CHLOROPHYLL ALGORITHMS FOR OCEAN COLOR SENSORS - OC4, OC5 & OC6.

A high degree of consistency and comparability among chlorophyll algorithms is necessary to meet the goals of merging data from concurrent overlapping ocean color missions for increased coverage of the global ocean and to extend existing time series to encompass data from recently launched missions and those planned for the near future, such as PACE, OLCI, HawkEye, EnMAP and SABIA-MAR. To accomplish these goals, we developed 65 empirical ocean color (OC) maximum band ratio (MBR) algorithms for 25 satellite instruments using the largest available and most globally representative database of coincident in situ chlorophyll a and remote sensing reflectances. Excellent internal consistency was achieved across these OC 'Version -7' algorithms, as demonstrated by a median regression slope and coefficient of determination (R2) of 0.985 and 0.859, respectively, between 903 pairwise comparisons of OC-modeled chlorophyll. SeaWiFS and MODIS-Aqua satellite-to-in situ match-up results indicated equivalent, and sometimes superior, performance to current heritage chlorophyll algorithms. During the past forty years of ocean color research the violet band (412 nm) has rarely been used in empirical algorithms to estimate chlorophyll concentrations in oceanic surface water. While the peak in chlorophyll-specific absorption coincides with the 443 nm band present on most ocean color sensors, the magnitude of chlorophyll-specific absorption at 412 nm can reach upwards of ~70% of that at 443 nm. Nearly one third of total chlorophyll-specific absorption between 400 and 700 nm occurs below 443 nm, suggesting that bands below 443 nm, such as the 412 nm band present on most ocean color sensors, may also be useful in detecting chlorophyll under certain conditions and assumptions. The 412 nm band is also the brightest band (that is, with the most dominant magnitude) in remotely sensed reflectances retrieved by heritage passive ocean color instruments when chlorophyll is less than ~0.1 mg m-3, which encompasses ~24% of the global ocean. To attempt to exploit this additional spectral information, we developed two new families of OC algorithms, the OC5 and OC6 algorithms, which include the 412 nm band in the MBR. By using this brightest band in MBR empirical chlorophyll algorithms, the highest possible dynamic range of MBR may be achieved in these oligotrophic areas. The terms oligotrophic, mesotrophic, and eutrophic get frequent use in the scientific literature to designate trophic status; however, quantitative definitions in terms of chlorophyll levels are arbitrarily defined. We developed a new, reproducible, bio-optically based index for trophic status based on the frequency of the brightest, maximum band in the MBR for the OC6_SEAWIFS algorithm, along with remote sensing reflectances from the entire SeaWiFS mission. This index defines oligotrophic water as chlorophyll less than ~0.1 mg m-3, eutrophic water as chlorophyll above 1.67 mg m-3 and mesotrophic water as chlorophyll between 0.1 and 1.67 mg m-3. Applying these criteria to the 40-year mean global ocean chlorophyll data set revealed that oligotrophic, mesotrophic, and eutrophic water occupy ~24%, 67%, and 9%, respectively, of the area of the global ocean on average.

Modeling the dynamics of continental shelf carbon.

Continental margin systems are important contributors to global nutrient and carbon budgets. Effort is needed to quantify this contribution and how it will be modified under changing patterns of climate and land use. Coupled models will be used to provide projections of future states of continental margin systems. Thus, it is appropriate to consider the limitations that impede the development of realistic models. Here, we provide an overview of the current state of modeling carbon cycling on continental margins as well as the processes and issues that provide the next challenges to such models. Our overview is done within the context of a coupled circulation-biogeochemical model developed for the northeastern North American continental shelf region. Particular choices of forcing and initial fields and process parameterizations are used to illustrate the consequences for simulated distributions, as revealed by comparisons to observations using quantitative statistical metrics.

NOAA-NASA Coastal Zone Color Scanner reanalysis effort.

Satellite observations of global ocean chlorophyll span more than two decades. However, incompatibilities between processing algorithms prevent us from quantifying natural variability. We applied a comprehensive reanalysis to the Coastal Zone Color Scanner (CZCS) archive, called the National Oceanic and Atmospheric Administration and National Aeronautics and Space Administration (NOAA-NASA) CZCS reanalysis (NCR) effort. NCR consisted of (1) algorithm improvement (AI), where CZCS processing algorithms were improved with modernized atmospheric correction and bio-optical algorithms and (2) blending where in situ data were incorporated into the CZCS AI to minimize residual errors. Global spatial and seasonal patterns of NCR chlorophyll indicated remarkable correspondence with modern sensors, suggesting compatibility. The NCR permits quantitative analyses of interannual and interdecadal trends in global ocean chlorophyll.