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The study of the distribution of primary production in the world oceans preoccupied biological oceanographers for most of the twentieth century. Understanding the distribution remains a problem for which there is no facile answer; it is a many-faceted problem to which the approaches differ depending on the temporal and spatial scales at which understanding is sought. The issues relate to limitations of measurement techniques, interpretation of measurements that are available, and paucity of data.

The question of how to derive and present uncertainty information in climate data records (CDRs) has received sustained attention within the European Space Agency Climate Change Initiative (CCI), a programme to generate CDRs addressing a range of essential climate variables (ECVs) from satellite data. Here, we review the nature, mathematics, practicalities, and communication of uncertainty information in CDRs from Earth observations. This review paper argues that CDRs derived from satellite-based Earth observation (EO) should include rigorous uncertainty information to support the application of the data in contexts such as policy, climate modelling, and numerical weather prediction reanalysis. Uncertainty, error, and quality are distinct concepts, and the case is made that CDR products should follow international metrological norms for presenting quantified uncertainty. As a baseline for good practice, total standard uncertainty should be quantified per datum in a CDR, meaning that uncertainty estimates should clearly discriminate more and less certain data. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence in the uncertainty estimate provided or indicators of conditions violating the retrieval assumptions). The paper discusses the many sources of error in CDRs, noting that different errors may be correlated across a wide range of timescales and space scales. Error effects that contribute negligibly to the total uncertainty in a single-satellite measurement can be the dominant sources of uncertainty in a CDR on the large space scales and long timescales that are highly relevant for some climate applications. For this reason, identifying and characterizing the relevant sources of uncertainty for CDRs is particularly challenging. The characterization of uncertainty caused by a given error effect involves assessing the magnitude of the effect, the shape of the error distribution, and the propagation of the uncertainty to the geophysical variable in the CDR accounting for its error correlation properties. Uncertainty estimates can and should be validated as part of CDR validation when possible. These principles are quite general, but the approach to providing uncertainty information appropriate to different ECVs is varied, as confirmed by a brief review across different ECVs in the CCI. User requirements for uncertainty information can conflict with each other, and a variety of solutions and compromises are possible. The concept of an ensemble CDR as a simple means of communicating rigorous uncertainty information to users is discussed. Our review concludes by providing eight concrete recommendations for good practice in providing and communicating uncertainty in EO-based climate data records.

16 pages, 10 figures, 5 tables.-- Heather A. Bouman ... et al.-- This work is distributed under the Creative Commons Attribution 3.0 License, The photosynthetic performance of marine phytoplankton varies in response to a variety of factors, environmental and taxonomic. One of the aims of the MArine primary Production: model Parameters from Space (MAPPS) project of the European Space Agency is to assemble a global database of photosynthesis– irradiance (P-E) parameters from a range of oceanographic regimes as an aid to examining the basin-scale variability in the photophysiological response of marine phytoplankton and to use this information to improve the assignment of P-E parameters in the estimation of global marine primary production using satellite data. The MAPPS P-E database, which consists of over 5000 P-E experiments, provides information on the spatiotemporal variability in the two P-E parameters (the assimilation number, PB m , and the initial slope, B, where the superscripts B indicate normalisation to concentration of chlorophyll) that are fundamental inputs for models (satellite-based and otherwise) of marine primary production that use chlorophyll as the state variable. Qualitycontrol measures consisted of removing samples with abnormally high parameter values and flags were added to denote whether the spectral quality of the incubator lamp was used to calculate a broad-band value of B. The MAPPS database provides a photophysiological data set that is unprecedented in number of observations and in spatial coverage. The database will be useful to a variety of research communities, including marine ecologists, biogeochemical modellers, remote-sensing scientists and algal physiologists. The compiled data are available at https://doi.org/10.1594/PANGAEA.874087 (Bouman et al., 2017).

RESUMEEn octobre-novembre 1989, deux etudes de teledetection ont ete menees a l'embouchure du fleuve Cardigan, sur l'Ile-du-Prince-Edouard, Canada, en relation avec l'intoxication par les mollusques du aux moules bleues (Mytilus edulis) cultivees dans la region. La toxine provenait de la floraison de la diatomee, Pseudo-nitzschia multiseries. Les etudes de teledetection aeroportees ont ete effectuees afin d'explorer l'etendue et la dynamique de la floraison dans l'embouchure du fleuve. En comparant les donnees multispectrales de luminance obtenues par la teledetection aeroportee contre les mesures in situ, il a ete possible d'etablir des algorithmes empiriques pour la localite, liant les concentrations en pigments dans les eaux de surface avec les mesures aeriennes. Ces algorithmes etaient ensuite utilises pour cartographier la repartition locale des pigments phytoplanctoniques. Une croissance rapide du phytoplancton etait evidente dans les deux semaines qui ont separe les sorties en avion.L'experience de...

We review the current state of our capabilities for the systematic sustained observation of ocean ecosystems, concentrating primarily on planktonic ecosystems. First, we describe the structure of ocean ecosystems – from the nutrients that support primary production, up through the plankton, and then through the various predators, from juvenile finfish to whales, sea lions and humans. We try to draw a picture of the ocean ecosystem (and related biogeochemical cycles) as complex, dynamic systems embedded in the equally complex and dynamic system represented by physical ocean processes. We describe the properties of ecosystems that biologists need to observe and understand, if they are to forecast the future behaviour of ocean ecosystems. Second, we identify the major users and uses for sustained observations of marine ecosystems. Third, we summarize how ocean ecosystems are observed from ships, trying to get across the need to describe the 'texture' as well as the dynamics of ocean ecosystems. Fourth, we review and present examples of the main components of emerging ecosystem observing systems. Finally, we discuss the gaps in existing capabilities and suggest a strategy to guide the development of sustained observations of planktonic ecosystems over the next decade.

Satellite-based ocean colour sensors can be used to estimate the global distribution of primary production. A general approach is presented, which consists of the development of a local algorithm to compute the photosynthetic rate by phytoplankton, and the application of this local result to estimate the integrated primary production at larger scales. Based on the well known relationship between light and photosynthesis, the local model uses spectral computation of the irradiance field at the ocean surface, and in situ observations of photosynthetic parameters. From satellite data and parametrisation of a generalised profile, the local structure of the vertical pigment profile is retrieved allowing then the computation of the submarine light field as a function of depth, wavelength and zenith angle. Finally, perspectives and applications of the model are discussed in parallel with some recent advances in scientific disciplines related to primary production.

A reflectance model is presented that takes into account the spectral signatures of phytoplankton, dissolved organic matter and non-chlorophyllous particles. The model is validated by comparison with observed reflectance spectra. It is then used to simulate a data bank of reflectance spectra for a wide range of combinations of the three optically active substances in various concentrations. The in vivo chlorophyll-a fluorescence is masked. The simulated data are subjected to eigenvector and multiple regression analyses. It appears that the spectral signatures are sufficiently orthogonal to permit retrieval of the concentrations of individual components from the reflectance spectra. However, due to the non-linearity of the system, site-specific algorithms tailored to suit local conditions are likely to yield better results than a single universal algorithm for case 2 waters. Results indicate that the use of 400 nm in addition to the CZCS channels greatly enhances the capability to separate the phytoplankton signal from that of dissolved yellow organic matter. It appears possible to use 5 key-wavelengths (400, 440, 520, 565 and 640 nm) instead of the complete spectrum, without significant loss of information. The consequence of the variability in the backscattering signal of non-chlorophyllous particles is also examined.