The MISR Research Product Algorithm – producing global, self-consistent, pixel-level aerosol retrievals for the Multi-angle Imaging SpectroRadiometer

Abstract. The MISR Research Aerosol retrieval algorithm (RA) was developed in parallel with the MISR standard operational algorithm (SA), to explore innovative retrieval ideas for possible implementation in the SA, and to provide higher-spatial-resolution results with enhanced sensitivity to particle properties, where possible. Whereas the SA was designed to run automatically on the entire MISR dataset, the RA, a research code, had to be run on a case-by-case basis, with considerable user involvement. We present here a version of the RA, the MISR Research Product Algorithm (MRPA), that has been streamlined and automated for wider use, along with validation results for this algorithm. The compromises required to automate the RA result in somewhat diminished particle-type sensitivity. However, the MRPA provides 1.1 km pixel resolution (compared to 4.4 km for the SA), and comparing the AOD data statistically with AERONET, it offers about half the statistical RMSE, significantly higher correlation coefficient, though somewhat higher bias, for mid-visible AOD compared to the SA over land, along with better Ångström exponent statistics, especially at higher AOD. Statistical validation of particle shape and single-scattering albedo is more difficult, but for sufficiently high AOD, retrievals in smoke-dominated regions show a preponderance of small-medium, spherical, light-absorbing particles, whereas dust-dominated regions tend to have larger, weakly absorbing, non-spherical particles.

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Publication Details

Journal
Atmospheric measurement techniques
Published
2026-10-16
DOI
https://doi.org/10.5194/amt-19-6503-2026
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00

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article

The MISR Research Product Algorithm – producing global, self-consistent, pixel-level aerosol retrievals for the Multi-angle Imaging SpectroRadiometer

James A. Limbacher, Michael Anstett, Ralph A. Kahn
Atmospheric measurement techniques
Atmospheric aerosols and clouds
article

The MISR Research Product Algorithm – producing global, self-consistent, pixel-level aerosol retrievals for the Multi-angle Imaging SpectroRadiometer

James A. Limbacher, Michael Anstett, Ralph A. Kahn
article en

Abstract

Abstract. The MISR Research Aerosol retrieval algorithm (RA) was developed in parallel with the MISR standard operational algorithm (SA), to explore innovative retrieval ideas for possible implementation in the SA, and to provide higher-spatial-resolution results with enhanced sensitivity to particle properties, where possible. Whereas the SA was designed to run automatically on the entire MISR dataset, the RA, a research code, had to be run on a case-by-case basis, with considerable user involvement. We present here a version of the RA, the MISR Research Product Algorithm (MRPA), that has been streamlined and automated for wider use, along with validation results for this algorithm. The compromises required to automate the RA result in somewhat diminished particle-type sensitivity. However, the MRPA provides 1.1 km pixel resolution (compared to 4.4 km for the SA), and comparing the AOD data statistically with AERONET, it offers about half the statistical RMSE, significantly higher correlation coefficient, though somewhat higher bias, for mid-visible AOD compared to the SA over land, along with better Ångström exponent statistics, especially at higher AOD. Statistical validation of particle shape and single-scattering albedo is more difficult, but for sufficiently high AOD, retrievals in smoke-dominated regions show a preponderance of small-medium, spherical, light-absorbing particles, whereas dust-dominated regions tend to have larger, weakly absorbing, non-spherical particles.

Atmospheric measurement techniquesVol. 19(20)
Goddard Space Flight Center (US), National Oceanic and Atmospheric Administration (US), University of Colorado Boulder (US), NOAA Oceanic and Atmospheric Research (US), Science Systems and Applications (United States) (US), Science and Technology Corporation (United States) (US)
National Aeronautics and Space Administration, Langley Research Center
Openalex Percentile: Top 86%
Atmospheric aerosols and clouds
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