Articles | Volume 17, issue 18
https://doi.org/10.5194/amt-17-5455-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-5455-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Increasing aerosol optical depth spatial and temporal availability by merging datasets from geostationary and sun-synchronous satellites
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Robert C. Levy
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Shana Mattoo
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Science Systems and Applications, Inc., Greenbelt, MD, USA
Lorraine A. Remer
University of Maryland Baltimore County, Baltimore, MD, USA
Zhaohui Zhang
NASA Goddard Space Flight Center, Greenbelt, MD, USA
ADNET Systems, Inc., Greenbelt, MD, USA
Virginia Sawyer
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Science Systems and Applications, Inc., Greenbelt, MD, USA
Jennifer Wei
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Sally Zhao
University of Maryland, College Park, MD, USA
Min Oo
Space Sciences and Engineering Center, University of Wisconsin, Madison, WI, USA
V. Praju Kiliyanpilakkil
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Science Systems and Applications, Inc., Greenbelt, MD, USA
Xiaohua Pan
NASA Goddard Space Flight Center, Greenbelt, MD, USA
ADNET Systems, Inc., Greenbelt, MD, USA
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Kirk Knobelspiesse, Amir Ibrahim, Bryan Franz, Sean Bailey, Robert Levy, Ziauddin Ahmad, Joel Gales, Meng Gao, Michael Garay, Samuel Anderson, and Olga Kalashnikova
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Cheng Chen, Oleg Dubovik, David Fuertes, Pavel Litvinov, Tatyana Lapyonok, Anton Lopatin, Fabrice Ducos, Yevgeny Derimian, Maurice Herman, Didier Tanré, Lorraine A. Remer, Alexei Lyapustin, Andrew M. Sayer, Robert C. Levy, N. Christina Hsu, Jacques Descloitres, Lei Li, Benjamin Torres, Yana Karol, Milagros Herrera, Marcos Herreras, Michael Aspetsberger, Moritz Wanzenboeck, Lukas Bindreiter, Daniel Marth, Andreas Hangler, and Christian Federspiel
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Nick Schutgens, Andrew M. Sayer, Andreas Heckel, Christina Hsu, Hiren Jethva, Gerrit de Leeuw, Peter J. T. Leonard, Robert C. Levy, Antti Lipponen, Alexei Lyapustin, Peter North, Thomas Popp, Caroline Poulsen, Virginia Sawyer, Larisa Sogacheva, Gareth Thomas, Omar Torres, Yujie Wang, Stefan Kinne, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 20, 12431–12457, https://doi.org/10.5194/acp-20-12431-2020, https://doi.org/10.5194/acp-20-12431-2020, 2020
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Anin Puthukkudy, J. Vanderlei Martins, Lorraine A. Remer, Xiaoguang Xu, Oleg Dubovik, Pavel Litvinov, Brent McBride, Sharon Burton, and Henrique M. J. Barbosa
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Executive editor
Air pollution is one of the greatest threats to human health, and many of the adverse health effects can be attributed to aerosols. In addition, aerosols play an important role in regulating climate, both through direct effects and through cloud formation. Aerosols can be detected using satellite-based instruments, but due to the broad range of characteristics and their variability in space and time, aerosol retrieval by remote sensing is not trivial.
This highlight paper presents the combination of data from six satellite instruments that complement each other. Three of the satellites are in sun-synchronous orbits (observing the whole Earth once per day) and three in geo-stationary orbit (observing a portion of the Earth several times per hour). The paper shows that by combining data from the six instruments a high-quality, consistent data set can be created with a higher combined spatio-temporal resolution and less gaps than existing data sets. The freely available new aerosol data product is provided at 30 minute resolution and on a 0.25 degree grid in a format convenient for use in satellite studies or ingestion by models, providing data that will further advance the field of aerosol studies.
Air pollution is one of the greatest threats to human health, and many of the adverse health...
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.
In this study, for the first time, we combined aerosol data from six satellites using a unified...