Original Research ARTICLE
Sensitivity of inherent optical properties from ocean reflectance inversion models to satellite instrument wavelength suites
- 1Goddard Space Flight Center, United States
- 2Go2Q Pty Ltd, Australia
The Earth science community seeks to develop climate data records (CDRs) from satellite measurements of ocean color, a continuous data record which now exceeds twenty years. Space agencies will launch additional instruments in the coming decade that will continue this data record, including the NASA PACE spectrometer. Inherent optical properties (IOPs) quantitatively describe the absorbing and scattering constituents of seawater and can be estimated from satellite-observed spectroradiometric data using semi-analytical algorithms (SAAs). SAAs exploit the contrasting optical signatures of constituent matter at spectral bands observed by satellite sensors. SAA performance, therefore, depends on the spectral resolution of the satellite spectroradiometer. A CDR spanning SeaWiFS, MODIS, OLCI, and PACE, for example, would include IOPs derived using varied wavelength suites if all available wavelengths were considered. Here, we explored differences in derived IOPs that stem simply from the use of (eight) different wavelength suites of input radiometric measurements. Using synthesized data and SeaWiFS Level-3 mission-long composites, we demonstrated equivalent SAA performance for all wavelength suites, but that IOP retrievals vary by several percent across wavelength suites and as a function of water type. The differences equate to roughly 6, 12, and 7% for adg(443), aph(443), and bbp(443), respectively, for waters with Ca 1 mg m-3. These values shrink for sensors with similar wavelength suites (e.g., SeaWiFS, MODIS, and MERIS) and rise to substantially larger values for higher Ca waters. Our results also indicate that including 400 nm (in the case of OLCI) influences the derived IOPs, using longer wavelengths (> 600 nm) influences the derived IOPs when there is a red signal, and, including additional spectral information shows potential for improved IOP estimation, but not without revisiting SAA parameterizations and execution. While modest in scope, we believe this study contributes to the knowledge base for CDR development. The implication of ignoring such an analysis as CDRs continue to be developed is a prolonged inability to distinguish between algorithmic and environmental contributions to trends and anomalies in the IOP time-series.
Keywords: Ocean Color satellites, Bio-optical modeling, Inherent optical properties (IOPs), Remote-sensing reflectance, ocean remote sensing, Semi-analytical algorithm
Received: 02 Nov 2018;
Accepted: 06 Mar 2019.
Edited by:David Antoine, Curtin University, Australia
Reviewed by:Vittorio E. Brando, Istituto di Scienze Marine (ISMAR), Italy
Severine ALVAIN, Centre National de la Recherche Scientifique (CNRS), France
Copyright: © 2019 Werdell and McKinna. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Jeremy Werdell, Goddard Space Flight Center, Greenbelt, 20771, Maryland, United States, firstname.lastname@example.org