POSTER Session 1

Preliminary Hyperspectral Closure Analyzes in Lake Erie using Hyper-bb backscattering data

In order to better calibrate and validate satellite remote sensing water quality algorithms, our lab group has routinely sampled the inherent and apparent optical properties of the Great Lakes since 2015. This dataset includes hyperspectral absorption and attenuation, multispectral (9-band) backscattering (using a Seabird ECO BB9), and hyperspectral above-water and profiling radiometry, along with biogeochemical measurements including chlorophyll-a concentrations, fractionated suspended particulate matter measurements, and CDOM absorption. In advance of the NASA PACE launch, this instrument suite was expanded to include a hyperspectral backscattering sensor (Sequoia Hyper-BB). Measurements have been made across a range of environmental conditions since summer 2022, with observed chlorophyll concentrations and particulate backscattering measurements spanning 3 orders of magnitude (chl from <1 to 190 mg/m3; bbp(530) from 0.002 to 0.4 m-1). Sampling has included many cruises in western Lake Erie during significant harmful algal bloom and sediment plume events, conditions that often saturate the ECO BB9 sensor. Initial comparisons revealed strong correlation between particulate backscattering measurements from the Hyper-bb and BB9, with the Hyper-bb able to generate measurements in conditions that saturate the BB9. Interestingly, the Hyper-bb data has revealed novel spectral shapes related to elevated pigment concentrations that have not historically been resolvable with the BB9, particularly in waters dominated by harmful algal blooms. This presentation details our measurements to date as well as our initial hyperspectral closure analyzes using the full suite of optical instruments (Hyper-bb, Seabird ac-s, Seabird HyperPro, Sequoia LISST-200x) and biogeochemical lab data.

*Karl Bosse, Michigan Tech Research Institute, USA, https://orcid.org/0009-0001-3080-1998

Michael Sayers, Michigan Tech Research Institute, USA

Zane Almquist, Michigan Tech Research Institute, USA

Steve Ruberg, NOAA Great Lakes Environmental Research Laboratory, USA

Reagan Errera, NOAA Great Lakes Environmental Research Laboratory, USA

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