Articles | Volume 17, issue 22
https://doi.org/10.5194/amt-17-6517-2024
© Author(s) 2024. 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-17-6517-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Nov 2024
Research article |
| 14 Nov 2024
| 14 Nov 2024
Total column optical depths retrieved from CALIPSO lidar ocean surface backscatter
Robert A. Ryan
CORRESPONDING AUTHOR
Coherent Application, Inc. – Psionic LLC, Hampton, VA, USA
Mark A. Vaughan
NASA Langley Research Center, Hampton, VA, USA
Sharon D. Rodier
ADNET Systems, Inc., Bethesda, MD, USA
Jason L. Tackett
NASA Langley Research Center, Hampton, VA, USA
John A. Reagan
Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA
Richard A. Ferrare
NASA Langley Research Center, Hampton, VA, USA
Johnathan W. Hair
NASA Langley Research Center, Hampton, VA, USA
John A. Smith
NASA Langley Research Center, Hampton, VA, USA
Brian J. Getzewich
NASA Langley Research Center, Hampton, VA, USA
Related authors
Travis Toth, Gregory Schuster, Marian Clayton, Zhujun Li, David Painemal, Sharon Rodier, Jayanta Kar, Tyler Thorsen, Richard Ferrare, Mark Vaughan, Jason Tackett, Huisheng Bian, Mian Chin, Anne Garnier, Ellsworth Welton, Robert Ryan, Charles Trepte, and David Winker
EGUsphere, https://doi.org/10.5194/egusphere-2025-2832, https://doi.org/10.5194/egusphere-2025-2832, 2025
Short summary
Short summary
NASA’s CALIPSO satellite mission observed aerosols (airborne particles) globally from 2006 to 2023. Its final data products update improves its aerosol optical parameters over oceans by adjusting for regional and seasonal differences in a new measurement-model synergistic approach. This results in a more realistic aerosol characterization, specifically near coastlines (where sea salt mixes with pollution), with potential impacts to future studies of science applications (e.g., climate effects).
Jason L. Tackett, Robert A. Ryan, Anne E. Garnier, Jayanta Kar, Brian J. Getzewich, Xia Cai, Mark A. Vaughan, Charles R. Trepte, Ron C. Verhappen, David M. Winker, and Kam-Pui A. Lee
EGUsphere, https://doi.org/10.5194/egusphere-2025-2376, https://doi.org/10.5194/egusphere-2025-2376, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
The spaceborne atmospheric lidar CALIOP experienced an increasing number of intermittent low energy laser pulses in the final seven years of the 17-year long CALIPSO mission. Low energy pulses degraded the quality of retrievals in affected profiles. This paper describes low energy mitigation (LEM) algorithms that remove affected data and minimize data loss. LEM is demonstrated to correct calibration biases, reduce false feature detections, and restore the integrity of the CALIOP data record.
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
Short summary
Short summary
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.
Jeffrey S. Reid, Robert E. Holz, Chris A. Hostetler, Richard A. Ferrare, Juli I. Rubin, Elizabeth J. Thompson, Susan C. van den Heever, Corey G. Amiot, Sharon P. Burton, Joshua P. DiGangi, Glenn S. Diskin, Joshua H. Cossuth, Daniel P. Eleuterio, Edwin W. Eloranta, Ralph Kuehn, Willem J. Marais, Hal B. Maring, Armin Sorooshian, Kenneth L. Thornhill, Charles R. Trepte, Jian Wang, Peng Xian, and Luke D. Ziemba
EGUsphere, https://doi.org/10.5194/egusphere-2025-2605, https://doi.org/10.5194/egusphere-2025-2605, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We document air and ship born measurements of the vertical distribution of pollution and biomass burning aerosol particles transported within the Maritime Continent’s monsoonal flows for 1000’s of kilometers, and yet still exhibit intricate patterns around clouds near the ocean’s surface. Findings demonstrate that, while aerosol transport occurs near the surface, there is heterogeneity in particle extinction that must be considered for both in situ observations and satellite retrievals.
Jayanta Kar, Mark A. Vaughan, Robert P. Damadeo, Mahesh Kovilakam, Jason L. Tackett, and Charles R. Trepte
EGUsphere, https://doi.org/10.5194/egusphere-2025-3141, https://doi.org/10.5194/egusphere-2025-3141, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
This paper assesses a possible bias in calibration of the spaceborne CALIOP lidar signals at 1064 nm resulting from relative attenuation of the signals at 1064 nm and 532 nm due to stratospheric aerosols. Multi-channel aerosol measurements from SAGE III instrument on ISS indicate that the bias is less than 1–2 % for background conditions and up to 5 % for strong stratospheric loading. Implications for extinction retrievals at 1064 nm and cascading errors for multi-layer scenes are discussed.
Travis Toth, Gregory Schuster, Marian Clayton, Zhujun Li, David Painemal, Sharon Rodier, Jayanta Kar, Tyler Thorsen, Richard Ferrare, Mark Vaughan, Jason Tackett, Huisheng Bian, Mian Chin, Anne Garnier, Ellsworth Welton, Robert Ryan, Charles Trepte, and David Winker
EGUsphere, https://doi.org/10.5194/egusphere-2025-2832, https://doi.org/10.5194/egusphere-2025-2832, 2025
Short summary
Short summary
NASA’s CALIPSO satellite mission observed aerosols (airborne particles) globally from 2006 to 2023. Its final data products update improves its aerosol optical parameters over oceans by adjusting for regional and seasonal differences in a new measurement-model synergistic approach. This results in a more realistic aerosol characterization, specifically near coastlines (where sea salt mixes with pollution), with potential impacts to future studies of science applications (e.g., climate effects).
Sharon P. Burton, Johnathan W. Hair, Chris A. Hostetler, Marta A. Fenn, John A. Smith, and Richard A. Ferrare
EGUsphere, https://doi.org/10.5194/egusphere-2025-2915, https://doi.org/10.5194/egusphere-2025-2915, 2025
Short summary
Short summary
Advanced lidars can retrieve atmospheric aerosol backscatter, extinction, and linear depolarization ratio. However excessive noise propagation in the traditional inversion method can make extinction unusable when the signal is weak, such as from space. Implementing a weak constraint can reduce the noise propagation while preserving accuracy. Here we also focus on fully characterizing both random and systematic uncertainties and examining the tradeoff between uncertainty and resolution.
Ewan Crosbie, Johnathan W. Hair, Amin R. Nehrir, Richard A. Ferrare, Chris Hostetler, Taylor Shingler, David Harper, Marta Fenn, James Collins, Rory Barton-Grimley, Brian Collister, K. Lee Thornhill, Christiane Voigt, Simon Kirschler, and Armin Sorooshian
Atmos. Meas. Tech., 18, 2639–2658, https://doi.org/10.5194/amt-18-2639-2025, https://doi.org/10.5194/amt-18-2639-2025, 2025
Short summary
Short summary
A method was developed to extract information from airborne lidar observations about the distribution of ice and liquid water within clouds. The method specifically targets signatures of horizontal and vertical gradients in ice and water that appear in the polarization of the lidar signals. The method was tested against direct measurements of the cloud properties collected by a second aircraft.
Jason L. Tackett, Robert A. Ryan, Anne E. Garnier, Jayanta Kar, Brian J. Getzewich, Xia Cai, Mark A. Vaughan, Charles R. Trepte, Ron C. Verhappen, David M. Winker, and Kam-Pui A. Lee
EGUsphere, https://doi.org/10.5194/egusphere-2025-2376, https://doi.org/10.5194/egusphere-2025-2376, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
The spaceborne atmospheric lidar CALIOP experienced an increasing number of intermittent low energy laser pulses in the final seven years of the 17-year long CALIPSO mission. Low energy pulses degraded the quality of retrievals in affected profiles. This paper describes low energy mitigation (LEM) algorithms that remove affected data and minimize data loss. LEM is demonstrated to correct calibration biases, reduce false feature detections, and restore the integrity of the CALIOP data record.
Emily D. Lenhardt, Lan Gao, Chris A. Hostetler, Richard A. Ferrare, Sharon P. Burton, Richard H. Moore, Luke D. Ziemba, Ewan Crosbie, Armin Sorooshian, Cassidy Soloff, and Jens Redemann
EGUsphere, https://doi.org/10.5194/egusphere-2025-2422, https://doi.org/10.5194/egusphere-2025-2422, 2025
Short summary
Short summary
Small particles that form cloud droplets greatly impact Earth's climate, but are very difficult to measure. If we can measure them using satellite-based instruments, we greatly increase the amount of available data on their concentrations. In this study we find that including information about particle size is most important to measure them accurately from such satellite-based instruments. This can inform future studies on how to obtain more accurate information about small particles.
Genevieve Rose Lorenzo, Luke D. Ziemba, Avelino F. Arellano, Mary C. Barth, Ewan C. Crosbie, Joshua P. DiGangi, Glenn S. Diskin, Richard Ferrare, Miguel Ricardo A. Hilario, Michael A. Shook, Simone Tilmes, Jian Wang, Qian Xiao, Jun Zhang, and Armin Sorooshian
Atmos. Chem. Phys., 25, 5469–5495, https://doi.org/10.5194/acp-25-5469-2025, https://doi.org/10.5194/acp-25-5469-2025, 2025
Short summary
Short summary
Novel aerosol hygroscopicity analyses of CAMP2Ex (Cloud, Aerosol, and Monsoon Processes Philippines Experiment) field campaign data show low aerosol hygroscopicity values in Southeast Asia. Organic carbon from smoke decreases hygroscopicity to levels more like those in continental than in polluted marine regions. Hygroscopicity changes at cloud level demonstrate how surface particles impact clouds in the region, affecting model representation of aerosol and cloud interactions in similar polluted marine regions with high organic carbon emissions.
Meloë S. F. Kacenelenbogen, Ralph Kuehn, Nandana Amarasinghe, Kerry Meyer, Edward Nowottnick, Mark Vaughan, Hong Chen, Sebastian Schmidt, Richard Ferrare, John Hair, Robert Levy, Hongbin Yu, Paquita Zuidema, Robert Holz, and Willem Marais
EGUsphere, https://doi.org/10.5194/egusphere-2025-1403, https://doi.org/10.5194/egusphere-2025-1403, 2025
Short summary
Short summary
Aerosols perturb the radiation balance of the Earth-atmosphere system. To reduce the uncertainty in quantifying present-day climate change, we combine two satellite sensors and a model to assess the aerosol effects on radiation in all-sky conditions. Satellite-based and coincident aircraft measurements of aerosol radiative effects agree well over the Southeast Atlantic. This constitutes a crucial first evaluation before we apply our method to more years and regions of the world.
Hongyu Liu, Bo Zhang, Richard H. Moore, Luke D. Ziemba, Richard A. Ferrare, Hyundeok Choi, Armin Sorooshian, David Painemal, Hailong Wang, Michael A. Shook, Amy Jo Scarino, Johnathan W. Hair, Ewan C. Crosbie, Marta A. Fenn, Taylor J. Shingler, Chris A. Hostetler, Gao Chen, Mary M. Kleb, Gan Luo, Fangqun Yu, Mark A. Vaughan, Yongxiang Hu, Glenn S. Diskin, John B. Nowak, Joshua P. DiGangi, Yonghoon Choi, Christoph A. Keller, and Matthew S. Johnson
Atmos. Chem. Phys., 25, 2087–2121, https://doi.org/10.5194/acp-25-2087-2025, https://doi.org/10.5194/acp-25-2087-2025, 2025
Short summary
Short summary
We use the GEOS-Chem model to simulate aerosol distributions and properties over the western North Atlantic Ocean (WNAO) during the winter and summer deployments in 2020 of the NASA ACTIVATE mission. Model results are evaluated against aircraft, ground-based, and satellite observations. The improved understanding of life cycle, composition, transport pathways, and distribution of aerosols has important implications for characterizing aerosol–cloud–meteorology interactions over WNAO.
Jan-Lukas Tirpitz, Santo Fedele Colosimo, Nathaniel Brockway, Robert Spurr, Matt Christi, Samuel Hall, Kirk Ullmann, Johnathan Hair, Taylor Shingler, Rodney Weber, Jack Dibb, Richard Moore, Elizabeth Wiggins, Vijay Natraj, Nicolas Theys, and Jochen Stutz
Atmos. Chem. Phys., 25, 1989–2015, https://doi.org/10.5194/acp-25-1989-2025, https://doi.org/10.5194/acp-25-1989-2025, 2025
Short summary
Short summary
We combine plume composition data from the 2019 NASA FIREX-AQ campaign with state-of-the-art radiative transfer modeling techniques to calculate distributions of actinic flux and photolysis frequencies in a wildfire plume. Excellent agreement of the model and observations demonstrates the applicability of this approach to constrain photochemistry in such plumes. We identify limiting factors for the modeling accuracy and discuss spatial and spectral features of the distributions.
Fernando Chouza, Thierry Leblanc, Patrick Wang, Steven S. Brown, Kristen Zuraski, Wyndom Chace, Caroline C. Womack, Jeff Peischl, John Hair, Taylor Shingler, and John Sullivan
Atmos. Meas. Tech., 18, 405–419, https://doi.org/10.5194/amt-18-405-2025, https://doi.org/10.5194/amt-18-405-2025, 2025
Short summary
Short summary
The JPL lidar group developed the SMOL (Small Mobile Ozone Lidar), an affordable ozone differential absorption lidar (DIAL) system covering all altitudes from 200 m to 10 km a.g.l. The comparison with airborne in situ and lidar measurements shows very good agreement. An additional comparison with nearby surface ozone measuring instruments indicates unbiased measurements by the SMOL lidars down to 200 m a.g.l.
Sanja Dmitrovic, Joseph S. Schlosser, Ryan Bennett, Brian Cairns, Gao Chen, Glenn S. Diskin, Richard A. Ferrare, Johnathan W. Hair, Michael A. Jones, Jeffrey S. Reid, Taylor J. Shingler, Michael A. Shook, Armin Sorooshian, Kenneth L. Thornhill, Luke D. Ziemba, and Snorre Stamnes
EGUsphere, https://doi.org/10.5194/egusphere-2024-3088, https://doi.org/10.5194/egusphere-2024-3088, 2024
Short summary
Short summary
This study focuses on aerosol particles, which critically influence the atmosphere by scattering and absorbing light. To understand these interactions, airborne field campaigns deploy instruments that can measure these particles’ directly or indirectly via remote sensing. We introduce the In Situ Aerosol Retrieval Algorithm (ISARA) to ensure consistency between aerosol measurements and show that the two data sets generally align, with some deviation caused by the presence of larger particles.
Soodabeh Namdari, Sanja Dmitrovic, Gao Chen, Yonghoon Choi, Ewan Crosbie, Joshua P. DiGangi, Glenn S. Diskin, Richard A. Ferrare, Johnathan W. Hair, Simon Kirschler, John B. Nowak, Kenneth L. Thornhill, Christiane Voigt, Holger Vömel, Xubin Zeng, and Armin Sorooshian
EGUsphere, https://doi.org/10.5194/egusphere-2024-3024, https://doi.org/10.5194/egusphere-2024-3024, 2024
Short summary
Short summary
We conducted this study to assess the accuracy of airborne measurements of wind, temperature, and humidity, essential for understanding atmospheric processes. Using data from NASA's ACTIVATE campaign, we compared measurements from the TAMMS and DLH aboard a Falcon aircraft with dropsondes from a King Air, matching data points based on location and time using statistical methods. The study showed strong agreement, confirming the reliability of these methods for advancing climate models.
Cassidy Soloff, Taiwo Ajayi, Yonghoon Choi, Ewan C. Crosbie, Joshua P. DiGangi, Glenn S. Diskin, Marta A. Fenn, Richard A. Ferrare, Francesca Gallo, Johnathan W. Hair, Miguel Ricardo A. Hilario, Simon Kirschler, Richard H. Moore, Taylor J. Shingler, Michael A. Shook, Kenneth L. Thornhill, Christiane Voigt, Edward L. Winstead, Luke D. Ziemba, and Armin Sorooshian
Atmos. Chem. Phys., 24, 10385–10408, https://doi.org/10.5194/acp-24-10385-2024, https://doi.org/10.5194/acp-24-10385-2024, 2024
Short summary
Short summary
Using aircraft measurements over the northwestern Atlantic between the US East Coast and Bermuda and trajectory modeling of continental outflow, we identify trace gas and particle properties that exhibit gradients with offshore distance and quantify these changes with high-resolution measurements of concentrations and particle chemistry, size, and scattering properties. This work furthers our understanding of the complex interactions between continental and marine environments.
Corey G. Amiot, Timothy J. Lang, Susan C. van den Heever, Richard A. Ferrare, Ousmane O. Sy, Lawrence D. Carey, Sundar A. Christopher, John R. Mecikalski, Sean W. Freeman, George Alexander Sokolowsky, Chris A. Hostetler, and Simone Tanelli
EGUsphere, https://doi.org/10.5194/egusphere-2024-2384, https://doi.org/10.5194/egusphere-2024-2384, 2024
Short summary
Short summary
Decoupling aerosol and environmental impacts on convection is challenging. Using airborne data, we correlated microwave-frequency convective metrics with aerosol concentrations in several different environments. Medium-to-high aerosol concentrations were often strongly and positively correlated with convective intensity and frequency, especially in favorable environments based on temperature lapse rates and K-Index. Storm environment is important to consider when evaluating aerosol effects.
Taiwo Ajayi, Yonghoon Choi, Ewan C. Crosbie, Joshua P. DiGangi, Glenn S. Diskin, Marta A. Fenn, Richard A. Ferrare, Johnathan W. Hair, Miguel Ricardo A. Hilario, Chris A. Hostetler, Simon Kirschler, Richard H. Moore, Taylor J. Shingler, Michael A. Shook, Cassidy Soloff, Kenneth L. Thornhill, Christiane Voigt, Edward L. Winstead, Luke D. Ziemba, and Armin Sorooshian
Atmos. Chem. Phys., 24, 9197–9218, https://doi.org/10.5194/acp-24-9197-2024, https://doi.org/10.5194/acp-24-9197-2024, 2024
Short summary
Short summary
This study uses airborne data to examine vertical profiles of trace gases, aerosol particles, and meteorological variables over a remote marine area (Bermuda). Results show distinct differences based on both air mass source region (North America, Ocean, Caribbean/North Africa) and altitude for a given air mass type. This work highlights the sensitivity of remote marine areas to long-range transport and the importance of considering the vertical dependence of trace gas and aerosol properties.
Claire L. Ryder, Clément Bézier, Helen F. Dacre, Rory Clarkson, Vassilis Amiridis, Eleni Marinou, Emmanouil Proestakis, Zak Kipling, Angela Benedetti, Mark Parrington, Samuel Rémy, and Mark Vaughan
Nat. Hazards Earth Syst. Sci., 24, 2263–2284, https://doi.org/10.5194/nhess-24-2263-2024, https://doi.org/10.5194/nhess-24-2263-2024, 2024
Short summary
Short summary
Desert dust poses a hazard to aircraft via degradation of engine components. This has financial implications for the aviation industry and results in increased fuel burn with climate impacts. Here we quantify dust ingestion by aircraft engines at airports worldwide. We find Dubai and Delhi in summer are among the dustiest airports, where substantial engine degradation would occur after 1000 flights. Dust ingestion can be reduced by changing take-off times and the altitude of holding patterns.
David Winker, Xia Cai, Mark Vaughan, Anne Garnier, Brian Magill, Melody Avery, and Brian Getzewich
Earth Syst. Sci. Data, 16, 2831–2855, https://doi.org/10.5194/essd-16-2831-2024, https://doi.org/10.5194/essd-16-2831-2024, 2024
Short summary
Short summary
Clouds play important roles in both weather and climate. In this paper we describe version 1.0 of a unique global ice cloud data product derived from over 12 years of global spaceborne lidar measurements. This monthly gridded product provides a unique vertically resolved characterization of the occurrence and properties, optical and physical, of thin ice clouds and the tops of deep convective clouds. It should provide significant value for cloud research and model evaluation.
Sanja Dmitrovic, Johnathan W. Hair, Brian L. Collister, Ewan Crosbie, Marta A. Fenn, Richard A. Ferrare, David B. Harper, Chris A. Hostetler, Yongxiang Hu, John A. Reagan, Claire E. Robinson, Shane T. Seaman, Taylor J. Shingler, Kenneth L. Thornhill, Holger Vömel, Xubin Zeng, and Armin Sorooshian
Atmos. Meas. Tech., 17, 3515–3532, https://doi.org/10.5194/amt-17-3515-2024, https://doi.org/10.5194/amt-17-3515-2024, 2024
Short summary
Short summary
This study introduces and evaluates a new ocean surface wind speed product from the NASA Langley Research Center (LARC) airborne High-Spectral-Resolution Lidar – Generation 2 (HSRL-2) during the NASA ACTIVATE mission. We show that HSRL-2 surface wind speed data are accurate when compared to ground-truth dropsonde measurements. Therefore, the HSRL-2 instrument is able obtain accurate, high-resolution surface wind speed data in airborne field campaigns.
Ewan Crosbie, Luke D. Ziemba, Michael A. Shook, Taylor Shingler, Johnathan W. Hair, Armin Sorooshian, Richard A. Ferrare, Brian Cairns, Yonghoon Choi, Joshua DiGangi, Glenn S. Diskin, Chris Hostetler, Simon Kirschler, Richard H. Moore, David Painemal, Claire Robinson, Shane T. Seaman, K. Lee Thornhill, Christiane Voigt, and Edward Winstead
Atmos. Chem. Phys., 24, 6123–6152, https://doi.org/10.5194/acp-24-6123-2024, https://doi.org/10.5194/acp-24-6123-2024, 2024
Short summary
Short summary
Marine clouds are found to clump together in regions or lines, readily discernible from satellite images of the ocean. While clustering is also a feature of deep storm clouds, we focus on smaller cloud systems associated with fair weather and brief localized showers. Two aircraft sampled the region around these shallow systems: one incorporated measurements taken within, adjacent to, and below the clouds, while the other provided a survey from above using remote sensing techniques.
Leong Wai Siu, Joseph S. Schlosser, David Painemal, Brian Cairns, Marta A. Fenn, Richard A. Ferrare, Johnathan W. Hair, Chris A. Hostetler, Longlei Li, Mary M. Kleb, Amy Jo Scarino, Taylor J. Shingler, Armin Sorooshian, Snorre A. Stamnes, and Xubin Zeng
Atmos. Meas. Tech., 17, 2739–2759, https://doi.org/10.5194/amt-17-2739-2024, https://doi.org/10.5194/amt-17-2739-2024, 2024
Short summary
Short summary
An unprecedented 3-year aerosol dataset was collected from a recent NASA field campaign over the western North Atlantic Ocean, which offers a special opportunity to evaluate two state-of-the-art remote sensing instruments, one lidar and the other polarimeter, on the same aircraft. Special attention has been paid to validate aerosol optical depth data and their uncertainties when no reference dataset is available. Physical reasons for the disagreement between two instruments are discussed.
Hiren T. Jethva, Omar Torres, Richard A. Ferrare, Sharon P. Burton, Anthony L. Cook, David B. Harper, Chris A. Hostetler, Jens Redemann, Vinay Kayetha, Samuel LeBlanc, Kristina Pistone, Logan Mitchell, and Connor J. Flynn
Atmos. Meas. Tech., 17, 2335–2366, https://doi.org/10.5194/amt-17-2335-2024, https://doi.org/10.5194/amt-17-2335-2024, 2024
Short summary
Short summary
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 and OMI–MODIS passive sensors to deduce a global product of AOD and SSA of absorbing aerosols above clouds.
Georgios I. Gkatzelis, Matthew M. Coggon, Chelsea E. Stockwell, Rebecca S. Hornbrook, Hannah Allen, Eric C. Apel, Megan M. Bela, Donald R. Blake, Ilann Bourgeois, Steven S. Brown, Pedro Campuzano-Jost, Jason M. St. Clair, James H. Crawford, John D. Crounse, Douglas A. Day, Joshua P. DiGangi, Glenn S. Diskin, Alan Fried, Jessica B. Gilman, Hongyu Guo, Johnathan W. Hair, Hannah S. Halliday, Thomas F. Hanisco, Reem Hannun, Alan Hills, L. Gregory Huey, Jose L. Jimenez, Joseph M. Katich, Aaron Lamplugh, Young Ro Lee, Jin Liao, Jakob Lindaas, Stuart A. McKeen, Tomas Mikoviny, Benjamin A. Nault, J. Andrew Neuman, John B. Nowak, Demetrios Pagonis, Jeff Peischl, Anne E. Perring, Felix Piel, Pamela S. Rickly, Michael A. Robinson, Andrew W. Rollins, Thomas B. Ryerson, Melinda K. Schueneman, Rebecca H. Schwantes, Joshua P. Schwarz, Kanako Sekimoto, Vanessa Selimovic, Taylor Shingler, David J. Tanner, Laura Tomsche, Krystal T. Vasquez, Patrick R. Veres, Rebecca Washenfelder, Petter Weibring, Paul O. Wennberg, Armin Wisthaler, Glenn M. Wolfe, Caroline C. Womack, Lu Xu, Katherine Ball, Robert J. Yokelson, and Carsten Warneke
Atmos. Chem. Phys., 24, 929–956, https://doi.org/10.5194/acp-24-929-2024, https://doi.org/10.5194/acp-24-929-2024, 2024
Short summary
Short summary
This study reports emissions of gases and particles from wildfires. These emissions are related to chemical proxies that can be measured by satellite and incorporated into models to improve predictions of wildfire impacts on air quality and climate.
Xueying Liu, Yuxuan Wang, Shailaja Wasti, Wei Li, Ehsan Soleimanian, James Flynn, Travis Griggs, Sergio Alvarez, John T. Sullivan, Maurice Roots, Laurence Twigg, Guillaume Gronoff, Timothy Berkoff, Paul Walter, Mark Estes, Johnathan W. Hair, Taylor Shingler, Amy Jo Scarino, Marta Fenn, and Laura Judd
Geosci. Model Dev., 16, 5493–5514, https://doi.org/10.5194/gmd-16-5493-2023, https://doi.org/10.5194/gmd-16-5493-2023, 2023
Short summary
Short summary
With a comprehensive suite of ground-based and airborne remote sensing measurements during the 2021 TRacking Aerosol Convection ExpeRiment – Air Quality (TRACER-AQ) campaign in Houston, this study evaluates the simulation of the planetary boundary layer (PBL) height and the ozone vertical profile by a high-resolution (1.33 km) 3-D photochemical model Weather Research and Forecasting-driven GEOS-Chem (WRF-GC).
Simon Kirschler, Christiane Voigt, Bruce E. Anderson, Gao Chen, Ewan C. Crosbie, Richard A. Ferrare, Valerian Hahn, Johnathan W. Hair, Stefan Kaufmann, Richard H. Moore, David Painemal, Claire E. Robinson, Kevin J. Sanchez, Amy J. Scarino, Taylor J. Shingler, Michael A. Shook, Kenneth L. Thornhill, Edward L. Winstead, Luke D. Ziemba, and Armin Sorooshian
Atmos. Chem. Phys., 23, 10731–10750, https://doi.org/10.5194/acp-23-10731-2023, https://doi.org/10.5194/acp-23-10731-2023, 2023
Short summary
Short summary
In this study we present an overview of liquid and mixed-phase clouds and precipitation in the marine boundary layer over the western North Atlantic Ocean. We compare microphysical properties of pure liquid clouds to mixed-phase clouds and show that the initiation of the ice phase in mixed-phase clouds promotes precipitation. The observational data presented in this study are well suited for investigating the processes that give rise to liquid and mixed-phase clouds, ice, and precipitation.
Armin Sorooshian, Mikhail D. Alexandrov, Adam D. Bell, Ryan Bennett, Grace Betito, Sharon P. Burton, Megan E. Buzanowicz, Brian Cairns, Eduard V. Chemyakin, Gao Chen, Yonghoon Choi, Brian L. Collister, Anthony L. Cook, Andrea F. Corral, Ewan C. Crosbie, Bastiaan van Diedenhoven, Joshua P. DiGangi, Glenn S. Diskin, Sanja Dmitrovic, Eva-Lou Edwards, Marta A. Fenn, Richard A. Ferrare, David van Gilst, Johnathan W. Hair, David B. Harper, Miguel Ricardo A. Hilario, Chris A. Hostetler, Nathan Jester, Michael Jones, Simon Kirschler, Mary M. Kleb, John M. Kusterer, Sean Leavor, Joseph W. Lee, Hongyu Liu, Kayla McCauley, Richard H. Moore, Joseph Nied, Anthony Notari, John B. Nowak, David Painemal, Kasey E. Phillips, Claire E. Robinson, Amy Jo Scarino, Joseph S. Schlosser, Shane T. Seaman, Chellappan Seethala, Taylor J. Shingler, Michael A. Shook, Kenneth A. Sinclair, William L. Smith Jr., Douglas A. Spangenberg, Snorre A. Stamnes, Kenneth L. Thornhill, Christiane Voigt, Holger Vömel, Andrzej P. Wasilewski, Hailong Wang, Edward L. Winstead, Kira Zeider, Xubin Zeng, Bo Zhang, Luke D. Ziemba, and Paquita Zuidema
Earth Syst. Sci. Data, 15, 3419–3472, https://doi.org/10.5194/essd-15-3419-2023, https://doi.org/10.5194/essd-15-3419-2023, 2023
Short summary
Short summary
The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions. HU-25 Falcon and King Air aircraft conducted systematic and spatially coordinated flights over the northwest Atlantic Ocean. This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes.
Haihui Zhu, Randall V. Martin, Betty Croft, Shixian Zhai, Chi Li, Liam Bindle, Jeffrey R. Pierce, Rachel Y.-W. Chang, Bruce E. Anderson, Luke D. Ziemba, Johnathan W. Hair, Richard A. Ferrare, Chris A. Hostetler, Inderjeet Singh, Deepangsu Chatterjee, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jack E. Dibb, Joshua S. Schwarz, and Andrew Weinheimer
Atmos. Chem. Phys., 23, 5023–5042, https://doi.org/10.5194/acp-23-5023-2023, https://doi.org/10.5194/acp-23-5023-2023, 2023
Short summary
Short summary
Particle size of atmospheric aerosol is important for estimating its climate and health effects, but simulating atmospheric aerosol size is computationally demanding. This study derives a simple parameterization of the size of organic and secondary inorganic ambient aerosol that can be applied to atmospheric models. Applying this parameterization allows a better representation of the global spatial pattern of aerosol size, as verified by ground and airborne measurements.
Emily D. Lenhardt, Lan Gao, Jens Redemann, Feng Xu, Sharon P. Burton, Brian Cairns, Ian Chang, Richard A. Ferrare, Chris A. Hostetler, Pablo E. Saide, Calvin Howes, Yohei Shinozuka, Snorre Stamnes, Mary Kacarab, Amie Dobracki, Jenny Wong, Steffen Freitag, and Athanasios Nenes
Atmos. Meas. Tech., 16, 2037–2054, https://doi.org/10.5194/amt-16-2037-2023, https://doi.org/10.5194/amt-16-2037-2023, 2023
Short summary
Short summary
Small atmospheric particles, such as smoke from wildfires or pollutants from human activities, impact cloud properties, and clouds have a strong influence on climate. To better understand the distributions of these particles, we develop relationships to derive their concentrations from remote sensing measurements from an instrument called a lidar. Our method is reliable for smoke particles, and similar steps can be taken to develop relationships for other particle types.
Ian Chang, Lan Gao, Connor J. Flynn, Yohei Shinozuka, Sarah J. Doherty, Michael S. Diamond, Karla M. Longo, Gonzalo A. Ferrada, Gregory R. Carmichael, Patricia Castellanos, Arlindo M. da Silva, Pablo E. Saide, Calvin Howes, Zhixin Xue, Marc Mallet, Ravi Govindaraju, Qiaoqiao Wang, Yafang Cheng, Yan Feng, Sharon P. Burton, Richard A. Ferrare, Samuel E. LeBlanc, Meloë S. Kacenelenbogen, Kristina Pistone, Michal Segal-Rozenhaimer, Kerry G. Meyer, Ju-Mee Ryoo, Leonhard Pfister, Adeyemi A. Adebiyi, Robert Wood, Paquita Zuidema, Sundar A. Christopher, and Jens Redemann
Atmos. Chem. Phys., 23, 4283–4309, https://doi.org/10.5194/acp-23-4283-2023, https://doi.org/10.5194/acp-23-4283-2023, 2023
Short summary
Short summary
Abundant aerosols are present above low-level liquid clouds over the southeastern Atlantic during late austral spring. The model simulation differences in the proportion of aerosol residing in the planetary boundary layer and in the free troposphere can greatly affect the regional aerosol radiative effects. This study examines the aerosol loading and fractional aerosol loading in the free troposphere among various models and evaluates them against measurements from the NASA ORACLES campaign.
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
Short summary
Short summary
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.
Allison B. Marquardt Collow, Virginie Buchard, Peter R. Colarco, Arlindo M. da Silva, Ravi Govindaraju, Edward P. Nowottnick, Sharon Burton, Richard Ferrare, Chris Hostetler, and Luke Ziemba
Atmos. Chem. Phys., 22, 16091–16109, https://doi.org/10.5194/acp-22-16091-2022, https://doi.org/10.5194/acp-22-16091-2022, 2022
Short summary
Short summary
Biomass burning aerosol impacts aspects of the atmosphere and Earth system through radiative forcing, serving as cloud condensation nuclei, and air quality. Despite its importance, the representation of biomass burning aerosol is not always accurate in models. Field campaign observations from CAMP2Ex are used to evaluate the mass and extinction of aerosols in the GEOS model. Notable biases in the model illuminate areas of future development with GEOS and the underlying GOCART aerosol module.
Youhua Tang, Patrick C. Campbell, Pius Lee, Rick Saylor, Fanglin Yang, Barry Baker, Daniel Tong, Ariel Stein, Jianping Huang, Ho-Chun Huang, Li Pan, Jeff McQueen, Ivanka Stajner, Jose Tirado-Delgado, Youngsun Jung, Melissa Yang, Ilann Bourgeois, Jeff Peischl, Tom Ryerson, Donald Blake, Joshua Schwarz, Jose-Luis Jimenez, James Crawford, Glenn Diskin, Richard Moore, Johnathan Hair, Greg Huey, Andrew Rollins, Jack Dibb, and Xiaoyang Zhang
Geosci. Model Dev., 15, 7977–7999, https://doi.org/10.5194/gmd-15-7977-2022, https://doi.org/10.5194/gmd-15-7977-2022, 2022
Short summary
Short summary
This paper compares two meteorological datasets for driving a regional air quality model: a regional meteorological model using WRF (WRF-CMAQ) and direct interpolation from an operational global model (GFS-CMAQ). In the comparison with surface measurements and aircraft data in summer 2019, these two methods show mixed performance depending on the corresponding meteorological settings. Direct interpolation is found to be a viable method to drive air quality models.
Eva-Lou Edwards, Jeffrey S. Reid, Peng Xian, Sharon P. Burton, Anthony L. Cook, Ewan C. Crosbie, Marta A. Fenn, Richard A. Ferrare, Sean W. Freeman, John W. Hair, David B. Harper, Chris A. Hostetler, Claire E. Robinson, Amy Jo Scarino, Michael A. Shook, G. Alexander Sokolowsky, Susan C. van den Heever, Edward L. Winstead, Sarah Woods, Luke D. Ziemba, and Armin Sorooshian
Atmos. Chem. Phys., 22, 12961–12983, https://doi.org/10.5194/acp-22-12961-2022, https://doi.org/10.5194/acp-22-12961-2022, 2022
Short summary
Short summary
This study compares NAAPS-RA model simulations of aerosol optical thickness (AOT) and extinction to those retrieved with a high spectral resolution lidar near the Philippines. Agreement for AOT was good, and extinction agreement was strongest below 1500 m. Substituting dropsonde relative humidities into NAAPS-RA did not drastically improve agreement, and we discuss potential reasons why. Accurately modeling future conditions in this region is crucial due to its susceptibility to climate change.
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
Short summary
Short summary
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.
Aditya Kumar, R. Bradley Pierce, Ravan Ahmadov, Gabriel Pereira, Saulo Freitas, Georg Grell, Chris Schmidt, Allen Lenzen, Joshua P. Schwarz, Anne E. Perring, Joseph M. Katich, John Hair, Jose L. Jimenez, Pedro Campuzano-Jost, and Hongyu Guo
Atmos. Chem. Phys., 22, 10195–10219, https://doi.org/10.5194/acp-22-10195-2022, https://doi.org/10.5194/acp-22-10195-2022, 2022
Short summary
Short summary
We use the WRF-Chem model with new implementations of GOES-16 wildfire emissions and plume rise based on fire radiative power (FRP) to interpret aerosol observations during the 2019 NASA–NOAA FIREX-AQ field campaign and perform model evaluations. The model shows significant improvements in simulating the variety of aerosol loading environments sampled during FIREX-AQ. Our results also highlight the importance of accurate wildfire diurnal cycle and aerosol chemical mechanisms in models.
Harshvardhan Harshvardhan, Richard Ferrare, Sharon Burton, Johnathan Hair, Chris Hostetler, David Harper, Anthony Cook, Marta Fenn, Amy Jo Scarino, Eduard Chemyakin, and Detlef Müller
Atmos. Chem. Phys., 22, 9859–9876, https://doi.org/10.5194/acp-22-9859-2022, https://doi.org/10.5194/acp-22-9859-2022, 2022
Short summary
Short summary
The evolution of aerosol in biomass burning smoke plumes that travel over marine clouds off the Atlantic coast of central Africa was studied using measurements made by a lidar deployed on a high-altitude aircraft. The main finding was that the physical properties of aerosol do not change appreciably once the plume has left land and travels over the ocean over a timescale of 1 to 2 d. Almost all particles in the plume are of radius less than 1 micrometer and spherical in shape.
Simon Kirschler, Christiane Voigt, Bruce Anderson, Ramon Campos Braga, Gao Chen, Andrea F. Corral, Ewan Crosbie, Hossein Dadashazar, Richard A. Ferrare, Valerian Hahn, Johannes Hendricks, Stefan Kaufmann, Richard Moore, Mira L. Pöhlker, Claire Robinson, Amy J. Scarino, Dominik Schollmayer, Michael A. Shook, K. Lee Thornhill, Edward Winstead, Luke D. Ziemba, and Armin Sorooshian
Atmos. Chem. Phys., 22, 8299–8319, https://doi.org/10.5194/acp-22-8299-2022, https://doi.org/10.5194/acp-22-8299-2022, 2022
Short summary
Short summary
In this study we show that the vertical velocity dominantly impacts the cloud droplet number concentration (NC) of low-level clouds over the western North Atlantic in the winter and summer season, while the cloud condensation nuclei concentration, aerosol size distribution and chemical composition impact NC within a season. The observational data presented in this study can evaluate and improve the representation of aerosol–cloud interactions for a wide range of conditions.
Zhujun Li, David Painemal, Gregory Schuster, Marian Clayton, Richard Ferrare, Mark Vaughan, Damien Josset, Jayanta Kar, and Charles Trepte
Atmos. Meas. Tech., 15, 2745–2766, https://doi.org/10.5194/amt-15-2745-2022, https://doi.org/10.5194/amt-15-2745-2022, 2022
Short summary
Short summary
For more than 15 years, CALIPSO has revolutionized our understanding of the role of aerosols in climate. Here we evaluate CALIPSO aerosol typing over the ocean using an independent CALIPSO–CloudSat product. The analysis suggests that CALIPSO correctly categorizes clean marine aerosol over the open ocean, elevated smoke over the SE Atlantic, and dust over the tropical Atlantic. Similarities between clean and dusty marine over the open ocean implies that algorithm modifications are warranted.
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
Short summary
Short summary
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.
Kevin J. Sanchez, Bo Zhang, Hongyu Liu, Matthew D. Brown, Ewan C. Crosbie, Francesca Gallo, Johnathan W. Hair, Chris A. Hostetler, Carolyn E. Jordan, Claire E. Robinson, Amy Jo Scarino, Taylor J. Shingler, Michael A. Shook, Kenneth L. Thornhill, Elizabeth B. Wiggins, Edward L. Winstead, Luke D. Ziemba, Georges Saliba, Savannah L. Lewis, Lynn M. Russell, Patricia K. Quinn, Timothy S. Bates, Jack Porter, Thomas G. Bell, Peter Gaube, Eric S. Saltzman, Michael J. Behrenfeld, and Richard H. Moore
Atmos. Chem. Phys., 22, 2795–2815, https://doi.org/10.5194/acp-22-2795-2022, https://doi.org/10.5194/acp-22-2795-2022, 2022
Short summary
Short summary
Atmospheric particle concentrations impact clouds, which strongly impact the amount of sunlight reflected back into space and the overall climate. Measurements of particles over the ocean are rare and expensive to collect, so models are necessary to fill in the gaps by simulating both particle and clouds. However, some measurements are needed to test the accuracy of the models. Here, we measure changes in particles in different weather conditions, which are ideal for comparison with models.
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
Short summary
Short summary
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).
Sarah J. Doherty, Pablo E. Saide, Paquita Zuidema, Yohei Shinozuka, Gonzalo A. Ferrada, Hamish Gordon, Marc Mallet, Kerry Meyer, David Painemal, Steven G. Howell, Steffen Freitag, Amie Dobracki, James R. Podolske, Sharon P. Burton, Richard A. Ferrare, Calvin Howes, Pierre Nabat, Gregory R. Carmichael, Arlindo da Silva, Kristina Pistone, Ian Chang, Lan Gao, Robert Wood, and Jens Redemann
Atmos. Chem. Phys., 22, 1–46, https://doi.org/10.5194/acp-22-1-2022, https://doi.org/10.5194/acp-22-1-2022, 2022
Short summary
Short summary
Between July and October, biomass burning smoke is advected over the southeastern Atlantic Ocean, leading to climate forcing. Model calculations of forcing by this plume vary significantly in both magnitude and sign. This paper compares aerosol and cloud properties observed during three NASA ORACLES field campaigns to the same in four models. It quantifies modeled biases in properties key to aerosol direct radiative forcing and evaluates how these biases propagate to biases in forcing.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
Short summary
Short summary
Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
Short summary
Short summary
Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Daniel Pérez-Ramírez, David N. Whiteman, Igor Veselovskii, Richard Ferrare, Gloria Titos, María José Granados-Muñoz, Guadalupe Sánchez-Hernández, and Francisco Navas-Guzmán
Atmos. Chem. Phys., 21, 12021–12048, https://doi.org/10.5194/acp-21-12021-2021, https://doi.org/10.5194/acp-21-12021-2021, 2021
Short summary
Short summary
This paper shows how aerosol hygroscopicity enhances the vertical profile of aerosol backscattering and extinction. The study is possible thanks to the large set of remote sensing instruments and focuses on the the Baltimore–Washington DC metropolitan area during hot and humid summer days with very relevant anthropogenic emission aerosol sources. The results illustrate how the combination of aerosol emissions and meteorological conditions ultimately alters the aerosol radiative forcing.
Kristopher M. Bedka, Amin R. Nehrir, Michael Kavaya, Rory Barton-Grimley, Mark Beaubien, Brian Carroll, James Collins, John Cooney, G. David Emmitt, Steven Greco, Susan Kooi, Tsengdar Lee, Zhaoyan Liu, Sharon Rodier, and Gail Skofronick-Jackson
Atmos. Meas. Tech., 14, 4305–4334, https://doi.org/10.5194/amt-14-4305-2021, https://doi.org/10.5194/amt-14-4305-2021, 2021
Short summary
Short summary
This paper demonstrates the Doppler Aerosol WiNd (DAWN) lidar and High Altitude Lidar Observatory (HALO) measurement capabilities across a range of atmospheric conditions, compares DAWN and HALO measurements with Aeolus satellite Doppler wind lidar to gain an initial perspective of Aeolus performance, and discusses how atmospheric dynamic processes can be resolved and better understood through simultaneous observations of wind, water vapour, and aerosol profile observations.
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
Short summary
Short summary
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.
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3253–3276, https://doi.org/10.5194/amt-14-3253-2021, https://doi.org/10.5194/amt-14-3253-2021, 2021
Short summary
Short summary
The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results are presented in a companion paper (Part II).
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3277–3299, https://doi.org/10.5194/amt-14-3277-2021, https://doi.org/10.5194/amt-14-3277-2021, 2021
Short summary
Short summary
The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part II) shows retrievals over ocean and describes the improvements made with respect to version 3 as a result of the significant changes implemented in the version 4 algorithms, which are presented in a companion paper (Part I).
Thibault Vaillant de Guélis, Mark A. Vaughan, David M. Winker, and Zhaoyan Liu
Atmos. Meas. Tech., 14, 1593–1613, https://doi.org/10.5194/amt-14-1593-2021, https://doi.org/10.5194/amt-14-1593-2021, 2021
Short summary
Short summary
We introduce a new lidar feature detection algorithm that dramatically improves the fine details of layers identified in the CALIOP data. By applying our two-dimensional scanning technique to the measurements in all three channels, we minimize false positives while accurately identifying previously undetected features such as subvisible cirrus and the full vertical extent of dense smoke plumes. Multiple comparisons to version 4.2 CALIOP retrievals illustrate the scope of the improvements made.
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
Short summary
Short summary
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.
Yohei Shinozuka, Pablo E. Saide, Gonzalo A. Ferrada, Sharon P. Burton, Richard Ferrare, Sarah J. Doherty, Hamish Gordon, Karla Longo, Marc Mallet, Yan Feng, Qiaoqiao Wang, Yafang Cheng, Amie Dobracki, Steffen Freitag, Steven G. Howell, Samuel LeBlanc, Connor Flynn, Michal Segal-Rosenhaimer, Kristina Pistone, James R. Podolske, Eric J. Stith, Joseph Ryan Bennett, Gregory R. Carmichael, Arlindo da Silva, Ravi Govindaraju, Ruby Leung, Yang Zhang, Leonhard Pfister, Ju-Mee Ryoo, Jens Redemann, Robert Wood, and Paquita Zuidema
Atmos. Chem. Phys., 20, 11491–11526, https://doi.org/10.5194/acp-20-11491-2020, https://doi.org/10.5194/acp-20-11491-2020, 2020
Short summary
Short summary
In the southeast Atlantic, well-defined smoke plumes from Africa advect over marine boundary layer cloud decks; both are most extensive around September, when most of the smoke resides in the free troposphere. A framework is put forth for evaluating the performance of a range of global and regional atmospheric composition models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016.
Yohei Shinozuka, Meloë S. Kacenelenbogen, Sharon P. Burton, Steven G. Howell, Paquita Zuidema, Richard A. Ferrare, Samuel E. LeBlanc, Kristina Pistone, Stephen Broccardo, Jens Redemann, K. Sebastian Schmidt, Sabrina P. Cochrane, Marta Fenn, Steffen Freitag, Amie Dobracki, Michal Segal-Rosenheimer, and Connor J. Flynn
Atmos. Chem. Phys., 20, 11275–11285, https://doi.org/10.5194/acp-20-11275-2020, https://doi.org/10.5194/acp-20-11275-2020, 2020
Short summary
Short summary
To help satellite retrieval of aerosols and studies of their radiative effects, we demonstrate that daytime aerosol optical depth over low-level clouds is similar to that in neighboring clear skies at the same heights. Based on recent airborne lidar and sun photometer observations above the southeast Atlantic, the mean AOD difference at 532 nm is between 0 and -0.01, when comparing the cloudy and clear sides of cloud edges, with each up to 20 km wide.
Kirk Knobelspiesse, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, Anthony Cook, Antonio Di Noia, Bastiaan van Diedenhoven, David J. Diner, Richard Ferrare, Guangliang Fu, Meng Gao, Michael Garay, Johnathan Hair, David Harper, Gerard van Harten, Otto Hasekamp, Mark Helmlinger, Chris Hostetler, Olga Kalashnikova, Andrew Kupchock, Karla Longo De Freitas, Hal Maring, J. Vanderlei Martins, Brent McBride, Matthew McGill, Ken Norlin, Anin Puthukkudy, Brian Rheingans, Jeroen Rietjens, Felix C. Seidel, Arlindo da Silva, Martijn Smit, Snorre Stamnes, Qian Tan, Sebastian Val, Andrzej Wasilewski, Feng Xu, Xiaoguang Xu, and John Yorks
Earth Syst. Sci. Data, 12, 2183–2208, https://doi.org/10.5194/essd-12-2183-2020, https://doi.org/10.5194/essd-12-2183-2020, 2020
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Archer, C. L. and Jacobson, M. Z.: Evaluation of global wind power, J. Geophys. Res., 110, D12110, https://doi.org/10.1029/2004JD005462, 2005.
Avery, M. A., Ryan, R. A., Getzewich, B. J., Vaughan, M. A., Winker, D. M., Hu, Y., Garnier, A., Pelon, J., and Verhappen, C. A.: CALIOP V4 cloud thermodynamic phase assignment and the impact of near-nadir viewing angles, Atmos. Meas. Tech., 13, 4539–4563, https://doi.org/10.5194/amt-13-4539-2020, 2020.
Barrick, D.: Rough Surface Scattering Based on the Specular Point Theory, IEEE T. Antenn. Propag., 16, 449–454, https://doi.org/10.1109/TAP.1968.1139220, 1968.
Bevington, P. R. and Robinson, D. K.: Data Reduction and Error Analysis for the Physical Sciences, 2nd edn., McGraw-Hill, Boston, 328 pp., ISBN 0-07-911243-9, 1992.
Bufton, J. L., Hoge, F. E., and Swift, R. N.: Airborne measurements of laser backscatter from the ocean surface, Appl. Optics, 22, 2603–2618, https://doi.org/10.1364/AO.22.002603, 1983.
Burton S. P., Hostetler C. A., Cook A. L., Hair, J. W., Seaman, S. T., Scola, S., Harper, D. B., Smith, J. A., Fenn, M. A., Ferrare, R. A., Saide, P. E., Chemyakin, E. V., and Müller, D.: Calibration of a high spectral resolution lidar using a Michelson interferometer, with data examples from ORACLES, Appl. Optics, 57, 6061–6075, https://doi.org/10.1364/AO.57.006061, 2018.
Carling, K.: Resistant outlier rules and the non-Gaussian case, Comput. Stat. Data An., 33, 249–258, https://doi.org/10.1016/S0167-9473(99)00057-2, 2000.
Carvalho, D.: An Assessment of NASA's GMAO MERRA-2 Reanalysis Surface Winds, J. Climate, 32, 8261–8281, https://doi.org/10.1175/JCLI-D-19-0199.1, 2019.
Dierssen, H.: Hyperspectral Measurements, Parameterizations, and Atmospheric Correction of Whitecaps and Foam from Visible to Shortwave Infrared for Ocean Color Remote Sensing, Front. Earth Sci., 7, 14, https://doi.org/10.3389/feart.2019.00014, 2019.
Fernald, F. G., Herman, B. M., and Reagan, J. A.: Determination of Aerosol Height Distributions by Lidar, J. Appl. Meteorol. Clim., 11, 482–489, https://doi.org/10.1175/1520-0450(1972)011<0482:DOAHDB>2.0.CO;2, 1972.
Ferrare, R., Hair, J., Hostetler, C., Shingler, T., Burton, S. P., Fenn, M., Clayton, M., Scarino, A. J., Harper, D., Seaman, S., Cook, A., Crosbie, E., Winstead, E., Ziemba, L., Thornhill, L., Robinson, C., Moore, R., Vaughan, M., Sorooshian, A., Schlosser, J. S., Liu, H., Zhang, B., Diskin, G., DiGangi, J., Nowak, J., Choi Y., Zuidema, P., and Chellappan, S.: Airborne HSRL-2 measurements of elevated aerosol depolarization associated with non-spherical sea salt, Front. Remote Sens., 4, 1143944, https://doi.org/10.3389/frsen.2023.1143944, 2023.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Getzewich, B. J., Vaughan, M. A., Hunt, W. H., Avery, M. A., Powell, K. A., Tackett, J. L., Winker, D. M., Kar, J., Lee, K.-P., and Toth, T. D.: CALIPSO lidar calibration at 532 nm: version 4 daytime algorithm, Atmos. Meas. Tech., 11, 6309–6326, https://doi.org/10.5194/amt-11-6309-2018, 2018.
GMAO (Global Modeling and Assimilation Office): MERRA-2 inst1_2d_asm_Nx: 2d,1-Hourly,Instantaneous,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], Greenbelt, MD, USA, https://doi.org/10.5067/3Z173KIE2TPD, 2015a.
GMAO (Global Modeling and Assimilation Office): MERRA-2 inst3_3d_asm_Nv: 3d,3-Hourly, Instantaneous, Model-Level, Assimilation, Assimilated Meteorological Fields V5.12.4, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], Greenbelt, MD, USA, https://doi.org/10.5067/WWQSXQ8IVFW8, 2015b.
GMAO (Global Modeling and Assimilation Office): MERRA-2 tavg1_2d_slv_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4, Goddard Space Flight Center Distributed Active Archive Center (GSFC DAAC) [data set], Greenbelt, MD, USA, https://doi.org/10.5067/VJAFPLI1CSIV, 2015c.
Hair, J. W., Hostetler, C. A., Cook, A. L., Harper, D. B., Ferrare, R A., Mack, T. L., Welch, W., Izquierdo, L. R., and Hovis, F. E.: Airborne High Spectral Resolution Lidar for profiling aerosol optical properties, Appl. Optics., 47, 6734–6752, https://doi.org/10.1364/AO.47.006734, 2008.
He, M., Hu, Y., Huang, J. P., and Stamnes, K.: Aerosol optical depth under “clear” sky conditions derived from sea surface reflection of lidar signals, Opt. Express, 24, A1618–A1634, https://doi.org/10.1364/OE.24.0A1618, 2016.
Hlavka, D. L., Yorks, J. E., Young, S. A., Vaughan, M. A., Kuehn, R. E., McGill, M. J., and Rodier, S. D.: Airborne validation of cirrus cloud properties derived from CALIPSO lidar measurements: Optical properties, J. Geophys. Res., 117, D09207, https://doi.org/10.1029/2011JD017053, 2012.
Holz, R. E., Platnick, S., Meyer, K., Vaughan, M., Heidinger, A., Yang, P., Wind, G., Dutcher, S., Ackerman, S., Amarasinghe, N., Nagle, F., and Wang, C.: Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals, Atmos. Chem. Phys., 16, 5075–5090, https://doi.org/10.5194/acp-16-5075-2016, 2016.
Hostetler, C. A., Liu, Z., Reagan, J. A., Vaughan, M. A., Winker, D. M., Osborn, M. T., Hunt, W. H., Powell, K. A., and Trepte, C. R.: CALIPSO algorithm theoretical basis document, PC-SCI-201, http://www-calipso.larc.nasa.gov/resources/project_documentation.php (last access: 27 November 2023), 2005.
Hu, Y., Stamnes, K., Vaughan, M., Pelon, J., Weimer, C., Wu, D., Cisewski, M., Sun, W., Yang, P., Lin, B., Omar, A., Flittner, D., Hostetler, C., Trepte, C., Winker, D., Gibson, G., and Santa-Maria, M.: Sea surface wind speed estimation from space-based lidar measurements, Atmos. Chem. Phys., 8, 3593–3601, https://doi.org/10.5194/acp-8-3593-2008, 2008.
Hunt, W. H., Winker, D. M., Vaughan, M. A., Powell, K. A., Lucker, P. L., and Weimer, C.: CALIPSO Lidar Description and Performance Assessment, J. Atmos. Ocean. Tech., 26, 1214–1228, https://doi.org/10.1175/2009JTECHA1223.1, 2009.
Josset, D., Pelon, J., Protat, A., and Flamant, C.: New approach to determine aerosol optical depth from combined CALIPSO and CloudSat ocean surface echoes, Geophys. Res. Lett., 35, L10805, https://doi.org/10.1029/2008GL033442, 2008.
Josset, D., Pelon, J., and Hu, Y.: Multi-Instrument Calibration Method Based on a Multiwavelength Ocean Surface Model, IEEE Geosci. Remote S., 7, 195–199, https://doi.org/10.1109/LGRS.2009.2030906, 2010a.
Josset, D., Zhai, P., Hu, Y., Pelon, J., and Lucker, P. L.: Lidar equation for ocean surface and subsurface, Opt. Express, 18, 20862–20875, https://doi.org/10.1364/OE.18.020862, 2010b.
Josset, D., Pelon, J., Garnier, A., Hu, Y., Vaughan, M., Zhai, P.-W., Kuehn, R., and Lucker, P.: Cirrus optical depth and lidar ratio retrieval from combined CALIPSO-CloudSat observations using ocean surface echo, J. Geophys. Res., 117, D05207, https://doi.org/10.1029/2011JD016959, 2012.
Josset, D., Hou, W., Pelon, J., Hu, Y., Tanelli, S., Ferrare, R., Burton, S., and Pascal, N.: Ocean and polarization observations from active remote sensing: atmospheric and ocean science applications, in: Proc. SPIE 9459, Ocean Sensing and Monitoring VII, SPIE Defense + Security, 2015, Baltimore, MD, United States, SPIE Digital Library, 94590N, https://doi.org/10.1117/12.2181544, 2015.
Kar, J., Vaughan, M. A., Lee, K.-P., Tackett, J. L., Avery, M. A., Garnier, A., Getzewich, B. J., Hunt, W. H., Josset, D., Liu, Z., Lucker, P. L., Magill, B., Omar, A. H., Pelon, J., Rogers, R. R., Toth, T. D., Trepte, C. R., Vernier, J.-P., Winker, D. M., and Young, S. A.: CALIPSO lidar calibration at 532 nm: version 4 nighttime algorithm, Atmos. Meas. Tech., 11, 1459–1479, https://doi.org/10.5194/amt-11-1459-2018, 2018.
Kim, M.-H., Omar, A. H., Vaughan, M. A., Winker, D. M., Trepte, C. R., Hu, Y., Liu, Z., and Kim, S.-W.: Quantifying the low bias of CALIPSO's column aerosol optical depth due to undetected aerosol layers, J. Geophys. Res. Atmos., 122, 1098–1113, https://doi.org/10.1002/2016JD025797, 2017.
Kim, M.-H., Omar, A. H., Tackett, J. L., Vaughan, M. A., Winker, D. M., Trepte, C. R., Hu, Y., Liu, Z., Poole, L. R., Pitts, M. C., Kar, J., and Magill, B. E.: The CALIPSO version 4 automated aerosol classification and lidar ratio selection algorithm, Atmos. Meas. Tech., 11, 6107–6135, https://doi.org/10.5194/amt-11-6107-2018, 2018.
Lancaster, R. S., Spinhirne, J. D., and Palm, S. P.: Laser pulse reflectance of the ocean surface from the GLAS satellite lidar, Geophys. Res. Lett., 32, L22S10, https://doi.org/10.1029/2005GL023732, 2005.
Levy, R. and Hsu, C.: MODIS Atmosphere L2 Aerosol Product, NASA MODIS Adaptive Processing System, Goddard Space Flight Center [data set], USA, https://doi.org/10.5067/MODIS/MOD04_L2.061, 2015.
Levy, R., Remer, L., Tanré, D., Mattoo, S., and Kaufman, Y.: Algorithm for Remote Sensing of Tropospheric Aerosol Over Dark Targets from MODIS, https://atmosphere-imager.gsfc.nasa.gov/sites/default/files/ModAtmo/ATBD_MOD04_C005_rev2_0.pdf (last access: 5 June 2024), 2009.
Liu, Z., Fairlie, T., Uno, I., Huang, J., Wu, D., Omar, A., Kar, J., Vaughan, M., Rogers, R., Winker, D., Trepte, C., Hu, Y., Sun, W., Lin, B., and Cheng, A.: Transpacific Transport and Evolution of the Optical Properties of Asian Dust, J. Quant. Spectrosc. Ra., 116, 24–33, https://doi.org/10.1016/j.jqsrt.2012.11.011, 2013.
Liu, Z., Kar, J., Zeng, S., Tackett, J., Vaughan, M., Avery, M., Pelon, J., Getzewich, B., Lee, K.-P., Magill, B., Omar, A., Lucker, P., Trepte, C., and Winker, D.: Discriminating between clouds and aerosols in the CALIOP version 4.1 data products, Atmos. Meas. Tech., 12, 703–734, https://doi.org/10.5194/amt-12-703-2019, 2019.
Lu, X., Hu, Y., Liu, Z., Rodier, S., Vaughan, M., Trepte, C., and Pelon, J.: Observations of Arctic snow and sea ice cover from CALIOP lidar measurements, Remote Sens. Environ., 194, 248–263, https://doi.org/10.1016/j.rse.2017.03.046, 2017.
McGill, M. J., Vaughan, M. A., Trepte, C. R., Hart, W. D., Hlavka, D. L., Winker, D. M., and Kuehn, R.: Airborne validation of spatial properties measured by the CALIPSO lidar, J. Geophys. Res., 112, D20201, https://doi.org/10.1029/2007JD008768. 2007.
MCST (MODIS Characterization Support Team): MODIS Geolocation Fields Product, NASA MODIS Adaptive Processing System, Goddard Space Flight Center [data set], USA, https://doi.org/10.5067/MODIS/MYD03.061, 2017.
Menzies, R. T., Tratt, D. M., and Hunt, W. H.: Lidar In-space Technology Experiment measurements of sea surface directional reflectance and the link to surface wind speed, Appl. Optics., 37, 5550–5559, 1998.
Nagle, F. W. and Holz, R. E.: Computationally Efficient Methods of Collocating Satellite, Aircraft, and Ground Observations, J. Atmos. Ocean. Tech., 26, 1585–1595, https://doi.org/10.1175/2008JTECHA1189.1, 2009.
NASA/LARC/SD/ASDC: CALIPSO Night Validation Flights High Spectral Resolution Lidar (HSRL-2) Data, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/SUBORBITAL/CALIPSO-NVF/DATA001, 2023.
NASA/LARC/SD/ASDC: CALIPSO Lidar Level 1B profile data, V4-51, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L1-Standard-V4-51, 2024a.
NASA/LARC/SD/ASDC: CALIPSO Lidar Level 2 5 km Merged Layer, V4-51, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L2_05kmMLay-Standard-V4-51, 2024b.
NASA/LARC/SD/ASDC: CALIPSO Lidar Level 2 Vertical Feature Mask (VFM), V4-51, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L2_VFM-Standard-V4-51, 2024c.
Powell, K. A., Hostetler, C. A., Vaughan, M. A., Lee, K., Trepte, C. R., Rogers, R. R., Winker, D. M., Liu, Z., Kuehn, R. E., Hunt, W. H., and Young, S. A.: CALIPSO Lidar Calibration Algorithms. Part I: Nighttime 532-nm Parallel Channel and 532-nm Perpendicular Channel, J. Atmos. Ocean. Tech., 26, 2015–2033, https://doi.org/10.1175/2009JTECHA1242.1, 2009.
Reagan, J. A. and Zielinskie, D. A.: Spaceborne lidar remote sensing techniques aided by surface returns, Opt. Eng., 30, 96–102, https://doi.org/10.1117/12.55776, 1991.
Reid, J. S., Gumber, A., Zhang, J., Holz, R. E., Rubin, J. I., Xian, P., Smirnov, A., Eck, T. F., O'Neill, N. T., Levy, R. C., Reid, E. A., Colarco, P. R., Benedetti, A., and Tanaka, T. A.: Coupled Evaluation of Operational MODIS and Model Aerosol Products for Maritime Environments Using Sun Photometry: Evaluation of the Fine and Coarse Mode, Remote Sens.-Basel, 14, 2978, https://doi.org/10.3390/rs14132978, 2022.
Ridley, D. A., Heald, C. L., and Ford, B.: North African dust export and deposition: A satellite and model perspective, J. Geophys. Res., 117, D02202, https://doi.org/10.1029/2011JD016794, 2012.
Rogers, R. R., Hair, J. W., Hostetler, C. A., Ferrare, R. A., Obland, M. D., Cook, A. L., Harper, D. B., Burton, S. P., Shinozuka, Y., McNaughton, C. S., Clarke, A. D., Redemann, J., Russell, P. B., Livingston, J. M., and Kleinman, L. I.: NASA LaRC airborne high spectral resolution lidar aerosol measurements during MILAGRO: observations and validation, Atmos. Chem. Phys., 9, 4811–4826, https://doi.org/10.5194/acp-9-4811-2009, 2009.
Sinha, P., Jaeglé, L., Hobbs, P. V., and Liang, Q.: Transport of biomass burning emissions from southern Africa, J. Geophys. Res., 109, D20204, https://doi.org/10.1029/2004JD005044, 2004.
Spencer, R. S., Levy, R. C., Remer, L. A., Mattoo, S., Arnold, G. T., Hlavka, D. L., Meyer, K. G., Marshak, A., Wilcox, E. M., and Platnick, S. E.: Exploring aerosols near clouds with high-spatial-resolution aircraft remote sensing during SEAC4RS, J. Geophys. Res.-Atmos., 124, 2148–2173, https://doi.org/10.1029/2018JD028989, 2019.
Sawamura, P., Moore, R. H., Burton, S. P., Chemyakin, E., Müller, D., Kolgotin, A., Ferrare, R. A., Hostetler, C. A., Ziemba, L. D., Beyersdorf, A. J., and Anderson, B. E.: HSRL-2 aerosol optical measurements and microphysical retrievals vs. airborne in situ measurements during DISCOVER-AQ 2013: an intercomparison study, Atmos. Chem. Phys., 17, 7229–7243, https://doi.org/10.5194/acp-17-7229-2017, 2017.
Tackett, J. L., Winker, D. M., Getzewich, B. J., Vaughan, M. A., Young, S. A., and Kar, J.: CALIPSO lidar level 3 aerosol profile product: version 3 algorithm design, Atmos. Meas. Tech., 11, 4129–4152, https://doi.org/10.5194/amt-11-4129-2018, 2018.
Tanelli, S., Durden, S. L., Im, E., Pak, K. S., Reinke, D. G., Partain, P., Haynes, J. M., and Marchand, R. T.: CloudSat's Cloud Profiling Radar After Two Years in Orbit: Performance, Calibration, and Processing, IEEE T. Geosci. Remote, 46, 3560–3573, https://doi.org/10.1109/TGRS.2008.2002030, 2008.
Thorsen, T. J., Ferrare, R. A., Hostetler, C. A., Vaughan, M. A., and Fu, Q.: The impact of lidar detection sensitivity on assessing aerosol direct radiative effects, Geophys. Res. Lett., 44, 9059–9067, https://doi.org/10.1002/2017GL074521, 2017.
Thorsen, T. J., Ryan, R. A., and Vaughan, M. A.: Validation of Aerosol Optical Depth Retrieved from CALIPSO Lidar Ocean Surface Backscatter, in preparation, 2024.
Toth, T. D., Campbell, J. R., Reid, J. S., Tackett, J. L., Vaughan, M. A., Zhang, J., and Marquis, J. W.: Minimum aerosol layer detection sensitivities and their subsequent impacts on aerosol optical thickness retrievals in CALIPSO level 2 data products, Atmos. Meas. Tech., 11, 499–514, https://doi.org/10.5194/amt-11-499-2018, 2018.
Vaughan, M., Garnier, A., Tackett, J., Avery, M., Young, S., Kar, J., Getzewich, B., Omar, A., Liu, Z., Lee, K., Cai, X., Zeng, S., Hu, Y., Lambeth, J., Ryan, R., Magill, B., Rodier, S., Murray, T., Beaumont, K., and Trepte, C.: Introducing CALIPSO's Version 4 Level 2 Lidar Data Products, in: 28th International Laser Radar Conference (ILRC), Bucharest, Romania, June 2017, 25–30, 2017.
Vaughan, M., Garnier, A., Josset, D., Avery, M., Lee, K.-P., Liu, Z., Hunt, W., Pelon, J., Hu, Y., Burton, S., Hair, J., Tackett, J. L., Getzewich, B., Kar, J., and Rodier, S.: CALIPSO lidar calibration at 1064 nm: version 4 algorithm, Atmos. Meas. Tech., 12, 51–82, https://doi.org/10.5194/amt-12-51-2019, 2019.
Vaughan, M., Pitts, M., Trepte, C., Winker, D., Getzewich, B., Tackett, J., Cai, X., Garnier, A., Ker, J., Lee, K.-P., Lucker, P., Detweiler, P., Lambeth, J., Murray, T., Rodier, S., Ryan, R., Tremas, T., Pelon, J., and Flamant, C.: Cloud-Aerosol LIDAR Infrared Pathfinder Satellite Observations (CALIPSO) data management system data products catalog, Release 4.97, NASA Langley Research Center Document PC-SCI-503, https://www-calipso.larc.nasa.gov/products/CALIPSO_DPC_Rev4x97.pdf (last access: 28 June 2024), 2024.
Vaughan, M. A., Powell, K. A., Winker, D. M., Hostetler, C. A., Kuehn, R. E., Hunt, W. H., Getzewich, B. J., Young, S. A., Liu, Z., and McGill, M. J.: Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar Measurements, J. Atmos. Ocean. Tech., 26, 2034–2050, https://doi.org/10.1175/2009JTECHA1228.1, 2009.
Venkata, S. L. and Reagan, J. A.: Aerosol Retrievals from CALIPSO Lidar Ocean Surface Returns, Remote Sens.-Basel, 8, 1006, https://doi.org/10.3390/rs8121006, 2016.
Wentz, F. J., Gentemann C. L., and Hilburn K.: Three years of ocean products from AMSR-E: Evaluation and applications, in: Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005, IGARSS '05, Seoul, South Korea, 29–29 July 2005, IEEE, 4929–4932, https://doi.org/10.1109/IGARSS.2005.1526780, 2005.
Wentz, F. J., Meissner, T., Gentemann, C., and Brewer, M.: RSS AQUA AMSR-E Daily Environmental Suite on 0.25 deg grid, Version 7, Remote Sensing Systems [data set], Santa Rosa, CA, USA, https://doi.org/10.56236/RSS-bm, 2014.
Wentz, F. J., Meissner, T., Gentemann, C., Hilburn, K. A., and Scott, J.: RSS GCOM-W1 AMSR2 Daily Environmental Suite on 0.25 deg grid, Version 8.2, Remote Sensing Systems [data set], Santa Rosa, CA, USA, https://doi.org/10.56236/RSS-bq, 2021.
Winker, D., Cai, X., Vaughan, M., Garnier, A., Magill, B., Avery, M., and Getzewich, B.: A Level 3 monthly gridded ice cloud dataset derived from 12 years of CALIOP measurements, Earth Syst. Sci. Data, 16, 2831–2855, https://doi.org/10.5194/essd-16-2831-2024, 2024.
Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z., Hunt, W. H., and Young, S. A.: Overview of the CALIPSO Mission and CALIOP Data Processing Algorithms, J. Atmos. Ocean. Tech., 26, 2310–2323, https://doi.org/10.1175/2009JTECHA1281.1, 2009.
Winker, D. M., Pelon, J., Coakley Jr., J. A., Ackerman, S. A., Charlson, R. J., Colarco, P. R., Flamant, P., Fu, Q., Hoff, R. M., Kittaka, C., Kubar, T. L., Le Treut, H., McCormick, M. P., Mégie, G., Poole, L., Powell, K., Trepte, C., Vaughan, M. A., and Wielicki, B. A.: The CALIPSO Mission, B. Am. Meteorol. Soc., 91, 1211–1230, https://doi.org/10.1175/2010BAMS3009.1, 2010.
Young, S. A. and Vaughan, M. A.: The Retrieval of Profiles of Particulate Extinction from Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) Data: Algorithm Description, J. Atmos. Ocean. Tech., 26, 1105–1119, https://doi.org/10.1175/2008JTECHA1221.1, 2009.
Young, S. A., Vaughan, M. A., Kuehn, R. E., and Winker, D. M.: The Retrieval of Profiles of Particulate Extinction from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Data: Uncertainty and Error Sensitivity Analyses, J. Atmos. Ocean. Tech., 30, 395–428, https://doi.org/10.1175/JTECH-D-12-00046.1, 2013.
Young, S. A., Vaughan, M. A., Garnier, A., Tackett, J. L., Lambeth, J. D., and Powell, K. A.: Extinction and optical depth retrievals for CALIPSO's Version 4 data release, Atmos. Meas. Tech., 11, 5701–5727, https://doi.org/10.5194/amt-11-5701-2018, 2018.
Yu, H., Zhang, Y., Chin, M., Liu, Z., Omar, A., Remer, L., Yang, Y., Yuan, T., and Zhang, J.: An integrated analysis of aerosol above clouds from A-Train multi-sensor measurements, Remote Sens. Environ., 121, 125–131, https://doi.org/10.1016/j.rse.2012.01.011, 2012.
Short summary
We introduce Ocean Derived Column Optical Depth (ODCOD), a new way to estimate column optical depths using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements from the ocean surface. ODCOD estimates include contributions from particulates in the full column, which CALIOP estimates do not, making it a complement measurement to CALIOP’s standard estimates. We find that ODCOD compares well with other established data sets in the daytime but tends to estimate higher at night.
We introduce Ocean Derived Column Optical Depth (ODCOD), a new way to estimate column optical...
