Preprints
https://doi.org/10.5194/amt-2022-95
https://doi.org/10.5194/amt-2022-95
 
23 Mar 2022
23 Mar 2022
Status: this preprint is currently under review for the journal AMT.

The New MISR Research Aerosol Retrieval Algorithm: A Multi-Angle, Multi-Spectral, Bounded-Variable Least Squares Retrieval of Aerosol Particle Properties over Both Land and Water

James A. Limbacher1,2,3, Ralph A. Kahn1, and Jaehwa Lee1,4 James A. Limbacher et al.
  • 1Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, 20771, USA
  • 2Science Systems and Applications Inc., Lanham, 20706, USA
  • 3Department of Meteorology and Atmospheric Science, The Pennsylvania State University, State College, 16802, USA
  • 4University of Maryland, College Park, MD, USA

Abstract. Launched in December 1999, NASA’s Multi-angle Imaging SpectroRadiometer (MISR) has given researchers the ability to observe the Earth from nine different views for the last 22 years. Among the many advancements that have since resulted from the launch of MISR is progress in the retrieval of aerosols from passive space-based remote-sensing. The MISR operational standard aerosol retrieval algorithm (SA) has been refined several times over the last twenty years, resulting in significant improvements to spatial resolution (now 4.4 km) and aerosol particle properties. However, the MISR SA still suffers from large biases in retrieved aerosol optical depth (AOD) as aerosol loading increases. Here, we present a new MISR research aerosol retrieval algorithm (RA) that utilizes over-land surface reflectance data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) to address these biases. This new over-land/over-water algorithm produces a self-consistent aerosol/surface retrieval when aerosol loading is low (AOD < 1); this is combined with a prescribed surface algorithm using a bounded-variable least squares solver when aerosol loading is elevated (AOD > 2). The two algorithms (prescribed + retrieved surface) are then merged as part of our combined-surface retrieval algorithm. Results are compared with AErosol RObotic NETwork (AERONET) validation sun-photometer direct-sun + almucantar inversion retrievals.

Over-land, with AERONET AOD (550 nm) direct-sun observations as the standard, the root-mean squared error (RMSE) of the MISR RA combined retrieval (n = 9680) is ~0.09, with a correlation coefficient (r) of ~0.93 and expected error of (0.225*[MISR AOD] + 0.025). For MISR RA-retrieved AOD > 0.5 (n = 565), we report Ångström exponent (ANG) RMSE of ~0.36, with a correlation coefficient of ~0.85. Retrievals of ANG and aerosol particle properties such as fine-mode fraction (FMF) and single-scattering albedo (SSA) improve as retrieved AOD increases. For AOD > 1.5 (n = 45), FMF RMSE is < 0.09 with correlation > 0.95, and SSA RMSE is < 0.02 with a correlation coefficient > 0.80.

Over-water, comparing AERONET AOD to the MISR RA combined retrieval (n = 4590), MISR RA RMSE is ~0.06 and r is ~0.94, with an expected error of (0.20*[MISR AOD] + 0.01). ANG sensitivity is excellent when MISR RA reported AOD > 0.5 (n = 211), with a RMSE of 0.30 and r = 0.88. Due to a lack of coincidences with AOD > 1 (n = 20), our conclusions about MISR RA high-AOD particle property retrievals over water are less robust (FMF RMSE = 0.12 and r = 0.96, whereas SSA RMSE = 0.022 and r = 0.32).

It is clear from the results presented that the new MISR RA has excellent sensitivity to aerosol particle properties (including FMF and SSA) when retrieved AOD exceeds 1–1.5, with qualitative sensitivity to aerosol type at lower AOD, while also eliminating the AOD bias found in the MISR SA at higher AODs. These results also demonstrate the advantage of using a prescribed surface when aerosol loading is elevated.

James A. Limbacher et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-95', Stefan Kinne, 07 Apr 2022
  • RC2: 'Comment on amt-2022-95', Stefan Kinne, 07 Apr 2022
  • RC3: 'Comment on amt-2022-95', Meng Gao, 10 Apr 2022
  • RC4: 'Comment on amt-2022-95', Anonymous Referee #3, 11 Apr 2022
  • RC5: 'Comment on amt-2022-95', Alexei Lyapustin, 13 Apr 2022

James A. Limbacher et al.

James A. Limbacher et al.

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Short summary
Launched in December 1999, NASA’s Multi-angle Imaging SpectroRadiometer (MISR) has given researchers qualitative constraints on aerosol particle properties for the past 22 years. Here, we present a new MISR research aerosol retrieval algorithm (RA) that utilizes over-land surface reflectance data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) to address limitations of the MISR operational aerosol retrieval algorithm and improve retrievals of aerosol particle properties.