ROSES Proposals

With previous NASA PACE Science Team support, Twardowski and Tonizzo (2018) (TT18) developed a new radiative transfer (RT) approximation for ocean color reflectance that includes the bidirectional reflectance distribution function (BRDF) and explicitly incorporates the volume scattering function (VSF). This model, called Zaneveld-Twardowski-Tonizzo (ZTT), has demonstrated improved performance relative to current state-of-the-art models by Morel et al. (2002) (M02) and Lee et al. (2011) that are based on simple first order approximations relating reflectance to absorption and backscattering based originally on Gordon et al. (1988). TT18 demonstrated the stronger performance was due to the greater degrees of freedom in describing the RT phenomenon relative to simple first order approximations.

The ZTT model is readily amenable to inversion within the Generalized IOP (GIOP) algorithm framework as currently implemented by NASA OBPG in SeaDAS and described in Werdell et al. (2013). Biogeochemical subcomponents of absorption and backscattering can similarly be derived. In preliminary assessments, the ZTT inversion has exhibited stronger overall performance than similar implementation configurations for GIOP. There are several additional expected advantages in application of the algorithm for the future PACE mission, as the model:

1. is natively hyperspectral (M02 is not);
2. enables direct assimilation of VSF data from concurrent PACE polarimetry measurements to potentially reduce uncertainties in IOP retrievals;
3. includes the backscattering ratio, a long sought-after product of ocean color remote sensing with valuable information on particle composition;
4. is generic to any natural water;
5. is a single analytical and invertible expression describing the RT process for all remote sensing geometries, i.e., it includes the BRDF and eliminates BRDF normalization steps;
6. retains native RT relationships directly linked to physically meaningful terms with more degrees of freedom than simple first order approximations;
7. allows the uncertainties for all parameters including the VSF to be readily characterized; and
8. can be readily enhanced by tuning one or more terms rather than developing new look-up tables from complete recomputations of full RT.

Our approach will start with characterizing uncertainties for the ZTT model for all remote sensing viewing geometries. TT18 were only able to validate the model for conventional nadir viewing radiance measurements. We will also provide a new BRDF normalization algorithm for PACE, needed for reflectance intercomparisons and mapping and will work with Marco Talone and Giuseppe Zibordi to quantify uncertainties in applying the ZTT BRDF model to the AERONET data sets.

We will assess uncertainties in applying the ZTT inversion within the GIOP framework to derive IOPs for available validation data sets and compare to current state-of-the-art inversion algorithms. We will seek to enhance the performance of ZTT inversions in GIOP by 1) compiling enhanced hyperspectral libraries of subcomponent IOPs to serve as spectral shape vectors in the algorithm and 2) by implementing a more robust, quicker, and accurate error minimization algorithm based on Particle Swarm Optimization (PSO). We will configure the ZTT inversion to incorporate concurrent VSF data from PACE polarimeters and to provide the particulate backscattering ratio as a new product. A final objective will be pursuing a polarized version of the ZTT model that may be implemented with PACE.

OUR OVERALL PROJECT GOAL: to provide IOP inversion algorithms to be implemented for the PACE mission based on the natively hyperspectral ZTT model with robustly characterized uncertainties for all IOP products.