Articles | Volume 19, issue 18
https://doi.org/10.5194/amt-19-6125-2026
© Author(s) 2026. 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-19-6125-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Sep 2026
Research article |
| 25 Sep 2026
| 25 Sep 2026
Employing smoothness of the time series of sky radiances measured in the solar aureole for cloud screening
Alexander Sinyuk
CORRESPONDING AUTHOR
Science Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USA
NASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
Thomas F. Eck
Science Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USA
University of Maryland Baltimore County (UMBC), GESTAR II, Baltimore, MD 21250, USA
Ilya Slutsker
Science Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USA
NASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
Jasper Lewis
Science Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USA
University of Maryland Baltimore County (UMBC), GESTAR II, Baltimore, MD 21250, USA
Petar Grigorov
Science Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USA
NASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
Alexander Smirnov
Science Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USA
NASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
Joel S. Schafer
Science Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USA
NASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
Mikhail Sorokin
Science Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USA
NASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
Elena Lind
NASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
Pawan Gupta
NASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
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Atmos. Meas. Tech., 15, 4135–4151, https://doi.org/10.5194/amt-15-4135-2022, https://doi.org/10.5194/amt-15-4135-2022, 2022
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Sujan Shrestha, Robert E. Holz, Willem J. Marais, Zachary Buckholtz, Ilya Razenkov, Edwin Eloranta, Jeffrey S. Reid, Hope E. Elliott, Nurun Nahar Lata, Zezhen Cheng, Swarup China, Edmund Blades, Albert D. Ortiz, Rebecca Chewitt-Lucas, Alyson Allen, Devon Blades, Ria Agrawal, Elizabeth A. Reid, Jesus Ruiz-Plancarte, Anthony Bucholtz, Ryan Yamaguchi, Qing Wang, Thomas Eck, Elena Lind, Mira L. Pöhlker, Andrew P. Ault, and Cassandra J. Gaston
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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
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Myungje Choi, Alexei Lyapustin, Gregory L. Schuster, Sujung Go, Yujie Wang, Sergey Korkin, Ralph Kahn, Jeffrey S. Reid, Edward J. Hyer, Thomas F. Eck, Mian Chin, David J. Diner, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, and Hans Moosmüller
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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
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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.
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
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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.
Peng Xian, Jeffrey S. Reid, Melanie Ades, Angela Benedetti, Peter R. Colarco, Arlindo da Silva, Tom F. Eck, Johannes Flemming, Edward J. Hyer, Zak Kipling, Samuel Rémy, Tsuyoshi Thomas Sekiyama, Taichu Tanaka, Keiya Yumimoto, and Jianglong Zhang
Atmos. Chem. Phys., 24, 6385–6411, https://doi.org/10.5194/acp-24-6385-2024, https://doi.org/10.5194/acp-24-6385-2024, 2024
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The study compares and evaluates monthly AOD of four reanalyses (RA) and their consensus (i.e., ensemble mean). The basic verification characteristics of these RA versus both AERONET and MODIS retrievals are presented. The study discusses the strength of each RA and identifies regions where divergence and challenges are prominent. The RA consensus usually performs very well on a global scale in terms of how well it matches the observational data, making it a good choice for various applications.
Mijin Kim, Robert C. Levy, Lorraine A. Remer, Shana Mattoo, and Pawan Gupta
Atmos. Meas. Tech., 17, 1913–1939, https://doi.org/10.5194/amt-17-1913-2024, https://doi.org/10.5194/amt-17-1913-2024, 2024
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The study focused on evaluating and modifying the surface reflectance parameterization (SRP) of the Dark Target (DT) algorithm for geostationary observation. When using the DT SRP with the ABIs sensor on GOES-R, artificial diurnal signatures were present in AOD retrieval. To overcome this issue, a new SRP was developed, incorporating solar zenith angle and land cover type. The revised SRP resulted in improved AOD retrieval, demonstrating reduced bias around local noon.
Cristina Gil-Díaz, Michäel Sicard, Adolfo Comerón, Daniel Camilo Fortunato dos Santos Oliveira, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Jasper R. Lewis, Ellsworth J. Welton, and Simone Lolli
Atmos. Meas. Tech., 17, 1197–1216, https://doi.org/10.5194/amt-17-1197-2024, https://doi.org/10.5194/amt-17-1197-2024, 2024
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In this paper, a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. The cloud optical depth, effective column lidar ratio and linear cloud depolarisation ratio have been calculated by a new approach to the two-way transmittance method, which is valid for both ground-based and spaceborne lidar systems. Their associated errors are also provided.
Amanda Gumber, Jeffrey S. Reid, Robert E. Holz, Thomas F. Eck, N. Christina Hsu, Robert C. Levy, Jianglong Zhang, and Paolo Veglio
Atmos. Meas. Tech., 16, 2547–2573, https://doi.org/10.5194/amt-16-2547-2023, https://doi.org/10.5194/amt-16-2547-2023, 2023
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The purpose of this study is to create and evaluate a gridded dataset composed of multiple satellite instruments and algorithms to be used for data assimilation. An important part of aerosol data assimilation is having consistent measurements, especially for severe aerosol events. This study evaluates 4 years of data from MODIS, VIIRS, and AERONET with a focus on aerosol severe event detection from a regional and global perspective.
Juli I. Rubin, Jeffrey S. Reid, Peng Xian, Christopher M. Selman, and Thomas F. Eck
Atmos. Chem. Phys., 23, 4059–4090, https://doi.org/10.5194/acp-23-4059-2023, https://doi.org/10.5194/acp-23-4059-2023, 2023
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This work aims to quantify the covariability between aerosol optical depth/extinction with water vapor (PW) globally, using NASA AERONET observations and NAAPS model data. Findings are important for data assimilation and radiative transfer. The study shows statistically significant and positive AOD–PW relationships are found across the globe, varying in strength with location and season and tied to large-scale aerosol events. Hygroscopic growth was also found to be an important factor.
Norman T. O'Neill, Keyvan Ranjbar, Liviu Ivănescu, Thomas F. Eck, Jeffrey S. Reid, David M. Giles, Daniel Pérez-Ramírez, and Jai Prakash Chaubey
Atmos. Meas. Tech., 16, 1103–1120, https://doi.org/10.5194/amt-16-1103-2023, https://doi.org/10.5194/amt-16-1103-2023, 2023
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Aerosols are atmospheric particles that vary in size (radius) from a fraction of a micrometer (µm) to around 20 µm. They tend to be either smaller than 1 µm (like smoke or pollution) or larger than 1 µm (like dust or sea salt). Their optical effect (scattering and absorbing sunlight) can be divided into FM (fine-mode) and CM (coarse-mode) parts using a cutoff radius around 1 µm or a spectral (color) technique. We present and validate a theoretical link between the types of FM and CM divisions.
Jing Wei, Zhanqing Li, Jun Wang, Can Li, Pawan Gupta, and Maureen Cribb
Atmos. Chem. Phys., 23, 1511–1532, https://doi.org/10.5194/acp-23-1511-2023, https://doi.org/10.5194/acp-23-1511-2023, 2023
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This study estimated the daily seamless 10 km ambient gaseous pollutants (NO2, SO2, and CO) across China using machine learning with extensive input variables measured on monitors, satellites, and models. Our dataset yields a high data quality via cross-validation at varying spatiotemporal scales and outperforms most previous related studies, making it most helpful to future (especially short-term) air pollution and environmental health-related studies.
Alexander Sinyuk, Brent N. Holben, Thomas F. Eck, David M. Giles, Ilya Slutsker, Oleg Dubovik, Joel S. Schafer, Alexander Smirnov, and Mikhail Sorokin
Atmos. Meas. Tech., 15, 4135–4151, https://doi.org/10.5194/amt-15-4135-2022, https://doi.org/10.5194/amt-15-4135-2022, 2022
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This paper describes modification of smoothness constraints on the imaginary part of the refractive index employed in the AERONET aerosol retrieval algorithm. This modification is termed relaxed due to the weaker strength of this new smoothness constraint. Applying the modified version of the smoothness constraint results in a significant reduction of retrieved light absorption by brown-carbon-containing aerosols.
Pawan Gupta, Prakash Doraiswamy, Jashwanth Reddy, Palak Balyan, Sagnik Dey, Ryan Chartier, Adeel Khan, Karmann Riter, Brandon Feenstra, Robert C. Levy, Nhu Nguyen Minh Tran, Olga Pikelnaya, Kurinji Selvaraj, Tanushree Ganguly, and Karthik Ganesan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-140, https://doi.org/10.5194/amt-2022-140, 2022
Revised manuscript not accepted
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The use of low-cost sensors in air quality monitoring has been gaining interest across all walks of society. We present the results of evaluations of the PurpleAir against regulatory-grade PM2.5. The results indicate that with proper calibration, we can achieve bias-corrected PM2.5 data using PA sensors. Our study also suggests that pre-deployment calibrations developed at local or regional scales are required for the PA sensors to correct data from the field for scientific data analysis.
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Short summary
The new technique for the clouds screening of aerosol optical depth is presented. It employs measurements of the sky radiances at smallest scattering angle to detect cirrus clouds which otherwise are difficult to detect by other methods. The method employs the smoothness of the time series of measurements throughout a day as a criterion for cloud-free conditions. Sharp spikes in the time series are detected and associated with clouds.
The new technique for the clouds screening of aerosol optical depth is presented. It employs...
