Articles | Volume 10, issue 11
https://doi.org/10.5194/amt-10-4121-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-10-4121-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
03 Nov 2017
Research article |
| 03 Nov 2017
Simulation of the Ozone Monitoring Instrument aerosol index using the NASA Goddard Earth Observing System aerosol reanalysis products
Peter R. Colarco
CORRESPONDING AUTHOR
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard
Space Flight Center, Greenbelt, MD, 20770, USA
Santiago Gassó
Climate and Radiation Laboratory, NASA Goddard Space Flight
Center, Greenbelt, MD, 20770, USA
GESTAR/Morgan State University, Baltimore, MD, 21251, USA
Changwoo Ahn
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard
Space Flight Center, Greenbelt, MD, 20770, USA
Science Systems and Applications Inc., Lanham, MD, 20706,
USA
Virginie Buchard
Global Modeling and Assimilation Office, NASA Goddard Space
Flight Center, Greenbelt, MD, 20770, USA
GESTAR/Universities Space Research Association, Columbia, MD, 21046,
USA
Arlindo M. da Silva
Global Modeling and Assimilation Office, NASA Goddard Space
Flight Center, Greenbelt, MD, 20770, USA
Omar Torres
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard
Space Flight Center, Greenbelt, MD, 20770, USA
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- Characterization of smoke and dust episode over West Africa: comparison of MERRA-2 modeling with multiwavelength Mie–Raman lidar observations I. Veselovskii et al. 10.5194/amt-11-949-2018
- Differences in the Evolution of Pyrocumulonimbus and Volcanic Stratospheric Plumes as Observed by CATS and CALIOP Space-Based Lidars K. Christian et al. 10.3390/atmos11101035
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- Computation of Atmospheric Optical Parameters Based on Deep Neural Network and PCA C. Chuan et al. 10.1109/ACCESS.2020.2996626
17 citations as recorded by crossref.
- Retrieval of UV–visible aerosol absorption using AERONET and OMI–MODIS synergy: spatial and temporal variability across major aerosol environments V. Kayetha et al. 10.5194/amt-15-845-2022
- Ozone Monitoring Instrument (OMI) UV aerosol index data analysis over the Arctic region for future data assimilation and climate forcing applications B. Sorenson et al. 10.5194/acp-23-7161-2023
- A new discrete wavelength backscattered ultraviolet algorithm for consistent volcanic SO<sub>2</sub> retrievals from multiple satellite missions B. Fisher et al. 10.5194/amt-12-5137-2019
- The long-term transport and radiative impacts of the 2017 British Columbia pyrocumulonimbus smoke aerosols in the stratosphere S. Das et al. 10.5194/acp-21-12069-2021
- Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS) A. Collow et al. 10.5194/gmd-17-1443-2024
- Improved simulations of biomass burning aerosol optical properties and lifetimes in the NASA GEOS Model during the ORACLES-I campaign S. Das et al. 10.5194/acp-24-4421-2024
- Retrievals of aerosol single scattering albedo by multiwavelength lidar measurements: Evaluations with NASA Langley HSRL-2 during discover-AQ field campaigns D. Pérez-Ramírez et al. 10.1016/j.rse.2018.12.022
- The interaction of ozone and aerosol in a semi-arid region in the Middle East: Ozone formation and radiative forcing implications M. Gharibzadeh et al. 10.1016/j.atmosenv.2020.118015
- Characterization of smoke and dust episode over West Africa: comparison of MERRA-2 modeling with multiwavelength Mie–Raman lidar observations I. Veselovskii et al. 10.5194/amt-11-949-2018
- Differences in the Evolution of Pyrocumulonimbus and Volcanic Stratospheric Plumes as Observed by CATS and CALIOP Space-Based Lidars K. Christian et al. 10.3390/atmos11101035
- An evaluation of biomass burning aerosol mass, extinction, and size distribution in GEOS using observations from CAMP2Ex A. Collow et al. 10.5194/acp-22-16091-2022
- Long-term Variation of Absorption and Total Aerosol Optical Properties over Typical Provinces of China from Satellite Observations H. Li 10.1088/1742-6596/2152/1/012001
- Quantifying the single-scattering albedo for the January 2017 Chile wildfires from simulations of the OMI absorbing aerosol index J. Sun et al. 10.5194/amt-11-5261-2018
- Stratospheric Injection of Massive Smoke Plume From Canadian Boreal Fires in 2017 as Seen by DSCOVR‐EPIC, CALIOP, and OMPS‐LP Observations O. Torres et al. 10.1029/2020JD032579
- The response of the Amazon ecosystem to the photosynthetically active radiation fields: integrating impacts of biomass burning aerosol and clouds in the NASA GEOS Earth system model H. Bian et al. 10.5194/acp-21-14177-2021
- Dynamical perturbation of the stratosphere by a pyrocumulonimbus injection of carbonaceous aerosols G. Doglioni et al. 10.5194/acp-22-11049-2022
- Computation of Atmospheric Optical Parameters Based on Deep Neural Network and PCA C. Chuan et al. 10.1109/ACCESS.2020.2996626
Latest update: 14 Dec 2024
Short summary
We need satellite observations to characterize the properties of atmospheric aerosols. Those observations have uncertainties associated with them because of assumptions made in their algorithms. We test the assumptions on a part of the aerosol algorithms used with the Ozone Monitoring Instrument (OMI) flying on the NASA Aura spacecraft. We simulate the OMI observations using a global aerosol model, and then compare what OMI tells us about the simulated aerosols with the model results directly.
We need satellite observations to characterize the properties of atmospheric aerosols. Those...
