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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 3 | Copyright
Atmos. Meas. Tech., 11, 1529-1547, 2018
https://doi.org/10.5194/amt-11-1529-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 19 Mar 2018

Research article | 19 Mar 2018

Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land

Antti Lipponen1, Tero Mielonen1, Mikko R. A. Pitkänen1,3, Robert C. Levy2, Virginia R. Sawyer2, Sami Romakkaniemi1, Ville Kolehmainen3, and Antti Arola1 Antti Lipponen et al.
  • 1Finnish Meteorological Institute, Atmospheric Research Centre of Eastern Finland, Kuopio, Finland
  • 2Climate and Radiation Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 3University of Eastern Finland, Department of Applied Physics, Kuopio, Finland

Abstract. We have developed a Bayesian aerosol retrieval (BAR) algorithm for the retrieval of aerosol optical depth (AOD) over land from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the BAR algorithm, we simultaneously retrieve all dark land pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 0.55µm, fine-mode fraction (FMF), and surface reflectances at four different wavelengths (0.47, 0.55, 0.64, and 2.1µm). The accuracy of the new algorithm is evaluated by comparing the AOD retrievals to Aerosol Robotic Network (AERONET) AOD. The results show that the BAR significantly improves the accuracy of AOD retrievals over the operational Dark Target (DT) algorithm. A reduction of about 29% in the AOD root mean square error and decrease of about 80% in the median bias of AOD were found globally when the BAR was used instead of the DT algorithm. Furthermore, the fraction of AOD retrievals inside the ±(0.05+15%) expected error envelope increased from 55 to 76%. In addition to retrieving the values of AOD, FMF, and surface reflectance, the BAR also gives pixel-level posterior uncertainty estimates for the retrieved parameters. The BAR algorithm always results in physical, non-negative AOD values, and the average computation time for a single granule was less than a minute on a modern personal computer.

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Atmospheric aerosols are small solid or liquid particles suspended in the atmosphere and they have a significant effect on the climate. Satellite data are used to get global estimates of atmospheric aerosols. In this work, a statistics-based Bayesian aerosol retrieval algorithm was developed to improve the accuracy and quantify the uncertainties related to the aerosol estimates. The algorithm is tested with NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data.
Atmospheric aerosols are small solid or liquid particles suspended in the atmosphere and they...
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