Hyperspectral In situ Support for PACE (HyperInSPACE); Open source data reduction for autonomously collected shipborne above water radiometry brings to light five years of NASA hyperspectral UV-VIS-NIR data.

The automated collection of above water hyperspectral radiometry is challenging even in a controlled environment, and especially problematic in the conditions routinely experienced on a ship underway passing through a broad range of optical water types. Deriving accurate estimates of ocean color under such circumstances requires that data are processed with dynamic and rigorous quality controls and methodologies corresponding to the platform configurations and diverse water types sampled from estuarine to pelagic environments. This most notably includes removal of sea surface reflection (sunlight, skylight, including polarization and spectral dependence) from the measured, upwelled total radiance, and extends to consideration of viewing and solar geometries, bi-directional correction, uncertainty quantification, platform effects, and a host of meteorological factors. HyperInSPACE is a newly developed Python software package designed to process above water hyperspectral radiometry from Satlantic HyperOCR raw binary counts to accurate ocean color products using established NASA and IOCCG protocols as well as emerging experimental methods in a traceable manner suitable for submission to the SeaWiFS Bio-optical Archive and Storage System. Unlike “black box” processing software such as ProSoft, HyperInSPACE is open source, platform independent, and freely available to the community. Its recent development has enabled the processing of >1800 hours of hyperspectral radiometry collections from the NASA Field Support Group from eight cruises over the past five years along the U.S. East and West Coasts, the Bahamas, the S.E. Pacific, E. Pacific, and N.E. Pacific, and the East Sea. These surveys will be compared with profiled radiometry and inherent optical and biogeochemical properties to improve estimates of instrument uncertainty and develop ocean color algorithms for retrieval of spectral IOPs, K_d, TSM, Chl-a, DOC, etc. from hyperspectral radiometry.