Characterizing CDOM Spectral Variability Across Diverse Regions and Spectral Ranges

Abstract

Satellite remote sensing of colored dissolved organic matter (CDOM) has focused on CDOM absorption (aCDOM) at a reference wavelength, as its magnitude provides insight into the underwater light field and large‐scale biogeochemical processes. CDOM spectral slope, SCDOM, has been treated as a constant or semiconstant parameter in satellite retrievals of aCDOM despite significant regional and temporal variabilities. SCDOM and other optical metrics provide insights into CDOM composition, processing, food web dynamics, and carbon cycling. To date, much of this work relies on fluorescence techniques or aCDOM in spectral ranges unavailable to current and planned satellite sensors (e.g., <300 nm). In preparation for anticipated future hyperspectral satellite missions, we take the first step here of exploring global variability in SCDOM and fit deviations in the aCDOM spectra using the recently proposed Gaussian decomposition method. From this, we investigate if global variability in retrieved SCDOM and Gaussian components is significant and regionally distinct. We iteratively decreased the spectral range considered and analyzed the number, location, and magnitude of fitted Gaussian components to understand if a reduced spectral range impacts information obtained within a common spectral window. We compared the fitted slope from the Gaussian decomposition method to absorption‐based indices that indicate CDOM composition to determine the ability of satellite‐derived slope to inform the analysis and modeling of large‐scale biogeochemical processes. Finally, we present implications of the observed variability for remote sensing of CDOM characteristics via SCDOM.

Evaluation of MODIS—Aqua Chlorophyll-a Algorithms in the Basilicata Ionian Coastal Waters

“…With regard to the local setting of CDM absorption spectra, the key parameter for a CDM (λ) setting was the average spectral slope S, which accounted for the contribution of each component, namely a CDOM (λ) and a NAP (λ). However, the S value could vary, depending on the different fitting technique (linear vs. non-linear) and wavelength reference range (starting at 300 nm or 400 nm) adopted [78,79]. In this work, the 350-500 nm wavelength range allowed for the maintenance of a sufficiently high signal to noise ratio, considering the CDOM and NAP high absorption properties at these wavelengths.…”

Deriving inherent optical properties from decomposition of hyperspectral non-water absorption

“…This is very likely due to the inclusion of chromophores in ag () and ad() that result in deviations from the typical exponential expression used to model these parameters, features visibly apparent in many of the adg() spectra. While often overlooked, these features have been recognized for some time (Babin et al 2003;Schwarz et al 2002) and a recent methodology for fitting these peaks provides a means of both quantifying them and more accurately modeling the underlying exponential signal (Catalá et al 2016;Massicotte and Markager 2016;Grunert et al 2018). This approach is useful for in situ data, but not practical for our proposed methodology and likely a non-factor when considering at-w() derived from satellite Rrs().…”

“…3 and 4 are empirical and follow band-ratio techniques used for fitting Sdg in current semi-analytical schemes (Lee et al 2009;Matsuoka et al 2013). Noise in this relationship was explained by variability in the exact shape of aph() due to varying phytoplankton composition, physiology and pigment packaging effects (Bricaud and Morel 1986;Bricaud et al 1983;Ciotti et al 2002;Johnsen et al 1994) as well as variability in the spectral shape and features of ag() and ad() (Grunert et al 2018). As the algorithm is currently optimized for a global approach, users may find that adjusting the empirical values used to initially estimate adg(440) and…”

“…Sg currently limits our ability to accurately track production and degradation of CDOM across broad spatial scales while also introducing significant uncertainty in estimates of aph() and derived products (e.g., chlorophyll-a concentration). Additionally, increasing observations of ag() have shown that Sg displays significant variability and is capable of characterizing CDOM of unique source, environmental conditions and degradation state (Asmala et al 2018;Danhiez et al 2017;Grunert et al 2018;Helms et al 2008Helms et al , 2013. Considering this, it is likely that this parameter contains very useful information regarding food web processes and marine carbon cycling relevant to understanding the balance of the marine DOM carbon reservoir.…”

A calibration/validation protocol for long/multi‐pathlength capillary waveguide spectrometers

“…CDOM plays a substantial role in determining the aquatic light field, with its absorption at short wavelengths (< 440 nm) usually dominating total absorption in the upper water column of the open oceans (Blough and Del Vecchio ; Nelson and Siegel ; Siegel et al ; Zepp et al ; Nelson and Siegel ). Because of its importance, optical spectroscopy as well as satellite ocean color measurements have been employed to examine its distribution and dynamics (Blough and Del Vecchio ; Mopper and Kieber ; Belz et al ; Nelson and Siegel ; Sharpless and Blough ; Grunert et al ; Werdell ). However, the very low levels of CDOM absorption observed in the open ocean are difficult to determine accurately by standard benchtop spectrometers, which are generally limited to short pathlengths (≤ 10 cm).…”