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

Limbacher, ., R.A. Kahn, and J. Lee (2022), 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, Atmos. Meas. Tech., 15, 6865-6887, doi:10.5194/amt-15-6865-2022.
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 (SA) retrieval algorithm has been refined several times over the last 20 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 (RA) retrieval algorithm that utilizes over-land surface reflectance data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) to address these biases. This new over-land and over-water algorithm produces a self-consistent aerosol and surface retrieval when aerosol loading is low (AOD < 0.75); this is combined with a prescribed surface algorithm using a bounded-variable least squares solver when aerosol loading is elevated (AOD > 1.5). 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 = 11563) is 0.084, with a correlation coefficient (r) of 0.935 and expected error of ±(0.20 × [MISR AOD] + 0.02). For MISR RA retrieved AOD > 0.5 (n = 664), we report an Ångström exponent (ANG) RMSE of ∼ 0.35, with a correlation coefficient of 0.844. Retrievals of ANG, fine-mode fraction (FMF), and single-scattering albedo (SSA) improve as retrieved AOD increases. For AOD > 1.5 (n = 66), FMF RMSE is < 0.09 with correlation > 0.95, and SSA RMSE is 0.015 with a correlation coefficient of ∼ 0.75.

Over water, comparing AERONET AOD to the MISR RA combined retrieval (n = 4596), MISR RA RMSE is 0.063 and r is 0.935, with an expected error of ±(0.15 × [MISR AOD] + 0.02). ANG sensitivity is excellent when MISR RA reported AOD > 0.5 (n = 188), with an RMSE of 0.27 and r = 0.89. Due to a lack of coincidences with AOD > 1 (n = 21), our conclusions about MISR RA highAOD particle property retrievals over water are less robust (FMF RMSE = 0.155 and r = 0.94, whereas SSA RMSE = 0.010 and r = 0.50).

In general, better aerosol particle property constraints can be made at lower AOD over water compared to our overland retrievals. It is clear from the results presented that the new MISR RA has quantitative sensitivity to FMF and SSA (and qualitative sensitivity to non-sphericity) when retrieved AOD exceeds 1, with qualitative sensitivity to aerosol type at lower AOD, while also eliminating the AOD bias found in the

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Research Program
Atmospheric Composition
Atmospheric Composition Modeling and Analysis Program (ACMAP)
Radiation Science Program (RSP)
Mission
Terra- MISR