Using empirical orthogonal functions derived from remote sensing reflectance for the prediction of concentrations of phytoplankton pigments.

The composition and abundance of algal pigments provide information on characteristics of a phytoplankton community in respect to its photoacclimation, overall biomass, and taxonomic composition. Particularly, these pigments play a major role in photoprotection and in the light-driven part of photosynthesis. Most phytoplankton pigments can be measured by High Performance Liquid Chromatography (HPLC) techniques to filtered water samples. This method, like others when water samples have to be analysed in the laboratory, is time consuming and therefore only a limited number of data points can be obtained. In order to receive information on phytoplankton pigment composition with a higher temporal and spatial resolution, we have developed a method to assess pigment concentrations from continuous optical measurements. The method applies an Empirical Orthogonal Function (EOF) analysis to remote sensing reflectance data derived from ship-based hyper-spectral underwater radiometric and from multispectral satellite data (using the MERIS Polymer product developed by Steinmetz et al., 2011) measured in the Eastern Tropical Atlantic. Subsequently we developed statistically linear models with measured (collocated) pigment concentrations as the response variable and EOF loadings as predictor variables. The model results, show that surface concentrations of a suite of pigments and pigment groups can be well predicted from the ship-based reflectance measurements, even when only a multi-spectral resolution is chosen (i.e. eight bands similar to those used by MERIS). Based on the MERIS reflectance data, concentrations of total and monovinyl chlorophyll a and the groups of photoprotective and photosynthetic carotenoids can be predicted with high quality. The fitted statistical model constructed on the satellite reflectance data as input was applied to one month of MERIS Polymer data to predict the concentration of those pigment groups for the whole Eastern Tropical Atlantic area. Bootstrapping explorations of cross-validation error indicate that the method can produce reliable predictions with relatively small data sets (e.g., < 50 collocated values of reflectance and pigment concentration). The method allows for the derivation of time series from continuous reflectance data of various pigment groups at various regions, which can be used to study variability and change of phytoplankton composition and photo-physiology

Toward autonomous measurements of photosynthetic electron transport rates: An evaluation of active fluorescence-based measurements of photochemistry

This study presents a methods evaluation and intercalibration of active fluorescence-based measurements of the quantum yield (ϕʹ 0 PSII) and absorption coefficient (aPSII) of photosystem II (PSII) photochemistry. Measurements of ϕʹ PSII , aPSII, and irradiance (E) can be scaled to derive photosynthetic electron transport rates (P e ), the process that fuels phytoplankton carbon fixation and growth. Bio-optical estimates of ϕ PSII and aPSII were evaluated using 10 phytoplankton cultures across different pigment groups with varying bio-optical absorption characteristics on six different fast-repetition rate fluorometers that span two different manufacturers and four different models. Culture measurements of ϕʹ PSII and the effective absorption cross section of PSII photochemistry (σPSII, a constituent of aPSII) showed a high degree of correspondence across instruments, although some instrument-specific biases are identified. A range of approaches have been used in the literature to estimate aPSII(λ) and are evaluated here.With the exception of ex situ aPSII(λ) estimates from paired σPSII and PSII reaction center concentration ([RCII]) measurements, the accuracy and precision of in situ aPSII(λ) methodologies are largely determined by the variance of method-specific coefficients. The accuracy and precision of these coefficients are evaluated, compared to literature data, and discussed within a framework of autonomous P e measurements. This study supports the application of an instrument-specific calibration coefficient (KR) that scales minimum fluorescence in the dark (F 0 ) to aPSII as both the most accurate in situ measurement of aPSII, and the methodology best suited for highly resolved autonomous P e measurements

Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern South Pacific and eastern Atlantic Oceans

International audienceWe have examined several approaches for estimating the surface concentration of particulate organic carbon, POC, from optical measurements of remote-sensing reflectance, <i>R_rs(?)</i>, using field data collected in tropical and subtropical waters of the eastern South Pacific and eastern Atlantic Oceans. These approaches include a direct empirical relationship between POC and the blue-to-green band ratio of reflectance, <i>R_rs(?_B)/R_rs</i>(555), and two-step algorithms that consist of relationships linking reflectance to an inherent optical property IOP (beam attenuation or backscattering coefficient) and POC to the IOP. We considered two-step empirical algorithms that exclusively include pairs of empirical relationships and two-step hybrid algorithms that consist of semianalytical models and empirical relationships. The surface POC in our data set ranges from about 10 mg m^-3 within the South Pacific Subtropical Gyre to 270 mg m^-3 in the Chilean upwelling area, and data on phytoplankton pigments, suspended particulate matter, and the backscattering ratio suggest a considerable variation in the composition of particulate assemblages in the investigated waters. The POC algorithm based on the direct relationship between POC and <i>R_rs(?_B)/R_rs</i>(555) promises reasonably good performance in the vast areas of the open ocean covering different provinces from hyperoligotrophic and oligotrophic waters within subtropical gyres to eutrophic coastal upwelling regimes characteristic of eastern ocean boundaries. The best error statistics were found for power function fits to the data of POC vs. <i>R_rs</i>(443)<i>/R_rs</i>(555) and POC vs. <i>R_rs</i>(490)<i>/R_rs</i>(555). For our data set that includes over 50 data pairs, these relationships are characterized by the mean normalized bias of about 2% and the normalized root mean square error of about 20%. We recommend that these algorithms be implemented for routine processing of ocean color satellite data to produce maps of surface POC with the status of an evaluation data product for continued work on algorithm development and refinements. The two-step algorithms also deserve further attention because they can utilize various models for estimating IOPs from reflectance, offer advantages for developing an understanding of bio-optical variability underlying the algorithms, and provide flexibility for regional or seasonal parameterizations of the algorithms

Determination of the absorption coefficient of chromophoric dissolved organic matter from underway spectrophotometry

Measurements of the absorption coefficient of chromophoric dissolved organic matter (ay) are needed to validate existing ocean-color algorithms. In the surface open ocean, these measurements are challenging because of low ay values. Yet, existing global datasets demonstrate that ay could contribute between 30% to 50% of the total absorption budget in the 400–450 nm spectral range, thus making accurate measurement of ay essential to constrain these uncertainties. In this study, we present a simple way of determining ay using a commercially-available in-situ spectrophotometer operated in underway mode. The obtained ay values were validated using independent collocated measurements. The method is simple to implement, can provide measurements with very high spatio-temporal resolution, and has an accuracy of about 0.0004 m−1 and a precision of about 0.0025 m−1 when compared to independent data (at 440 nm). The only limitation for using this method at sea is that it relies on the availability of relatively large volumes of ultrapure water. Despite this limitation, the method can deliver the ay data needed for validating and assessing uncertainties in ocean-colour algorithms

Determination of the absorption coefficient of chromophoric dissolved organic matter from underway spectrophotometry

This is the final version. Available on open access from Optical Society of America via the DOI in this recordMeasurements of the absorption coefficient of chromophoric dissolved organic matter (ay) are needed to validate existing ocean-color algorithms. In the surface open ocean, these measurements are challenging because of low ay values. Yet, existing global datasets demonstrate that ay could contribute between 30% to 50% of the total absorption budget in the 400-450 nm spectral range, thus making accurate measurement of ay essential to constrain these uncertainties. In this study, we present a simple way of determining ay using a commercially-available in-situ spectrophotometer operated in underway mode. The obtained ay values were validated using independent collocated measurements. The method is simple to implement, can provide measurements with very high spatio-temporal resolution, and has an accuracy of about 0.0004 m−1 and a precision of about 0.0025 m−1 when compared to independent data (at 440 nm). The only limitation for using this method at sea is that it relies on the availability of relatively large volumes of ultrapure water. Despite this limitation, the method can deliver the ay data needed for validating and assessing uncertainties in ocean-colour algorithms.European Space Agency (ESA)National Atmospheric and Space Administration (NASA

Optical closure in marine waters from in situ inherent optical property measurements

Optical closure using radiative transfer simulations can be used to determine the consistency of in situ measurements of inherent optical properties (IOPs) and radiometry. Three scattering corrections are applied to in situ absorption and attenuation profile data for a range of coastal and oceanic waters, but are found to have only very limited impact on subsequent closure attempts for these stations. Best-fit regressions on logtransformed measured and modelled downwards irradiance, Ed, and upwards radiance, Lu, profiles have median slopes between 0.92-1.24, revealing a tendency to underestimate Ed and Lu with depth. This is only partly explained by non-inclusion of fluorescence emission from CDOM and chlorophyll in the simulations. There are several stations where multiple volume scattering function related data processing steps perform poorly which suggests the potential existence of unresolved features in the modelling of the angular distribution of scattered photons. General optical closure therefore remains problematic, even though there are many cases in the data set where the match between measured and modelled radiometric data is within 25% RMS%E. These results are significant for applications that rely on optical closure e.g. assimilating ocean colour data into coupled physical-ecosystem models

Inhibition of Rac controls NPM–ALK-dependent lymphoma development and dissemination

Nucleophosmin-anaplastic lymphoma kinase (NPM–ALK) is a tyrosine kinase oncogene responsible for the pathogenesis of the majority of human ALK-positive lymphomas. We recently reported that it activated the Rac1 GTPase in anaplastic large-cell lymphoma (ALCL), leading to Rac-dependent formation of active invadopodia required for invasiveness. Herein, we went further into the study of this pathway and used the inhibitor of Rac, NSC23766, to validate its potential as a molecular target in ALCL in vitro and in vivo in a xenograft model and in a conditional model of NPM–ALK transgenic mice. Our data demonstrate that Rac regulates important effectors of NPM–ALK-induced transformation such as Erk1/2, p38 and Akt. Moreover, inhibition of Rac signaling abrogates NPM–ALK-elicited disease progression and metastasis in mice, highlighting the potential of small GTPases and their regulators as additional therapic targets in lymphomas

CoastColour Round Robin data sets: A database 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

Introduction to special section on Recent Advances in the Study of Optical Variability in the Near-Surface and Upper Ocean

Optical variability occurs in the near-surface and upper ocean on very short time and space scales (e.g., milliseconds and millimeters and less) as well as greater scales. This variability is caused by solar, meteorological, and other physical forcing as well as biological and chemical processes that affect optical properties and their distributions, which in turn control the propagation of light across the air-sea interface and within the upper ocean. Recent developments in several technologies and modeling capabilities have enabled the investigation of a variety of fundamental and applied problems related to upper ocean physics, chemistry, and light propagation and utilization in the dynamic near-surface ocean. The purpose here is to provide background for and an introduction to a collection of papers devoted to new technologies and observational results as well as model simulations, which are facilitating new insights into optical variability and light propagation in the ocean as they are affected by changing atmospheric and oceanic conditions