Capturing optically important constituents and properties in a marine biogeochemical and ecosystem model

Abstract

Abstract. We present a numerical model of the ocean that couples a three-stream radiative transfer component with a marine biogeochemical-ecosystem component in a dynamic three-dimensional physical framework. The radiative transfer component resolves the penetration of spectral irradiance as it is absorbed and scattered within the water column. We explicitly include the effect of several optically important water constituents (different phytoplankton functional types; detrital particles; and coloured dissolved organic matter, CDOM). The model is evaluated against in situ-observed and satellite-derived products. In particular we compare to concurrently measured biogeochemical, ecosystem, and optical data along a meridional transect of the Atlantic Ocean. The simulation captures the patterns and magnitudes of these data, and estimates surface upwelling irradiance analogous to that observed by ocean colour satellite instruments. We find that incorporating the different optically important constituents explicitly and including spectral irradiance was crucial to capture the variability in the depth of the subsurface chlorophyll a (Chl a) maximum. We conduct a series of sensitivity experiments to demonstrate, globally, the relative importance of each of the water constituents, as well as the crucial feedbacks between the light field, the relative fitness of phytoplankton types, and the biogeochemistry of the ocean. CDOM has proportionally more importance at attenuating light at short wavelengths and in more productive waters, phytoplankton absorption is relatively more important at the subsurface Chl a maximum, and water molecules have the greatest contribution when concentrations of other constituents are low, such as in the oligotrophic gyres. Scattering had less effect on attenuation, but since it is important for the amount and type of upwelling irradiance, it is crucial for setting sea surface reflectance. Strikingly, sensitivity experiments in which absorption by any of the optical constituents was increased led to a decrease in the size of the oligotrophic regions of the subtropical gyres: lateral nutrient supplies were enhanced as a result of decreasing high-latitude productivity. This new model that captures biooptical feedbacks will be important for improving our understanding of the role of light and optical constituents on ocean biogeochemistry, especially in a changing environment. Further, resolving surface upwelling irradiance will make it easier to connect to satellite-derived products in the future.

Modelling ocean-colour-derived chlorophyll <i>a</i>

“…We use the biogeochemical/ecosystem/optical numerical model as configured in Dutkiewicz et al (2015). We provide a brief description of the pertinent features here but refer the reader to that paper for more details, equations, parameter values and evaluation.…”

“…The phytoplankton also differ in their spectral absorption and scattering (see Fig. 1 in Dutkiewicz et al, 2015) and maximum Chl a : C ratio. The different scattering and absorption spectra for each functional group incorporate the packaging effect (e.g.…”

“…We did not do this for model validation purposes (see evaluation in Dutkiewicz et al, 2015) but rather to re-emphasis that the satellite-derived Chl a products are proxies for realworld actual Chl a -the two are not the same thing. We compare climatological monthly model derived Chl a and model actual Chl a to OC-CCI monthly climatology regridded to the model configuration (1 • resolution).…”

“…However, there are some models that have recently incorporated a more thorough treatment of the light field (e.g. Gregg and Casey, 2007;Mobley et al, 2009;Dutkiewicz et al, 2015), and some now include aspects such as reflectance or water-leaving irradiances that more directly relate to ocean colour Baird et al, 2016;Gregg and Rousseaux, 2017).…”

“…However, it is only recently that models have directly included the treatment of ocean optics to allow for explicitly including diagnostics such as remotely sensed reflectance (e.g. Dutkiewicz et al, 2015;Baird et al, 2016). Here we use one of these models; a global three-dimensional biogeochemical, ecosystem and radiative transfer numerical model that can act as a virtual laboratory to explore the connections between satellite-derived products and the ecosystem variability that they are attempting to capture.…”