Articles | Volume 13, issue 11
https://doi.org/10.5194/amt-13-5955-2020
© Author(s) 2020. 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-13-5955-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Nov 2020
Research article |
| 09 Nov 2020
| 09 Nov 2020
Improving GOES Advanced Baseline Imager (ABI) aerosol optical depth (AOD) retrievals using an empirical bias correction algorithm
Hai Zhang
CORRESPONDING AUTHOR
I.M. Systems Group, 5825 University Research Ct, Suite 3250, College Park, MD 20740, USA
Shobha Kondragunta
NOAA/NESDIS, 5825 University Research Ct, Suite 3250, College Park, MD 20740, USA
Istvan Laszlo
NOAA/NESDIS, 5825 University Research Ct, Suite 3250, College Park, MD 20740, USA
Mi Zhou
I.M. Systems Group, 5825 University Research Ct, Suite 3250, College Park, MD 20740, USA
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Cited
25 citations as recorded by crossref.
- Validation of the improved GOES-16 aerosol optical depth product over North America D. Fu et al. 10.1016/j.atmosenv.2023.119642
- Daily and Hourly Surface PM2.5 Estimation From Satellite AOD H. Zhang & S. Kondragunta 10.1029/2020EA001599
- JEDI‐Based Three‐Dimensional Ensemble‐Variational Data Assimilation System for Global Aerosol Forecasting at NCEP B. Huang et al. 10.1029/2022MS003232
- First atmospheric aerosol-monitoring results from the Geostationary Environment Monitoring Spectrometer (GEMS) over Asia Y. Cho et al. 10.5194/amt-17-4369-2024
- Automated Low-Cost LED-Based Sun Photometer for City Scale Distributed Measurements C. Garrido et al. 10.3390/rs13224585
- 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 M. Kim et al. 10.5194/amt-17-4317-2024
- Providing Fine Temporal and Spatial Resolution Analyses of Airborne Particulate Matter Utilizing Complimentary In Situ IoT Sensor Network and Remote Sensing Approaches P. Dewage et al. 10.3390/rs16132454
- A Geometry-Discrete Minimum Reflectance Aerosol Retrieval Algorithm (GeoMRA) for Geostationary Meteorological Satellite Over Heterogeneous Surfaces T. Zhang et al. 10.1109/TGRS.2022.3200425
- Public Health Benefits From Improved Identification of Severe Air Pollution Events With Geostationary Satellite Data K. O'Dell et al. 10.1029/2023GH000890
- Quasi‐Global Maps of Daily Aerosol Optical Depth From a Ring of Five Geostationary Meteorological Satellites Using AERUS‐GEO X. Ceamanos et al. 10.1029/2021JD034906
- Geographical coverage analysis and usage suggestions of temporal averaged aerosol optical depth product from GOES-R satellite data X. Jiang et al. 10.1080/01431161.2024.2331978
- Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization C. Jin et al. 10.3390/rs13224689
- Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager M. Kim et al. 10.5194/amt-17-1913-2024
- MODIS high-resolution MAIAC aerosol product: Global validation and analysis W. Qin et al. 10.1016/j.atmosenv.2021.118684
- High-Frequency Mapping of Downward Shortwave Radiation From GOES-R Using Gradient Boosting S. Ranjbar et al. 10.1109/JSTARS.2024.3420148
- Operational AOD Retrieval at Subkilometer Resolution Using OceanSat‐2 OCM Over Land: SAER Algorithm, Uncertainties, Validation & Inter‐Sensor Comparison M. Mishra et al. 10.1029/2023EA002896
- Improving Dust Aerosol Optical Depth (DAOD) Retrieval from the GEOKOMPSAT-2A (GK-2A) Satellite for Daytime and Nighttime Monitoring S. Ahn et al. 10.3390/s24051490
- Constraining Aerosol Phase Function Using Dual‐View Geostationary Satellites Q. Bian et al. 10.1029/2021JD035209
- Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within‐The‐Atmosphere Observations: A Three‐Way Street R. Kahn et al. 10.1029/2022RG000796
- Toward More Integrated Utilizations of Geostationary Satellite Data for Disaster Management and Risk Mitigation A. Higuchi 10.3390/rs13081553
- Exploring geometrical stereoscopic aerosol top height retrieval from geostationary satellite imagery in East Asia M. Kim et al. 10.5194/amt-16-2673-2023
- GOES-R land surface products at Western Hemisphere eddy covariance tower locations D. Losos et al. 10.1038/s41597-024-03071-z
- MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm J. Limbacher et al. 10.5194/amt-17-471-2024
- Tracking Smoke from a Prescribed Fire and Its Impacts on Local Air Quality Using Temporally Resolved GOES-16 ABI Aerosol Optical Depth (AOD) A. Huff et al. 10.1175/JTECH-D-20-0162.1
- Application of geostationary satellite and high-resolution meteorology data in estimating hourly PM2.5 levels during the Camp Fire episode in California B. Vu et al. 10.1016/j.rse.2022.112890
25 citations as recorded by crossref.
- Validation of the improved GOES-16 aerosol optical depth product over North America D. Fu et al. 10.1016/j.atmosenv.2023.119642
- Daily and Hourly Surface PM2.5 Estimation From Satellite AOD H. Zhang & S. Kondragunta 10.1029/2020EA001599
- JEDI‐Based Three‐Dimensional Ensemble‐Variational Data Assimilation System for Global Aerosol Forecasting at NCEP B. Huang et al. 10.1029/2022MS003232
- First atmospheric aerosol-monitoring results from the Geostationary Environment Monitoring Spectrometer (GEMS) over Asia Y. Cho et al. 10.5194/amt-17-4369-2024
- Automated Low-Cost LED-Based Sun Photometer for City Scale Distributed Measurements C. Garrido et al. 10.3390/rs13224585
- 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 M. Kim et al. 10.5194/amt-17-4317-2024
- Providing Fine Temporal and Spatial Resolution Analyses of Airborne Particulate Matter Utilizing Complimentary In Situ IoT Sensor Network and Remote Sensing Approaches P. Dewage et al. 10.3390/rs16132454
- A Geometry-Discrete Minimum Reflectance Aerosol Retrieval Algorithm (GeoMRA) for Geostationary Meteorological Satellite Over Heterogeneous Surfaces T. Zhang et al. 10.1109/TGRS.2022.3200425
- Public Health Benefits From Improved Identification of Severe Air Pollution Events With Geostationary Satellite Data K. O'Dell et al. 10.1029/2023GH000890
- Quasi‐Global Maps of Daily Aerosol Optical Depth From a Ring of Five Geostationary Meteorological Satellites Using AERUS‐GEO X. Ceamanos et al. 10.1029/2021JD034906
- Geographical coverage analysis and usage suggestions of temporal averaged aerosol optical depth product from GOES-R satellite data X. Jiang et al. 10.1080/01431161.2024.2331978
- Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization C. Jin et al. 10.3390/rs13224689
- Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager M. Kim et al. 10.5194/amt-17-1913-2024
- MODIS high-resolution MAIAC aerosol product: Global validation and analysis W. Qin et al. 10.1016/j.atmosenv.2021.118684
- High-Frequency Mapping of Downward Shortwave Radiation From GOES-R Using Gradient Boosting S. Ranjbar et al. 10.1109/JSTARS.2024.3420148
- Operational AOD Retrieval at Subkilometer Resolution Using OceanSat‐2 OCM Over Land: SAER Algorithm, Uncertainties, Validation & Inter‐Sensor Comparison M. Mishra et al. 10.1029/2023EA002896
- Improving Dust Aerosol Optical Depth (DAOD) Retrieval from the GEOKOMPSAT-2A (GK-2A) Satellite for Daytime and Nighttime Monitoring S. Ahn et al. 10.3390/s24051490
- Constraining Aerosol Phase Function Using Dual‐View Geostationary Satellites Q. Bian et al. 10.1029/2021JD035209
- Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within‐The‐Atmosphere Observations: A Three‐Way Street R. Kahn et al. 10.1029/2022RG000796
- Toward More Integrated Utilizations of Geostationary Satellite Data for Disaster Management and Risk Mitigation A. Higuchi 10.3390/rs13081553
- Exploring geometrical stereoscopic aerosol top height retrieval from geostationary satellite imagery in East Asia M. Kim et al. 10.5194/amt-16-2673-2023
- GOES-R land surface products at Western Hemisphere eddy covariance tower locations D. Losos et al. 10.1038/s41597-024-03071-z
- MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm J. Limbacher et al. 10.5194/amt-17-471-2024
- Tracking Smoke from a Prescribed Fire and Its Impacts on Local Air Quality Using Temporally Resolved GOES-16 ABI Aerosol Optical Depth (AOD) A. Huff et al. 10.1175/JTECH-D-20-0162.1
- Application of geostationary satellite and high-resolution meteorology data in estimating hourly PM2.5 levels during the Camp Fire episode in California B. Vu et al. 10.1016/j.rse.2022.112890
Latest update: 22 Nov 2024
Short summary
Geostationary Operational Environmental Satellites (GOES) retrieve high temporal resolution aerosol optical depth, which is a measure of the aerosol quantity within the atmospheric column. This work introduces an algorithm that improves the accuracy of the aerosol optical depth retrievals from GOES. The resulting data product can be used in monitoring the air quality and climate change research.
Geostationary Operational Environmental Satellites (GOES) retrieve high temporal resolution...
