Articles | Volume 13, issue 7
https://doi.org/10.5194/amt-13-3939-2020
© Author(s) 2020. 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-13-3939-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jul 2020
Research article |
| 22 Jul 2020
| 22 Jul 2020
Inversion of multiangular polarimetric measurements from the ACEPOL campaign: an application of improving aerosol property and hyperspectral ocean color retrievals
SSAI, NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
Peng-Wang Zhai
JCET, Physics Department, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
Bryan A. Franz
NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
Kirk Knobelspiesse
NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
Amir Ibrahim
SSAI, NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
Brian Cairns
NASA Goddard Institute for Space Studies, New York, NY 10025, USA
Susanne E. Craig
Universities Space Research Association, NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
Guangliang Fu
Netherlands Institute for Space Research (SRON, NWO-I), Utrecht, the Netherlands
Otto Hasekamp
Netherlands Institute for Space Research (SRON, NWO-I), Utrecht, the Netherlands
Yongxiang Hu
MS 475 NASA Langley Research Center, Hampton, VA 23681-2199, USA
P. Jeremy Werdell
NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
Related authors
Sean R. Foley, Kirk D. Knobelspiesse, Andrew M. Sayer, Meng Gao, James Hays, and Judy Hoffman
Atmos. Meas. Tech., 17, 7027–7047, https://doi.org/10.5194/amt-17-7027-2024, https://doi.org/10.5194/amt-17-7027-2024, 2024
Short summary
Short summary
Measuring the shape of clouds helps scientists understand how the Earth will continue to respond to climate change. Satellites measure clouds in different ways. One way is to take pictures of clouds from multiple angles and to use the differences between the pictures to measure cloud structure. However, doing this accurately can be challenging. We propose a way to use machine learning to recover the shape of clouds from multi-angle satellite data.
Meng Gao, Bryan A. Franz, Peng-Wang Zhai, Kirk Knobelspiesse, Andrew M. Sayer, Xiaoguang Xu, J. Vanderlei Martins, Brian Cairns, Patricia Castellanos, Guangliang Fu, Neranga Hannadige, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Frederick Patt, Anin Puthukkudy, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 5863–5881, https://doi.org/10.5194/amt-16-5863-2023, https://doi.org/10.5194/amt-16-5863-2023, 2023
Short summary
Short summary
This study evaluated the retrievability and uncertainty of aerosol and ocean properties from PACE's HARP2 instrument using enhanced neural network models with the FastMAPOL algorithm. A cascading retrieval method is developed to improve retrieval performance. A global set of simulated HARP2 data is generated and used for uncertainty evaluations. The performance assessment demonstrates that the FastMAPOL algorithm is a viable approach for operational application to HARP2 data after PACE launch.
Neranga K. Hannadige, Peng-Wang Zhai, Meng Gao, Yongxiang Hu, P. Jeremy Werdell, Kirk Knobelspiesse, and Brian Cairns
Atmos. Meas. Tech., 16, 5749–5770, https://doi.org/10.5194/amt-16-5749-2023, https://doi.org/10.5194/amt-16-5749-2023, 2023
Short summary
Short summary
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 three- and seven-parameter bio-optical models can be used to accurately represent both open and coastal waters, whereas the one-parameter model has smaller retrieval uncertainty over open water.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Brian Cairns, Xiaoguang Xu, and J. Vanderlei Martins
Atmos. Meas. Tech., 16, 2067–2087, https://doi.org/10.5194/amt-16-2067-2023, https://doi.org/10.5194/amt-16-2067-2023, 2023
Short summary
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.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 15, 4859–4879, https://doi.org/10.5194/amt-15-4859-2022, https://doi.org/10.5194/amt-15-4859-2022, 2022
Short summary
Short summary
In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
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.
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
Short summary
Short summary
We assessed atmospheric aerosol and ocean surface wind speed remote sensing capability with NASA's Multi-angle Imaging SpectroRadiometer (MISR), using synthetic data and a Bayesian inference technique called generalized nonlinear retrieval analysis (GENRA). We found success using three aerosol parameters plus wind speed. This shows that MISR can perform an atmospheric correction for the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same spacecraft (Terra).
Kirk Knobelspiesse, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, Anthony Cook, Antonio Di Noia, Bastiaan van Diedenhoven, David J. Diner, Richard Ferrare, Guangliang Fu, Meng Gao, Michael Garay, Johnathan Hair, David Harper, Gerard van Harten, Otto Hasekamp, Mark Helmlinger, Chris Hostetler, Olga Kalashnikova, Andrew Kupchock, Karla Longo De Freitas, Hal Maring, J. Vanderlei Martins, Brent McBride, Matthew McGill, Ken Norlin, Anin Puthukkudy, Brian Rheingans, Jeroen Rietjens, Felix C. Seidel, Arlindo da Silva, Martijn Smit, Snorre Stamnes, Qian Tan, Sebastian Val, Andrzej Wasilewski, Feng Xu, Xiaoguang Xu, and John Yorks
Earth Syst. Sci. Data, 12, 2183–2208, https://doi.org/10.5194/essd-12-2183-2020, https://doi.org/10.5194/essd-12-2183-2020, 2020
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Yusuf Bhatti, Duncan Watson-Parris, Leighton Regayre, Hailing Jia, David Neubauer, Ulas Im, Carl Svenhag, Nick Schutgens, Athanasios Tsikerdekis, Athanasios Nenes, Irfan Muhammed, Bastiaan van Diedenhoven, Ardit Arifi, Guangliang Fu, and Otto Hasekamp
EGUsphere, https://doi.org/10.5194/egusphere-2025-2848, https://doi.org/10.5194/egusphere-2025-2848, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Aerosols (small airborne particles) impact Earth's climate, but their extent is unknown. By running climate model simulations and emulating millions of additional variants with different settings, we found that natural emissions like sea spray and sulfur are key sources of uncertainty in climate predictions. Our work shows that understanding these natural processes better can help improve climate models and make future climate projections more accurate.
Andrew M. Sayer, Brian Cairns, Kirk D. Knobelspiesse, Luca Lelli, Chamara Rajapakshe, Scott E. Giangrande, Gareth E. Thomas, and Damao Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-2005, https://doi.org/10.5194/egusphere-2025-2005, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
Satellites can estimate cloud height in several ways: two include a thermal technique (colder clouds being higher up), and another looking at colours of light that oxygen in the atmosphere absorbs (darker clouds being lower down). It can also be measured (from ground or space) by radar and lidar. We compare satellite data we developed using the oxygen method with other estimates to help us refine our technique.
Florian Tornow, Ann Fridlind, George Tselioudis, Brian Cairns, Andrew Ackerman, Seethala Chellappan, David Painemal, Paquita Zuidema, Christiane Voigt, Simon Kirschler, and Armin Sorooshian
Atmos. Chem. Phys., 25, 5053–5074, https://doi.org/10.5194/acp-25-5053-2025, https://doi.org/10.5194/acp-25-5053-2025, 2025
Short summary
Short summary
The recent NASA campaign ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment) performed 71 tandem flights in mid-latitude marine cold-air outbreaks off the US eastern seaboard. We provide meteorological and cloud transition stage context, allowing us to identify days that are most suitable for Lagrangian modeling and analysis. Surveyed cloud properties show signatures of cloud microphysical processes, such as cloud-top entrainment and secondary ice formation.
Zihao Yuan, Guangliang Fu, Hai Xiang Lin, Jan Willem Erisman, and Otto P. Hasekamp
EGUsphere, https://doi.org/10.5194/egusphere-2025-1488, https://doi.org/10.5194/egusphere-2025-1488, 2025
Short summary
Short summary
This work develops an Neural-Network-based above cloud aerosol (ACA) detection and retrieval scheme for multi-angular polarimetric (MAP) instruments. On one year of PARASOL data, the retrieved aerosol properties (aerosol optical thickness, AOT, Angstrom Exponent, AE, and Single Scattering Albedo, SSA) agree well with adjacent clear-sky RemoTAP-PARASOL aerosol retrievals. The seasonal global pattern of ACA events and above cloud AOT are also within expectation.
Kerry Meyer, Steven Platnick, G. Thomas Arnold, Nandana Amarasinghe, Daniel Miller, Jennifer Small-Griswold, Mikael Witte, Brian Cairns, Siddhant Gupta, Greg McFarquhar, and Joseph O'Brien
Atmos. Meas. Tech., 18, 981–1011, https://doi.org/10.5194/amt-18-981-2025, https://doi.org/10.5194/amt-18-981-2025, 2025
Short summary
Short summary
Satellite remote sensing retrievals of cloud droplet size are used to understand clouds and their interactions with aerosols and radiation but require many simplifying assumptions. Evaluation of these retrievals is typically done by comparing against direct measurements of droplets from airborne cloud probes. This paper details an evaluation of proxy airborne remote sensing droplet size retrievals against several cloud probes and explores the impact of key assumptions on retrieval agreement.
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.
Sean R. Foley, Kirk D. Knobelspiesse, Andrew M. Sayer, Meng Gao, James Hays, and Judy Hoffman
Atmos. Meas. Tech., 17, 7027–7047, https://doi.org/10.5194/amt-17-7027-2024, https://doi.org/10.5194/amt-17-7027-2024, 2024
Short summary
Short summary
Measuring the shape of clouds helps scientists understand how the Earth will continue to respond to climate change. Satellites measure clouds in different ways. One way is to take pictures of clouds from multiple angles and to use the differences between the pictures to measure cloud structure. However, doing this accurately can be challenging. We propose a way to use machine learning to recover the shape of clouds from multi-angle satellite data.
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.
Brent A. McBride, J. Vanderlei Martins, J. Dominik Cieslak, Roberto Fernandez-Borda, Anin Puthukkudy, Xiaoguang Xu, Noah Sienkiewicz, Brian Cairns, and Henrique M. J. Barbosa
Atmos. Meas. Tech., 17, 5709–5729, https://doi.org/10.5194/amt-17-5709-2024, https://doi.org/10.5194/amt-17-5709-2024, 2024
Short summary
Short summary
The Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) is a new Earth-observing instrument that provides highly accurate measurements of the atmosphere and surface. Using a physics-based calibration technique, we show that AirHARP achieves high measurement accuracy in laboratory and field environments and exceeds a benchmark accuracy requirement for modern aerosol and cloud climate observations. Therefore, the HARP design is highly attractive for upcoming NASA climate missions.
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024, https://doi.org/10.5194/amt-17-3583-2024, 2024
Short summary
Short summary
This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.
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.
Zihao Yuan, Guangliang Fu, Bastiaan van Diedenhoven, Hai Xiang Lin, Jan Willem Erisman, and Otto P. Hasekamp
Atmos. Meas. Tech., 17, 2595–2610, https://doi.org/10.5194/amt-17-2595-2024, https://doi.org/10.5194/amt-17-2595-2024, 2024
Short summary
Short summary
Currently, aerosol properties from spaceborne multi-angle polarimeter (MAP) instruments can only be retrieved in cloud-free areas or in areas where an aerosol layer is located above a cloud. Therefore, it is important to be able to identify cloud-free pixels for which an aerosol retrieval algorithm can provide meaningful output. The developed neural network cloud screening demonstrates that cloud masking for MAP aerosol retrieval can be based on the MAP measurements themselves.
Otto Hasekamp, Pavel Litvinov, Guangliang Fu, Cheng Chen, and Oleg Dubovik
Atmos. Meas. Tech., 17, 1497–1525, https://doi.org/10.5194/amt-17-1497-2024, https://doi.org/10.5194/amt-17-1497-2024, 2024
Short summary
Short summary
Aerosols are particles in the atmosphere that cool the climate by reflecting and absorbing sunlight (direct effect) and changing cloud properties (indirect effect). The scale of aerosol cooling is uncertain, hampering accurate climate predictions. We compare two algorithms for the retrieval of aerosol properties from multi-angle polarimetric measurements: Generalized Retrieval of Atmosphere and Surface Properties (GRASP) and Remote sensing of Trace gas and Aerosol Products (RemoTAP).
Zihan Zhang, Guangliang Fu, and Otto Hasekamp
Atmos. Meas. Tech., 16, 6051–6063, https://doi.org/10.5194/amt-16-6051-2023, https://doi.org/10.5194/amt-16-6051-2023, 2023
Short summary
Short summary
In order to conduct accurate aerosol retrieval over snow, the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) algorithm is extended with a bi-directional reflection distribution function for snow surfaces. The experiments with both synthetic and real data show that the extended RemoTAP maintains capability for snow-free pixels and has obvious advantages in accuracy and the fraction of successful retrievals for retrieval over snow, especially over surfaces with snow cover > 75 %.
Meng Gao, Bryan A. Franz, Peng-Wang Zhai, Kirk Knobelspiesse, Andrew M. Sayer, Xiaoguang Xu, J. Vanderlei Martins, Brian Cairns, Patricia Castellanos, Guangliang Fu, Neranga Hannadige, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Frederick Patt, Anin Puthukkudy, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 5863–5881, https://doi.org/10.5194/amt-16-5863-2023, https://doi.org/10.5194/amt-16-5863-2023, 2023
Short summary
Short summary
This study evaluated the retrievability and uncertainty of aerosol and ocean properties from PACE's HARP2 instrument using enhanced neural network models with the FastMAPOL algorithm. A cascading retrieval method is developed to improve retrieval performance. A global set of simulated HARP2 data is generated and used for uncertainty evaluations. The performance assessment demonstrates that the FastMAPOL algorithm is a viable approach for operational application to HARP2 data after PACE launch.
Neranga K. Hannadige, Peng-Wang Zhai, Meng Gao, Yongxiang Hu, P. Jeremy Werdell, Kirk Knobelspiesse, and Brian Cairns
Atmos. Meas. Tech., 16, 5749–5770, https://doi.org/10.5194/amt-16-5749-2023, https://doi.org/10.5194/amt-16-5749-2023, 2023
Short summary
Short summary
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 three- and seven-parameter bio-optical models can be used to accurately represent both open and coastal waters, whereas the one-parameter model has smaller retrieval uncertainty over open water.
Athanasios Tsikerdekis, Otto P. Hasekamp, Nick A. J. Schutgens, and Qirui Zhong
Atmos. Chem. Phys., 23, 9495–9524, https://doi.org/10.5194/acp-23-9495-2023, https://doi.org/10.5194/acp-23-9495-2023, 2023
Short summary
Short summary
Aerosols are tiny particles of different substances (species) that can be emitted into the atmosphere by natural processes or by anthropogenic activities. However, the actual aerosol emission amount per species is highly uncertain. Thus in this work we correct the aerosol emissions used to drive a global aerosol–climate model using satellite observations through a process called data assimilation. These more accurate aerosol emissions can lead to a more accurate weather and climate prediction.
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.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Brian Cairns, Xiaoguang Xu, and J. Vanderlei Martins
Atmos. Meas. Tech., 16, 2067–2087, https://doi.org/10.5194/amt-16-2067-2023, https://doi.org/10.5194/amt-16-2067-2023, 2023
Short summary
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.
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.
Edward Gryspeerdt, Adam C. Povey, Roy G. Grainger, Otto Hasekamp, N. Christina Hsu, Jane P. Mulcahy, Andrew M. Sayer, and Armin Sorooshian
Atmos. Chem. Phys., 23, 4115–4122, https://doi.org/10.5194/acp-23-4115-2023, https://doi.org/10.5194/acp-23-4115-2023, 2023
Short summary
Short summary
The impact of aerosols on clouds is one of the largest uncertainties in the human forcing of the climate. Aerosol can increase the concentrations of droplets in clouds, but observational and model studies produce widely varying estimates of this effect. We show that these estimates can be reconciled if only polluted clouds are studied, but this is insufficient to constrain the climate impact of aerosol. The uncertainty in aerosol impact on clouds is currently driven by cases with little aerosol.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
Short summary
Short summary
We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Andrew M. Sayer, Luca Lelli, Brian Cairns, Bastiaan van Diedenhoven, Amir Ibrahim, Kirk D. Knobelspiesse, Sergey Korkin, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 969–996, https://doi.org/10.5194/amt-16-969-2023, https://doi.org/10.5194/amt-16-969-2023, 2023
Short summary
Short summary
This paper presents a method to estimate the height of the top of clouds above Earth's surface using satellite measurements. It is based on light absorption by oxygen in Earth's atmosphere, which darkens the signal that a satellite will see at certain wavelengths of light. Clouds "shield" the satellite from some of this darkening, dependent on cloud height (and other factors), because clouds scatter light at these wavelengths. The method will be applied to the future NASA PACE mission.
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Thomas Jackson, Andrei Chuprin, Malcolm Taberner, Ruth Airs, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Yngve Borsheim, Astrid Bracher, Vittorio Brando, Robert J. W. Brewin, Elisabetta Canuti, Francisco P. Chavez, Andrés Cianca, Hervé Claustre, Lesley Clementson, Richard Crout, Afonso Ferreira, Scott Freeman, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Ralf Goericke, Richard Gould, Nathalie Guillocheau, Stanford B. Hooker, Chuamin Hu, Mati Kahru, Milton Kampel, Holger Klein, Susanne Kratzer, Raphael Kudela, Jesus Ledesma, Steven Lohrenz, Hubert Loisel, Antonio Mannino, Victor Martinez-Vicente, Patricia Matrai, David McKee, Brian G. Mitchell, Tiffany Moisan, Enrique Montes, Frank Muller-Karger, Aimee Neeley, Michael Novak, Leonie O'Dowd, Michael Ondrusek, Trevor Platt, Alex J. Poulton, Michel Repecaud, Rüdiger Röttgers, Thomas Schroeder, Timothy Smyth, Denise Smythe-Wright, Heidi M. Sosik, Crystal Thomas, Rob Thomas, Gavin Tilstone, Andreia Tracana, Michael Twardowski, Vincenzo Vellucci, Kenneth Voss, Jeremy Werdell, Marcel Wernand, Bozena Wojtasiewicz, Simon Wright, and Giuseppe Zibordi
Earth Syst. Sci. Data, 14, 5737–5770, https://doi.org/10.5194/essd-14-5737-2022, https://doi.org/10.5194/essd-14-5737-2022, 2022
Short summary
Short summary
A compiled set of in situ data is vital to evaluate the quality of ocean-colour satellite data records. Here we describe the global compilation of bio-optical in situ data (spanning from 1997 to 2021) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Bastiaan van Diedenhoven, Otto P. Hasekamp, Brian Cairns, Gregory L. Schuster, Snorre Stamnes, Michael Shook, and Luke Ziemba
Atmos. Meas. Tech., 15, 7411–7434, https://doi.org/10.5194/amt-15-7411-2022, https://doi.org/10.5194/amt-15-7411-2022, 2022
Short summary
Short summary
The strong variability in the chemistry of atmospheric particulate matter affects the amount of water aerosols absorb and their effect on climate. We present a remote sensing method to determine the amount of water in particulate matter. Its application to airborne instruments indicates that the observed aerosols have rather low water contents and low fractions of soluble particles. Future satellites will be able to yield global aerosol water uptake data.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, Andre Butz, Otto P. Hasekamp, Lianghai Wu, and Jochen Landgraf
Atmos. Meas. Tech., 15, 6585–6603, https://doi.org/10.5194/amt-15-6585-2022, https://doi.org/10.5194/amt-15-6585-2022, 2022
Short summary
Short summary
The TROPOspheric Monitoring Instrument (TROPOMI) performs observations over ocean in every orbit, enhancing the monitoring capabilities of methane from space. In the sun glint geometry the mirror-like reflection at the water surface provides a signal that is high enough to retrieve methane with high accuracy and precision. We present 4 years of methane concentrations over the ocean, and we assess its quality. We also show the importance of ocean observations to quantify total CH4 emissions.
Santiago Gassó and Kirk D. Knobelspiesse
Atmos. Chem. Phys., 22, 13581–13605, https://doi.org/10.5194/acp-22-13581-2022, https://doi.org/10.5194/acp-22-13581-2022, 2022
Short summary
Short summary
Atmospheric particles interact with light resulting in observable optical polarization. Thus, we can learn about their composition from space. New satellite sensor technology measures full polarization of reflected sunlight. This paper considers circular polarization, an overlooked category of polarization with distinctive features that could bring new insights. We review existing literature and make novel computations to consider this previously underappreciated category of polarization.
Matthieu Dogniaux, Cyril Crevoisier, Silvère Gousset, Étienne Le Coarer, Yann Ferrec, Laurence Croizé, Lianghai Wu, Otto Hasekamp, Bojan Sic, and Laure Brooker
Atmos. Meas. Tech., 15, 4835–4858, https://doi.org/10.5194/amt-15-4835-2022, https://doi.org/10.5194/amt-15-4835-2022, 2022
Short summary
Short summary
The Space Carbon Observatory (SCARBO) concept proposes a constellation of small satellites that would carry a miniaturized Fabry–Pérot imaging interferometer named NanoCarb and an aerosol instrument named SPEXone. In this work, we assess the performance of this concept for the retrieval of the total weighted columns of CO2 and CH4 and show the interest of adding the SPEXone aerosol instrument to improve the CO2 and CH4 column retrieval.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 15, 4859–4879, https://doi.org/10.5194/amt-15-4859-2022, https://doi.org/10.5194/amt-15-4859-2022, 2022
Short summary
Short summary
In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
Dongwei Fu, Larry Di Girolamo, Robert M. Rauber, Greg M. McFarquhar, Stephen W. Nesbitt, Jesse Loveridge, Yulan Hong, Bastiaan van Diedenhoven, Brian Cairns, Mikhail D. Alexandrov, Paul Lawson, Sarah Woods, Simone Tanelli, Sebastian Schmidt, Chris Hostetler, and Amy Jo Scarino
Atmos. Chem. Phys., 22, 8259–8285, https://doi.org/10.5194/acp-22-8259-2022, https://doi.org/10.5194/acp-22-8259-2022, 2022
Short summary
Short summary
Satellite-retrieved cloud microphysics are widely used in climate research because of their central role in water and energy cycles. Here, we provide the first detailed investigation of retrieved cloud drop sizes from in situ and various satellite and airborne remote sensing techniques applied to real cumulus cloud fields. We conclude that the most widely used passive remote sensing method employed in climate research produces high biases of 6–8 µm (60 %–80 %) caused by 3-D radiative effects.
Athanasios Tsikerdekis, Nick A. J. Schutgens, Guangliang Fu, and Otto P. Hasekamp
Geosci. Model Dev., 15, 3253–3279, https://doi.org/10.5194/gmd-15-3253-2022, https://doi.org/10.5194/gmd-15-3253-2022, 2022
Short summary
Short summary
In our study we quantify the ability of the future satellite sensor SPEXone, part of the NASA PACE mission, to estimate aerosol emissions. The sensor will be able to retrieve accurate information of aerosol light extinction and most importantly light absorption. We simulate SPEXone spatial coverage and combine it with an aerosol model. We found that SPEXone will be able to estimate species-specific (e.g. dust, sea salt, organic or black carbon, sulfates) aerosol emissions very accurately.
Meloë S. F. Kacenelenbogen, Qian Tan, Sharon P. Burton, Otto P. Hasekamp, Karl D. Froyd, Yohei Shinozuka, Andreas J. Beyersdorf, Luke Ziemba, Kenneth L. Thornhill, Jack E. Dibb, Taylor Shingler, Armin Sorooshian, Reed W. Espinosa, Vanderlei Martins, Jose L. Jimenez, Pedro Campuzano-Jost, Joshua P. Schwarz, Matthew S. Johnson, Jens Redemann, and Gregory L. Schuster
Atmos. Chem. Phys., 22, 3713–3742, https://doi.org/10.5194/acp-22-3713-2022, https://doi.org/10.5194/acp-22-3713-2022, 2022
Short summary
Short summary
The impact of aerosols on Earth's radiation budget and human health is important and strongly depends on their composition. One desire of our scientific community is to derive the composition of the aerosol from satellite sensors. However, satellites observe aerosol optical properties (and not aerosol composition) based on remote sensing instrumentation. This study assesses how much aerosol optical properties can tell us about aerosol composition.
David Painemal, Douglas Spangenberg, William L. Smith Jr., Patrick Minnis, Brian Cairns, Richard H. Moore, Ewan Crosbie, Claire Robinson, Kenneth L. Thornhill, Edward L. Winstead, and Luke Ziemba
Atmos. Meas. Tech., 14, 6633–6646, https://doi.org/10.5194/amt-14-6633-2021, https://doi.org/10.5194/amt-14-6633-2021, 2021
Short summary
Short summary
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.
William G. K. McLean, Guangliang Fu, Sharon P. Burton, and Otto P. Hasekamp
Atmos. Meas. Tech., 14, 4755–4771, https://doi.org/10.5194/amt-14-4755-2021, https://doi.org/10.5194/amt-14-4755-2021, 2021
Short summary
Short summary
In this study, we present results from aerosol retrievals using both synthetic and real lidar datasets, including measurements from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, a combined initiative between NASA and SRON (the Netherlands Institute for Space Research). Aerosol microphysical retrievals were performed using the High Spectral Resolution Lidar-2 (HSRL-2) setup, alongside several others, with the ACEPOL retrievals also compared to polarimeter retrievals.
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.
Nick Schutgens, Oleg Dubovik, Otto Hasekamp, Omar Torres, Hiren Jethva, Peter J. T. Leonard, Pavel Litvinov, Jens Redemann, Yohei Shinozuka, Gerrit de Leeuw, Stefan Kinne, Thomas Popp, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 21, 6895–6917, https://doi.org/10.5194/acp-21-6895-2021, https://doi.org/10.5194/acp-21-6895-2021, 2021
Short summary
Short summary
Absorptive aerosol has a potentially large impact on climate change. We evaluate and intercompare four global satellite datasets of absorptive aerosol optical depth (AAOD) and single-scattering albedo (SSA). We show that these datasets show reasonable correlations with the AErosol RObotic NETwork (AERONET) reference, although significant biases remain. In a follow-up paper we show that these observations nevertheless can be used for model evaluation.
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
Short summary
Short summary
We assessed atmospheric aerosol and ocean surface wind speed remote sensing capability with NASA's Multi-angle Imaging SpectroRadiometer (MISR), using synthetic data and a Bayesian inference technique called generalized nonlinear retrieval analysis (GENRA). We found success using three aerosol parameters plus wind speed. This shows that MISR can perform an atmospheric correction for the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same spacecraft (Terra).
Andrew M. Dzambo, Tristan L'Ecuyer, Kenneth Sinclair, Bastiaan van Diedenhoven, Siddhant Gupta, Greg McFarquhar, Joseph R. O'Brien, Brian Cairns, Andrzej P. Wasilewski, and Mikhail Alexandrov
Atmos. Chem. Phys., 21, 5513–5532, https://doi.org/10.5194/acp-21-5513-2021, https://doi.org/10.5194/acp-21-5513-2021, 2021
Short summary
Short summary
This work highlights a new algorithm using data collected from the 2016–2018 NASA ORACLES field campaign. This algorithm synthesizes cloud and rain measurements to attain estimates of cloud and precipitation properties over the southeast Atlantic Ocean. Estimates produced by this algorithm compare well against in situ estimates. Increased rain fractions and rain rates are found in regions of atmospheric instability. This dataset can be used to explore aerosol–cloud–precipitation interactions.
Athanasios Tsikerdekis, Nick A. J. Schutgens, and Otto P. Hasekamp
Atmos. Chem. Phys., 21, 2637–2674, https://doi.org/10.5194/acp-21-2637-2021, https://doi.org/10.5194/acp-21-2637-2021, 2021
Short summary
Short summary
Accurate representation of aerosols in the atmosphere is hard to achieve due to their complex microphysical and optical properties and uncertain emissions. In our work, we employ a data assimilation method which integrates model simulations with satellite observation related to the amount, size and the light absorption of aerosol. The use of these observations in an experiment improves aerosol representation and it is recommended for utilization in future data assimilation practices.
Stephanie P. Rusli, Otto Hasekamp, Joost aan de Brugh, Guangliang Fu, Yasjka Meijer, and Jochen Landgraf
Atmos. Meas. Tech., 14, 1167–1190, https://doi.org/10.5194/amt-14-1167-2021, https://doi.org/10.5194/amt-14-1167-2021, 2021
Short summary
Short summary
This study investigates the added value of multi-angle polarimeter (MAP) measurements for XCO2 retrievals, particularly in the context of the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission. In this paper, we derive the required MAP instrument specification, and we demonstrate that MAP observations significantly improve the retrieval performance and are needed to meet the XCO2 precision and accuracy requirements of the CO2M mission.
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.
Alba Lorente, Tobias Borsdorff, Andre Butz, Otto Hasekamp, Joost aan de Brugh, Andreas Schneider, Lianghai Wu, Frank Hase, Rigel Kivi, Debra Wunch, David F. Pollard, Kei Shiomi, Nicholas M. Deutscher, Voltaire A. Velazco, Coleen M. Roehl, Paul O. Wennberg, Thorsten Warneke, and Jochen Landgraf
Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, https://doi.org/10.5194/amt-14-665-2021, 2021
Short summary
Short summary
TROPOMI aboard Sentinel-5P satellite provides methane (CH4) measurements with exceptional temporal and spatial resolution. The study describes a series of improvements developed to retrieve CH4 from TROPOMI. The updated CH4 product features (among others) a more accurate a posteriori correction derived independently of any reference data. The validation of the improved data product shows good agreement with ground-based and satellite measurements, which highlights the quality of the TROPOMI CH4.
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
Short summary
Short summary
Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Adeyemi A. Adebiyi, Paquita Zuidema, Ian Chang, Sharon P. Burton, and Brian Cairns
Atmos. Chem. Phys., 20, 11025–11043, https://doi.org/10.5194/acp-20-11025-2020, https://doi.org/10.5194/acp-20-11025-2020, 2020
Short summary
Short summary
Over the southeast Atlantic, interactions between the low-level clouds and the overlying smoke aerosols have previously been highlighted, but no study has yet focused on the presence of the mid-level clouds that complicate the aerosol–cloud interactions. Here we show that these optically thin super-cooled mid-level clouds are relatively common, and they frequently occur at the top of the smoke layer between August and October with significant radiative impacts on the low-level clouds.
Kirk Knobelspiesse, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, Anthony Cook, Antonio Di Noia, Bastiaan van Diedenhoven, David J. Diner, Richard Ferrare, Guangliang Fu, Meng Gao, Michael Garay, Johnathan Hair, David Harper, Gerard van Harten, Otto Hasekamp, Mark Helmlinger, Chris Hostetler, Olga Kalashnikova, Andrew Kupchock, Karla Longo De Freitas, Hal Maring, J. Vanderlei Martins, Brent McBride, Matthew McGill, Ken Norlin, Anin Puthukkudy, Brian Rheingans, Jeroen Rietjens, Felix C. Seidel, Arlindo da Silva, Martijn Smit, Snorre Stamnes, Qian Tan, Sebastian Val, Andrzej Wasilewski, Feng Xu, Xiaoguang Xu, and John Yorks
Earth Syst. Sci. Data, 12, 2183–2208, https://doi.org/10.5194/essd-12-2183-2020, https://doi.org/10.5194/essd-12-2183-2020, 2020
Short summary
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.
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
Short summary
Short summary
A neural network (NN) is developed and used to retrieve cloud microphysical properties from multiangular and multispectral polarimetric remote sensing observations. The NN is applied to research scanning polarimeter (RSP) observations obtained during the ORACLES field campaign and compared to other co-located remote sensing retrievals of cloud effective radius and optical thickness. A NN approach can advance more complex iterative search retrieval algorithms by providing a quick initial guess.
Kimberly A. Casey, Cecile S. Rousseaux, Watson W. Gregg, Emmanuel Boss, Alison P. Chase, Susanne E. Craig, Colleen B. Mouw, Rick A. Reynolds, Dariusz Stramski, Steven G. Ackleson, Annick Bricaud, Blake Schaeffer, Marlon R. Lewis, and Stéphane Maritorena
Earth Syst. Sci. Data, 12, 1123–1139, https://doi.org/10.5194/essd-12-1123-2020, https://doi.org/10.5194/essd-12-1123-2020, 2020
Short summary
Short summary
An increase in spectral resolution in forthcoming remote-sensing missions will improve our ability to understand and characterize aquatic ecosystems. We organize and provide a global compilation of high spectral resolution inherent and apparent optical property data from polar, midlatitude, and equatorial open-ocean, estuary, coastal, and inland waters. The data are intended to aid in development of remote-sensing data product algorithms and to perform calibration and validation activities.
Yaping Zhou, Yuekui Yang, Meng Gao, and Peng-Wang Zhai
Atmos. Meas. Tech., 13, 1575–1591, https://doi.org/10.5194/amt-13-1575-2020, https://doi.org/10.5194/amt-13-1575-2020, 2020
Short summary
Short summary
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.
Maximilian Reuter, Michael Buchwitz, Oliver Schneising, Stefan Noël, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Antonio Di Noia, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Lianghai Wu, Otto P. Hasekamp, Ilse Aben, Akihiko Kuze, Hiroshi Suto, Kei Shiomi, Yukio Yoshida, Isamu Morino, David Crisp, Christopher W. O'Dell, Justus Notholt, Christof Petri, Thorsten Warneke, Voltaire A. Velazco, Nicholas M. Deutscher, David W. T. Griffith, Rigel Kivi, David F. Pollard, Frank Hase, Ralf Sussmann, Yao V. Té, Kimberly Strong, Sébastien Roche, Mahesh K. Sha, Martine De Mazière, Dietrich G. Feist, Laura T. Iraci, Coleen M. Roehl, Christian Retscher, and Dinand Schepers
Atmos. Meas. Tech., 13, 789–819, https://doi.org/10.5194/amt-13-789-2020, https://doi.org/10.5194/amt-13-789-2020, 2020
Short summary
Short summary
We present new satellite-derived data sets of atmospheric carbon dioxide (CO2) and methane (CH4). The data products are column-averaged dry-air mole fractions of CO2 and CH4, denoted XCO2 and XCH4. The products cover the years 2003–2018 and are merged Level 2 (satellite footprints) and merged Level 3 (gridded at monthly time and 5° x 5° spatial resolution) products obtained from combining several individual sensor products. We present the merging algorithms and product validation results.
Lianghai Wu, Joost aan de Brugh, Yasjka Meijer, Bernd Sierk, Otto Hasekamp, Andre Butz, and Jochen Landgraf
Atmos. Meas. Tech., 13, 713–729, https://doi.org/10.5194/amt-13-713-2020, https://doi.org/10.5194/amt-13-713-2020, 2020
Short summary
Short summary
The future European CO2 monitoring constellation is targeting a moderate spectral resolution of 0.1, 0.3, and 0.3–0.55 nm in the spectral bands of 0.76, 1.61, and 2.06 μm. To assess this choice, we perform XCO2 retrievals using both satellite (OCO-2 and GOSAT) and synthetic observations, which we spectrally degrade to the target spectral resolution. We see that moderate spectral resolution mainly reduces XCO2 precision and has little effect on the the systematic error.
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
Short summary
Short summary
In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON (the Netherlands Institute for Space Research). We perform aerosol retrievals from different multi-angle polarimeters employed during the ACEPOL campaign and evaluate them against ground-based AERONET measurements and High Spectral Resolution Lidar-2 (HSRL-2) measurements.
Wenbo Sun, Yongxiang Hu, Rosemary R. Baize, Gorden Videen, Sungsoo S. Kim, Young-Jun Choi, Kyungin Kang, Chae Kyung Sim, Minsup Jeong, Ali Omar, Snorre A. Stamnes, David G. MacDonnell, and Evgenij Zubko
Atmos. Chem. Phys., 19, 15583–15586, https://doi.org/10.5194/acp-19-15583-2019, https://doi.org/10.5194/acp-19-15583-2019, 2019
Short summary
Short summary
Dusts have a significant impact on climate and environment. Detecting dust using satellite instruments is generally conducted by measuring at multiple observation angles due to the uncertainty of the surface reflection. This report shows that the degree of polarization of reflected light can be used for retrieving the optical depth of dust at backscatter angles only, regardless of surface conditions. This simple method is suitable for surveying dust aerosols over oceans with low-cost satellites.
Andrew M. Sayer and Kirk D. Knobelspiesse
Atmos. Chem. Phys., 19, 15023–15048, https://doi.org/10.5194/acp-19-15023-2019, https://doi.org/10.5194/acp-19-15023-2019, 2019
Short summary
Short summary
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.
Lianghai Wu, Otto Hasekamp, Haili Hu, Joost aan de Brugh, Jochen Landgraf, Andre Butz, and Ilse Aben
Atmos. Meas. Tech., 12, 6049–6058, https://doi.org/10.5194/amt-12-6049-2019, https://doi.org/10.5194/amt-12-6049-2019, 2019
Short summary
Short summary
We propose a one–band XCO2 retrieval technique which uses only the 2.06 µm band measurements from the Orbiting Carbon Observatory–2 (OCO–2) satellite. Compared to the current state–of–the–art three–band retrievals, XCO2 retrievals using only the 2.06 µm band have similar retrieval accuracy, precision, and data yield. For future missions it may be better to replace the O2 A band with measurements that have larger information content on aerosols, like a multi–angle polarimeter (MAP).
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
Short summary
Short summary
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
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Malcolm Taberner, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Yngve Borsheim, Astrid Bracher, Vittorio Brando, Elisabetta Canuti, Francisco Chavez, Andrés Cianca, Hervé Claustre, Lesley Clementson, Richard Crout, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Richard Gould, Stanford B. Hooker, Mati Kahru, Milton Kampel, Holger Klein, Susanne Kratzer, Raphael Kudela, Jesus Ledesma, Hubert Loisel, Patricia Matrai, David McKee, Brian G. Mitchell, Tiffany Moisan, Frank Muller-Karger, Leonie O'Dowd, Michael Ondrusek, Trevor Platt, Alex J. Poulton, Michel Repecaud, Thomas Schroeder, Timothy Smyth, Denise Smythe-Wright, Heidi M. Sosik, Michael Twardowski, Vincenzo Vellucci, Kenneth Voss, Jeremy Werdell, Marcel Wernand, Simon Wright, and Giuseppe Zibordi
Earth Syst. Sci. Data, 11, 1037–1068, https://doi.org/10.5194/essd-11-1037-2019, https://doi.org/10.5194/essd-11-1037-2019, 2019
Short summary
Short summary
A compiled set of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the compilation of global bio-optical in situ data (spanning from 1997 to 2018) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Shan Zeng, Mark Vaughan, Zhaoyan Liu, Charles Trepte, Jayanta Kar, Ali Omar, David Winker, Patricia Lucker, Yongxiang Hu, Brian Getzewich, and Melody Avery
Atmos. Meas. Tech., 12, 2261–2285, https://doi.org/10.5194/amt-12-2261-2019, https://doi.org/10.5194/amt-12-2261-2019, 2019
Short summary
Short summary
We use a fuzzy k-means (FKM) classifier to assess the ability of the CALIPSO cloud–aerosol discrimination (CAD) algorithm to correctly distinguish between clouds and aerosols detected in the CALIPSO lidar backscatter signals. FKM is an unsupervised learning algorithm, so the classifications it derives are wholly independent from those reported by the CAD scheme. For a full month of measurements, the two techniques agree in ~ 95 % of all cases, providing strong evidence for CAD correctness.
Meloë S. Kacenelenbogen, Mark A. Vaughan, Jens Redemann, Stuart A. Young, Zhaoyan Liu, Yongxiang Hu, Ali H. Omar, Samuel LeBlanc, Yohei Shinozuka, John Livingston, Qin Zhang, and Kathleen A. Powell
Atmos. Chem. Phys., 19, 4933–4962, https://doi.org/10.5194/acp-19-4933-2019, https://doi.org/10.5194/acp-19-4933-2019, 2019
Short summary
Short summary
Significant efforts are required to estimate the direct radiative effects of aerosols above clouds (DAREcloudy). We have used a combination of passive and active A-Train satellite sensors and derive mainly positive global and regional DAREcloudy values (e.g., global seasonal values between 0.13 and 0.26 W m-2). Despite differences in methods and sensors, the DAREcloudy values in this study are generally higher than previously reported. We discuss the primary reasons for these higher estimates.
Tobias Borsdorff, Joost aan de Brugh, Sudhanshu Pandey, Otto Hasekamp, Ilse Aben, Sander Houweling, and Jochen Landgraf
Atmos. Chem. Phys., 19, 3579–3588, https://doi.org/10.5194/acp-19-3579-2019, https://doi.org/10.5194/acp-19-3579-2019, 2019
Short summary
Short summary
The Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite provides carbon monoxide (CO) total column concentrations based on measurements in the 2.3 μm spectral range with a spatial resolution of 7 km x 7 km and daily global coverage. In this study, we analyzed local CO enhancements in an area around Iran from 1 November to 20 December 2017 using the WRF model and evaluated CO emissions from the cities of Tehran, Yerevan, Urmia, and Tabriz.
Antonio Di Noia, Otto P. Hasekamp, Bastiaan van Diedenhoven, and Zhibo Zhang
Atmos. Meas. Tech., 12, 1697–1716, https://doi.org/10.5194/amt-12-1697-2019, https://doi.org/10.5194/amt-12-1697-2019, 2019
Short summary
Short summary
We present a neural network algorithm for the retrieval of cloud physical properties from multi-angle polarimetric measurements. We have trained the algorithm on a large dataset of synthetic measurements and applied it to a year of POLDER-3 data. A comparison against MODIS cloud products reveals that our algorithm is capable of performing cloud property retrievals on a global scale and possibly improves the estimates of cloud effective radius over land with respect to existing POLDER-3 products.
Mark Vaughan, Anne Garnier, Damien Josset, Melody Avery, Kam-Pui Lee, Zhaoyan Liu, William Hunt, Jacques Pelon, Yongxiang Hu, Sharon Burton, Johnathan Hair, Jason L. Tackett, Brian Getzewich, Jayanta Kar, and Sharon Rodier
Atmos. Meas. Tech., 12, 51–82, https://doi.org/10.5194/amt-12-51-2019, https://doi.org/10.5194/amt-12-51-2019, 2019
Short summary
Short summary
The version 4 (V4) release of the CALIPSO data products includes substantial improvements to the calibration of the CALIOP 1064 nm channel. In this paper we review the fundamentals of 1064 nm lidar calibration, explain the motivations for the changes made to the algorithm, and describe the mechanics of the V4 calibration technique. Internal consistency checks and comparisons to collocated high spectral resolution lidar measurements show the V4 1064 nm calibration coefficients to within ~ 3 %.
Guangliang Fu and Otto Hasekamp
Atmos. Meas. Tech., 11, 6627–6650, https://doi.org/10.5194/amt-11-6627-2018, https://doi.org/10.5194/amt-11-6627-2018, 2018
Short summary
Short summary
We implement a multimode approach in which each mode has fixed effective radius and effective variance. In this way the algorithm obtains more flexibility in describing the aerosol size distribution and avoids the high nonlinear dependence of the forward model on the aerosol size parameters. The synthetic and real data experiments show that multimode retrievals are good alternatives to the parametric two-mode approach.
Michael Buchwitz, Maximilian Reuter, Oliver Schneising, Stefan Noël, Bettina Gier, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Rob G. Detmers, Otto P. Hasekamp, Ilse Aben, André Butz, Akihiko Kuze, Hiroshi Suto, Yukio Yoshida, David Crisp, and Christopher O'Dell
Atmos. Chem. Phys., 18, 17355–17370, https://doi.org/10.5194/acp-18-17355-2018, https://doi.org/10.5194/acp-18-17355-2018, 2018
Short summary
Short summary
We present a new satellite data set of column-averaged mixing ratios of carbon dioxide (CO2), which covers the time period 2003 to 2016. We used this data set to compute annual mean atmospheric CO2 growth rates. We show that the growth rate is highest during 2015 and 2016 despite nearly constant CO2 emissions from fossil fuel burning in recent years. The high growth rates are attributed to year 2015-2016 El Nino episodes. We present correlations with fossil fuel emissions and ENSO indices.
Man-Hae Kim, Ali H. Omar, Jason L. Tackett, Mark A. Vaughan, David M. Winker, Charles R. Trepte, Yongxiang Hu, Zhaoyan Liu, Lamont R. Poole, Michael C. Pitts, Jayanta Kar, and Brian E. Magill
Atmos. Meas. Tech., 11, 6107–6135, https://doi.org/10.5194/amt-11-6107-2018, https://doi.org/10.5194/amt-11-6107-2018, 2018
Short summary
Short summary
This paper discusses recent advances made in distinguishing among different aerosols species detected in the CALIPSO lidar measurements. A new classification algorithm now classifies four different aerosol types in the stratosphere, and the number of aerosol types recognized in the troposphere has increased from six to seven. The lidar ratios characterizing each type have been updated and the effects of these changes on CALIPSO retrievals of aerosol optical depth are examined in detail.
Tobias Borsdorff, Joost aan de Brugh, Haili Hu, Otto Hasekamp, Ralf Sussmann, Markus Rettinger, Frank Hase, Jochen Gross, Matthias Schneider, Omaira Garcia, Wolfgang Stremme, Michel Grutter, Dietrich G. Feist, Sabrina G. Arnold, Martine De Mazière, Mahesh Kumar Sha, David F. Pollard, Matthäus Kiel, Coleen Roehl, Paul O. Wennberg, Geoffrey C. Toon, and Jochen Landgraf
Atmos. Meas. Tech., 11, 5507–5518, https://doi.org/10.5194/amt-11-5507-2018, https://doi.org/10.5194/amt-11-5507-2018, 2018
Short summary
Short summary
On 13 October 2017, the S5-P satellite was launched with TROPOMI as its only payload. One of the primary products is atmospheric CO observed with daily global coverage and spatial resolution of 7 × 7 km2. The new dataset allows the sensing of CO enhancements above cities and industrial areas and can track pollution transport from biomass burning regions. Through validation with ground-based TCCON measurements we show that the CO data product is already well within the mission requirement.
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
Short summary
Short summary
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
Short summary
Short summary
Prior satellite comparisons of bispectral and polarimetric cloud droplet size retrievals exhibited systematic biases. However, similar airborne instrument retrievals have been found to be quite similar to one another. This study explains this discrepancy in terms of differing sensitivity to vertical profile, as well as spatial and angular resolution. This is accomplished by using a satellite retrieval simulator – an LES cloud model coupled to radiative transfer and cloud retrieval algorithms.
Xiaomei Lu, Yongxiang Hu, Yuekui Yang, Mark Vaughan, Zhaoyan Liu, Sharon Rodier, William Hunt, Kathy Powell, Patricia Lucker, and Charles Trepte
Atmos. Meas. Tech., 11, 3281–3296, https://doi.org/10.5194/amt-11-3281-2018, https://doi.org/10.5194/amt-11-3281-2018, 2018
Short summary
Short summary
This paper presents an innovative retrieval method that translates the CALIOP land surface laser pulse returns into the surface bidirectional reflectance. The surface bidirectional reflectances retrieved from CALIOP measurements contribute complementary data for existing MODIS standard data products and could be used to detect and monitor seasonal surface reflectance changes in high latitude regions where passive MODIS measurements are limited.
Lianghai Wu, Otto Hasekamp, Haili Hu, Jochen Landgraf, Andre Butz, Joost aan de Brugh, Ilse Aben, Dave F. Pollard, David W. T. Griffith, Dietrich G. Feist, Dmitry Koshelev, Frank Hase, Geoffrey C. Toon, Hirofumi Ohyama, Isamu Morino, Justus Notholt, Kei Shiomi, Laura Iraci, Matthias Schneider, Martine de Mazière, Ralf Sussmann, Rigel Kivi, Thorsten Warneke, Tae-Young Goo, and Yao Té
Atmos. Meas. Tech., 11, 3111–3130, https://doi.org/10.5194/amt-11-3111-2018, https://doi.org/10.5194/amt-11-3111-2018, 2018
Jonathan Lemay, Helmuth Thomas, Susanne E. Craig, William J. Burt, Katja Fennel, and Blair J. W. Greenan
Biogeosciences, 15, 2111–2123, https://doi.org/10.5194/bg-15-2111-2018, https://doi.org/10.5194/bg-15-2111-2018, 2018
Short summary
Short summary
We report a detailed mechanistic investigation of the impact of Hurricane Arthur on the CO2 cycling on the Scotian Shelf. We can show that in contrast to common thinking, the deepening of the surface during the summer months can lead to increased CO2 uptake as carbon-poor waters from subsurface water are brought up to the surface. Only during prolonged storm events is the deepening of the mixed layer strong enough to bring the (expected) carbon-rich water to the surface.
Astrid M. M. Manders, Peter J. H. Builtjes, Lyana Curier, Hugo A. C. Denier van der Gon, Carlijn Hendriks, Sander Jonkers, Richard Kranenburg, Jeroen J. P. Kuenen, Arjo J. Segers, Renske M. A. Timmermans, Antoon J. H. Visschedijk, Roy J. Wichink Kruit, W. Addo J. van Pul, Ferd J. Sauter, Eric van der Swaluw, Daan P. J. Swart, John Douros, Henk Eskes, Erik van Meijgaard, Bert van Ulft, Peter van Velthoven, Sabine Banzhaf, Andrea C. Mues, Rainer Stern, Guangliang Fu, Sha Lu, Arnold Heemink, Nils van Velzen, and Martijn Schaap
Geosci. Model Dev., 10, 4145–4173, https://doi.org/10.5194/gmd-10-4145-2017, https://doi.org/10.5194/gmd-10-4145-2017, 2017
Short summary
Short summary
The regional-scale air quality model LOTOS–EUROS has been developed by a consortium of Dutch institutes. Recently, version 2.0 of the model was released as an open-source version. Next to a technical description and model evaluation for 2012, this paper presents the model developments in context of the history of air quality modelling and provides an outlook for future directions. Key and innovative applications of LOTOS–EUROS are also highlighted.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Michael Buchwitz, Oliver Schneising, Maximilian Reuter, Jens Heymann, Sven Krautwurst, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Robert J. Parker, Peter Somkuti, Rob G. Detmers, Otto P. Hasekamp, Ilse Aben, André Butz, Christian Frankenberg, and Alexander J. Turner
Atmos. Chem. Phys., 17, 5751–5774, https://doi.org/10.5194/acp-17-5751-2017, https://doi.org/10.5194/acp-17-5751-2017, 2017
Short summary
Short summary
Methane is an important greenhouse gas and increasing atmospheric concentrations result in global warming. We present a simple method to derive annual methane emission estimates of methane hotspot areas from satellite data. We present results for four source areas. We found that our estimates are in good agreement with other studies/data sets for the Four Corners region in the USA and for Azerbaijan but we also found higher emissions for parts of California and Turkmenistan.
Guangliang Fu, Hai Xiang Lin, Arnold Heemink, Sha Lu, Arjo Segers, Nils van Velzen, Tongchao Lu, and Shiming Xu
Geosci. Model Dev., 10, 1751–1766, https://doi.org/10.5194/gmd-10-1751-2017, https://doi.org/10.5194/gmd-10-1751-2017, 2017
Short summary
Short summary
We propose a mask-state algorithm (MS) which records the sparsity information of the full ensemble state matrix and transforms the full matrix into a relatively small one. It will reduce the computational cost in the analysis step for plume assimilation applications. Ensemble-based DA with the mask-state algorithm is generic and flexible, because it implements exactly the standard DA without any approximation and it realizes the satisfying performance without any change of the full model.
Guangliang Fu, Fred Prata, Hai Xiang Lin, Arnold Heemink, Arjo Segers, and Sha Lu
Atmos. Chem. Phys., 17, 1187–1205, https://doi.org/10.5194/acp-17-1187-2017, https://doi.org/10.5194/acp-17-1187-2017, 2017
Short summary
Short summary
A Satellite Observational Operator (SOO) is proposed to translates satellite-retrieved 2-D volcanic ash mass loadings to 3-D concentrations. The SOO makes the analysis step of assimilation comparable in the 3-D model space, and thus it avoids the artificial vertical correlations by not involving the integral operator in directly assimilating 2-D data. The results show that satellite data assimilation with SOO can efficiently improve the estimate of volcanic ash state and the forecast.
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
Short summary
Short summary
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.
Jochen Landgraf, Joost aan de Brugh, Remco Scheepmaker, Tobias Borsdorff, Haili Hu, Sander Houweling, Andre Butz, Ilse Aben, and Otto Hasekamp
Atmos. Meas. Tech., 9, 4955–4975, https://doi.org/10.5194/amt-9-4955-2016, https://doi.org/10.5194/amt-9-4955-2016, 2016
Short summary
Short summary
In 2016, the Sentinel 5 Precursor mission will be launched, with the TROPOMI instrument as its single payload. It will deliver daily global measurements of carbon monoxide for air quality monitoring as part of the Copernicus atmospheric services. In this paper, we focus on the operational data processing of the CO product from TROPOMI measurements of the shortwave infrared spectral range, and we discuss the algorithm's maturity.
Guangliang Fu, Arnold Heemink, Sha Lu, Arjo Segers, Konradin Weber, and Hai-Xiang Lin
Atmos. Chem. Phys., 16, 9189–9200, https://doi.org/10.5194/acp-16-9189-2016, https://doi.org/10.5194/acp-16-9189-2016, 2016
Short summary
Short summary
Assimilating aircraft in situ measurements can significantly improve aviation advice on distal part of volcanic ash plume.
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
Short summary
Short summary
We developed an algorithm for aerosol and water-leaving radiance retrieval in a simultaneous way.
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Malcolm Taberner, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Vittorio Brando, Elisabetta Canuti, Francisco Chavez, Hervé Claustre, Richard Crout, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Richard Gould, Stanford Hooker, Mati Kahru, Holger Klein, Susanne Kratzer, Hubert Loisel, David McKee, Brian G. Mitchell, Tiffany Moisan, Frank Muller-Karger, Leonie O'Dowd, Michael Ondrusek, Alex J. Poulton, Michel Repecaud, Timothy Smyth, Heidi M. Sosik, Michael Twardowski, Kenneth Voss, Jeremy Werdell, Marcel Wernand, and Giuseppe Zibordi
Earth Syst. Sci. Data, 8, 235–252, https://doi.org/10.5194/essd-8-235-2016, https://doi.org/10.5194/essd-8-235-2016, 2016
Short summary
Short summary
A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite data records. Here we describe the compilation of global bio-optical in situ data (spanning from 1997 to 2012) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Joel McCorkel, Brian Cairns, and Andrzej Wasilewski
Atmos. Meas. Tech., 9, 955–962, https://doi.org/10.5194/amt-9-955-2016, https://doi.org/10.5194/amt-9-955-2016, 2016
Short summary
Short summary
The transfer and maintenance of international radiometric standards to satellite remote-sensing instruments is a labor-intensive and costly one. The goal is to provide specific examples for calibration implementation for a potential instrument mission and, with this, advance debate on the roles that the various satellite calibration techniques play in providing the best radiometric standards for Earth-observing sensors.
B. Nechad, K. Ruddick, T. Schroeder, K. Oubelkheir, D. Blondeau-Patissier, N. Cherukuru, V. Brando, A. Dekker, L. Clementson, A. C. Banks, S. Maritorena, P. J. Werdell, C. Sá, V. Brotas, I. Caballero de Frutos, Y.-H. Ahn, S. Salama, G. Tilstone, V. Martinez-Vicente, D. Foley, M. McKibben, J. Nahorniak, T. Peterson, A. Siliò-Calzada, R. Röttgers, Z. Lee, M. Peters, and C. Brockmann
Earth Syst. Sci. Data, 7, 319–348, https://doi.org/10.5194/essd-7-319-2015, https://doi.org/10.5194/essd-7-319-2015, 2015
Short summary
Short summary
The CoastColour Round Robin (CCRR) project (European Space Agency) was designed to set up the first database for remote-sensing algorithm testing and accuracy assessment of water quality parameter retrieval in coastal waters, from satellite imagery. This paper analyses the CCRR database, which includes in situ bio-geochemical and optical measurements in various water types, match-up reflectance products from the MEdium Resolution Imaging Spectrometer (MERIS), and radiative transfer simulations.
W. Sun, R. R. Baize, G. Videen, Y. Hu, and Q. Fu
Atmos. Chem. Phys., 15, 11909–11918, https://doi.org/10.5194/acp-15-11909-2015, https://doi.org/10.5194/acp-15-11909-2015, 2015
Short summary
Short summary
A method is reported for retrieving super-thin cloud optical depth with polarized light. It is found that near-backscatter p-polarized light is sensitive to clouds, but not to ocean conditions. Near-backscatter p-polarized intensity linearly relates to super-thin cloud optical depth. Based on these findings, super-thin cloud optical depth can be retrieved with little effect from surface reflection.
M. Ottaviani, B. van Diedenhoven, and B. Cairns
The Cryosphere, 9, 1933–1942, https://doi.org/10.5194/tc-9-1933-2015, https://doi.org/10.5194/tc-9-1933-2015, 2015
W. Sun, R. R. Baize, C. Lukashin, and Y. Hu
Atmos. Chem. Phys., 15, 7725–7734, https://doi.org/10.5194/acp-15-7725-2015, https://doi.org/10.5194/acp-15-7725-2015, 2015
L. Wu, O. Hasekamp, B. van Diedenhoven, and B. Cairns
Atmos. Meas. Tech., 8, 2625–2638, https://doi.org/10.5194/amt-8-2625-2015, https://doi.org/10.5194/amt-8-2625-2015, 2015
F. A. Stap, O. P. Hasekamp, and T. Röckmann
Atmos. Meas. Tech., 8, 1287–1301, https://doi.org/10.5194/amt-8-1287-2015, https://doi.org/10.5194/amt-8-1287-2015, 2015
Short summary
Short summary
We present the capability of an aerosol retrieval algorithm, intended for multi-angle, multi-wavelength photopolarimetric measurements, to intrinsically screen for sub-pixel liquid water cloud contamination.
The screening is based on goodness-of-fit criteria. The algorithm has been applied to a synthetic data set of partially clouded scenes and (non-cloud-screened) POLDER3/PARASOL observations.
Z. Liu, D. Winker, A. Omar, M. Vaughan, J. Kar, C. Trepte, Y. Hu, and G. Schuster
Atmos. Chem. Phys., 15, 1265–1288, https://doi.org/10.5194/acp-15-1265-2015, https://doi.org/10.5194/acp-15-1265-2015, 2015
M. Reuter, M. Buchwitz, M. Hilker, J. Heymann, O. Schneising, D. Pillai, H. Bovensmann, J. P. Burrows, H. Bösch, R. Parker, A. Butz, O. Hasekamp, C. W. O'Dell, Y. Yoshida, C. Gerbig, T. Nehrkorn, N. M. Deutscher, T. Warneke, J. Notholt, F. Hase, R. Kivi, R. Sussmann, T. Machida, H. Matsueda, and Y. Sawa
Atmos. Chem. Phys., 14, 13739–13753, https://doi.org/10.5194/acp-14-13739-2014, https://doi.org/10.5194/acp-14-13739-2014, 2014
Short summary
Short summary
Current knowledge about the European terrestrial biospheric carbon sink relies upon bottom-up and global surface flux inverse model estimates using in situ measurements. Our analysis of five satellite data sets comprises a regional inversion designed to be insensitive to potential retrieval biases and transport errors. We show that the satellite-derived sink is larger (1.0±0.3GtC/a) than previous estimates (0.4±0.4GtC/a).
A. Lyapustin, Y. Wang, X. Xiong, G. Meister, S. Platnick, R. Levy, B. Franz, S. Korkin, T. Hilker, J. Tucker, F. Hall, P. Sellers, A. Wu, and A. Angal
Atmos. Meas. Tech., 7, 4353–4365, https://doi.org/10.5194/amt-7-4353-2014, https://doi.org/10.5194/amt-7-4353-2014, 2014
S. Zeng, J. Riedi, C. R. Trepte, D. M. Winker, and Y.-X. Hu
Atmos. Chem. Phys., 14, 7125–7134, https://doi.org/10.5194/acp-14-7125-2014, https://doi.org/10.5194/acp-14-7125-2014, 2014
B. Dils, M. Buchwitz, M. Reuter, O. Schneising, H. Boesch, R. Parker, S. Guerlet, I. Aben, T. Blumenstock, J. P. Burrows, A. Butz, N. M. Deutscher, C. Frankenberg, F. Hase, O. P. Hasekamp, J. Heymann, M. De Mazière, J. Notholt, R. Sussmann, T. Warneke, D. Griffith, V. Sherlock, and D. Wunch
Atmos. Meas. Tech., 7, 1723–1744, https://doi.org/10.5194/amt-7-1723-2014, https://doi.org/10.5194/amt-7-1723-2014, 2014
S. Rodier, Y. Hu, and M. Vaughan
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-4681-2013, https://doi.org/10.5194/tcd-7-4681-2013, 2013
Revised manuscript has not been submitted
S. E. Craig, H. Thomas, C. T. Jones, W. K. W. Li, B. J. W. Greenan, E. H. Shadwick, and W. J. Burt
Biogeosciences Discuss., https://doi.org/10.5194/bgd-10-11255-2013, https://doi.org/10.5194/bgd-10-11255-2013, 2013
Revised manuscript not accepted
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
Improvements in aerosol layer height retrievals from TROPOMI oxygen A-band measurements by surface albedo fitting in optimal estimation
Using neural networks for near-real-time aerosol retrievals from OMPS Limb Profiler measurements
Retrieval algorithm for aerosol effective height from the Geostationary Environment Monitoring Spectrometer (GEMS)
ACDL/DQ-1 calibration algorithms – Part 1: Nighttime 532 nm polarization and the high-spectral-resolution channel
Aerosol composition retrieval from a combination of three different spaceborne instruments: information content analysis
Compact dual-wavelength depolarization lidar for aerosol characterization over the subtropical North Atlantic
Towards gridded nighttime aerosol optical thickness retrievals using VIIRS day–night band observations over regions with artificial light sources
Ångström exponent impact on the aerosol optical properties obtained from vibrational-rotational Raman lidar observations
Multi-layer retrieval of aerosol optical depth in the troposphere using SEVIRI data: a case study of the European continent
Star photometry with all-sky cameras to retrieve aerosol optical depth at night-time
Ground-based contrail observations: comparisons with reanalysis weather data and contrail model simulations
Retrieval of stratospheric aerosol extinction coefficients from sun-normalized Ozone Mapper and Profiler Suite Limb Profiler (OMPS-LP) measurements
Total column optical depths retrieved from CALIPSO lidar ocean surface backscatter
ALICENET – an Italian network of automated lidar ceilometers for four-dimensional aerosol monitoring: infrastructure, data processing, and applications
Post-process correction improves the accuracy of satellite PM2.5 retrievals
Increasing aerosol optical depth spatial and temporal availability by merging datasets from geostationary and sun-synchronous satellites
Synergy of active and passive airborne observations for heating rates calculation during the AEROCLO-SA field campaign in Namibia
Multi-angle aerosol optical depth retrieval method based on improved surface reflectance
Comparison of diurnal aerosol products retrieved from combinations of micro-pulse lidar and sun photometer observations over the KAUST observation site
First atmospheric aerosol-monitoring results from the Geostationary Environment Monitoring Spectrometer (GEMS) over Asia
Aerosol optical depth data fusion with Geostationary Korea Multi-Purpose Satellite (GEO-KOMPSAT-2) instruments GEMS, AMI, and GOCI-II: statistical and deep neural network methods
Stratospheric aerosol characteristics from SCIAMACHY limb observations: two-parameter retrieval
Retrieval and analysis of the composition of an aerosol mixture through Mie–Raman–fluorescence lidar observations
Transport of the Hunga volcanic aerosols inferred from Himawari-8/9 limb measurements
A near-global multiyear climate data record of the fine-mode and coarse-mode components of atmospheric pure dust
Innovative aerosol hygroscopic growth study from Mie–Raman–fluorescence lidar and microwave radiometer synergy
Evaluation of calibration performance of a low-cost particulate matter sensor using collocated and distant NO2
Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires
Multi-wavelength dataset of aerosol extinction profiles retrieved from GOMOS stellar occultation measurements
Deep-Pathfinder: a boundary layer height detection algorithm based on image segmentation
An iterative algorithm to simultaneously retrieve aerosol extinction and effective radius profiles using CALIOP
Cloud detection from multi-angular polarimetric satellite measurements using a neural network ensemble approach
Producing aerosol size distributions consistent with optical particle counters measurements using space-based measurements of aerosol extinction coefficient
Retrieving UV–Vis spectral single-scattering albedo of absorbing aerosols above clouds from synergy of ORACLES airborne and A-train sensors
Characterization of stratospheric particle size distribution uncertainties using SAGE II and SAGE III/ISS extinction spectra
Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager
Aerosol and cloud data processing and optical property retrieval algorithms for the spaceborne ACDL/DQ-1
Derivation of depolarization ratios of aerosol fluorescence and water vapor Raman backscatters from lidar measurements
Long-term aerosol particle depolarization ratio measurements with HALO Photonics Doppler lidar
HETEAC-Flex: an optimal estimation method for aerosol typing based on lidar-derived intensive optical properties
MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm
Multi-section reference value for the analysis of horizontally scanning aerosol lidar observations
Retrieval of aerosol optical depth over the Arctic cryosphere during spring and summer using satellite observations
Quantifying particulate matter optical properties and flow rate in industrial stack plumes from the PRISMA hyperspectral imager
Aerosol retrieval over snow using the RemoTAP algorithm
Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign
Simultaneous retrieval of aerosol and ocean properties from PACE HARP2 with uncertainty assessment using cascading neural network radiative transfer models
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
Martin de Graaf, Maarten Sneep, Mark ter Linden, L. Gijsbert Tilstra, David P. Donovan, Gerd-Jan van Zadelhoff, and J. Pepijn Veefkind
Atmos. Meas. Tech., 18, 2553–2571, https://doi.org/10.5194/amt-18-2553-2025, https://doi.org/10.5194/amt-18-2553-2025, 2025
Short summary
Short summary
The aerosol layer height (ALH) from the TROPOspheric Monitoring Instrument (TROPOMI) has been constantly improved since its release in 2019. Over bright surfaces, fitting the albedo improved the retrieval, as shown for a set of situations, ranging from multiple layers of smoke to thick desert dust plumes and low-altitude industrial pollution. The latest results of the operational ALH are compared to profiles from the ATmospheric LIDar (ATLID) on board the recently launched EarthCARE mission.
Michael D. Himes, Ghassan Taha, Daniel Kahn, Tong Zhu, and Natalya A. Kramarova
Atmos. Meas. Tech., 18, 2523–2536, https://doi.org/10.5194/amt-18-2523-2025, https://doi.org/10.5194/amt-18-2523-2025, 2025
Short summary
Short summary
The Ozone Mapping and Profiler Suite's Limb Profiler (OMPS LP) yields near-global coverage and information about how aerosols from volcanic eruptions and major wildfires is vertically distributed through the atmosphere. We developed a machine learning method to characterize aerosols using OMPS LP measurements about 60 times faster than the current approach.
Sang Seo Park, Jhoon Kim, Yeseul Cho, Hanlim Lee, Junsung Park, Dong-Won Lee, Won-Jin Lee, and Deok-Rae Kim
Atmos. Meas. Tech., 18, 2241–2259, https://doi.org/10.5194/amt-18-2241-2025, https://doi.org/10.5194/amt-18-2241-2025, 2025
Short summary
Short summary
An operational aerosol effective height (AEH) retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS) was developed that solely uses the O2–O2 absorption band considering aerosol and surface properties. AEH retrievals are only performed when aerosol optical depth is larger than 0.3. The retrieval results show significant estimations by comparing the aerosol height from the Cloud–Aerosol Lidar with Orthogonal Polarization and the Tropospheric Monitoring Instrument.
Fanqian Meng, Junwu Tang, Guangyao Dai, Wenrui Long, Kangwen Sun, Zhiyu Zhang, Xiaoquan Song, Jiqiao Liu, Weibiao Chen, and Songhua Wu
Atmos. Meas. Tech., 18, 2021–2039, https://doi.org/10.5194/amt-18-2021-2025, https://doi.org/10.5194/amt-18-2021-2025, 2025
Short summary
Short summary
This paper presents a comprehensive calibration procedure for the first spaceborne high-spectral-resolution lidar with an iodine vapor absorption filter Aerosol and Carbon Detection Lidar (ACDL) on board DQ-1 by utilizing nighttime 532 nm multi-channel data. We analyzed the error sources of the multi-channel calibration coefficients and assessed the results. The results indicate that the uncertainty of the clear-air scattering ratio was within the anticipated range of 7.9 %.
Ulrike Stöffelmair, Thomas Popp, Marco Vountas, and Hartmut Bösch
Atmos. Meas. Tech., 18, 2005–2020, https://doi.org/10.5194/amt-18-2005-2025, https://doi.org/10.5194/amt-18-2005-2025, 2025
Short summary
Short summary
Aerosol composition has a large influence on the climate system. This study uses realistic simulated scenarios to look at the information content of a combination of three satellite-based instruments (SLSTR, IASI and GOME-2). It shows that it is possible to retrieve 6 to 15 different aerosol components in addition to the aerosol optical depth (AOD) and different surface parameters. The results are used for the development of a synergistic multi-sensor retrieval algorithm.
Yenny González, María F. Sánchez-Barrero, Ioana Popovici, África Barreto, Stephane Victori, Ellsworth J. Welton, Rosa D. García, Pablo G. Sicilia, Fernando A. Almansa, Carlos Torres, and Philippe Goloub
Atmos. Meas. Tech., 18, 1885–1908, https://doi.org/10.5194/amt-18-1885-2025, https://doi.org/10.5194/amt-18-1885-2025, 2025
Short summary
Short summary
We characterize the optical properties of various aerosols using a compact dual-wavelength depolarization lidar (CIMEL CE376) at 532 and 808 nm. Through a modified two-wavelength Klett inversion method, we assess the vertical distribution and temporal evolution of Saharan dust, volcanic aerosols and wildfire smoke in the subtropical North Atlantic from August 2021 to August 2023. The study confirms the CE376 lidar's effectiveness in monitoring and characterizing atmospheric aerosols over time.
Jianglong Zhang, Jeffrey S. Reid, Blake T. Sorenson, Steven D. Miller, Miguel O. Román, Zhuosen Wang, Robert J. D. Spurr, Shawn Jaker, Thomas F. Eck, and Juli I. Rubin
Atmos. Meas. Tech., 18, 1787–1810, https://doi.org/10.5194/amt-18-1787-2025, https://doi.org/10.5194/amt-18-1787-2025, 2025
Short summary
Short summary
Using observations from the Visible Infrared Imaging Radiometer Suite day–night band, we developed a method for constructing gridded nighttime aerosol optical thickness (AOT) data based on the spatial derivative of measured top-of-atmosphere attenuated upwelling artificial lights at night. The gridded nighttime AOT retrievals, compared against Aerosol Robotic Network data, show reasonable skill levels for potential data assimilation, air quality, and climate studies of significant events.
Gladiola Malollari, Albert Ansmann, Holger Baars, Cristofer Jimenez, Julian Hofer, Ronny Engelmann, Nathan Skupin, and Seit Shallari
EGUsphere, https://doi.org/10.5194/egusphere-2025-1386, https://doi.org/10.5194/egusphere-2025-1386, 2025
Short summary
Short summary
This study presents, for the first time, the uncertainty analysis of the Ångström exponent assumption on the full set of retrievable optical properties obtained with Raman lidar. A quantitative comparison between the pure rotational and vibrational-rotational Raman lidar approaches is presented. A minor impact of a wrong Ångström exponent on the determined aerosol optical properties is found.
Maryam Pashayi, Mehran Satari, and Mehdi Momeni Shahraki
Atmos. Meas. Tech., 18, 1415–1439, https://doi.org/10.5194/amt-18-1415-2025, https://doi.org/10.5194/amt-18-1415-2025, 2025
Short summary
Short summary
Multi-layer aerosol optical depth (AOD) is retrieved using the geostationary Spinning Enhanced Visible and Infrared Imager (SEVIRI) and machine learning, trained on Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data. The model provides AOD at a 3 km × 3 km spatial and 15 min temporal resolution over Europe. It accurately captured multi-layer AOD dynamics during Saharan dust transport and the Mount Etna eruption, demonstrating consistent physical accuracy.
Roberto Román, Daniel González-Fernández, Juan Carlos Antuña-Sánchez, Celia Herrero del Barrio, Sara Herrero-Anta, África Barreto, Victoria E. Cachorro, Lionel Doppler, Ramiro González, Christoph Ritter, David Mateos, Natalia Kouremeti, Gustavo Copes, Abel Calle, María José Granados-Muñoz, Carlos Toledano, and Ángel M. de Frutos
EGUsphere, https://doi.org/10.5194/egusphere-2025-667, https://doi.org/10.5194/egusphere-2025-667, 2025
Short summary
Short summary
This paper presents a novel technique to extract starlight signals from all-sky images and retrieve aerosol optical depth (AOD). It is validated against lunar photometry, showing a strong correlation between both data series. This innovative approach will expand nocturnal AOD measurements to more locations, as all-sky cameras are a simpler and more cost-effective alternative to stellar and lunar photometers.
Jade Low, Roger Teoh, Joel Ponsonby, Edward Gryspeerdt, Marc Shapiro, and Marc E. J. Stettler
Atmos. Meas. Tech., 18, 37–56, https://doi.org/10.5194/amt-18-37-2025, https://doi.org/10.5194/amt-18-37-2025, 2025
Short summary
Short summary
The radiative forcing due to contrails is of the same order of magnitude as aviation CO2 emissions but has a higher uncertainty. Observations are vital to improve our understanding of the contrail lifecycle, improve models, and measure the effect of mitigation action. Here, we use ground-based cameras combined with flight telemetry to track visible contrails and measure their lifetime and width. We evaluate model predictions and demonstrate the capability of this approach.
Alexei Rozanov, Christine Pohl, Carlo Arosio, Adam Bourassa, Klaus Bramstedt, Elizaveta Malinina, Landon Rieger, and John P. Burrows
Atmos. Meas. Tech., 17, 6677–6695, https://doi.org/10.5194/amt-17-6677-2024, https://doi.org/10.5194/amt-17-6677-2024, 2024
Short summary
Short summary
We developed a new algorithm to retrieve vertical distributions of aerosol extinction coefficients in the stratosphere. The algorithm is applied to measurements of scattered solar light from the spaceborne OMPS-LP (Ozone Mapper and Profiler Suite Limb Profiler) instrument. The retrieval results are compared to data from other spaceborne instruments and used to investigate the evolution of the aerosol plume following the eruption of the Hunga Tonga–Hunga Ha'apai volcano in January 2022.
Robert A. Ryan, Mark A. Vaughan, Sharon D. Rodier, Jason L. Tackett, John A. Reagan, Richard A. Ferrare, Johnathan W. Hair, John A. Smith, and Brian J. Getzewich
Atmos. Meas. Tech., 17, 6517–6545, https://doi.org/10.5194/amt-17-6517-2024, https://doi.org/10.5194/amt-17-6517-2024, 2024
Short summary
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.
Annachiara Bellini, Henri Diémoz, Luca Di Liberto, Gian Paolo Gobbi, Alessandro Bracci, Ferdinando Pasqualini, and Francesca Barnaba
Atmos. Meas. Tech., 17, 6119–6144, https://doi.org/10.5194/amt-17-6119-2024, https://doi.org/10.5194/amt-17-6119-2024, 2024
Short summary
Short summary
We provide a comprehensive overview of the Italian Automated LIdar-CEilometer network, ALICENET, describing its infrastructure, aerosol retrievals, and main applications. The supplement covers data-processing details. We include examples of output products, comparisons with independent data, and examples of the network capability to provide near-real-time aerosol fields over Italy. ALICENET is expected to benefit the sectors of air quality, radiative budget/solar energy, and aviation safety.
Andrea Porcheddu, Ville Kolehmainen, Timo Lähivaara, and Antti Lipponen
Atmos. Meas. Tech., 17, 5747–5764, https://doi.org/10.5194/amt-17-5747-2024, https://doi.org/10.5194/amt-17-5747-2024, 2024
Short summary
Short summary
This study focuses on improving the accuracy of satellite-based PM2.5 retrieval, crucial for monitoring air quality and its impact on health. It employs machine learning to correct the AOD-to-PM2.5 conversion ratio using various data sources. The approach produces high-resolution PM2.5 estimates with improved accuracy. The method is flexible and can incorporate additional training data from different sources, making it a valuable tool for air quality monitoring and epidemiological studies.
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine A. Remer, Zhaohui Zhang, Virginia Sawyer, Jennifer Wei, Sally Zhao, Min Oo, V. Praju Kiliyanpilakkil, and Xiaohua Pan
Atmos. Meas. Tech., 17, 5455–5476, https://doi.org/10.5194/amt-17-5455-2024, https://doi.org/10.5194/amt-17-5455-2024, 2024
Short summary
Short summary
In this study, for the first time, we combined aerosol data from six satellites using a unified algorithm. The global datasets are generated at a high spatial resolution of about 25 km with an interval of 30 min. The new datasets are compared against ground truth and verified. They will be useful for various applications such as air quality monitoring, climate research, pollution diurnal variability, long-range smoke and dust transport, and evaluation of regional and global models.
Mégane Ventura, Fabien Waquet, Isabelle Chiapello, Gérard Brogniez, Frédéric Parol, Frédérique Auriol, Rodrigue Loisil, Cyril Delegove, Luc Blarel, Oleg Dubovik, Marc Mallet, Cyrille Flamant, and Paola Formenti
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-121, https://doi.org/10.5194/amt-2024-121, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
Biomass burning aerosols (BBA) from Central Africa, are transported above stratocumulus clouds. The absorption of solar energy by aerosols induce warming, altering the clouds dynamics. We developed an approach that combines polarimeter and lidar to quantify it. This methodology is assessed during the AEROCLO-SA campaign. To validate it, we used flux measurements acquired during aircraft loop descents. Major perspective is the generalization of this method to the global level.
Lijuan Chen, Ren Wang, Ying Fei, Peng Fang, Yong Zha, and Haishan Chen
Atmos. Meas. Tech., 17, 4411–4424, https://doi.org/10.5194/amt-17-4411-2024, https://doi.org/10.5194/amt-17-4411-2024, 2024
Short summary
Short summary
This study explores the problems of surface reflectance estimation from previous MISR satellite remote sensing images and develops an error correction model to obtain a higher-precision aerosol optical depth (AOD) product. High-accuracy AOD is important not only for the daily monitoring of air pollution but also for the study of energy exchange between land and atmosphere. This will help further improve the retrieval accuracy of multi-angle AOD on large spatial scales and for long time series.
Anton Lopatin, Oleg Dubovik, Georgiy Stenchikov, Ellsworth J. Welton, Illia Shevchenko, David Fuertes, Marcos Herreras-Giralda, Tatsiana Lapyonok, and Alexander Smirnov
Atmos. Meas. Tech., 17, 4445–4470, https://doi.org/10.5194/amt-17-4445-2024, https://doi.org/10.5194/amt-17-4445-2024, 2024
Short summary
Short summary
We compare aerosol properties over the King Abdullah University of Science and Technology campus using Generalized Retrieval of Aerosol and Surface Properties (GRASP) and the Micro-Pulse Lidar Network (MPLNET). We focus on the impact of different aerosol retrieval assumptions on daytime and nighttime retrievals and analyze seasonal variability in aerosol properties, aiding in understanding aerosol behavior and improving retrieval. Our work has implications for climate and public health.
Yeseul Cho, Jhoon Kim, Sujung Go, Mijin Kim, Seoyoung Lee, Minseok Kim, Heesung Chong, Won-Jin Lee, Dong-Won Lee, Omar Torres, and Sang Seo Park
Atmos. Meas. Tech., 17, 4369–4390, https://doi.org/10.5194/amt-17-4369-2024, https://doi.org/10.5194/amt-17-4369-2024, 2024
Short summary
Short summary
Aerosol optical properties have been provided by the Geostationary Environment Monitoring Spectrometer (GEMS), the world’s first geostationary-Earth-orbit (GEO) satellite instrument designed for atmospheric environmental monitoring. This study describes improvements made to the GEMS aerosol retrieval algorithm (AERAOD) and presents its validation results. These enhancements aim to provide more accurate and reliable aerosol-monitoring results for Asia.
Minseok Kim, Jhoon Kim, Hyunkwang Lim, Seoyoung Lee, Yeseul Cho, Yun-Gon Lee, Sujung Go, and Kyunghwa Lee
Atmos. Meas. Tech., 17, 4317–4335, https://doi.org/10.5194/amt-17-4317-2024, https://doi.org/10.5194/amt-17-4317-2024, 2024
Short summary
Short summary
Information about aerosol loading in the atmosphere can be collected from various satellite instruments. Aerosol products from various satellite instruments have their own error characteristics. This study statistically merged aerosol optical depth datasets from multiple instruments aboard geostationary satellites considering uncertainties. Also, a deep neural network technique is adopted for aerosol data merging.
Christine Pohl, Felix Wrana, Alexei Rozanov, Terry Deshler, Elizaveta Malinina, Christian von Savigny, Landon A. Rieger, Adam E. Bourassa, and John P. Burrows
Atmos. Meas. Tech., 17, 4153–4181, https://doi.org/10.5194/amt-17-4153-2024, https://doi.org/10.5194/amt-17-4153-2024, 2024
Short summary
Short summary
Knowledge of stratospheric aerosol characteristics is important for understanding chemical and climate aerosol feedbacks. Two particle size distribution parameters, the aerosol extinction coefficient and the effective radius, are obtained from SCIAMACHY limb observations. The aerosol characteristics show good agreement with independent data sets from balloon-borne and satellite observations. This data set expands the limited knowledge of stratospheric aerosol characteristics.
Igor Veselovskii, Boris Barchunov, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Mikhail Korenskii, Gaël Dubois, William Boissiere, and Nikita Kasianik
Atmos. Meas. Tech., 17, 4137–4152, https://doi.org/10.5194/amt-17-4137-2024, https://doi.org/10.5194/amt-17-4137-2024, 2024
Short summary
Short summary
The paper presents a new method that categorizes atmospheric aerosols by analyzing their optical properties with a Mie–Raman–fluorescence lidar. The research specifically looks into understanding the presence of smoke, urban, and dust aerosols in the mixtures identified by this lidar. The reliability of the results is evaluated using the Monte Carlo technique. The effectiveness of this approach is successfully demonstrated through testing in ATOLL, an observatory influenced by diverse aerosols.
Fred Prata
Atmos. Meas. Tech., 17, 3751–3764, https://doi.org/10.5194/amt-17-3751-2024, https://doi.org/10.5194/amt-17-3751-2024, 2024
Short summary
Short summary
Geostationary satellite data have been used to measure the stratospheric aerosols from the explosive Hunga volcanic eruption by using the data in a novel way. The onboard imager views part of the Earth's limb and data from this region were analysed to generate vertical cross-sections of aerosols high in the atmosphere. The analyses show the hemispheric spread of the aerosols and their vertical structure in layers from 22–28 km in the stratosphere.
Emmanouil Proestakis, Antonis Gkikas, Thanasis Georgiou, Anna Kampouri, Eleni Drakaki, Claire L. Ryder, Franco Marenco, Eleni Marinou, and Vassilis Amiridis
Atmos. Meas. Tech., 17, 3625–3667, https://doi.org/10.5194/amt-17-3625-2024, https://doi.org/10.5194/amt-17-3625-2024, 2024
Short summary
Short summary
A new four-dimensional, multiyear, and near-global climate data record of the fine-mode (submicrometer diameter) and coarse-mode (supermicrometer diameter) components of atmospheric pure dust is presented. The dataset is considered unique with respect to a wide range of potential applications, including climatological, time series, and trend analysis over extensive geographical domains and temporal periods, validation of atmospheric dust models and datasets, and air quality.
Robin Miri, Olivier Pujol, Qiaoyun Hu, Philippe Goloub, Igor Veselovskii, Thierry Podvin, and Fabrice Ducos
Atmos. Meas. Tech., 17, 3367–3375, https://doi.org/10.5194/amt-17-3367-2024, https://doi.org/10.5194/amt-17-3367-2024, 2024
Short summary
Short summary
This paper focuses on the use of fluorescence to study aerosols with lidar. An innovative method for aerosol hygroscopic growth study using fluorescence is presented. The paper presents case studies to showcase the effectiveness and potential of the proposed approach. These advancements will contribute to better understanding the interactions between aerosols and water vapor, with future work expected to be dedicated to aerosol–cloud interaction.
Kabseok Ko, Seokheon Cho, and Ramesh R. Rao
Atmos. Meas. Tech., 17, 3303–3322, https://doi.org/10.5194/amt-17-3303-2024, https://doi.org/10.5194/amt-17-3303-2024, 2024
Short summary
Short summary
In our study, we examined how NO2, temperature, and relative humidity influence the calibration of PurpleAir PA-II sensors. We found that incorporating NO2 data from collocated reliable instruments enhances PM2.5 calibration performance. Due to the impracticality of collocating reliable NO2 instruments with sensors, we suggest using distant NO2 data for calibration. We demonstrated that performance improves when distant NO2 correlates highly with collocated NO2 measurements.
Daniel J. V. Robbins, Caroline A. Poulsen, Steven T. Siems, Simon R. Proud, Andrew T. Prata, Roy G. Grainger, and Adam C. Povey
Atmos. Meas. Tech., 17, 3279–3302, https://doi.org/10.5194/amt-17-3279-2024, https://doi.org/10.5194/amt-17-3279-2024, 2024
Short summary
Short summary
Extreme wildfire events are becoming more common with climate change. The smoke plumes associated with these wildfires are not captured by current operational satellite products due to their high optical thickness. We have developed a novel aerosol retrieval for the Advanced Himawari Imager to study these plumes. We find very high values of optical thickness not observed in other operational satellite products, suggesting these plumes have been missed in previous studies.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Didier Fussen, Christine Bingen, Filip Vanhellemont, Nina Mateshvili, Alexei Rozanov, and Christine Pohl
Atmos. Meas. Tech., 17, 3085–3101, https://doi.org/10.5194/amt-17-3085-2024, https://doi.org/10.5194/amt-17-3085-2024, 2024
Short summary
Short summary
We have developed the new multi-wavelength dataset of aerosol extinction profiles, which are retrieved from the averaged transmittance spectra by the Global Ozone Monitoring by Occultation of Stars instrument aboard Envisat. The retrieved aerosol extinction profiles are provided in the altitude range 10–40 km at 400, 440, 452, 470, 500, 525, 550, 672 and 750 nm for the period 2002–2012. FMI-GOMOSaero aerosol profiles have improved quality; they are in good agreement with other datasets.
Jasper S. Wijnands, Arnoud Apituley, Diego Alves Gouveia, and Jan Willem Noteboom
Atmos. Meas. Tech., 17, 3029–3045, https://doi.org/10.5194/amt-17-3029-2024, https://doi.org/10.5194/amt-17-3029-2024, 2024
Short summary
Short summary
The mixing of air in the lower atmosphere influences the concentration of air pollutants and greenhouse gases. Our study developed a new method, Deep-Pathfinder, to estimate mixing layer height. Deep-Pathfinder analyses imagery with aerosol observations using artificial intelligence techniques for computer vision. Compared to existing methods, it improves temporal consistency and resolution and can be used in real time, which is valuable for aviation, forecasting, and air quality monitoring.
Liang Chang, Jing Li, Jingjing Ren, Changrui Xiong, and Lu Zhang
Atmos. Meas. Tech., 17, 2637–2648, https://doi.org/10.5194/amt-17-2637-2024, https://doi.org/10.5194/amt-17-2637-2024, 2024
Short summary
Short summary
We described a modified lidar inversion algorithm to retrieve aerosol extinction and size distribution simultaneously from two-wavelength elastic lidar measurements. Its major advantage is that the lidar ratio of each layer is determined iteratively by a lidar ratio–Ångström exponent lookup table. The algorithm was applied to the Raman lidar and CALIOP measurements. The retrieved results by our method are in good agreement with those achieved by Raman method.
Zihao Yuan, Guangliang Fu, Bastiaan van Diedenhoven, Hai Xiang Lin, Jan Willem Erisman, and Otto P. Hasekamp
Atmos. Meas. Tech., 17, 2595–2610, https://doi.org/10.5194/amt-17-2595-2024, https://doi.org/10.5194/amt-17-2595-2024, 2024
Short summary
Short summary
Currently, aerosol properties from spaceborne multi-angle polarimeter (MAP) instruments can only be retrieved in cloud-free areas or in areas where an aerosol layer is located above a cloud. Therefore, it is important to be able to identify cloud-free pixels for which an aerosol retrieval algorithm can provide meaningful output. The developed neural network cloud screening demonstrates that cloud masking for MAP aerosol retrieval can be based on the MAP measurements themselves.
Nicholas Ernest, Larry W. Thomason, and Terry Deshler
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-62, https://doi.org/10.5194/amt-2024-62, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
We use balloon-borne measurements of aerosol size distribution (ASD) made by the University of Wyoming (UW) to derive distributions which are representative of the ASDs that underlie measurements made by the Stratospheric Aerosol and Gas Experiment II (SAGE II). A simple single mode log-normal distribution has in the past been used to derive ASD from SAGE II data; here we derive bimodal log-normal distributions. Reproducing median aerosol properties, however sometimes with wide variance.
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.
Travis N. Knepp, Mahesh Kovilakam, Larry Thomason, and Stephen J. Miller
Atmos. Meas. Tech., 17, 2025–2054, https://doi.org/10.5194/amt-17-2025-2024, https://doi.org/10.5194/amt-17-2025-2024, 2024
Short summary
Short summary
An algorithm is presented to derive a new SAGE III/ISS (Stratospheric Aerosol and Gas Experiment III on the International Space Station) Level-2 product: the size distribution of stratospheric particles. This is a significant improvement over previous techniques in that we now provide uncertainty estimates for all inferred parameters. We also evaluated the stability of this method in retrieving bimodal distribution parameters. We present a special application to the 2022 eruption of Hunga Tonga.
Mijin Kim, Robert C. Levy, Lorraine A. Remer, Shana Mattoo, and Pawan Gupta
Atmos. Meas. Tech., 17, 1913–1939, https://doi.org/10.5194/amt-17-1913-2024, https://doi.org/10.5194/amt-17-1913-2024, 2024
Short summary
Short summary
The study focused on evaluating and modifying the surface reflectance parameterization (SRP) of the Dark Target (DT) algorithm for geostationary observation. When using the DT SRP with the ABIs sensor on GOES-R, artificial diurnal signatures were present in AOD retrieval. To overcome this issue, a new SRP was developed, incorporating solar zenith angle and land cover type. The revised SRP resulted in improved AOD retrieval, demonstrating reduced bias around local noon.
Guangyao Dai, Songhua Wu, Wenrui Long, Jiqiao Liu, Yuan Xie, Kangwen Sun, Fanqian Meng, Xiaoquan Song, Zhongwei Huang, and Weibiao Chen
Atmos. Meas. Tech., 17, 1879–1890, https://doi.org/10.5194/amt-17-1879-2024, https://doi.org/10.5194/amt-17-1879-2024, 2024
Short summary
Short summary
An overview is given of the main algorithms applied to derive the aerosol and cloud optical property product of the Aerosol and Carbon Detection Lidar (ACDL), which is capable of globally profiling aerosol and cloud optical properties with high accuracy. The paper demonstrates the observational capabilities of ACDL for aerosol and cloud vertical structure and global distribution through two optical property product measurement cases and global aerosol optical depth profile observations.
Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, William Boissiere, Mikhail Korenskiy, Nikita Kasianik, Sergey Khaykyn, and Robin Miri
Atmos. Meas. Tech., 17, 1023–1036, https://doi.org/10.5194/amt-17-1023-2024, https://doi.org/10.5194/amt-17-1023-2024, 2024
Short summary
Short summary
Measurements of transported smoke layers were performed with a lidar in Lille and a five-channel fluorescence lidar in Moscow. Results show the peak of fluorescence in the boundary layer is at 438 nm, while in the smoke layer it shifts to longer wavelengths. The fluorescence depolarization is 45 % to 55 %. The depolarization ratio of the water vapor channel is low (2 ± 0.5 %) in the absence of fluorescence and can be used to evaluate the contribution of fluorescence to water vapor signal.
Viet Le, Hannah Lobo, Ewan J. O'Connor, and Ville Vakkari
Atmos. Meas. Tech., 17, 921–941, https://doi.org/10.5194/amt-17-921-2024, https://doi.org/10.5194/amt-17-921-2024, 2024
Short summary
Short summary
This study offers a long-term overview of aerosol particle depolarization ratio at the wavelength of 1565 nm obtained from vertical profiling measurements by Halo Doppler lidars during 4 years at four different locations across Finland. Our observations support the long-term usage of Halo Doppler lidar depolarization ratio such as the detection of aerosols that may pose a safety risk for aviation. Long-range Saharan dust transport and pollen transport are also showcased here.
Athena Augusta Floutsi, Holger Baars, and Ulla Wandinger
Atmos. Meas. Tech., 17, 693–714, https://doi.org/10.5194/amt-17-693-2024, https://doi.org/10.5194/amt-17-693-2024, 2024
Short summary
Short summary
We introduce an aerosol-typing scheme (HETEAC-Flex) based on lidar-derived intensive optical properties and applicable to ground-based and spaceborne lidars. HETEAC-Flex utilizes the optimal estimation method and enables the identification of up to four different aerosol components, as well as the determination of their contribution to the aerosol mixture in terms of relative volume. The aerosol components represent common aerosol types such as dust, sea salt, smoke and pollution.
James A. Limbacher, Ralph A. Kahn, Mariel D. Friberg, Jaehwa Lee, Tyler Summers, and Hai Zhang
Atmos. Meas. Tech., 17, 471–498, https://doi.org/10.5194/amt-17-471-2024, https://doi.org/10.5194/amt-17-471-2024, 2024
Short summary
Short summary
We present the new Multi-Angle Geostationary Aerosol Retrieval Algorithm (MAGARA) that fuses observations from GOES-16 and GOES-17 to retrieve information about aerosol loading (at 10–15 min cadence) and aerosol particle properties (daily), all at pixel-level resolution. We present MAGARA results for three case studies: the 2018 California Camp Fire, the 2019 Williams Flats Fire, and the 2019 Kincade Fire. We also compare MAGARA aerosol loading and particle properties with AERONET.
Juseon Shin, Gahyeong Kim, Dukhyeon Kim, Matthias Tesche, Gahyeon Park, and Youngmin Noh
Atmos. Meas. Tech., 17, 397–406, https://doi.org/10.5194/amt-17-397-2024, https://doi.org/10.5194/amt-17-397-2024, 2024
Short summary
Short summary
We introduce the multi-section method, a novel approach for stable extinction coefficient retrievals in horizontally scanning aerosol lidar measurements, in this study. Our method effectively removes signal–noise-induced irregular peaks and derives a reference extinction coefficient, αref, from multiple scans, resulting in a strong correlation (>0.74) with PM2.5 mass concentrations. Case studies demonstrate its utility in retrieving spatio-temporal aerosol distributions and PM2.5 concentrations.
Basudev Swain, Marco Vountas, Adrien Deroubaix, Luca Lelli, Yanick Ziegler, Soheila Jafariserajehlou, Sachin S. Gunthe, Andreas Herber, Christoph Ritter, Hartmut Bösch, and John P. Burrows
Atmos. Meas. Tech., 17, 359–375, https://doi.org/10.5194/amt-17-359-2024, https://doi.org/10.5194/amt-17-359-2024, 2024
Short summary
Short summary
Aerosols are suspensions of particles dispersed in the air. In this study, we use a novel retrieval of satellite data to investigate an optical property of aerosols, the aerosol optical depth, in the high Arctic to assess their direct and indirect roles in climate change. This study demonstrates that the presented approach shows good quality and very promising potential.
Gabriel Calassou, Pierre-Yves Foucher, and Jean-François Léon
Atmos. Meas. Tech., 17, 57–71, https://doi.org/10.5194/amt-17-57-2024, https://doi.org/10.5194/amt-17-57-2024, 2024
Short summary
Short summary
We propose analyzing the aerosol composition of plumes emitted by different industrial stacks using PRISMA satellite hyperspectral observations. Three industrial sites have been observed: a coal-fired power plant in South Africa, a steel plant in China, and gas flaring at an oil extraction site in Algeria. Aerosol optical thickness and particle radius are retrieved within the plumes. The mass flow rate of particulate matter is estimated in the plume using the integrated mass enhancement method.
Zihan Zhang, Guangliang Fu, and Otto Hasekamp
Atmos. Meas. Tech., 16, 6051–6063, https://doi.org/10.5194/amt-16-6051-2023, https://doi.org/10.5194/amt-16-6051-2023, 2023
Short summary
Short summary
In order to conduct accurate aerosol retrieval over snow, the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) algorithm is extended with a bi-directional reflection distribution function for snow surfaces. The experiments with both synthetic and real data show that the extended RemoTAP maintains capability for snow-free pixels and has obvious advantages in accuracy and the fraction of successful retrievals for retrieval over snow, especially over surfaces with snow cover > 75 %.
Alexandra Tsekeri, Anna Gialitaki, Marco Di Paolantonio, Davide Dionisi, Gian Luigi Liberti, Alnilam Fernandes, Artur Szkop, Aleksander Pietruczuk, Daniel Pérez-Ramírez, Maria J. Granados Muñoz, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Diego Bermejo Pantaleón, Juan Antonio Bravo-Aranda, Anna Kampouri, Eleni Marinou, Vassilis Amiridis, Michael Sicard, Adolfo Comerón, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Salvatore Romano, Maria Rita Perrone, Xiaoxia Shang, Mika Komppula, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Diofantos Hadjimitsis, Francisco Navas-Guzmán, Alexander Haefele, Dominika Szczepanik, Artur Tomczak, Iwona S. Stachlewska, Livio Belegante, Doina Nicolae, Kalliopi Artemis Voudouri, Dimitris Balis, Athena A. Floutsi, Holger Baars, Linda Miladi, Nicolas Pascal, Oleg Dubovik, and Anton Lopatin
Atmos. Meas. Tech., 16, 6025–6050, https://doi.org/10.5194/amt-16-6025-2023, https://doi.org/10.5194/amt-16-6025-2023, 2023
Short summary
Short summary
EARLINET/ACTRIS organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. The work presented herein focuses on deriving a common methodology for applying a synergistic retrieval that utilizes the network's ground-based passive and active remote sensing measurements and deriving the aerosols from anthropogenic activities over Europe.
Meng Gao, Bryan A. Franz, Peng-Wang Zhai, Kirk Knobelspiesse, Andrew M. Sayer, Xiaoguang Xu, J. Vanderlei Martins, Brian Cairns, Patricia Castellanos, Guangliang Fu, Neranga Hannadige, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Frederick Patt, Anin Puthukkudy, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 5863–5881, https://doi.org/10.5194/amt-16-5863-2023, https://doi.org/10.5194/amt-16-5863-2023, 2023
Short summary
Short summary
This study evaluated the retrievability and uncertainty of aerosol and ocean properties from PACE's HARP2 instrument using enhanced neural network models with the FastMAPOL algorithm. A cascading retrieval method is developed to improve retrieval performance. A global set of simulated HARP2 data is generated and used for uncertainty evaluations. The performance assessment demonstrates that the FastMAPOL algorithm is a viable approach for operational application to HARP2 data after PACE launch.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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 %.
Cited articles
Ahmad, Z., Franz, B. A., McClain, C. R., Kwiatkowska, E. J., Werdell, J.,
Shettle, E. P., and Holben, B. N.: New aerosol models for the retrieval of
aerosol optical thickness and normalized water-leaving radiances from the
SeaWiFS and MODIS sensors over coastal regions and open oceans,
Appl. Optics, 49, 5545–5560, 2010. a
Anderson, G., Clough, S., Kneizys, F., Chetwynd, J., and Shettle, E.: AFGL
Atmospheric Constituent Profiles (0.120 km), Air Force Geophysics Lab., Hanscom AFB, MA, USA, p. 46, 1986. a
Bohren, C. F. and Huffman, D. R.: Absorption and Scattering of Light by Small
Particles, WILEY‐VCH Verlag GmbH & Co. KGaA, 1998. a
Burton, S. P., Hair, J. W., Kahnert, M., Ferrare, R. A., Hostetler, C. A., Cook, A. L., Harper, D. B., Berkoff, T. A., Seaman, S. T., Collins, J. E., Fenn, M. A., and Rogers, R. R.: Observations of the spectral dependence of linear particle depolarization ratio of aerosols using NASA Langley airborne High Spectral Resolution Lidar, Atmos. Chem. Phys., 15, 13453–13473, https://doi.org/10.5194/acp-15-13453-2015, 2015. a
Cairns, B., Russell, E. E., and Travis, L. D.: Research Scanning Polarimeter:
calibration and ground-based measurements, Proc. SPIE, 3754, 186–196, https://doi.org/10.1117/12.366329,
1999. a, b
Carr, M.-E., Friedrichs, M. A., Schmeltz, M., Aita, M. N., Antoine, D., Arrigo,
K. R., Asanuma, I., Aumont, O., Barber, R., Behrenfeld, M., Bidigare, R.,
Buitenhuis, E. T., Campbell, J., Ciotti, A., Dierssen, H., Dowell, M., Dunne,
J., Esaias, W., Gentili, B., Gregg, W., Groom, S., Hoepffner, N., Ishizaka,
J., Kameda, T., Quéré, C. L., Lohrenz, S., Marra, J., Mélin, F., Moore,
K., Morel, A., Reddy, T. E., Ryan, J., Scardi, M., Smyth, T., Turpie, K.,
Tilstone, G., Waters, K., and Yamanaka, Y.: A comparison of global estimates
of marine primary production from ocean color,
Deep-Sea Res. Pt. II, 53, 741–770,
https://doi.org/10.1016/j.dsr2.2006.01.028,
2006. a
Chowdhary, J., Cairns, B., Mishchenko, M., and Travis, L.: Retrieval of aerosol
properties over the ocean using multispectral and multiangle
Photopolarimetric measurements from the Research Scanning Polarimeter,
Geophys. Res. Lett., 28, 243–246, https://doi.org/10.1029/2000GL011783,
2001. a
Chowdhary, J., Cairns, B., Mishchenko, M. I., Hobbs, P. V., Cota, G. F.,
Redemann, J., Rutledge, K., Holben, B. N., and Russell, E.: Retrieval of
Aerosol Scattering and Absorption Properties from Photopolarimetric
Observations over the Ocean during the CLAMS Experiment,
J. Atmos. Sci., 62, 1093–1117, https://doi.org/10.1175/JAS3389.1,
2005. a
Chowdhary, J., Cairns, B., Waquet, F., Knobelspiesse, K., Ottaviani, M.,
Redemann, J., Travis, L., and Mishchenko, M.: Sensitivity of multiangle,
multispectral polarimetric remote sensing over open oceans to water-leaving
radiance: Analyses of RSP data acquired during the MILAGRO campaign, Remote Sens. Environ., 118, 284–308, 2012. a
Chowdhary, J., Stamnes, S., Zhang, M., Scarino, A., Wasilewski, A., and Cairns,
B.: Combining multispectral VIS-SWIR polarimetry and UV-NIR hyperspectral
imagery to retrieve aerosol and ocean color properties from remote sensing:
case studies for airborne RSP and GCAS observations, American Geophysical
Union, Fall Meeting, abstract #OS11D-1435, 2018. a
Chowdhary, J., Zhai, P.-W., Boss, E., Dierssen, H., Frouin, R., Ibrahim, A.,
Lee, Z., Remer, L. A., Twardowski, M., Xu, F., Zhang, X., Ottaviani, M.,
Espinosa, W. R., and Ramon, D.: Modeling Atmosphere-Ocean Radiative Transfer:
A PACE Mission Perspective, Front. Earth Sci., 7, 100,
https://doi.org/10.3389/feart.2019.00100,
2019. a, b, c
Cox, C. and Munk, W.: Measurement of the Roughness of the Sea Surface from
Photographs of the Sun's Glitter, J. Opt. Soc. Am., 44, 838–850, 1954. a
Craig, S. E., Jones, C. T., Li, W. K., Lazin, G., Horne, E., Caverhill, C., and
Cullen, J. J.: Deriving optical metrics of coastal phytoplankton biomass from
ocean colour, Remote Sens. Environ., 119, 72–83,
https://doi.org/10.1016/j.rse.2011.12.007,
2012. a
Croft, B., Martin, R. V., Leaitch, W. R., Burkart, J., Chang, R. Y.-W., Collins, D. B., Hayes, P. L., Hodshire, A. L., Huang, L., Kodros, J. K., Moravek, A., Mungall, E. L., Murphy, J. G., Sharma, S., Tremblay, S., Wentworth, G. R., Willis, M. D., Abbatt, J. P. D., and Pierce, J. R.: Arctic marine secondary organic aerosol contributes significantly to summertime particle size distributions in the Canadian Arctic Archipelago, Atmos. Chem. Phys., 19, 2787–2812, https://doi.org/10.5194/acp-19-2787-2019, 2019. a
d'Almeida, G. A., Koepke, P., and Shettle, E. P.: Atmospheric aerosols: global
climatology and radiative characteristics, Hampton, Va, USA, A. Deepak Pub., 1991 a
Aerosol Robotic Network (Aeronet) Technical Document: Description of Aerosol Inversion Uncertainty for Level 2 Products, available at: https://aeronet.gsfc.nasa.gov/new_web/optical_properties.html,
last access: 7 July 2020. a
Dierssen, H. M. and Randolph, K.: Remote Sensing of Ocean Color,
Springer New York, New York, NY, 439–472, https://doi.org/10.1007/978-1-4614-5684-1_18,
2013. a
Diner, D. J., Xu, F., Garay, M. J., Martonchik, J. V., Rheingans, B. E., Geier, S., Davis, A., Hancock, B. R., Jovanovic, V. M., Bull, M. A., Capraro, K., Chipman, R. A., and McClain, S. C.: The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI): a new tool for aerosol and cloud remote sensing, Atmos. Meas. Tech., 6, 2007–2025, https://doi.org/10.5194/amt-6-2007-2013, 2013. a
Diner, D. J., Boland, S. W., Brauer, M., Bruegge, C., Burke, K. A., Chipman,
R., Girolamo, L. D., Garay, M. J., Hasheminassab, S., Hyer, E., Jerrett, M.,
Jovanovic, V., Kalashnikova, O. V., Liu, Y., Lyapustin, A. I., Martin, R. V.,
Nastan, A., Ostro, B. D., Ritz, B., Schwartz, J., Wang, J., and Xu, F.:
Advances in multiangle satellite remote sensing of speciated airborne
particulate matter and association with adverse health effects: from MISR to
MAIA, J. Appl. Remote Sens., 12, 1–22,
https://doi.org/10.1117/1.JRS.12.042603,
2018. a
Dubovik, O. and King, M. D.: A flexible inversion algorithm for retrieval of
aerosol optical properties from Sun and sky radiance measurements,
J. Geophys. Res.-Atmos., 105, 20673–20696, 2000. a
Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B. N., Mishchenko, M., Yang, P.,
Eck, T. F., Volten, H., Muñoz, O., Veihelmann, B., van der Zande, W. J.,
Leon, J.-F., Sorokin, M., and Slutsker, I.: Application of spheroid models to
account for aerosol particle nonsphericity in remote sensing of desert dust,
J. Geophys. Res.-Atmos., 111, D11208,
https://doi.org/10.1029/2005JD006619,
2006. a, b
Dubovik, O., Herman, M., Holdak, A., Lapyonok, T., Tanré, D., Deuzé, J. L., Ducos, F., Sinyuk, A., and Lopatin, A.: Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations, Atmos. Meas. Tech., 4, 975–1018, https://doi.org/10.5194/amt-4-975-2011, 2011. a
Dubovik, O., Lapyonok, T., Litvinov, P., Herman, M., Fuertes, D., Ducos, F.,
Lopatin, A., Chaikovsky, A., Torres, B., Derimian, Y., Huang, X.,
Aspetsberger, M., and Federspiel, C.: GRASP: a versatile algorithm for
characterizing the atmosphere, SPIE Newsroom, https://doi.org/10.1117/2.1201408.005558,
2014. a
Dubovik, O., Li, Z., Mishchenko, M. I., Tanré, D., Karol, Y., Bojkov, B.,
Cairns, B., Diner, D. J., Espinosa, W. R., Goloub, P., Gu, X., Hasekamp, O.,
Hong, J., Hou, W., Knobelspiesse, K. D., Landgraf, J., Li, L., Litvinov, P.,
Liu, Y., Lopatin, A., Marbach, T., Maring, H., Martins, V., Meijer, Y.,
Milinevsky, G., Mukai, S., Parol, F., Qiao, Y., Remer, L., Rietjens, J.,
Sano, I., Stammes, P., Stamnes, S., Sun, X., Tabary, P., Travis, L. D.,
Waquet, F., Xu, F., Yan, C., and Yin, D.: Polarimetric remote sensing of
atmospheric aerosols: Instruments, methodologies, results, and perspectives,
J. Quant. Spectrosc. Ra., 224, 474–511,
https://doi.org/10.1016/j.jqsrt.2018.11.024,
2019. a
Eck, T. F., Holben, B. N., Reid, J. S., Dubovik, O., Smirnov, A., O'Neill,
N. T., Slutsker, I., and Kinne, S.: Wavelength dependence of the optical
depth of biomass burning, urban, and desert dust aerosols, J. Geophys. Res.-Atmos., 104, 31333–31349,
https://doi.org/10.1029/1999JD900923,
1999. a
Fan, C., Fu, G., Di Noia, A., Smit, M., H.H. Rietjens, J., A. Ferrare, R.,
Burton, S., Li, Z., and P. Hasekamp, O.: Use of A Neural Network-Based Ocean
Body Radiative Transfer Model for Aerosol Retrievals from Multi-Angle
Polarimetric Measurements, Remote Sens., 11, 2877, https://doi.org/10.3390/rs11232877,
2019. a
Fedarenka, A., Dubovik, O., Goloub, P., Li, Z., Lapyonok, T., Litvinov, P.,
Barel, L., Gonzalez, L., Podvin, T., and Crozel, D.: Utilization of AERONET
polarimetric measurements for improving retrieval of aerosol microphysics:
GSFC, Beijing and Dakar data analysis, J. Quant. Spectrosc. Ra., 179, 72–97,
https://doi.org/10.1016/j.jqsrt.2016.03.021,
2016. a
Fichot, C. G. and Benner, R.: A novel method to estimate DOC concentrations
from CDOM absorption coefficients in coastal waters, Geophys. Res. Lett., 38, L03610, https://doi.org/10.1029/2010GL046152,
2011. a
Fougnie, B., Marbach, T., Lacan, A., Lang, R., Schlüssel, P., Poli, G., Munro,
R., and Couto, A. B.: The multi-viewing multi-channel multi-polarisation
imager – Overview of the 3MI polarimetric mission for aerosol and cloud
characterization, J. Quant. Spectrosc. Ra., 219, 23–32, https://doi.org/10.1016/j.jqsrt.2018.07.008,
2018. a
Franz, B. A., Bailey, S. W., Werdell, P. J., and McClain, C. R.:
Sensor-independent approach to the vicarious calibration of satellite ocean
color radiometry, Appl. Optics, 46, 5068–5082, https://doi.org/10.1364/AO.46.005068,
2007. a
Frouin, R. J., Franz, B. A., Ibrahim, A., Knobelspiesse, K., Ahmad, Z., Cairns,
B., Chowdhary, J., Dierssen, H. M., Tan, J., Dubovik, O., Huang, X., Davis,
A. B., Kalashnikova, O., Thompson, D. R., Remer, L. A., Boss, E., Coddington,
O., Deschamps, P.-Y., Gao, B.-C., Gross, L., Hasekamp, O., Omar, A.,
Pelletier, B., Ramon, D., Steinmetz, F., and Zhai, P.-W.: Atmospheric
Correction of Satellite Ocean-Color Imagery During the PACE Era,
Front. Earth Sci., 7, 145, https://doi.org/10.3389/feart.2019.00145,
2019. a, b
Fu, G. and Hasekamp, O.: Retrieval of aerosol microphysical and optical properties over land using a multimode approach, Atmos. Meas. Tech., 11, 6627–6650, https://doi.org/10.5194/amt-11-6627-2018, 2018. a, b
Fu, G., Hasekamp, O., Rietjens, J., Smit, M., Di Noia, A., Cairns, B., Wasilewski, A., Diner, D., Seidel, F., Xu, F., Knobelspiesse, K., Gao, M., da Silva, A., Burton, S., Hostetler, C., Hair, J., and Ferrare, R.: Aerosol retrievals from different polarimeters during the ACEPOL campaign using a common retrieval algorithm, Atmos. Meas. Tech., 13, 553–573, https://doi.org/10.5194/amt-13-553-2020, 2020. a, b
Gao, M., Zhai, P.-W., Franz, B., Hu, Y., Knobelspiesse, K., Werdell, P. J.,
Ibrahim, A., Xu, F., and Cairns, B.: Retrieval of aerosol properties and
water-leaving reflectance from multi-angular polarimetric measurements over
coastal waters, Opt. Express, 26, 8968–8989, https://doi.org/10.1364/OE.26.008968,
2018. a, b, c, d, e, f
Gao, M., Zhai, P.-W., Franz, B. A., Hu, Y., Knobelspiesse, K., Werdell, P. J., Ibrahim, A., Cairns, B., and Chase, A.: Inversion of multiangular polarimetric measurements over open and coastal ocean waters: a joint retrieval algorithm for aerosol and water-leaving radiance properties, Atmos. Meas. Tech., 12, 3921–3941, https://doi.org/10.5194/amt-12-3921-2019, 2019. a, b, c, d, e, f, g, h, i
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.-K., 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. a
Giles, D. M., Sinyuk, A., Sorokin, M. G., Schafer, J. S., Smirnov, A., Slutsker, I., Eck, T. F., Holben, B. N., Lewis, J. R., Campbell, J. R., Welton, E. J., Korkin, S. V., and Lyapustin, A. I.: Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements, Atmos. Meas. Tech., 12, 169–209, https://doi.org/10.5194/amt-12-169-2019, 2019. a
Gordon, H. R. and Wang, M.: Retrieval of water-leaving radiance and aerosol
optical thickness over the oceans with SeaWiFS: a preliminary algorithm,
Appl. Optics, 33, 443–452, 1994. a
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. a
Hasekamp, O. P. and Landgraf, J.: Retrieval of aerosol properties over land
surfaces: capabilities of multiple-viewing-angle intensity and polarization
measurements, Appl. Optics, 46, 3332–3344, https://doi.org/10.1364/AO.46.003332,
2007. a
Hasekamp, O. P., Litvinov, P., and Butz, A.: Aerosol properties over the ocean
from PARASOL multiangle photopolarimetric measurements,
J. Geophys. Res.-Oceans, 116, D14204, https://doi.org/10.1029/2010JD015469, 2011. a, b
Hasekamp, O. P., Fu, G., Rusli, S. P., Wu, L., Noia, A. D., aan de Brugh, J.,
Landgraf, J., Smit, J. M., Rietjens, J., and van Amerongen, A.: Aerosol
measurements by SPEXone on the NASA PACE mission: expected retrieval
capabilities, J. Quant. Spectrosc. Ra.,
227, 170–184, https://doi.org/10.1016/j.jqsrt.2019.02.006,
2019. a
Holben, B., Eck, T., Slutsker, I., Tanré, D., Buis, J., Setzer, A., Vermote,
E., Reagan, J., Kaufman, Y., Nakajima, T., Lavenu, F., Jankowiak, I., and
Smirnov, A.: AERONET–A Federated Instrument Network and Data Archive for
Aerosol Characterization, Remote Sens. Environ., 66, 1–16,
https://doi.org/10.1016/S0034-4257(98)00031-5,
1998. a, b
Holben, B. N., Tanré, D., Smirnov, A., Eck, T. F., Slutsker, I., Abuhassan,
N., Newcomb, W. W., Schafer, J. S., Chatenet, B., Lavenu, F., Kaufman, Y. J.,
Castle, J. V., Setzer, A., Markham, B., Clark, D., Frouin, R., Halthore, R.,
Karneli, A., O'Neill, N. T., Pietras, C., Pinker, R. T., Voss, K., and
Zibordi, G.: An emerging ground-based aerosol climatology: Aerosol optical
depth from AERONET, J. Geophys. Res.-Atmos., 106,
12067–12097, https://doi.org/10.1029/2001JD900014,
2001. a
Hu, C., Feng, L., and Lee, Z.: Uncertainties of SeaWiFS and MODIS remote
sensing reflectance: Implications from clear water measurements, Remote Sens. Environ., 133, 168–182,
https://doi.org/10.1016/j.rse.2013.02.012,
2013. a
Ibrahim, A., Franz, B., Ahmad, Z., Healy, R., Knobelspiesse, K., Gao, B.-C.,
Proctor, C., and Zhai, P.-W.: Atmospheric correction for hyperspectral ocean
color retrieval with application to the Hyperspectral Imager for the Coastal
Ocean (HICO), Remote Sens. Environ., 204, 60–75,
https://doi.org/10.1016/j.rse.2017.10.041,
2018. a, b, c
Ibrahim, A., Franz, B. A., Ahmad, Z., and Bailey, S. W.: Multiband Atmospheric
Correction Algorithm for Ocean Color Retrievals, Front. Earth Sci.,
7, 116, https://doi.org/10.3389/feart.2019.00116,
2019. a, b
Jamet, C., Ibrahim, A., Ahmad, Z., Angelini, F., Babin, M., Behrenfeld, M. J.,
Boss, E., Cairns, B., Churnside, J., Chowdhary, J., Davis, A. B., Dionisi,
D., Duforêt-Gaurier, L., Franz, B., Frouin, R., Gao, M., Gray, D., Hasekamp,
O., He, X., Hostetler, C., Kalashnikova, O. V., Knobelspiesse, K., Lacour,
L., Loisel, H., Martins, V., Rehm, E., Remer, L., Sanhaj, I., Stamnes, K.,
Stamnes, S., Victori, S., Werdell, J., and Zhai, P.-W.: Going Beyond Standard
Ocean Color Observations: Lidar and Polarimetry,
Front. Mar. Sci.,
6, 251, https://doi.org/10.3389/fmars.2019.00251,
2019. a
Kaufman, Y. J., Martins, J. V., Remer, L. A., Schoeberl, M. R., and Yamasoe,
M. A.: Satellite retrieval of aerosol absorption over the oceans using
sunglint, Geophys. Res. Lett., 29, 34-1–34-4,
https://doi.org/10.1029/2002GL015403,
2002. a
Kawata, Y.: Circular polarization of sunlight reflected by planetary
atmospheres, Icarus, 33, 217–232,
https://doi.org/10.1016/0019-1035(78)90035-0,
1978. a
Knobelspiesse, K., Cairns, B., Mishchenko, M., Chowdhary, J., Tsigaridis, K.,
van Diedenhoven, B., Martin, W., Ottaviani, M., and Alexandrov, M.: Analysis
of fine-mode aerosol retrieval capabilities by different passive remote
sensing instrument designs, Opt. Express, 20, 21457–21484,
https://doi.org/10.1364/OE.20.021457,
2012. a, b, c, d, e, f, g
Knobelspiesse, K., Tan, Q., Bruegge, C., Cairns, B., Chowdhary, J., van
Diedenhoven, B., Diner, D., Ferrare, R., van Harten, G., Jovanovic, V.,
Ottaviani, M., Redemann, J., Seidel, F., and Sinclair, K.: Intercomparison of
airborne multi-angle polarimeter observations from the Polarimeter Definition
Experiment, Appl. Optics, 58, 650–669, https://doi.org/10.1364/AO.58.000650,
2019. a, b
Knobelspiesse, K., Barbosa, H. M. J., Bradley, C., Bruegge, C., Cairns, B., Chen, G., Chowdhary, J., Cook, A., Di Noia, A., van Diedenhoven, B., Diner, D. J., Ferrare, R., Fu, G., Gao, M., Garay, M., Hair, J., Harper, D., van Harten, G., Hasekamp, O., Helmlinger, M., Hostetler, C., Kalashnikova, O., Kupchock, A., Longo De Freitas, K., Maring, H., Martins, J. V., McBride, B., McGill, M., Norlin, K., Puthukkudy, A., Rheingans, B., Rietjens, J., Seidel, F. C., da Silva, A., Smit, M., Stamnes, S., Tan, Q., Val, S., Wasilewski, A., Xu, F., Xu, X., and Yorks, J.: The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) airborne field campaign, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-76, in review, 2020. a, b, c
Li, Z., Hou, W., Hong, J., Zheng, F., Luo, D., Wang, J., Gu, X., and Qiao, Y.:
Directional Polarimetric Camera (DPC): Monitoring aerosol spectral optical
properties over land from satellite observation, J. Quant. Spectrosc. Ra., 218, 21–37,
https://doi.org/10.1016/j.jqsrt.2018.07.003,
2018. a
Mahowald, N. M., Baker, A. R., Bergametti, G., Brooks, N., Duce, R. A.,
Jickells, T. D., Kubilay, N., Prospero, J. M., and Tegen, I.: Atmospheric
global dust cycle and iron inputs to the ocean,
Global Biogeochem. Cy.,
19, GB4025, https://doi.org/10.1029/2004GB002402,
2005. a
Martins, J. V., Fernandez-Borda, R., McBride, B., Remer, L., and
Barbosa, H. M. J.: The Harp Hype Ran Gular Imaging Polarimeter and the Need
for Small Satellite Payloads with High Science Payoff for Earth Science
Remote Sensing, in: IGARSS 2018–2018 IEEE International Geoscience and
Remote Sensing Symposium, 6304–6307, https://doi.org/10.1109/IGARSS.2018.8518823,
2018. a
McBride, B. A., Martins, J. V., Barbosa, H. M. J., Birmingham, W., and Remer, L. A.: Spatial distribution of cloud droplet size properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) measurements, Atmos. Meas. Tech., 13, 1777–1796, https://doi.org/10.5194/amt-13-1777-2020, 2020. a
McCoy, D. T., Burrows, S. M., Wood, R., Grosvenor, D. P., Elliott, S. M., Ma,
P.-L., Rasch, P. J., and Hartmann, D. L.: Natural aerosols explain seasonal
and spatial patterns of Southern Ocean cloud albedo, Sci. Adv., 1, e1500157,
https://doi.org/10.1126/sciadv.1500157,
2015. a
McGill, M., Hlavka, D., Hart, W., Scott, V. S., Spinhirne, J., and Schmid, B.:
Cloud Physics Lidar: instrument description and initial measurement results,
Appl. Optics, 41, 3725–3734, https://doi.org/10.1364/AO.41.003725,
2002. a
Mishchenko, M. I. and Travis, L. D.: Satellite retrieval of aerosol properties
over the ocean using polarization as well as intensity of reflected sunlight,
J. Geophys. Res.-Atmos., 102, 16989–17013,
https://doi.org/10.1029/96JD02425,
1997. a
Ocean Biology Processing Group (OBPG): NASA Ocean Color Web, available at: https://oceancolor.gsfc.nasa.gov/atbd/rrs/, last access: 7 July 2020. a
NASA Goddard Institute for Space Studies (GISS): NASA RSP Data Archive, available at: https://data.giss.nasa.gov/pub/rsp, last access: 7 July 2020. a
O'Dowd, C. D., Jimenez, J. L., Bahreini, R., Flagan, R. C., Seinfeld, J. H.,
Hämeri, K., Pirjola, L., Kulmala, M., Jennings, S. G., and Hoffmann, T.:
Marine aerosol formation from biogenic iodine emissions, Nature, 417,
632–636, https://doi.org/10.1038/nature00775, 2002. a
Ottaviani, M., Knobelspiesse, K., Cairns, B., and Mishchenko, M.: Information
content of aerosol retrievals in the sunglint region, Geophys. Res. Lett., 40, 631–634, https://doi.org/10.1002/grl.50148,
2013. a
PACE: Pre-Aerosol,Clouds, and ocean Ecosystem (PACE) Mission Science Definition
Team Report, The National Aeronautics and Space Administration (NASA),
available at: https://pace.oceansciences.org/docs/PACE_TM2018-219027_Vol_2.pdf (last access: 7 July 2020),
2018. a
PACE Science Data Product Validation Plan: PACE Science Data Product Validation Plan, available at:
https://pace.oceansciences.org/docs/PACE_Validation_Plan_DRAFT_version_24March2020_posted.pdf, last access: 7 July 2020. a
Remer, L. A., Davis, A. B., Mattoo, S., Levy, R. C., Kalashnikova, O. V.,
Coddington, O., Chowdhary, J., Knobelspiesse, K., Xu, X., Ahmad, Z., Boss,
E., Cairns, B., Dierssen, H. M., Diner, D. J., Franz, B., Frouin, R., Gao,
B.-C., Ibrahim, A., Martins, J. V., Omar, A. H., Torres, O., Xu, F., and
Zhai, P.-W.: Retrieving Aerosol Characteristics From the PACE Mission, Part
1: Ocean Color Instrument, Front. Earth Sci., 7, 152,
https://doi.org/10.3389/feart.2019.00152,
2019a. a, b
Remer, L. A., Knobelspiesse, K., Zhai, P.-W., Xu, F., Kalashnikova, O. V.,
Chowdhary, J., Hasekamp, O., Dubovik, O., Wu, L., Ahmad, Z., Boss, E.,
Cairns, B., Coddington, O., Davis, A. B., Dierssen, H. M., Diner, D. J.,
Franz, B., Frouin, R., Gao, B.-C., Ibrahim, A., Levy, R. C., Martins, J. V.,
Omar, A. H., and Torres, O.: Retrieving Aerosol Characteristics From the PACE
Mission, Part 2: Multi-Angle and Polarimetry,
Front. Environ. Sci., 7, 94, https://doi.org/10.3389/fenvs.2019.00094,
2019b. a
Rietjens, J., Campo, J., Chanumolu, A., Smit, M., Nalla, R., Fernandez, C.,
Dingjan, J., van Amerongen, A., and Hasekamp, O.: Expected performance and
error analysis for SPEXone, a multi-angle channeled spectropolarimeter for
the NASA PACE mission, in: Polarization Science and Remote Sensing IX,
edited by: Craven, J. M., Shaw, J. A., and Snik, F., 11132, 34–47,
International Society for Optics and Photonics, SPIE,
https://doi.org/10.1117/12.2530729,
2019. a
Shettle, E. P. and Fenn, R. W.: Models for the aerosols of the lower atmosphere
and the effects of humidity variations on their optical properties,
Environmental Research Papers, Air Force Geophysics Lab., Hanscom AFB, MA.
Optical Physics Div, 1979. a
Siegel, D. A., Buesseler, K. O., Doney, S. C., Sailley, S. F., Behrenfeld,
M. J., and Boyd, P. W.: Global assessment of ocean carbon export by combining
satellite observations and food-web models, Global Biogeochem. Cy., 28,
181–196, https://doi.org/10.1002/2013GB004743,
2014. a
Smirnov, A., Holben, B., Eck, T., Dubovik, O., and Slutsker, I.:
Cloud-Screening and Quality Control Algorithms for the AERONET Database,
Remote Sens. Environ., 73, 337–349,
https://doi.org/10.1016/S0034-4257(00)00109-7,
2000. a
Smit, J. M., Rietjens, J. H. H., van Harten, G., Noia, A. D., Laauwen, W.,
Rheingans, B. E., Diner, D. J., Cairns, B., Wasilewski, A., Knobelspiesse,
K. D., Ferrare, R., and Hasekamp, O. P.: SPEX airborne spectropolarimeter
calibration and performance, Appl. Optics, 58, 5695–5719,
https://doi.org/10.1364/AO.58.005695, 2019. a, b, c, d
Stamnes, S., Hostetler, C., Ferrare, R., Burton, S., Liu, X., Hair, J., Hu, Y.,
Wasilewski, A., Martin, W., van Diedenhoven, B., Chowdhary, J., Cetinić,
I., Berg, L. K., Stamnes, K., and Cairns, B.: Simultaneous polarimeter
retrievals of microphysical aerosol and ocean color parameters from the
“MAPP” algorithm with comparison to high-spectral-resolution lidar aerosol
and ocean products, Appl. Optics, 57, 2394–2413, https://doi.org/10.1364/AO.57.002394,
2018. a
Tanré, D., Bréon, F. M., Deuzé, J. L., Dubovik, O., Ducos, F., François, P., Goloub, P., Herman, M., Lifermann, A., and Waquet, F.: Remote sensing of aerosols by using polarized, directional and spectral measurements within the A-Train: the PARASOL mission, Atmos. Meas. Tech., 4, 1383–1395, https://doi.org/10.5194/amt-4-1383-2011, 2011. a
Wang, J., Xu, X., Ding, S., Zeng, J., Spurr, R., Liu, X., Chance, K., and
Mishchenko, M.: A numerical testbed for remote sensing of aerosols, and its
demonstration for evaluating retrieval synergy from a geostationary satellite
constellation of GEO-CAPE and GOES-R, J. Quant. Spectrosc. Ra., 146, 510–528,
https://doi.org/10.1016/j.jqsrt.2014.03.020,
2014. a
Wang, M. (Ed.): Atmospheric Correction for Remotely-Sensed Ocean-Colour,
International Ocean Colour Coordinating Group (IOCCG), IOCCG Report Number 10, 2010. a
Werdell, P. J., Behrenfeld, M. J., Bontempi, P. S., Boss, E., Cairns, B.,
Davis, G. T., Franz, B. A., Gliese, U. B., Gorman, E. T., Hasekamp, O.,
Knobelspiesse, K. D., Mannino, A., Martins, J. V., McClain, C. R., Meister,
G., and Remer, L. A.: The Plankton, Aerosol, Cloud, Ocean Ecosystem Mission:
Status, Science, Advances, B. Am. Meteorol. Soc.,
100, 1775–1794, https://doi.org/10.1175/BAMS-D-18-0056.1,
2019. a, b, c, d, e
Westberry, T., Shi, Y., Yu, H., Behrenfeld, M., and Remer, L.:
Satellite-Detected Ocean Ecosystem Response to Volcanic Eruptions in the
Subarctic Northeast Pacific Ocean, Geophys. Res. Lett., 46,
11270–11280, https://doi.org/10.1029/2019GL083977,
2019. a
Wu, L., Hasekamp, O., van Diedenhoven, B., and Cairns, B.: Aerosol retrieval from multiangle, multispectral photopolarimetric measurements: importance of spectral range and angular resolution, Atmos. Meas. Tech., 8, 2625–2638, https://doi.org/10.5194/amt-8-2625-2015, 2015. a, b
Xu, F., Dubovik, O., Zhai, P.-W., Diner, D. J., Kalashnikova, O. V., Seidel, F. C., Litvinov, P., Bovchaliuk, A., Garay, M. J., van Harten, G., and Davis, A. B.: Joint retrieval of aerosol and water-leaving radiance from multispectral, multiangular and polarimetric measurements over ocean, Atmos. Meas. Tech., 9, 2877–2907, https://doi.org/10.5194/amt-9-2877-2016, 2016.
a, b
Xu, F., van Harten, G., Diner, D. J., Kalashnikova, O. V., Seidel, F. C.,
Bruegge, C. J., and Dubovik, O.: Coupled retrieval of aerosol properties and
land surface reflection using the Airborne Multiangle SpectroPolarimetric
Imager, J. Geophys. Res.-Atmos., 122, 7004–7026,
https://doi.org/10.1002/2017JD026776,
2017. a
Xu, F., Diner, D. J., Dubovik, O., and Schechner, Y.: A Correlated Multi-Pixel
Inversion Approach for Aerosol Remote Sensing, Remote Sens., 11,
https://doi.org/10.3390/rs11070746,
2019. a
Xu, X. and Wang, J.: Retrieval of aerosol microphysical properties from AERONET
photopolarimetric measurements: 1. Information content analysis, J. Geophys. Res.-Atmos., 120, 7059–7078,
https://doi.org/10.1002/2015JD023108,
2015. a
Xu, X., Wang, J., Zeng, J., Spurr, R., Liu, X., Dubovik, O., Li, L., Li, Z.,
Mishchenko, M. I., Siniuk, A., and Holben, B. N.: Retrieval of aerosol
microphysical properties from AERONET photopolarimetric measurements: 2. A
new research algorithm and case demonstration, J. Geophys. Res.-Atmos., 120, 7079–7098, https://doi.org/10.1002/2015JD023113,
2015. a
Zhai, P.-W., Knobelspiesse, K., Ibrahim, A., Franz, B. A., Hu, Y., Gao, M., and
Frouin, R.: Water-leaving contribution to polarized radiation field over
ocean, Opt. Express, 25, A689–A708,
https://doi.org/10.1364/OE.25.00A689, 2017. a
Zhai, P.-W., Boss, E., Franz, B., Werdell, P. J., and Hu, Y.: Radiative
Transfer Modeling of Phytoplankton Fluorescence Quenching Processes, Remote
Sens., 10, 1309, https://doi.org/10.3390/rs10081309,
2018. a, b
Zibordi, G., Mélin, F., Berthon, J.-F., Holben, B., Slutsker, I., Giles, D.,
D’Alimonte, D., Vandemark, D., Feng, H., Schuster, G., Fabbri, B. E.,
Kaitala, S., and Seppälä, J.: AERONET-OC: A Network for the Validation of
Ocean Color Primary Products, J. Atmos. Ocean. Tech.,
26, 1634–1651, https://doi.org/10.1175/2009JTECHO654.1,
2009. a, b, c
