Assessment of severe aerosol events from NASA MODIS and VIIRS aerosol products for data assimilation and climate continuity
<p>While the use and data assimilation (DA) of operational Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol data is commonplace, MODIS is scheduled to sunset in the next year. For data continuity, focus has turned to the development of next-generation aerosol products and sensors...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2023-05-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://amt.copernicus.org/articles/16/2547/2023/amt-16-2547-2023.pdf |
| _version_ | 1797818833464983552 |
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| author | A. Gumber J. S. Reid R. E. Holz T. F. Eck T. F. Eck N. C. Hsu R. C. Levy J. Zhang P. Veglio |
| author_facet | A. Gumber J. S. Reid R. E. Holz T. F. Eck T. F. Eck N. C. Hsu R. C. Levy J. Zhang P. Veglio |
| author_sort | A. Gumber |
| collection | DOAJ |
| description | <p>While the use and data assimilation (DA) of operational Moderate
Resolution Imaging Spectroradiometer (MODIS) aerosol data is commonplace,
MODIS is scheduled to sunset in the next year. For data continuity, focus
has turned to the development of next-generation aerosol products and
sensors such as those associated with the Visible Infrared Imaging
Radiometer Suite (VIIRS) on Suomi NPOESS Preparation Project (S-NPP) and
NOAA-20. Like MODIS algorithms, products from these sensors require their
own set of extensive error characterization and correction exercises. This
is particularly true in the context of monitoring significant aerosol events that tax an algorithm's ability to separate cloud from aerosol and account for multiple scattering related errors exacerbated by uncertainties in aerosol optical properties. To investigate the performance of polar-orbiting satellite algorithms to monitor and characterize significant events, a level 3 (L3) product has been developed using a consistent aggregation methodology for 4 years of observations (2016–2019) that is referred to as the SSEC/NRL L3 product. Included in this product are the AErosol RObotic NETwork (AERONET), MODIS Dark Target, Deep Blue, and Multi-Angle
Implementation of Atmospheric Correction (MAIAC) algorithms. These MODIS
“baseline algorithms” are compared to NASA's recently released NASA Deep
Blue algorithm for use with VIIRS. Using this new dataset, the relative
performance of the algorithms for both land and ocean were investigated with a focus on the relative skill of detecting severe events and accuracy of the retrievals using AERONET. Maps of higher-percentile aerosol optical
depth (AOD) regions of the world by product identified those with the highest measured AODs and determined what is high by local standards. While patterns in AOD match across products and median to moderate AOD values match well, there are regionally correlated biases between products based on sampling, algorithm differences, and AOD range – in particular for higher AOD events. Most notable are differences in boreal biomass burning and Saharan dust. Significant percentile biases must be accounted for when data are used in trend studies, data assimilation, or inverse modeling. These biases vary by aerosol regime and are likely due to retrieval assumptions in lower boundary conditions and aerosol optical models.</p> |
| first_indexed | 2024-03-13T09:13:56Z |
| format | Article |
| id | doaj.art-30e14d84223b4fc99281fc4a6754cd60 |
| institution | Directory Open Access Journal |
| issn | 1867-1381 1867-8548 |
| language | English |
| last_indexed | 2024-03-13T09:13:56Z |
| publishDate | 2023-05-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Measurement Techniques |
| spelling | doaj.art-30e14d84223b4fc99281fc4a6754cd602023-05-26T12:07:14ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482023-05-01162547257310.5194/amt-16-2547-2023Assessment of severe aerosol events from NASA MODIS and VIIRS aerosol products for data assimilation and climate continuityA. Gumber0J. S. Reid1R. E. Holz2T. F. Eck3T. F. Eck4N. C. Hsu5R. C. Levy6J. Zhang7P. Veglio8Space Science and Engineering Center, University of Wisconsin-Madison, Madison, WI 53706, USAU.S. Naval Research Laboratory, Monterey, CA 93943, USASpace Science and Engineering Center, University of Wisconsin-Madison, Madison, WI 53706, USAGoddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland Baltimore County, Baltimore, MD 21250, USANASA Goddard Space Flight Center, Greenbelt, MD 20771, USANASA Goddard Space Flight Center, Greenbelt, MD 20771, USANASA Goddard Space Flight Center, Greenbelt, MD 20771, USADepartment of Atmospheric Sciences, University of North Dakota, Grand Forks, ND 58202, USASpace Science and Engineering Center, University of Wisconsin-Madison, Madison, WI 53706, USA<p>While the use and data assimilation (DA) of operational Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol data is commonplace, MODIS is scheduled to sunset in the next year. For data continuity, focus has turned to the development of next-generation aerosol products and sensors such as those associated with the Visible Infrared Imaging Radiometer Suite (VIIRS) on Suomi NPOESS Preparation Project (S-NPP) and NOAA-20. Like MODIS algorithms, products from these sensors require their own set of extensive error characterization and correction exercises. This is particularly true in the context of monitoring significant aerosol events that tax an algorithm's ability to separate cloud from aerosol and account for multiple scattering related errors exacerbated by uncertainties in aerosol optical properties. To investigate the performance of polar-orbiting satellite algorithms to monitor and characterize significant events, a level 3 (L3) product has been developed using a consistent aggregation methodology for 4 years of observations (2016–2019) that is referred to as the SSEC/NRL L3 product. Included in this product are the AErosol RObotic NETwork (AERONET), MODIS Dark Target, Deep Blue, and Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms. These MODIS “baseline algorithms” are compared to NASA's recently released NASA Deep Blue algorithm for use with VIIRS. Using this new dataset, the relative performance of the algorithms for both land and ocean were investigated with a focus on the relative skill of detecting severe events and accuracy of the retrievals using AERONET. Maps of higher-percentile aerosol optical depth (AOD) regions of the world by product identified those with the highest measured AODs and determined what is high by local standards. While patterns in AOD match across products and median to moderate AOD values match well, there are regionally correlated biases between products based on sampling, algorithm differences, and AOD range – in particular for higher AOD events. Most notable are differences in boreal biomass burning and Saharan dust. Significant percentile biases must be accounted for when data are used in trend studies, data assimilation, or inverse modeling. These biases vary by aerosol regime and are likely due to retrieval assumptions in lower boundary conditions and aerosol optical models.</p>https://amt.copernicus.org/articles/16/2547/2023/amt-16-2547-2023.pdf |
| spellingShingle | A. Gumber J. S. Reid R. E. Holz T. F. Eck T. F. Eck N. C. Hsu R. C. Levy J. Zhang P. Veglio Assessment of severe aerosol events from NASA MODIS and VIIRS aerosol products for data assimilation and climate continuity Atmospheric Measurement Techniques |
| title | Assessment of severe aerosol events from NASA MODIS and VIIRS aerosol products for data assimilation and climate continuity |
| title_full | Assessment of severe aerosol events from NASA MODIS and VIIRS aerosol products for data assimilation and climate continuity |
| title_fullStr | Assessment of severe aerosol events from NASA MODIS and VIIRS aerosol products for data assimilation and climate continuity |
| title_full_unstemmed | Assessment of severe aerosol events from NASA MODIS and VIIRS aerosol products for data assimilation and climate continuity |
| title_short | Assessment of severe aerosol events from NASA MODIS and VIIRS aerosol products for data assimilation and climate continuity |
| title_sort | assessment of severe aerosol events from nasa modis and viirs aerosol products for data assimilation and climate continuity |
| url | https://amt.copernicus.org/articles/16/2547/2023/amt-16-2547-2023.pdf |
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