25 Jul 2023
 | 25 Jul 2023
Status: this preprint is currently under review for the journal AMT.

Performance evaluation of three bio-optical models in aerosol and ocean color joint retrievals

Neranga K. Hannadige, Peng-Wang Zhai, Meng Gao, Yongxiang Hu, P. Jeremy Werdell, Kirk Knobelspiesse, and Brian Cairns

Abstract. Multi-angle polarimeters (MAP) are powerful instruments to perform remote sensing of the environment. Joint retrieval algorithms of aerosols and ocean color have been developed to extract the rich information content of MAPs. These are optimization algorithms that fit the sensor measurements with forward models, which include radiative transfer simulations of the coupled atmosphere and ocean systems (CAOS) based on adjustable atmosphere and ocean properties. The forward mode consists of sub-models to represent the optics of the atmosphere, ocean water surface, and ocean body. The representativeness of these models for observed scenes is important for retrieval success. In this study, we have evaluated the impact on MAP retrieval accuracy of three different ocean bio-optical models with 1, 3, and 7 optimization parameters that represent the spectral variation of inherent optical properties (IOP(λ)s) of the water body. The Multi-Angular Polarimetric Ocean coLor (MAPOL) joint retrieval algorithm was used to process data from the airborne Research Scanning Polarimeter (RSP) instrument acquired in different field campaigns. We performed ensemble retrievals along three RSP legs to evaluate the applicability of bio-optical models along geographically varying waters. The average differences between the MAPOL aerosol optical depth (AOD) and spectral remote sensing reflectance (Rrs(λ)) retrievals and the MODerate resolution Imaging Spectroradiometer (MODIS) products are also reported. We studied the distribution of retrieval cost function values obtained for the ensemble retrievals using the 3 bio-optical models under clear to highly turbid waters. For the 1-parameter model, retrieval cost function values show narrow distributions over any type of water, regardless of the cost function values, whereas for the 3 and 7- parameter models, the retrieval cost function distribution is water type dependent, showing the widest distribution over clear, open waters. We observed that the 3 and 7-parameter models have similar MAP retrieval performances relative to the 1- parameter model. We also demonstrated that the 3 and 7-parameter bio-optical models can be used to accurately represent both clear, open, and turbid, coastal waters, whereas the 1-parameter model is most successful over extremely clear waters. Given the computational efficiency requirements, we recommend the 3-parameter bio-optical model as the coastal water bio-optical model for future MAPOL studies. This study guides MAP algorithm development for current and future satellite missions such as NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission and ESA’s Meteorological Operational-Second Generation (MetOp-SG) mission.

Neranga K. Hannadige 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-2023-142', Anonymous Referee #1, 10 Aug 2023
  • RC2: 'Comment on amt-2023-142', Anonymous Referee #2, 15 Aug 2023

Neranga K. Hannadige et al.

Neranga K. Hannadige et al.


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Short summary
We evaluated the impact of three ocean optical models with different numbers of free parameters on the performance of an aerosol and ocean color remote sensing algorithm using the multi-angle polarimeter (MAP) measurements. It was demonstrated that the 3 and 7-parameter bio-optical models can be used to accurately represent both open and coastal waters, whereas the 1-parameter model does have smaller retrieval uncertainty over open waters.