Hyperspectral optical absorption closure experiment in complex coastal waters

Abstract

Accurate measurements of absorption data are required for the development and validation of inversion algorithms for upcoming hyperspectral ocean color imaging sensors, such as the NASA Phytoplankton, Aerosol, Cloud, and ocean Ecosystem mission. This study aims to provide uncertainty estimates associated with leading approaches to measure hyperspectral absorption coefficients in complex coastal waters. Absorption spectra were collected at 12 different stations, all located in the Indian River Lagoon, Florida, USA, between 09 January 2017 and 13 January 2017. Measurements included spectral absorption coefficients in the visible range (400-700 nm) associated with dissolved, a CDOM , total particulate, a p , and total nonwater, a nw , fractions, and were made both in situ and from discrete samples. Discrete sample approaches included dual-beam spectrophotometer, liquid waveguide capillary cell, point-source integrating cavity absorption meter (PSICAM) for dissolved matter absorption samples, and quantitative filter technique ICAM measurements and the dual-beam spectrophotometer with center-mounted integrating sphere filter pad technique, while the Turner Designs ICAM, and WET Labs AC-s, and AC-9 instruments were used to determine absorption coefficients in situ. The Gershun approach, determining absorption from measurement of the irradiance quartet with respect to depth was also assessed in situ. Measurement uncertainties and relative accuracies were quantified for each of these approaches. Results showed generally strong agreements between different discrete sample methods, with average percent absolute error %δ abs < 7% for a CDOM and < 9% for a p . In situ approaches showed higher variability and reduced accuracy. For a nw , %δ abs deviation relative to PSICAM data was on average 12% to 20%. Results help identify remaining technological gaps and need for improvements in the different absorption measurement approaches.Light absorption is a fundamental property of natural waters influencing the propagation of the underwater light field (Mobley 1994;Zaneveld et al. 2005;Wo zniak and Dera 2007). Absorption acts as a spectral filter for incident and scattered solar irradiance (e.g., Jerlov 1976;Morel and Prieur 1977;Lewis et al. 1990). Light absorption is commonly quantified as spectral absorption coefficient a(λ) (m À1 ), where λ is the wavelength in vacuum. The accurate quantification of this coefficient and its variability are important for understanding many physical and biological processes in the upper ocean, which are driven by or depend on solar radiation, for example, various photochemical reactions, heating of water column, availability of energy for photosynthesis, or availability of light for animal vision that is important even at mesopelagic depths. Absorption coefficients can provide information on the nature and concentration of various nonwater constituents dissolved and suspended within water (e.g., Twardowski et al. 2005;Wo zniak and Dera 2007;Twardowski et al. 2018a), such as phytoplankton pigments...

Physiological and interspecific factors determine diel changes in phytoplankton bio‐optical properties

“…Particulate absorption ( a p ) and attenuation ( c p ) were estimated using a calibration‐independent technique in which measurements of 0.2‐ μ m filtered sample water were subtracted from unfiltered measurements (Slade et al 2010). A semiempirical scattering correction was applied to particulate absorption and attenuation spectra following Röttgers et al (2013), which was shown by Kostakis et al (2021) to consistently perform well over a wide range of water types and with less error propagation relative to other correction methods. Particulate scattering ( b p ) was estimated as the difference between attenuation and absorption.…”

Recipes for the Derivation of Water Quality Parameters Using the High-Spatial-Resolution Data from Sensors on Board Sentinel-2A, Sentinel-2B, Landsat-5, Landsat-7, Landsat-8, and Landsat-9 Satellites

“…This level of disagreement among different instruments and methods for absorption measurements is typical. The paper by Kostakis et al (2021) shows an additional ten stations and many other comparisons, including the effects of different scattering corrections for the as9 and acs instruments. Figure 10.20 shows measurements of the particle backscatter coefficient b bp made by four different instruments on a water sample containing E. huxleyi coccolithophores.…”

Estimation of the Global Distribution of Phytoplankton Light Absorption From Pigment Concentrations

“…This will increase the sources of phytoplankton absorption spectra which can be used in data modeling or oceanic ecological studies. Moreover, accurate measurements of absorption spectra are required for the development and validation of the algorithms for upcoming hyperspectral ocean color imaging sensors, such as the NASA's Plankton, Aerosol, Cloud, and ocean Ecosystem mission (Kostakis et al., 2021; Werdell et al., 2019).…”

“…However, the main source of uncertainty in the QFT results from the correction of the amplification of the light pathlength (e.g., Bricaud & Stramski, 1990;IOCCG, 2018;Lefering et al, 2016;Mitchell, 1990;Roesler, 1998;Röttgers & Gehnke, 2012;Stramski et al, 2015;Tassan, 2002;Tassan & Ferrari, 1995).Reflective Tube Absorption Meters (e.g., AC-S) or Integrating Cavity Absorption Meters (e.g., point-source integrating cavity absorption meter or quantitative filter technique-integrating cavity absorption meter; IOCCG, 2018; Kostakis et al, 2021;Röttgers et al, 2005Röttgers et al, , 2016 provide another means to measure absorption. However, these meters provide the absorption of all particles rather than just phytoplankton.…”