Articles | Volume 12, issue 12
https://doi.org/10.5194/amt-12-6557-2019
© Author(s) 2019. 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-12-6557-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Applying the Dark Target aerosol algorithm with Advanced Himawari Imager observations during the KORUS-AQ field campaign
STI, Science and Technology Institute, Universities Space Research Association (USRA),
Huntsville, 35806 AL, USA
NASA Marshall Space Flight Center, Huntsville, AL 35758,
USA
Robert C. Levy
NASA Goddard Space Flight Center, Greenbelt, MD 20771,
USA
Shana Mattoo
NASA Goddard Space Flight Center, Greenbelt, MD 20771,
USA
Science Systems and Applications, Inc, Lanham, MD 20709,
USA
Lorraine A. Remer
JCET, University of Maryland – Baltimore County,
Baltimore, MD 21228, USA
Robert E. Holz
SSEC, University of Wisconsin-Madison, Madison, WI 53707,
USA
Andrew K. Heidinger
NOAA Advanced Satellite Product Branch, Madison, WI
53707, USA
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41 citations as recorded by crossref.
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- Estimation of high-resolution aerosol optical depth (AOD) from Landsat and Sentinel images using SEMARA model over selected locations in South Asia B. Gayen et al. 10.1016/j.atmosres.2023.107141
- Wide and Deep Learning Model for Satellite-Based Real-Time Aerosol Retrievals in China N. Luo et al. 10.3390/atmos15050564
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40 citations as recorded by crossref.
- Performance comparison of Fengyun-4A and Himawari-8 in PM2.5 estimation in China Y. Hu et al. 10.1016/j.atmosenv.2021.118898
- Comparison of hourly aerosol retrievals from JAXA Himawari/AHI in version 3.0 and a simple customized method W. Xu et al. 10.1038/s41598-020-77948-5
- Observing ocean ecosystem responses to volcanic ash K. Bisson et al. 10.1016/j.rse.2023.113749
- A New Algorithm for Himawari-8 Aerosol Optical Depth Retrieval by Integrating Regional PM₂.₅ Concentrations W. Xu et al. 10.1109/TGRS.2022.3155503
- Increasing aerosol optical depth spatial and temporal availability by merging datasets from geostationary and sun-synchronous satellites P. Gupta et al. 10.5194/amt-17-5455-2024
- Exploring high-resolution near-surface CO concentrations based on Himawari-8 top-of-atmosphere radiation data: Assessing the distribution of city-level CO hotspots in China B. Chen et al. 10.1016/j.atmosenv.2023.120021
- Improving aerosol optical depth retrievals from Himawari-8 with ensemble learning enhancement: Validation over Asia D. Fu et al. 10.1016/j.atmosres.2023.106624
- Estimation of high-resolution aerosol optical depth (AOD) from Landsat and Sentinel images using SEMARA model over selected locations in South Asia B. Gayen et al. 10.1016/j.atmosres.2023.107141
- Wide and Deep Learning Model for Satellite-Based Real-Time Aerosol Retrievals in China N. Luo et al. 10.3390/atmos15050564
- Observation-based quantification of aerosol transport using optical flow: A satellite perspective to characterize interregional transport of atmospheric pollution T. Zhang et al. 10.1016/j.rse.2024.114457
- Retrieval of Aerosol Optical Depth from the Himawari-8 Advanced Himawari Imager data: Application over Beijing in the summer of 2016 L. Wang et al. 10.1016/j.atmosenv.2020.117788
- Global evaluation of Fengyun-3 MERSI dark target aerosol retrievals over land L. Yang et al. 10.1080/17538947.2024.2344580
- MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm J. Limbacher et al. 10.5194/amt-17-471-2024
- Applying the Dark Target Aerosol Algorithm to MERSI-II: Retrieval and Validation of Aerosol Optical Depth over the Ocean X. Pei et al. 10.1007/s00376-024-4032-y
- Accuracy and error cause analysis, and recommendations for usage of Himawari-8 aerosol products over Asia and Oceania L. Feng et al. 10.1016/j.scitotenv.2021.148958
- Comparison of different methods of determining land surface reflectance for AOD retrieval Q. Wang et al. 10.1016/j.apr.2021.101143
- Himawari-8 High Temporal Resolution AOD Products Recovery: Nested Bayesian Maximum Entropy Fusion Blending GEO With SSO Satellite Observations T. Zhang et al. 10.1109/TGRS.2023.3262785
- The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. 10.3390/rs12182900
- Improving GOES Advanced Baseline Imager (ABI) aerosol optical depth (AOD) retrievals using an empirical bias correction algorithm H. Zhang et al. 10.5194/amt-13-5955-2020
- Adapting the Dark Target Algorithm to Advanced MERSI Sensor on the FengYun-3-D Satellite: Retrieval and Validation of Aerosol Optical Depth Over Land S. Jin et al. 10.1109/TGRS.2020.3021021
- 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
- Instantaneous aerosol and surface retrieval using satellites in geostationary orbit (iAERUS-GEO) – estimation of 15 min aerosol optical depth from MSG/SEVIRI and evaluation with reference data X. Ceamanos et al. 10.5194/amt-16-2575-2023
- Refining aerosol optical depth retrievals over land by constructing the relationship of spectral surface reflectances through deep learning: Application to Himawari-8 T. Su et al. 10.1016/j.rse.2020.112093
- Simulating wildfire emissions and plume rise using geostationary satellite fire radiative power measurements: a case study of the 2019 Williams Flats fire A. Kumar et al. 10.5194/acp-22-10195-2022
- Integration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaigns H. Lim et al. 10.5194/amt-14-4575-2021
- Investigating the Spatial and Temporal Limitations for Remote Sensing of Wildfire Smoke Using Satellite and Airborne Imagers During FIREX‐AQ Y. Shi et al. 10.1029/2023JD039085
- Towards long-term, high-accuracy, and continuous satellite total and fine-mode aerosol records: Enhanced Land General Aerosol (e-LaGA) retrieval algorithm for VIIRS L. Wang et al. 10.1016/j.isprsjprs.2024.06.022
- Retrieving Hourly Aerosol Optical Depth for Geostationary Satellite FY-4B/AGRI by Surface-related Dynamic Spectral Reflectance Ratio Method W. Wang et al. 10.1016/j.asr.2024.10.057
- Evaluation of Aerosol Properties Observed by DSCOVR/EPIC Instrument From the Earth‐Sun Lagrange 1 Orbit C. Ahn et al. 10.1029/2020JD033651
- 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
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- Controlling factors analysis for the Himawari-8 aerosol optical depth accuracy from the standpoint of size distribution, solar zenith angles and scattering angles M. Zhang et al. 10.1016/j.atmosenv.2020.117501
- A High-Precision Aerosol Retrieval Algorithm (HiPARA) for Advanced Himawari Imager (AHI) data: Development and verification X. Su et al. 10.1016/j.rse.2020.112221
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- Dust Aerosol Retrieval Over the Oceans With the MODIS/VIIRS Dark Target Algorithm: 2. Nonspherical Dust Model Y. Zhou et al. 10.1029/2020EA001222
- Preliminary Retrieval and Validation of Aerosol Optical Depths from FY-4B Advanced Geostationary Radiation Imager Images D. Zhou et al. 10.3390/rs16020372
Latest update: 20 Nov 2024
Short summary
Aerosol optical depth (AOD) from a geostationary satellite has been retrieved, and validated and diurnal cycles of aerosols are discussed over the eastern hemisphere and a 2-month period of May–June 2016. The new AOD product matches well with AERONET as well as with the standard MODIS product. Future work to make this algorithm operational will need to re-examine masking including snow masks, re-evaluate assumed aerosol models for geosynchronous geometry and address the surface characterization.
Aerosol optical depth (AOD) from a geostationary satellite has been retrieved, and validated and...