GEO-LEO Deep Blue Aerosol
Aerosols comprise a variety of fine solid particles or liquid droplets that are suspended in the air. These aerosol particles — such as dust, smoke, volcanic ash and sea salt — are traceable to various natural (e.g., deserts, volcanos and the world’s oceans) and anthropogenic (e.g., urban, industrial and agricultural activities) origins. Aerosols can have significant impacts on human health especially when they affect air quality near the surface. Understanding atmospheric aerosols remains a leading research domain given their substantial influence on Earth’s climate and their effects on the global biosphere.
Deep Blue Aerosols define retrievals over bright surfaces such as ocean glint, deserts, or snow and ice. They have become a standard component, along with the original Dark Target algorithm, to produce a more complete and global view of aerosol retrievals from the v6.0 MODIS collections and onward. The Geostationary Earth Orbit (GEO) – Low-Earth Orbit (LEO) Deep Blue Aerosol project is funded by NASA’s ESROGSS (Earth Science Research from Operational Geostationary Satellite Systems) program element that ran from 2019 through 2020. This project has helped develop a suite of products based on a common algorithm approach for global Deep Blue Aerosol products. The GEO and GEO-LEO Merged Deep Blue Aerosol products are available from May 1, 2019, through April 30, 2020. The GEO sources include the Advanced Baseline Imager (ABI) from NOAA’s Geostationary Operational Environmental Satellites (GOES-16 and GOES-17) and the Advanced Himawari Imager (AHI) from the Japanese Himawari-8 geostationary weather satellite. The LEO sources include Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (SNPP VIIRS), NOAA20-VIIRS, Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Aqua MODIS. Future plans may lead us to extend this demonstration collection record beyond a single year.
Aim/Objectives
This project aims to use the Deep Blue Aerosol Optical Thickness (AOT) retrieval algorithm, which itself comprises two parts, the Deep Blue (DB) over land, and the Satellite Ocean Aerosol Retrieval (SOAR) algorithm over ocean to derive nine GEO and three GEO-LEO Merged products. The Level-2 (L2) GEO products for GOES-16, GOES-17 and Himawari-8 satellites, are produced every 30 minutes and contain full-disk observation data. Further aggregation of the L2 dataset yields daily- and monthly-scale products as well. The Level-2 Gridded (L2G) GEO-LEO Merged Deep Blue Aerosol product contains gridded AOT at 550 nm reference wavelength, derived from seven merged GEO-LEO AOT layers (G16-ABI, G17-ABI, H08-AHI, SNPP-VIIRS, NOAA20-VIIRS, Terra MODIS and Aqua MODIS) and from each of the individual (three GEO and four LEO) instrument sources. At a 30-minute interval, the 0.25°x0.25° aggregated composites of the L2G GEO-LEO Merged dataset also yield daily- and monthly-scale products at 1° x 1° spatial resolution.
Project/PI name(s)
Christina Hsu, NASA GSFC Code 613
Project's timespan:
2019 – 2020
Funding source:
NASA Earth Science Research from Operational Geostationary Satellite Systems (ESROGSS) Program Element
Benefits
Describe the scientific relevance of this project's data products and the benefits to the user community?
The new L2 GEO products provide Aerosol Optical Thickness (AOT) and other parameters at full-disk resolution every 30 minutes, which helps characterize aerosol changes within a day’s time-scale. These products can aid us in tracking the rapid changes and dynamics in smoke and dust plumes that have severe impacts on air quality. The resulting statistics of the aerosol diurnal cycle can prove useful to study the relationships with meteorology (e.g., general cloud formation, land/sea breezes, boundary layer changes, etc.), and human activities (e.g., vehicle “rush hour,” etc.). We can compare results generated using the L2 and the aggregated products against transportation and meteorological model results besides their use for data assimilation.
The L3 GEO-LEO Merged products are also expected to provide constraints on aerosol diurnal cycles, globally. Aerosol measurements retrieved at 30-minute intervals uniquely offer the potential to explore new research perspectives. For instance, it could support users investigating diurnal variations in global loading and spatial extent of aerosols. The data assimilation and modelling community could benefit via the high temporal resolution GEO and GEO-LEO Merged aerosol products to initialize models and to better characterize the sources of dust and other air pollutants.
Output products
| Platform | Instrument | Temporal Cadence | Spatial Res. | Product |
|---|---|---|---|---|
| GOES-16 | Advanced Baseline Imager | 30 Min. | 10 km |
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| GOES-17 | Advanced Baseline Imager | 30 Min. | 10 km |
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| Himawari-8 | Advanced Himawari Imager | 30 Min. | 10 km |
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| GOES-16 | Advanced Baseline Imager | Daily | 1°×1° |
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| GOES-17 | Advanced Baseline Imager | Daily | 1°×1° |
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| Himawari-8 | Advanced Himawari Imager | Daily | 1°×1° |
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| GOES-16 | Advanced Baseline Imager | Monthly | 1°×1° |
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| GOES-17 | Advanced Baseline Imager | Monthly | 1°×1° |
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| Himawari-8 | Advanced Himawari Imager | Monthly | 1°×1° |
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| Multiple* | ABI, AHI, VIIRS, MODIS* | 30 Min. | 0.25°×0.25° |
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| Multiple* | ABI, AHI, VIIRS, MODIS* | Daily | 1°×1° |
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| Multiple* | ABI, AHI, VIIRS, MODIS* | Monthly | 1°×1° |
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Project Documentation
GEO Deep Blue Aerosol User Guide v1.0
GEOLEO Merged Deep Blue Aerosol User Guide v1.0
Published Papers
- Lee, J., N. C. Hsu, W. V. Kim, A. M. Sayer, and S.-C. Tsay (2024), VIIRS Version 2 Deep Blue aerosol products, J. Geophys. Res. Atmos., 129, e2023JD040082.
- Hsu, N. C., J. Lee, A. M. Sayer, W. Kim, C. Bettenhausen, and S.-C. Tsay (2019), VIIRS Deep Blue aerosol products over land: extending EOS long-term aerosol data records, J. Geophys. Res. Atmos., 124, 4026–4053.
- Sayer, A. M., N, C, Hsu, J. Lee, C, Bettenhausen, W. V. Kim, and A. Smirnov (2018), Satellite Ocean Aerosol Retrieval (SOAR) algorithm extension to S-NPP VIIRS as part of the “Deep Blue” aerosol project. J. Geophys. Res. Atmos., 123, 380–400.
- Hsu, N. C., M.-J. Jeong, C. Bettenhausen, A. M. Sayer, R. Hansell, C. S. Seftor, J. Huang, and S.-C. Tsay (2013), Enhanced Deep Blue aerosol retrieval algorithm: The second generation, J. Geophys. Res. Atmos., 118, 9296–9315.
- Sayer, A. M., N. C. Hsu, J. Lee, W. V. Kim, and S. T. Dutcher (2019), Validation, stability, and consistency of MODIS Collection 6.1 and VIIRS Version 1 Deep Blue aerosol data over land, J. Geophys. Res. Atmos., 124, 4658–4688.
- Sayer, A. M., N. C. Hsu, J. Lee, W. V. Kim, O. Dubovik, S. T. Dutcher, D. Huang, P. Litvinov, A. Lyapustin, J. L. Tackett, and D. M. Winker (2018), Validation of SOAR VIIRS over-water aerosol retrievals, and context within the global satellite aerosol data record, J. Geophys. Res. Atmos., 123, 13,496–13,526.
Citation Information
If you incorporate products from the NASA ESROGSS Deep Blue Aerosol project in your research or applications, please use the following acknowledgment within your published work:
“These data products are processed by the NASA ESROGSS Deep Blue Aerosol project and distributed by the Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC) at the Goddard Space Flight Center.”
Please e-mail or send us reprints/citations of papers or oral presentations that are based on the GEO or GEO-LEO Merged aerosol products (see below for email).
This will help us to stay informed regarding how our data are being used.
There are no restrictions for use of data from the NASA ESROGSS Deep Blue Aerosol project unless otherwise expressly stated.