Articles | Volume 17, issue 18
https://doi.org/10.5194/amt-17-5455-2024
https://doi.org/10.5194/amt-17-5455-2024
Research article
 | Highlight paper
 | 
16 Sep 2024
Research article | Highlight paper |  | 16 Sep 2024

Increasing aerosol optical depth spatial and temporal availability by merging datasets from geostationary and sun-synchronous satellites

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

Related authors

Long-term trends in aerosol properties derived from AERONET measurements
Zhenyu Zhang, Jing Li, Huizheng Che, Yueming Dong, Oleg Dubovik, Thomas Eck, Pawan Gupta, Brent Holben, Jhoon Kim, Elena Lind, Trailokya Saud, Sachchida Nand Tripathi, and Tong Ying
EGUsphere, https://doi.org/10.5194/egusphere-2024-2533,https://doi.org/10.5194/egusphere-2024-2533, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager
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
Ground-level gaseous pollutants (NO2, SO2, and CO) in China: daily seamless mapping and spatiotemporal variations
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
Short summary
Low-Cost Air Quality Sensor Evaluation and Calibration in Contrasting Aerosol Environments
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
Short summary
Satellite-based estimation of the impacts of summertime wildfires on PM2.5 concentration in the United States
Zhixin Xue, Pawan Gupta, and Sundar Christopher
Atmos. Chem. Phys., 21, 11243–11256, https://doi.org/10.5194/acp-21-11243-2021,https://doi.org/10.5194/acp-21-11243-2021, 2021
Short summary

Related subject area

Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Multi-angle aerosol optical depth retrieval method based on improved surface reflectance
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
Comparison of diurnal aerosol products retrieved from combinations of micro-pulse lidar and sun photometer observations over the KAUST observation site
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
First atmospheric aerosol-monitoring results from the Geostationary Environment Monitoring Spectrometer (GEMS) over Asia
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
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
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
Stratospheric aerosol characteristics from SCIAMACHY limb observations: two-parameter retrieval
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

Cited articles

Al-Saadi, J., Szykman, J., Pierce, R. B., Kittaka, C., Neil, D., Chu, D. A., Remer, L., Gumley, L., Prins, E., Weinstock, L., MacDonald, C., Wayland, R., Dimmick, F., and Fishman, J.: Improving National Air Quality Forecasts with Satellite Aerosol Observations, B. Am. Meteorol. Soc., 86, 1249–1262, https://doi.org/10.1175/BAMS-86-9-1249, 2005. 
Arola, A., Eck, T. F., Huttunen, J., Lehtinen, K. E. J., Lindfors, A. V., Myhre, G., Smirnov, A., Tripathi, S. N., and Yu, H.: Influence of observed diurnal cycles of aerosol optical depth on aerosol direct radiative effect, Atmos. Chem. Phys., 13, 7895–7901, https://doi.org/10.5194/acp-13-7895-2013, 2013. 
ATBD: Algorithm Theoretical Basis Document for the Dark Target Aerosol Retrieval Algorithm, https://darktarget.gsfc.nasa.gov/atbd/overview (last access: 9 September 2024), 2023. 
Bellouin, N., Jones, A., Haywood, J., and Christopher, S. A.: Updated estimate of aerosol direct radiative forcing from satellite observations and comparison against the Hadley Centre climate model, J. Geophys. Res., 113, D10205, https://doi.org/10.1029/2007JD009385, 2008. 
Benedetti, A., Morcrette, J. J., Boucher, O., Dethof, A., Engelen, R. J., Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., and Kinne, S.: Aerosol analysis and forecast in the European centre for medium-range weather forecasts integrated forecast system: 2. Data assimilation, J. Geophys. Res.-Atmos., 114, D13205, https://doi.org/10.1029/2008JD011115, 2009. 
Download
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.
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.