An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe

Abstract. Nearly half of the earth’s photosynthetically fixed carbon derives from the oceans. To determine global and region specific rates, we rely on models that estimate marine net primary productivity (NPP) thus it is essential that these models are evaluated to determine their accuracy. Here we assessed the skill of 21 ocean color models by comparing their estimates of depth-integrated NPP to 1156 in situ 14C measurements encompassing ten marine regions including the Sargasso Sea, pelagic North Atlantic, coastal Northeast Atlantic, Black Sea, Mediterranean Sea, Arabian Sea, subtropical North Pacific, Ross Sea, West Antarctic Peninsula, and the Antarctic Polar Frontal Zone. Average model skill, as determined by root-mean square difference calculations, was lowest in the Black and Mediterranean Seas, highest in the pelagic North Atlantic and the Antarctic Polar Frontal Zone, and intermediate in the other six regions. The maximum fraction of model skill that may be attributable to uncertainties in both the input variables and in situ NPP measurements was nearly 72%. On average, the simplest depth/wavelength integrated models performed no worse than the more complex depth/wavelength resolved models. Ocean color models were not highly challenged in extreme conditions of surface chlorophyll-a and sea surface temperature, nor in high-nitrate low-chlorophyll waters. Water column depth was the primary influence on ocean color model performance such that average skill was significantly higher at depths greater than 250 m, suggesting that ocean color models are more challenged in Case-2 waters (coastal) than in Case-1 (pelagic) waters. Given that in situ chlorophyll-a data was used as input data, algorithm improvement is required to eliminate the poor performance of ocean color NPP models in Case-2 waters that are close to coastlines. Finally, ocean color chlorophyll-a algorithms are challenged by optically complex Case-2 waters, thus using satellite-derived chlorophyll-a to estimate NPP in coastal areas would likely further reduce the skill of ocean color models

Integration

The Carbon cycle transcends traditional domains: ocean, land, and atmosphere, inter-connects them, and is intimately coupled with climate. Carbon cycle processes exhibit different behaviour and the importance of these processes varies with both spatial and temporal scales. This chapter attempts to encompass several elements to integration, including: integration across disciplines, integration across domains, integration across observing systems, integration of observations and models, integration across multiple sensors, integration of products.JRC.H.1-Water Resource

The specific inherent optical properties of three sub-tropical and tropical water reservoirs in Queensland, Australia

The underwater light climate, which is a major influence on the ecology of aquatic systems, is affected by the absorption and scattering processes that take place within the water column. Knowledge of the Specific Inherent Optical Properties (SIOPs) of water quality parameters and their spatial variation is essential for the modelling of underwater light fields and remote sensing applications. We measured the SIOPs and water quality parameter concentrations of three large inland water impoundments in Queensland, Australia. The measurements ranged from 0.9–42.7 μgl/1 for chlorophyll a concentration, 0.9–170.4 mgl/1 for tripton concentration, 0.36–1.59 m/1 for aCDOM(440) and 0.15–2.5 m for Secchi depth. The SIOP measurements showed that there is sufficient intra-impoundment variation in the specific absorption and specific scattering of phytoplankton and tripton to require a well distributed network of measurement stations to fully characterise the SIOPs of the optical water quality parameters. While significantly different SIOP sets were measured for each of the study sites the measurements were consistent with published values in other inland waters. The multiple measurement stations were allocated into optical domains as a necessary step to parameterise a semi-analytical inversion remote sensing algorithm. This paper also addresses the paucity of published global inland water SIOP sets by contributing Australian SIOP sets to allow international and national comparison