is shown here theoretically to have rich information for characterizing aerosol vertical profile over land. This paper presents a passive remote sensing technique supplementary to the existing technique to retrieve aerosol vertical distribution over land from space.
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.
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
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
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
A. Rocha-Lima, J. V. Martins, L. A. Remer, N. A. Krotkov, M. H. Tabacniks, Y. Ben-Ami, and P. Artaxo
Atmos. Chem. Phys., 14, 10649–10661, https://doi.org/10.5194/acp-14-10649-2014, https://doi.org/10.5194/acp-14-10649-2014, 2014
B. S. Meland, X. Xu, D. K. Henze, and J. Wang
Atmos. Meas. Tech., 6, 3441–3457, https://doi.org/10.5194/amt-6-3441-2013, https://doi.org/10.5194/amt-6-3441-2013, 2013
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
Linear polarization signatures of atmospheric dust with the SolPol direct-sun polarimeter
Retrieval of aerosol properties from zenith sky radiance measurements
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
Simultaneous retrieval of aerosol and ocean properties from PACE HARP2 with uncertainty assessment using cascading neural network radiative transfer models
Global 3-D distribution of aerosol composition by synergistic use of CALIOP and MODIS observations
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
Combined sun-photometer/lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 Campaign
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
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
Long-term aerosol particle depolarization ratio measurements with Halo Doppler lidar
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
Effective uncertainty quantification for multi-angle polarimetric aerosol remote sensing over ocean
Employing relaxed smoothness constraints on imaginary part of refractive index in AERONET aerosol retrieval algorithm
Observation of bioaerosol transport using wideband integrated bioaerosol sensor and coherent Doppler lidar
Retrieval of UVB aerosol extinction profiles from the ground-based Langley Mobile Ozone Lidar (LMOL) system
Enhancing MAX-DOAS atmospheric state retrievals by multispectral polarimetry – studies using synthetic data
Assessing the benefits of Imaging Infrared Radiometer observations for the CALIOP version 4 cloud and aerosol discrimination algorithm
A semi-automated procedure for the emitter–receiver geometry characterization of motor-controlled lidars
Aerosol optical characteristics in the urban area of Rome, Italy, and their impact on the UV index
Aerosol models from the AERONET database: application to surface reflectance validation
Continuous mapping of fine particulate matter (PM2.5) air quality in East Asia at daily 6 × 6 km2 resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data
Deep-learning-based post-process correction of the aerosol parameters in the high-resolution Sentinel-3 Level-2 Synergy product
Retrieval of UV–visible aerosol absorption using AERONET and OMI–MODIS synergy: spatial and temporal variability across major aerosol environments
Estimating cloud condensation nuclei concentrations from CALIPSO lidar measurements
Ash particle refractive index model for simulating the brightness temperature spectrum of volcanic ash clouds from satellite infrared sounder measurements
Retrieval of aerosol properties using relative radiance measurements from an all-sky camera
Optimization of Aeolus' aerosol optical properties by maximum-likelihood estimation
A Bayesian parametric approach to the retrieval of the atmospheric number size distribution from lidar data
Biomass burning aerosol heating rates from the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) 2016 and 2017 experiments
Aeolus L2A aerosol optical properties product: standard correct algorithm and Mie correct algorithm
Methodology to obtain highly resolved SO2 vertical profiles for representation of volcanic emissions in climate models
Inferring the absorption properties of organic aerosol in Siberian biomass burning plumes from remote optical observations
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.
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.
Meng Gao, Bryan A. Franz, Peng-Wang Zhai, Kirk Knobelspiesse, Andrew Sayer, Xiaoguang Xu, Vanderlei Martins, Brian Cairns, Patricia Castellanos, Guangliang Fu, Neranga Hannadige, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Frederick Patt, Anin Puthukkudy, and P. Jeremy Werdell
EGUsphere, https://doi.org/10.5194/egusphere-2023-1843, https://doi.org/10.5194/egusphere-2023-1843, 2023
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This study evaluates the retrievability and uncertainty on aerosol and ocean parameter from PACE's HARP2 instrument using enhanced neural network models within the FastMAPOL algorithm. The approach streamlined data processing and utilized a cascading retrieval method for optimization. Testing with synthetic HARP2 data revealed reliable retrieval of aerosol properties, though with some uncertainties in other areas. Overall, the algorithm is effective and viable for operational data analysis.
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.
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.
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 Stachlewska, Livio Belegante, Doina Nicolae, Kalliopi Artemis Voudouri, Dimitris Balis, Athina A. Floutsi, Holger Baars, Linda Miladi, Nicolas Pascal, Oleg Dubovik, and Anton Lopatin
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-76, https://doi.org/10.5194/amt-2023-76, 2023
Revised manuscript accepted for AMT
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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 derive the aerosols from antrhopogenic activities over Europe.
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.
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.
Viet Le, Hannah Lobo, Ewan J. O'Connor, and Ville Vakkari
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-37, https://doi.org/10.5194/amt-2023-37, 2023
Revised manuscript accepted for AMT
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This study offers a long-term overview of aerosol particle depolarization ratio at a wavelength of 1565 nm obtained from vertical profiling measurements by Halo Doppler lidars during four years at four different locations across Finland. Our observations support the long-term usage of Halo Doppler lidar depolarization ratio including detection of aerosols that may pose a safety risk for aviation. Long-range Saharan dust transport and pollen transport are also showcased here.
Jason L. Tackett, Jayanta Kar, Mark A. Vaughan, Brian J. Getzewich, Man-Hae Kim, Jean-Paul Vernier, Ali H. Omar, Brian E. Magill, Michael C. Pitts, and David M. Winker
Atmos. Meas. Tech., 16, 745–768, https://doi.org/10.5194/amt-16-745-2023, https://doi.org/10.5194/amt-16-745-2023, 2023
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The accurate identification of aerosol types in the stratosphere is important to characterize their impacts on the Earth climate system. The space-borne lidar on board CALIPSO is well-posed to identify aerosols in the stratosphere from volcanic eruptions and major wildfire events. This paper describes improvements implemented in the version 4.5 CALIPSO data release to more accurately discriminate between volcanic ash, sulfate, and smoke within the stratosphere.
Ilaria Petracca, Davide De Santis, Matteo Picchiani, Stefano Corradini, Lorenzo Guerrieri, Fred Prata, Luca Merucci, Dario Stelitano, Fabio Del Frate, Giorgia Salvucci, and Giovanni Schiavon
Atmos. Meas. Tech., 15, 7195–7210, https://doi.org/10.5194/amt-15-7195-2022, https://doi.org/10.5194/amt-15-7195-2022, 2022
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The authors propose a near-real-time procedure for the detection of volcanic clouds by means of Sentinel-3 satellite data and neural networks. The algorithm results in an automatic image classification where ashy pixels are distinguished from other surfaces with remarkable accuracy. The model is considerably faster if compared to other approaches which are time consuming, case specific, and not automatic. The algorithm can be significantly helpful for emergency management during eruption events.
James A. Limbacher, Ralph A. Kahn, and Jaehwa Lee
Atmos. Meas. Tech., 15, 6865–6887, https://doi.org/10.5194/amt-15-6865-2022, https://doi.org/10.5194/amt-15-6865-2022, 2022
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Launched in December 1999, NASA’s Multi-angle Imaging SpectroRadiometer (MISR) has given researchers qualitative constraints on aerosol particle properties for the past 22 years. Here, we present a new MISR research aerosol retrieval algorithm (RA) that utilizes over-land surface reflectance data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) to address limitations of the MISR operational aerosol retrieval algorithm and improve retrievals of aerosol particle properties.
Futing Wang, Ting Yang, Zifa Wang, Haibo Wang, Xi Chen, Yele Sun, Jianjun Li, Guigang Tang, and Wenxuan Chai
Atmos. Meas. Tech., 15, 6127–6144, https://doi.org/10.5194/amt-15-6127-2022, https://doi.org/10.5194/amt-15-6127-2022, 2022
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We develop a new algorithm to get the vertical mass concentration profiles of fine aerosol components based on the synergy of ground-based remote sensing for the first time. The comparisons with in situ observations and chemistry transport models validate the performance of the algorithm. Uncertainties caused by input parameters are also assessed in this paper. We expected that the algorithm can provide a new idea for lidar inversion and promote the development of aerosol component profiles.
Manuel Queißer, Michael Harris, and Steven Knoop
Atmos. Meas. Tech., 15, 5527–5544, https://doi.org/10.5194/amt-15-5527-2022, https://doi.org/10.5194/amt-15-5527-2022, 2022
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Visibility is how well we can see something. Visibility sensors, such as employed in meteorological observatories and airports, measure at a point at the instrument location, which may not be representative of visibilities further away, e.g. near the sea surface during sea spray. Light detecting and ranging (lidar) can measure visibility further away. We find wind lidar to be a viable tool to measure visibility with low accuracy, which could suffice for safety-uncritical applications.
Travis N. Knepp, Larry Thomason, Mahesh Kovilakam, Jason Tackett, Jayanta Kar, Robert Damadeo, and David Flittner
Atmos. Meas. Tech., 15, 5235–5260, https://doi.org/10.5194/amt-15-5235-2022, https://doi.org/10.5194/amt-15-5235-2022, 2022
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We used aerosol profiles from the SAGE III/ISS instrument to develop an aerosol classification method that was tested on four case-study events (two volcanic, two fire) and supported with CALIOP aerosol products. The method worked well in identifying smoke and volcanic aerosol in the stratosphere for these events. Raikoke is presented as a demonstration of the limitations of this method.
Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Boris Barchunov, and Mikhail Korenskii
Atmos. Meas. Tech., 15, 4881–4900, https://doi.org/10.5194/amt-15-4881-2022, https://doi.org/10.5194/amt-15-4881-2022, 2022
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An approach to reveal variability in aerosol type at a high spatiotemporal resolution, by combining fluorescence and Mie–Raman lidar data, is presented. We applied this new classification scheme to lidar data obtained by LOA, University of Lille, in 2020–2021. It is demonstrated that the separation of the main particle types, such as smoke, dust, pollen, and urban, can be performed with a height resolution of 60 m and temporal resolution better than 10 min for the current lidar configuration.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 15, 4859–4879, https://doi.org/10.5194/amt-15-4859-2022, https://doi.org/10.5194/amt-15-4859-2022, 2022
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In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
Alexander Sinyuk, Brent N. Holben, Thomas F. Eck, David M. Giles, Ilya Slutsker, Oleg Dubovik, Joel S. Schafer, Alexander Smirnov, and Mikhail Sorokin
Atmos. Meas. Tech., 15, 4135–4151, https://doi.org/10.5194/amt-15-4135-2022, https://doi.org/10.5194/amt-15-4135-2022, 2022
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This paper describes modification of smoothness constraints on the imaginary part of the refractive index employed in the AERONET aerosol retrieval algorithm. This modification is termed relaxed due to the weaker strength of this new smoothness constraint. Applying the modified version of the smoothness constraint results in a significant reduction of retrieved light absorption by brown-carbon-containing aerosols.
Dawei Tang, Tianwen Wei, Jinlong Yuan, Haiyun Xia, and Xiankang Dou
Atmos. Meas. Tech., 15, 2819–2838, https://doi.org/10.5194/amt-15-2819-2022, https://doi.org/10.5194/amt-15-2819-2022, 2022
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During 11–20 March 2020, three aerosol transport events were investigated by a lidar system and an online bioaerosol detection system in Hefei, China.
Observation results reveal that the events not only contributed to high particulate matter pollution but also to the transport of external bioaerosols, resulting in changes in the fraction of fluorescent biological aerosol particles.
This detection method improved the time resolution and provided more parameters for aerosol detection.
Liqiao Lei, Timothy A. Berkoff, Guillaume Gronoff, Jia Su, Amin R. Nehrir, Yonghua Wu, Fred Moshary, and Shi Kuang
Atmos. Meas. Tech., 15, 2465–2478, https://doi.org/10.5194/amt-15-2465-2022, https://doi.org/10.5194/amt-15-2465-2022, 2022
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Aerosol extinction in the UVB (280–315 nm) is difficult to retrieve using simple lidar techniques due to the lack of lidar ratios at those wavelengths. The 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City region provided the opportunity to characterize the lidar ratio for UVB aerosol retrieval for the Langley Mobile Ozone Lidar (LMOL). A 292 nm aerosol product comparison between the NASA Langley High Altitude Lidar Observatory (HALO) and LMOL was also carried out.
Jan-Lukas Tirpitz, Udo Frieß, Robert Spurr, and Ulrich Platt
Atmos. Meas. Tech., 15, 2077–2098, https://doi.org/10.5194/amt-15-2077-2022, https://doi.org/10.5194/amt-15-2077-2022, 2022
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MAX-DOAS is a widely used measurement technique for the remote detection of atmospheric aerosol and trace gases. It relies on the analysis of ultra-violet and visible radiation spectra of skylight. To date, information contained in the skylight's polarisation state has not been utilised. On the basis of synthetic data, we carried out sensitivity analyses to assess the potential of polarimetry for MAX-DOAS applications.
Thibault Vaillant de Guélis, Gérard Ancellet, Anne Garnier, Laurent C.-Labonnote, Jacques Pelon, Mark A. Vaughan, Zhaoyan Liu, and David M. Winker
Atmos. Meas. Tech., 15, 1931–1956, https://doi.org/10.5194/amt-15-1931-2022, https://doi.org/10.5194/amt-15-1931-2022, 2022
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A new IIR-based cloud and aerosol discrimination (CAD) algorithm is developed using the IIR brightness temperature differences for cloud and aerosol features confidently identified by the CALIOP version 4 CAD algorithm. IIR classifications agree with the majority of V4 cloud identifications, reduce the ambiguity in a notable fraction of
not confidentV4 cloud classifications, and correct a few V4 misclassifications of cloud layers identified as dense dust or elevated smoke layers by CALIOP.
Marco Di Paolantonio, Davide Dionisi, and Gian Luigi Liberti
Atmos. Meas. Tech., 15, 1217–1231, https://doi.org/10.5194/amt-15-1217-2022, https://doi.org/10.5194/amt-15-1217-2022, 2022
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A procedure for the characterization of the lidar transmitter–receiver geometry was developed. This characterization is currently implemented in the Rome RMR lidar to optimize the telescope/beam alignment, retrieve the overlap function, and estimate the absolute and relative tilt of the laser beam. This procedure can be potentially used to complement the standard EARLINET quality assurance tests.
Monica Campanelli, Henri Diémoz, Anna Maria Siani, Alcide di Sarra, Anna Maria Iannarelli, Rei Kudo, Gabriele Fasano, Giampietro Casasanta, Luca Tofful, Marco Cacciani, Paolo Sanò, and Stefano Dietrich
Atmos. Meas. Tech., 15, 1171–1183, https://doi.org/10.5194/amt-15-1171-2022, https://doi.org/10.5194/amt-15-1171-2022, 2022
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The aerosol optical depth (AOD) characteristics in an urban area of Rome were retrieved over a period of 11 years (2010–2020) to determine, for the first time, their effect on the incoming ultraviolet (UV) solar radiation. The surface forcing efficiency shows that the AOD is the primary parameter affecting the surface irradiance in Rome, and it is found to be greater for smaller zenith angles and for larger and more absorbing particles in the UV range (such as, e.g., mineral dust).
Jean-Claude Roger, Eric Vermote, Sergii Skakun, Emilie Murphy, Oleg Dubovik, Natacha Kalecinski, Bruno Korgo, and Brent Holben
Atmos. Meas. Tech., 15, 1123–1144, https://doi.org/10.5194/amt-15-1123-2022, https://doi.org/10.5194/amt-15-1123-2022, 2022
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From measurements of the sky performed by AERONET, we determined the microphysical properties of the atmospheric particles (aerosols) for each AERONET site. We used the aerosol optical thickness and its variation over the visible spectrum. This allows us to determine an aerosol model useful for (but not only) the validation of the surface reflectance satellite-derived product. The impact of the aerosol model uncertainties on the surface reflectance validation has been found to be 1 % to 3 %.
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, Ja-Ho Koo, Seoyoung Lee, Minah Bae, Soontae Kim, Hong Liao, and Daniel J. Jacob
Atmos. Meas. Tech., 15, 1075–1091, https://doi.org/10.5194/amt-15-1075-2022, https://doi.org/10.5194/amt-15-1075-2022, 2022
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This paper uses a machine learning algorithm to infer high-resolution maps of particulate air quality in eastern China, Japan, and the Korean peninsula, using data from a geostationary satellite along with meteorology. We then perform an extensive evaluation of this inferred air quality and use it to diagnose trends in the region. We hope this paper and the associated data will be valuable to other scientists interested in epidemiology, air quality, remote sensing, and machine learning.
Antti Lipponen, Jaakko Reinvall, Arttu Väisänen, Henri Taskinen, Timo Lähivaara, Larisa Sogacheva, Pekka Kolmonen, Kari Lehtinen, Antti Arola, and Ville Kolehmainen
Atmos. Meas. Tech., 15, 895–914, https://doi.org/10.5194/amt-15-895-2022, https://doi.org/10.5194/amt-15-895-2022, 2022
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We have developed a machine-learning-based model that can be used to correct the Sentinel-3 satellite-based aerosol parameter data of the Synergy data product. The strength of the model is that the original satellite data processing does not have to be carried out again but the correction can be carried out with the data already available. We show that the correction significantly improves the accuracy of the satellite aerosol parameters.
Vinay Kayetha, Omar Torres, and Hiren Jethva
Atmos. Meas. Tech., 15, 845–877, https://doi.org/10.5194/amt-15-845-2022, https://doi.org/10.5194/amt-15-845-2022, 2022
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Existing measurements of spectral aerosol absorption are limited, particularly in the UV region. We use the synergy of satellite and ground measurements to derive spectral single scattering albedo of aerosols from the UV–visible spectrum. The resulting spectral SSAs are used to investigate seasonality in absorption for carbonaceous, dust, and urban aerosols. Regional aerosol absorption models that could be used to make reliable assumptions in satellite remote sensing of aerosols are derived.
Goutam Choudhury and Matthias Tesche
Atmos. Meas. Tech., 15, 639–654, https://doi.org/10.5194/amt-15-639-2022, https://doi.org/10.5194/amt-15-639-2022, 2022
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Aerosols are tiny particles suspended in the atmosphere. A fraction of these particles can form clouds and are called cloud condensation nuclei (CCN). Measurements of such aerosol particles are necessary to study the aerosol–cloud interactions and reduce the uncertainty in our future climate predictions. We present a novel methodology to estimate global 3D CCN concentrations from the CALIPSO satellite measurements. The final data set will be used to study the aerosol–cloud interactions.
Hiroshi Ishimoto, Masahiro Hayashi, and Yuzo Mano
Atmos. Meas. Tech., 15, 435–458, https://doi.org/10.5194/amt-15-435-2022, https://doi.org/10.5194/amt-15-435-2022, 2022
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Using data from the Infrared Atmospheric Sounding Interferometer (IASI) measurements of volcanic ash clouds (VACs) and radiative transfer calculations, we attempt to simulate the measured brightness temperature spectra (BTS) of volcanic ash aerosols in the infrared region. In particular, the dependence on the ash refractive index (RI) model is investigated.
Roberto Román, Juan C. Antuña-Sánchez, Victoria E. Cachorro, Carlos Toledano, Benjamín Torres, David Mateos, David Fuertes, César López, Ramiro González, Tatyana Lapionok, Marcos Herreras-Giralda, Oleg Dubovik, and Ángel M. de Frutos
Atmos. Meas. Tech., 15, 407–433, https://doi.org/10.5194/amt-15-407-2022, https://doi.org/10.5194/amt-15-407-2022, 2022
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An all-sky camera is used to obtain the relative sky radiance, and this radiance is used as input in an inversion code to obtain aerosol properties. This paper is really interesting because it pushes forward the use and capability of sky cameras for more advanced science purposes. Enhanced aerosol properties can be retrieved with accuracy using only an all-sky camera, but synergy with other instruments providing aerosol optical depth could even increase the power of these low-cost instruments.
Frithjof Ehlers, Thomas Flament, Alain Dabas, Dimitri Trapon, Adrien Lacour, Holger Baars, and Anne Grete Straume-Lindner
Atmos. Meas. Tech., 15, 185–203, https://doi.org/10.5194/amt-15-185-2022, https://doi.org/10.5194/amt-15-185-2022, 2022
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The Aeolus satellite observes the Earth and can vertically detect any kind of particles (aerosols or clouds) in the atmosphere below it. These observations are typically very noisy, which needs to be accounted for. This work dampens the noise in Aeolus' aerosol and cloud data, which are provided publicly by the ESA, so that the scientific community can make better use of it. This makes the data potentially more useful for weather prediction and climate research.
Alberto Sorrentino, Alessia Sannino, Nicola Spinelli, Michele Piana, Antonella Boselli, Valentino Tontodonato, Pasquale Castellano, and Xuan Wang
Atmos. Meas. Tech., 15, 149–164, https://doi.org/10.5194/amt-15-149-2022, https://doi.org/10.5194/amt-15-149-2022, 2022
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We present a novel approach that can be used to obtain microphysical properties of atmospheric aerosol, up to several kilometers in the atmosphere, from lidar measurements taken from the ground. Our approach provides accurate reconstructions under many different experimental conditions. Our results can contribute to the expansion of the use of remote sensing techniques for air quality monitoring and atmospheric science in general.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Michal Segal Rozenhaimer, Meloë Kacenelenbogen, Yohei Shinozuka, Connor Flynn, Rich Ferrare, Sharon Burton, Chris Hostetler, Marc Mallet, and Paquita Zuidema
Atmos. Meas. Tech., 15, 61–77, https://doi.org/10.5194/amt-15-61-2022, https://doi.org/10.5194/amt-15-61-2022, 2022
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This work presents heating rates derived from aircraft observations from the 2016 and 2017 field campaigns of ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS). We separate the total heating rates into aerosol and gas (primarily water vapor) absorption and explore some of the co-variability of heating rate profiles and their primary drivers, leading to the development of a new concept: the heating rate efficiency (HRE; the heating rate per unit aerosol extinction).
Thomas Flament, Dimitri Trapon, Adrien Lacour, Alain Dabas, Frithjof Ehlers, and Dorit Huber
Atmos. Meas. Tech., 14, 7851–7871, https://doi.org/10.5194/amt-14-7851-2021, https://doi.org/10.5194/amt-14-7851-2021, 2021
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This paper presents the main algorithms of the Aeolus Level 2 aerosol optical properties product. The processing chain was developed under contract with ESA.
We show that the ALADIN instrument, although primarily designed to retrieve atmospheric winds, is also able to provide valuable information about aerosol and cloud optical properties. The algorithms are detailed, and validation on simulated and real examples is shown.
Oscar S. Sandvik, Johan Friberg, Moa K. Sporre, and Bengt G. Martinsson
Atmos. Meas. Tech., 14, 7153–7165, https://doi.org/10.5194/amt-14-7153-2021, https://doi.org/10.5194/amt-14-7153-2021, 2021
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Short summary
A method to form SO2 profiles in the stratosphere with high vertical resolution following volcanic eruptions is introduced. The method combines space-based high-resolution vertical aerosol profiles and SO2 measurements the first 2 weeks after an eruption with air mass trajectory analyses. The SO2 is located at higher altitude than in most previous studies. The detailed resolution of the SO2 profile is unprecedented compared to other methods.
Igor B. Konovalov, Nikolai A. Golovushkin, Matthias Beekmann, Mikhail V. Panchenko, and Meinrat O. Andreae
Atmos. Meas. Tech., 14, 6647–6673, https://doi.org/10.5194/amt-14-6647-2021, https://doi.org/10.5194/amt-14-6647-2021, 2021
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Short summary
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.
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Short summary
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.
Multi-angle polarimetric measurements have been shown to greatly improve the remote sensing...
