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PACE data sets will offer unprecedented opportunities to improve, and even provide new, aerosol and ocean products from inversions of space-borne observations. Of particular interest will be the synergy between UV radiometry (from the OCI sensor) and UV-VIS multi-angle polarimetry (from the SPEXone and HARP2 sensors). Enhanced multiple scattering (EMS) in the atmosphere, which results from an increase in molecular optical depth, causes space-borne UV radiance to be more sensitive to absorbing aerosols such as Black Carbon (BC) and Brown Carbon (BrC). At the same time, EMS increases the diffuse skylight illuminating the ocean, and therefore the radiative coupling between ocean and atmosphere. Hence, satellite retrievals of atmospheric and oceanic UV products must be carried out simultaneously; such inversions provide as an added bonus a rigorous evaluation of associated uncertainty budgets. The radiative coupling between atmosphere and ocean also highlights the importance of absorption by colored detrital matter (CDM) in the ocean. CDM exhibits similar absorption spectra as BrC aerosols and therefor has a similar impact on space-borne UV radiance. An advantage of polarized radiance is that it is less sensitive to multiple scattering, and thus to radiative coupling of atmosphere and ocean. Hence, polarimetric measurements constitute a crucial asset in simultaneous retrievals of BC/BrC and CDM UV products from space-borne observations.

The objective of our proposal is to perform simultaneous retrievals of CDM, BC and BrC products from (i) combined OCI-SPEXone data sets; and (ii) combined OCI-HARP2 data sets. OCI observations cover the UV down to 350 nm, but its radiance data sets are sensitive to variations in both atmospheric and oceanic properties. SPEXone observations complement OCI observations by also providing multi-angle polarized radiance observations down to 385 nm; however, the swath of SPEXone observations is significantly smaller than OCI's. HARP2 observations complement OCI observations by providing multi-angle polarized radiance observations for a swath similar to that of OCI observations; however, HARP2 observations capture the spectrum down to only 440 nm. Hence, for HARP2 we will focus on how the CDM/BC/BrC product retrievals from OCI-SPEXone data sets can be applied to analyses of OCI-HARP2 data sets obtained over a larger swath.

We will use the MAPP retrieval algorithm, which was developed to retrieve aerosol and ocean color properties from airborne multiangle polarimetry observations down to 410 nm by our RSP instrument. We will apply this algorithm to both simulated PACE data sets and available airborne data sets to develop and optimize the retrieval of CDM/BC/BrC UV products from PACE observations. MAPP will be extended to include (a) variations in phytoplankton absorption in the UV; (b) variations in spectral slopes of CDM absorption and in underwater light scattering coefficient; (c) variations in complex refractive indices for BrC aerosols. We will use MAPP inversions of (1) OCI radiance in the VIS to select appropriate phytoplankton absorption spectra for use in the UV; and (2) SPEXone/HARP2 VIS polarized radiance to mask dust-contaminated scenes.

We will use existing in-situ, airborne, and simulated space-borne data sets for our analyses of information content on, and retrieval uncertainties of, atmospheric and oceanic properties. For the in-situ and airborne data sets, we will focus on the SABOR and NAAMES campaigns where RSP observations were coordinated with ship measurements. For the NAAMES campaign, we will also use UV hyperspectral measurements from the airborne GCAS that were co-located with RSP observations. To simulate PACE observations, we will use SeaWiFS retrievals for extrapolation of UV ocean properties, and GISS ModelE results for global variations in aerosol UV properties.

The 2013 ROSES A.25 solicitation calls for studies on atmospheric correction in support of the PACE (Pre-Aerosol, Cloud, ocean Ecosystem) mission. To address this call, we will examine the capacity of PACE-like observations for atmospheric correction by (i) applying statistical methods to compute data information content, and (ii) inverting synthetic and real PACE-like observations into ocean spectra. In step (i), we will focus on the instrument options proposed in the PACE SDT (Science Definition Team) report. Specifically, we will consider the base instrument option OCI (Ocean Color Imager, which includes the 350, 865, 1240, 1640, and 2130 nm channels for atmospheric correction), and elements of instrument options OCI/OG (i.e. OCI base option augmented by a 820 nm band and an Oxygen A band), OCI/+ (i.e. OCI base option augmented by 940, 1378, and 2250 nm bands), OCI-3M (i.e. OCI base option plus a multi-angle multispectral multi-polarization, or 3M, imager), and OCI/A-3M (i.e. OCI/+ option plus a 3M imager). In step (ii), we will apply optimization techniques to extract ocean spectra from various data sets. Specifically, we will apply these techniques to synthetic data created for instrument options with a range of atmospheric-correction performances, as identified in step (i). In addition, we will apply these techniques to three existing measurement sets: the 2011 HOPE-COAST (Hands On Project Experience-Coastal and Ocean Airborne Science Testbed) and the 2013 OCEANIA/ACOCO (Ocean Color Ecosystem Assessments with Novel Instruments and Aircraft/Atmospheric Correction Over Coastal Oceans) measurements acquired in Monterey Bay (which include measurements of inherent optical properties and of chlorophyll), and coinciding HICO (Hyperspectral Imager for the Coastal Ocean) and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) measurements acquired across the globe. These measurement sets incorporate aspects of the instrument options proposed for PACE and contain data to validate atmospheric correction and/or ocean color spectra retrievals.

Using statistical methods to examine the information content and inversion of ocean color remote sensing observations is a complex undertaking that requires a multidisciplinary team. Dr. Chowdhary has worked on ocean and aerosol retrievals from observations by the RSP (Research Scanning Polarimeter) instrument, which is an airborne version of the Aerosol Polarimeter Sensor (APS) onboard the failed 2011 NASA/Glory mission. He wrote a radiative transfer program for polarized underwater light, was a member of the Glory ST (Science Team) and PACE SDT, and is PI of ACOCO. Dr. Alexandrov has written cloud inversion algorithms for RSP, and was also a member of the Glory ST. Dr. Knobelspiesse has worked on inverting coincident RSP and Lidar data, has done information content analyses for different satellite instrument options in support of Glory ST and PACE SDT reports, and was a member of the Glory ST. Dr. van Diedenhoven has expertise in simulating and analyzing hyper-spectral and polarimetry data and the Oxygen A-band, as well as in information content analyses. Dr. Cairns was a member of the Glory ST and the PACE SDT, and has developed techniques for the efficient implementation of inversion algorithms. Dr. Kudela has worked extensively on ocean color retrievals and modeling of underwater light field to describe biological-physical coupling in coastal waters. He is the PI of the coastal ocean project that collaborated with OCEANIA. Dr. Guild has expertise in coastal ecosystem science, and was PI of HOPECOAST and OCEANIA. She is now leading the HQ2O (High-Quality Optical Observations: Improving Atmospheric Correction and Remote Sensing of Water Quality in the Coastal Zone) project with Dr. Kudela. Dr. Palacios has expertise in discriminating phytoplankton types from ocean color, and is processing and analyzing coastal data from the HOPE-COAST and OCEANIA campaigns for the HQ2O project.