An Evaluation of Oceanographic Optical Instruments and Deployment Methodologies

The primary objective of the Sea-viewing, Wide Field-of-view Sensor (SeaWiFS) Project is to produce water- leaving radiances with an uncertainty of 5% in clear-water regions and chlorophyll a concentrations within +/- 35% over the range of 0.05-50 mg/cu m. Any global mission, like SeaWiFS, requires validation data be submitted from a wide variety of investigators which places a significant challenge on quantifying the total uncertainty associated with the in situ measurements, because each investigator follows slightly different practices when it comes to implementing all of the steps associated with collecting field data, even those with a prescribed set of protocols. This study uses data from multiple cruises to quantify the uncertainties associated with implementing data collection procedures while utilizing differing in-water optical instruments and deployment methods. A comprehensive approach is undertaken and includes: (1) the use of a portable light source and in-water intercomparisons to monitor the stability of the field radiometers, (2) alternative methods for acquiring reference measurements, and (3) different techniques for making in-water profiles. The only system to meet the 5% radiometric objective of the SeaWiFS Project was a free-fall profiler using (relatively inexpensive) modular components, although a more sophisticated (and comparatively expensive) profiler using integral components was very close and only 1% higher. A relatively inexpensive system deployed with a winch and crane was also close, but the ship shadow contamination problem increased the total uncertainty to approximately 6.5%

Annual cycles of phytoplankton biomass in the subarctic Atlantic and Pacific Ocean

High-latitude phytoplankton blooms support productive fisheries and play an important role in oceanic uptake of atmospheric carbon dioxide. In the subarctic North Atlantic Ocean, blooms are a recurrent feature each year, while in the eastern subarctic Pacific only small changes in chlorophyll (Chl) are seen over the annual cycle. Here we show that when evaluated using phytoplankton carbon biomass (C[subscript]phyto) rather than Chl, an annual bloom in the North Pacific is evident and can even rival blooms observed in the North Atlantic. The annual increase in subarctic Pacific phytoplankton biomass is not readily observed in the Chl record because it is paralleled by light- and nutrient-driven decreases in cellular pigment levels (C[subscript]phyto:Chl). Specifically, photoacclimation and iron stress effects on C[subscript]phyto:Chl oppose the biomass increase, leading to only modest changes in bulk Chl. The magnitude of the photoacclimation effect is quantified using descriptors of the near-surface light environment and a photophysiological model. Iron stress effects are diagnosed from satellite chlorophyll fluorescence data. Lastly, we show that biomass accumulation in the Pacific is slower than that in the Atlantic but is closely tied to similar levels of seasonal nutrient uptake in both basins. Annual cycles of satellite-derived Chl and C[subscript]phyto are reproduced by in situ autonomous profiling floats. These results contradict the long-standing paradigm that environmental conditions prevent phytoplankton accumulation in the subarctic Northeast Pacific and suggest a greater seasonal decoupling between phytoplankton growth and losses than traditionally implied. Further, our results highlight the role of physiological processes in shaping bulk properties, such as Chl, and their interpretation in studies of ocean ecosystem dynamics and climate change.Keywords: remote sensing, phytoplanktonKeywords: remote sensing, phytoplankto

An Overview of Approaches and Challenges for Retrieving Marine Inherent Optical Properties from Ocean Color Remote Sensing

Ocean color measured from satellites provides daily global, synoptic views of spectral water-leaving reflectancesthat can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namelythe ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a watermass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and itsdissolved and particulate constituents. Because of their dependence on the concentration and composition ofmarine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This informationis critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbonproduction and export, phytoplankton dynamics, and responses to climatic disturbances. Given their im-portance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products intothe community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., theglobal, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mis-sion), we present a synopsis of the current state of the art in the retrieval of these core optical properties.Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separatedbased their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated witheach approach are provided, as well as common performance metrics used to evaluate them. We discuss currentknowledge gaps and make recommendations for future investment for upcoming missions whose instrumentcharacteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches

CoastColour Round Robin datasets: A data base to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

The use of in situ measurements is essential in the validation and evaluation of the algorithms that provide coastal water quality data products from ocean colour satellite remote sensing. Over the past decade, various types of ocean colour algorithms have been developed to deal with the optical complexity of coastal waters. Yet there is a lack of a comprehensive intercomparison due to the availability of quality checked in situ databases. The CoastColour Round Robin (CCRR) project, funded by the European Space Agency (ESA), was designed to bring together three reference data sets using these to test algorithms and to assess their accuracy for retrieving water quality parameters. This paper provides a detailed description of these reference data sets, which include the Medium Resolution Imaging Spectrometer (MERIS) level 2 match-ups, in situ reflectance measurements, and synthetic data generated by a radiative transfer model (HydroLight). These data sets, representing mainly coastal waters, are available from doi:10.1594/PANGAEA.841950. The data sets mainly consist of 6484 marine reflectance (either multispectral or hyperspectral) associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: total suspended matter (TSM) and chlorophyll a (CHL) concentrations, and the absorption of coloured dissolved organic matter (CDOM). Inherent optical properties are also provided in the simulated data sets (5000 simulations) and from 3054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three data sets are compared. Match-up and in situ sites where deviations occur are identified. The distributions of the three reflectance data sets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.JRC.H.1-Water Resource

Optimization Of Ocean Color Algorithms: Application To Satellite And In Situ Data Merging

The objective of our program is to develop and validate a procedure for ocean color data merging which is one of the major goals of the SIMBIOS project (McClain et al., 1995). The need for a merging capability is dictated by the fact that since the launch of MODIS on the Terra platform and over the next decade, several global ocean color missions from various space agencies are or will be operational simultaneously. The apparent redundancy in simultaneous ocean color missions can actually be exploited to various benefits. The most obvious benefit is improved coverage (Gregg et al., 1998; Gregg & Woodward, 1998). The patchy and uneven daily coverage from any single sensor can be improved by using a combination of sensors. Beside improved coverage of the global ocean the merging of ocean color data should also result in new, improved, more diverse and better data products with lower uncertainties. Ultimately, ocean color data merging should result in the development of a unified, scientific quality, ocean color time series, from SeaWiFS to NPOESS and beyond. Various approaches can be used for ocean color data merging and several have been tested within the frame of the SIMBIOS program (see e.g. Kwiatkowska & Fargion, 2003, Franz et al., 2003). As part of the SIMBIOS Program, we have developed a merging method for ocean color data. Conversely to other methods our approach does not combine end-products like the subsurface chlorophyll concentration (chl) from different sensors to generate a unified product. Instead, our procedure uses the normalized waterleaving radiances (LwN( )) from single or multiple sensors and uses them in the inversion of a semianalytical ocean color model that allows the retrieval of several ocean color variables simultaneously. Beside ensuring simultaneity and consistency of the retrievals (all products are derived from a single algorithm), this model-based approach has various benefits over techniques that blend end-products (e.g. chlorophyll): 1) it works with single or multiple data sources regardless of their specific bands, 2) it exploits band redundancies and band differences, 3) it accounts for uncertainties in the LwN( ) data and, 4) it provides uncertainty estimates for the retrieved variables

Results of the Second SeaWiFS Data Analysis Round Robin, March 2000 (DARR-00)

The accurate determination of upper ocean apparent optical properties (AOPs) is essential for the vicarious calibration of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) instrument and the validation of the derived data products. To evaluate the importance of data analysis methods upon derived AOP values, the Second Data Analysis Round Robin (DARR-00) activity was planned during the latter half of 1999 and executed during March 2000. The focus of the study was the intercomparison of several standard AOP parameters: (1) the upwelled radiance immediately below the sea surface, L(sub u)(0(-),lambda); (2) the downward irradiance immediately below the sea surface, E(sub d)(0(-),lambda); (3) the diffuse attenuation coefficients from the upwelling radiance and the downward irradiance profiles, L(sub L)(lambda) and K(sub d)(lambda), respectively; (4) the incident solar irradiance immediately above the sea surface, E(sub d)(0(+),lambda); (5) the remote sensing reflectance, R(sub rs)(lambda); (6) the normalized water-leaving radiance, [L(sub W)(lambda)](sub N); (7) the upward irradiance immediately below the sea surface, E(sub u)(0(-)), which is used with the upwelled radiance to derive the nadir Q-factor immediately below the sea surface, Q(sub n)(0(-),lambda); and (8) ancillary parameters like the solar zenith angle, theta, and the total chlorophyll concentration, C(sub Ta), derived from the optical data through statistical algorithms. In the results reported here, different methodologies from three research groups were applied to an identical set of 40 multispectral casts in order to evaluate the degree to which differences in data analysis methods influence AOP estimation, and whether any general improvements can be made. The overall results of DARR-00 are presented in Chapter 1 and the individual methods used by the three groups and their data processors are presented in Chapters 2-4

WestberryAnnualCyclesPhytoplanktonSupplement.pdf

High-latitude phytoplankton blooms support productive fisheries and play an important role in oceanic uptake of atmospheric carbon dioxide. In the subarctic North Atlantic Ocean, blooms are a recurrent feature each year, while in the eastern subarctic Pacific only small changes in chlorophyll (Chl) are seen over the annual cycle. Here we show that when evaluated using phytoplankton carbon biomass (C[subscript]phyto) rather than Chl, an annual bloom in the North Pacific is evident and can even rival blooms observed in the North Atlantic. The annual increase in subarctic Pacific phytoplankton biomass is not readily observed in the Chl record because it is paralleled by light- and nutrient-driven decreases in cellular pigment levels (C[subscript]phyto:Chl). Specifically, photoacclimation and iron stress effects on C[subscript]phyto:Chl oppose the biomass increase, leading to only modest changes in bulk Chl. The magnitude of the photoacclimation effect is quantified using descriptors of the near-surface light environment and a photophysiological model. Iron stress effects are diagnosed from satellite chlorophyll fluorescence data. Lastly, we show that biomass accumulation in the Pacific is slower than that in the Atlantic but is closely tied to similar levels of seasonal nutrient uptake in both basins. Annual cycles of satellite-derived Chl and C[subscript]phyto are reproduced by in situ autonomous profiling floats. These results contradict the long-standing paradigm that environmental conditions prevent phytoplankton accumulation in the subarctic Northeast Pacific and suggest a greater seasonal decoupling between phytoplankton growth and losses than traditionally implied. Further, our results highlight the role of physiological processes in shaping bulk properties, such as Chl, and their interpretation in studies of ocean ecosystem dynamics and climate change.Keywords: remote sensing, phytoplankto

SeaWiFS Postlaunch Technical Report Series

Volume 11 continues the sequential presentation of postlaunch data analysis and algorithm descriptions begun in Volume 9. Chapters 1 and 2 present the OC2 (version 2) and OC4 (version 4) chlorophyll a algorithms used in the SeaWiFS data second and third reprocessings, August 1998 and May 2000, respectively. Chapter 3 describes a revision of the K(490) algorithm designed to use water-leaving radiances at 490 nm which was implemented for the third reprocessing. Finally, Chapter 4 is an analysis of in situ radiometer calibration data over several years at the University of California, Santa Barbara (UCSB) to establish the temporal consistency of their in-water optical measurements

SeaWiFS Postlaunch Technical Report Series

This report documents the fifth Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Intercalibration Round-Robin Experiment (SIRREX-5), which was held at the National Institute of Standards and Technology (NIST) on 23-30 July 1996. The agenda for SIRREX-5 was established based on recommendations made during SIRREX-4. For the first time in a SIRREX activity, instrument intercomparisons were performed at field sites, which were near NIST. The goals of SIRREX-5 were to continue the emphasis on training and the implementation of standard measurement practices, investigate the calibration methods and measurement chains in use by the oceanographic community, provide opportunities for discussion, and intercompare selected instruments. As at SIRREX-4, the day was divided between morning lectures and afternoon laboratory exercises. A set of core laboratory sessions were performed: 1) in-water radiant flux measurements; 2) in-air radiant flux measurements; 3) spectral radiance responsivity measurements using the plaque method; 4) device calibration or stability monitoring with portable field sources; and 5) various ancillary exercises designed to illustrate radiometric concepts. Before, during, and after SIRREX-5, NIST calibrated the SIRREX-5 participating radiometers for radiance and irradiance responsivity. The Facility for Automated Spectroradiometric Calibrations (FASCAL) was scheduled for spectral irradiance calibrations for standard lamps during SIRREX-5. Three lamps from the SeaWiFS community were submitted and two were calibrated

The Ocean Colour Climate Change Initiative: III. A Round-Robin Comparison on In-Water Bio-Optical Algorithms

Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situ Rrs as input to the models, the performance of eleven semianalytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies