Temporal Variability of Ocean Colour Derived Products in the European Seas

The ten-year record of ocean colour data provided by the SeaWiFS mission is an important asset for monitoring and research activities conducted on the optically-complex European seas. This study mainly makes use of the SeaWiFS data set of normalized water leaving radiances LWN to study the major characteristics of temporal variability associated with optical properties across the entire European domain. Specifically, the time series of LWN, band ratios, diffuse attenuation coefficient Kd(490) and concentration of chlorophyll a Chla are decomposed into terms representing a fixed seasonal cycle, irregular variations and trends, and the contribution of these components to the total variance is described for the various basins. The diversity of the European waters is fully reflected by the range of results varying with regions and wavelengths. Generally, the Mediterranean and Baltic seas appear as two end-members with, respectively, high and low contributions of the seasonal component to the total variance. The existence of linear trends affecting the satellite products is also explored for each basin. The interpretation of the trends observed for LWN and band ratios is not straightforward, but it circumvents the limitations resulting from the levels of uncertainty, very variable in space and often high, that characterize derived products such as Chla in European waters. Results for Kd(490) and Chla are also analyzed. Statistically significant, and in some cases large, trends are detected in the Atlantic Ocean west of the European western shelf, the central North Sea, the English Channel, the Black Sea, the northern Adriatic, and various regions of the Mediterranean Sea and the northern Baltic Sea, revealing changes in the concentrations of optically significant constituents in these regions.JRC.H.3-Global environement monitorin

Multi-Year Analysis of Standard Ocean Colour Products for the European Seas

A 10-year time series of ocean colour products has been assembled for the European Seas from the SeaWiFS and MODIS full resolution satellite imagery. The JRC ocean colour archive is first briefly described. Then the study focuses on the analysis of the spatial and temporal variability of standard products such as the chlorophyll a pigment concentration and the diffuse attenuation coefficient. The European seas are partitioned into a set of specific regions for which average time series are derived and analysed in terms of seasonal and inter-annual variability. Finally, a statistical analysis yields a decomposition of the series into seasonal, irregular and linear trend components, thus providing a classification of the European waters on the basis of their temporal variations.JRC.H.3-Global environement monitorin

Selected UV Photochemical and Photobiological Impacts on Marine Ecosystems: General Characteristics and Sensitivity Analyses

In the recent years, numerous efforts have been performed in order to characterize the impacts of UVR on marine photobiology and photochemistry. The quantification of these UV-dependent processes through modelling approaches requires (i) an accurate description of UV underwater light field (ii) an adapted parameterization of the response of marine water compounds and/or organisms to spatio-temporal changes in solar radiations. The spatial and temporal variability of the absorption coefficient of the colored detrital material, which is a key element for studying undersea UV climate, has been characterized in the two basins selected for this study (the Mediterranean Sea and the Norwegian Seas) using the SeaWiFS products archive recently achieved for the period 1998-2006. Moreover, the various models currently available for the description of selected optical (CDOM photobleaching), photochemical (CO and DIC production) and photobiological (primary production inhibition) effects of UVR on marine waters have been described. Further, the general characteristics of these UV-dependent processes have been presented focusing, in particularly, on their variability along the daily, vertical and spectral dimensions. Several sensitivity analyses have been performed in order to define the relative importance of the various inputs of the spectral and depth resolved model on the final estimations. Finally, some of the straightforward models recently proposed in order to estimate some of the UV impacts at large temporal and or spatial scales have been tested and their limits of application have been discussed.JRC.H.3-Global environement monitorin

Challenges and New Advances in Ocean Color Remote Sensing of Coastal Waters

Knowing that coastal areas concentrate about 60% of the world's population (within 100 km from the coast), that 75-90% of the global sink of suspended river load takes place in coastal waters in which about 15% of the primary production occurs, the ecological, societal and economical value of these areas are obvious (fish resources, aquaculture, water quality information, recreation areas management, global carbon budget, etc). In that context, precise assessment of suspended particulate matter (SPM) concentrations and of the phenomena controlling its temporal variability is a key objective for many research fields in coastal areas. SPM which encompasses organic (living and non-living) and inorganic matter controls the penetration of light into the water and brings new nutrients into the system, both key parameters influencing phytoplankton primary production. Concentrations and availability of SPM are also known to control rates of food intake, growth and reproduction for various filter feeder organisms. Phytoplankton is highly sensitive to environmental perturbations (such as nutrient inputs, light, and turbulence). The abundance, biomass and dynamics of phytoplankton in coastal areas therefore reflect the prevailing environmental conditions and represent key parameters for assessing information on the ecological conditions, as well as on the coastal water quality. Because phytoplankton is highly sensitive to environmental perturbations [1], its distribution patterns and temporal variability represent good indicators of the ecological conditions of a defined region [2, 3]. Coastal waters also host complex ecosystems and represent important fishery areas that support industry and provide livelihood to coastal settlements. The food chain in the coastal ocean is generally short (especially in upwelling systems, having as low as three trophic levels) whereas the open ocean food web presents up to six trophic levels [4]. As a result, when compared to the open ocean, a relative lower fraction of the primary production gets respired in the coastal ocean while a higher fraction reaches the uppermost trophic level (fish) [5] or is exported to adjacent areas (coastal or open sea)..

Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll- a data

In this work, trend estimates are used as indicators to compare the multi-annual variability of different satellite chlorophyll-a (Chla) data and to assess the fitness-for-purpose of multi-mission Chla products as climate data records (CDR). Under the assumption that single-mission products are free from spurious temporal artifacts and can be used as benchmark time series, multi-mission CDRs should reproduce the main trend patterns observed by single-mission series when computed over their respective periods. This study introduces and applies quantitative metrics to compare trend distributions from different data records. First, contingency matrices compare the trend diagnostics associated with two satellite products when expressed in binary categories such as existence, significance and signs of trends. Contingency matrices can be further summarized by metrics such as Cohen's κ index that rates the overall agreement between the two distributions of diagnostics. A more quantitative measure of the discrepancies between trends is provided by the distributions of differences between trend slopes. Thirdly, maps of the level of significance P of a t-test quantifying the degree to which two trend estimates differ provide a statistical, spatially-resolved, evaluation. The proposed methodology is applied to the multi-mission Ocean Colour-Climate Change Initiative (OC-CCI) Chla data. The agreement between trend distributions associated with OC-CCI data and single-mission products usually appears as good as when single-mission products are compared. As the period of analysis is extended beyond 2012 to 2015, the level of agreement tends to be degraded, which might be at least partly due to the aging of the MODIS sensor on-board Aqua. On the other hand, the trends displayed by the OC-CCI series over the short period 2012–2015 are very consistent with those observed with VIIRS. These results overall suggest that the OC-CCI Chla data can be used for multi-annual time series analysis (including trend detection), but with some caution required if recent years are included, particularly in the central tropical Pacific. The study also recalls the challenges associated with creating a multi-mission ocean color data record suitable for climate research

Reduce the opacity of the systems in order to have a better sense of agency and acceptability for the automated system

During Human–computer interaction (HCI), human can distinguish his own actions from the actions caused by the system or an external event. This feeling is called “Sense of Agency” (SoA; Gallagher, 2000). This form of self-awareness is important not only for motor control but also for the ascription of causal responsibility and serves as a key motivational force for human behaviour. Scientifically, the formation of the SoA is still questioned, but a consensus has been found by explaining this formation with a causal chain: “Intention – Action – Effect”

Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North Sea

Over the past years, a large number of new approaches in the domain of ocean-color have been developed, leading to a variety of innovative descriptors for phytoplankton communities. One of these methods, named PHYSAT, currently allows for the qualitative detection of five main phytoplankton groups from ocean-color measurements. Even though PHYSAT products are widely used in various applications and projects, the approach is limited by the fact it identifies only dominant phytoplankton groups. This current limitation is due to the use of biomarker pigment ratios for establishing empirical relationships between in-situ information and specific ocean-color radiance anomalies in open ocean waters. However, theoretical explanations of PHYSAT suggests that it could be possible to detect more than dominance cases but move more toward phytoplanktonic assemblage detection. Thus, to evaluate the potential of PHYSAT for the detection of phytoplankton assemblages, we took advantage of the Continuous Plankton Recorder (CPR) survey, collected in both the English Channel and the North Sea. The available CPR dataset contains information on diatom abundance in two large areas of the North Sea for the period 1998-2010. Using this unique dataset, recurrent diatom assemblages were retrieved based on classification of CPR samples. Six diatom assemblages were identified in-situ, each having indicators taxa or species. Once this first step was completed, the in-situ analysis was used to empirically associate the diatom assemblages with specific PHYSAT spectral anomalies. This step was facilitated by the use of previous classifications of regional radiance anomalies in terms of shape and amplitude, coupled with phenological tools. Through a matchup exercise, three CPR assemblages were associated with specific radiance anomalies. The maps of detection of these specific radiances anomalies are in close agreement with current in-situ ecological knowledge

Temporal changes in total and size-fractioned chlorophyll-a in surface waters of three provinces in the Atlantic Ocean (September to November) between 2003 and 2010

Phytoplankton total chlorophyll concentration (TCHLa) and phytoplankton size structure are two important ecological indicators in biological oceanography. Using high performance liquid chromatography (HPLC) pigment data, collected from surface waters along the Atlantic Meridional Transect (AMT), we examine temporal changes in TCHLa and phytoplankton size class (PSC: micro-, nano- and pico-phytoplankton) between 2003 and 2010 (September to November cruises only), in three ecological provinces of the Atlantic Ocean. The HPLC data indicate no significant change in TCHLa in northern and equatorial provinces, and an increase in the southern province. These changes were not significantly different to changes in TCHLa derived using satellite ocean-colour data over the same study period. Despite no change in AMT TCHLa in northern and equatorial provinces, significant differences in PSC were observed, related to changes in key diagnostic pigments (fucoxanthin, peridinin, 19’-hexanoyloxyfucoxanthin and zeaxanthin), with an increase in small cells (nano- and pico-phytoplankton) and a decrease in larger cells (micro-phytoplankton). When fitting a three-component model of phytoplankton size structure ̶ designed to quantify the relationship between PSC and TCHLa ̶ to each AMT cruise, model parameters varied over the study period. Changes in the relationship between PSC and TCHLa have wide implications in ecology and marine biogeochemistry, and provide key information for the development and use of empirical ocean-colour algorithms. Results illustrate the importance of maintaining a time-series of in-situ observations in remote regions of the ocean, such as that acquired in the AMT programme

Detection of linear trends in multi-sensor time series in the presence of autocorrelated noise: Application to the chlorophyll-a SeaWiFS and MERIS datasets and extrapolation to the incoming Sentinel 3-OLCI mission

The detection of long-term trends in geophysical time series is a key issue in climate change studies. This detection is affected by many factors: the size of the trend to be detected, the length of the available data sets, and the noise properties. Although the noise autocorrelation observed in geophysical time series does not bias the trend estimate, it affects the estimation of its uncertainty and consequently the ability to detect, or not, a significant trend. Ignoring the noise autocorrelation level typically leads to an overdetection of significant trends. Due to satellite lifetime, usually between 5 and 10 years, sea surface time series do not cover the same period and are acquired by different sensors with different characteristics. These differences lead to unknown level shifts (biases) between the datasets, which affect the trend detection. In this work, we develop a generic framework to detect and evaluate linear trends and level shifts in multisensor time series of satellite chlorophyll-a concentrations, as provided by the Medium Resolution Imaging Spectrometer instrument (MERIS) and sea-viewing wide field-of-view sensor (SeaWiFS) ocean-color missions. We also discuss the optimization of the observation networks, in terms of needed time overlap between successive time series to reduce the uncertainty on the detection of long-term trends. For the incoming Sentinel 3-Ocean and Land Color Instrument (3-OLCI)mission that should be launched at the end of 2014, we propose a global map of the number of months of observations to enhance the trend detection performed with the joint SeaWiFS-MERIS analysis