Session: Ocean I

The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) delivers operational weather and climate-related satellite data, images and products throughout all day and year. EUMETSAT also has commitments to operational oceanography and atmospheric composition monitoring. Activities over the next twenty years include the continuation of the Mandatory Programmes (MSG, EPS) and future (MTG, EPS-SG), and participation in the European Commission’s Copernicus programme. All include ocean observations of Sea Surface Temperature.

An overview of the oceanography activities at EUMETSAT relating to Sea Surface Temperature will be described. This includes information on activities at EUMETSAT central facilities; the EUMETSAT Ocean and Sea-Ice Satellite Application Facility (OSI-SAF); and those in preparation for the Sea and Land Surface Temperature radiometer (SLSTR) planned to be on-board the Copernicus Sentinel-3 satellite.

The presentation will include further information on the SLSTR SST product, which has been developed together with ESA and industry. EUMETSAT will be the Sentinel-3 marine centre and are responsible for the production and distribution of the level-2 marine products. Details of the scientific characteristics of the product, and references to the SST algorithm and operational and prototype processor development will be given. Information will be given on the both the current status of the SST product and the future evolutions that are envisaged. Details on how to find further information will be presented, and opportunities described on how to participate in the Sentinel-3 Validation team for Temperature.

One of the goals of climate research is to create uninterrupted, climate-quality time series of Essential Climate Variables as defined by the Global Climate Observing System (GCOS). Of these, ocean colour is the only marine variable that is capable of probing the marine ecosystem. Ocean colour is an essential tool to study at the global scale the distribution of chlorophyll (a measure of the abundance of phytoplankton, microscopic plants at the base of the pelagic food chain) and of marine primary production (fixation of carbon dioxide dissolved in the ocean as organic material). Ocean colour allows the study of the timings of major events in the annual cycle of phytoplankton (phenology) and of variability in phytoplankton community structure. It is key to understanding variability in the availability of food from the sea. Because phytoplankton absorb light, they also modulate the distribution of sun-induced heating within the ocean. Though the importance of ocean colour for climate research is clear, creating a high-quality, uninterrupted, consistent and multi-decadal time series of ocean-colour data is difficult. Since satellites have a finite life span, of the order of ten years, data from multiple sensors have to be woven together to create the time series. But differences in the spectral definition of the data from different sensors make it difficult to eliminate inter-sensor bias. Not all sensors currently available have the desirable band-set or the high-quality sensor calibration.

Against this background, the OLCI sensor on board Sentinel-3 marks a step-change: it is designed with high spectral resolution similar to MERIS, which would make it better suited to study the response of different components of the phytoplankton community to climate compared with other sensors with lower spectral resolution. It is planned as the first in a series of identical sensors to be launched in operational mode, which would facilitate correction of inter-sensor bias, if present. The plan to have more than one sensor in orbit at the same time in constellation mode would help reduce gaps in coverage, especially at the daily scale, which is a GCOS requirement, and would improve estimates of phenology. Validation and uncertainty characterization are key aspects of creating products for climate research, and hence it is laudable that validation is seen as an important component of Sentinel-3 Ground Segment. It is essential to launch Sentinel-3 without further delay: the ocean-colour time series for climate research, launched under the Climate Change Initiative of ESA, has been precarious ever since the demise of MERIS in 2012, since it now relies solely on the aged MODIS-A sensor. We need Sentinel-3 now.

The Gulf of Guinea is a dynamic ecosystem along the West African coasts. In order to better understand phytoplankton variability in the region, we quantified the effect of sea-surface temperature (SST), fronts, eddy kinetic energy (EKE) and winds on the spatial distribution of the chlorophyll-a concentration (Chla) using satellite data and a statistical Boosted Regression Tree (BRT) model. The data from the ESA Ocean Colour Climate Change Initiative (OC_CCI), resulting from the merging of ESA’s MERIS, and NASA’s SeaWiFS and MODIS data, were used for analysis. The OC_CCI data are shown to provide a much improved coverage with respect to standard single-mission products in this region affected by clouds and aerosols. Because the Gulf of Guinea has a heterogeneous nature, it was partitioned into five subsystems based on both Chla and physical variables.  The distance from the coast to the Chla concentration 1 mg/m³ isoline (DChla) was used as response variable. The explanatory variables are free from the effects of clouds, since we used a merged microwave-infrared SST dataset, EKE from altimetry and ocean winds from scatterometer. Based on 11 years of satellite data (2002-2012), the modeled results showed that DChla is strongly influenced by physical variables for each subsystem (with models accounting for 63-90% of the mean total deviance), mainly SST and EKE, albeit with substantial seasonal variations and, to a lesser extent, interannual variations. DChla extends further offshore during upwelling months, cold SST, strong EKE and fronts and moderate local winds. For specific subsystems, other factors were also investigated such as the influence of remote forcing generated by zonal wind stress along the equator on the upwelling off Ivory Coast and the effect of river flow off Nigeria.

Posidonia oceanica (L.) Delile, 1813 is a seagrass species endemic to the Mediterranean sea, which is considered as one of the key habitats of the coastal areas. This species forms large meadows sensitive to several anthropogenic pressures, that can be regarded as indicators of environment quality in coastal environments and its distributional patterns should be take into account when evaluating the Environmental Status following the Ecosystem approach promoted by the Mediterranean Action Plan of UNEP and the EU Marine Strategy Framework Directive (2008/56/EC). The aim of this study was to develop a Species Distribution Model for P. oceanica, to be applied to the whole Mediterranean North African coast, in order to obtain an estimation of the potential distribution of this species in the region to be considered as an indicator for the assessment of good Environmental Status. As the study area is a data-poor zone with regard to seagrass distribution (i.e. only for some areas detailed distribution maps are available), the Species Distribution Model (SDM) was calibrated using high resolution data from 5 Mediterranean sites, located in Italy and Spain and validated using available data from the North African coast. Usually, when developing SDMs species occupancy data is available at coarser resolution than the information of environmental variables, and thus has to be downscaled at the appropriate grain to be coupled to the environmental conditions. Tackling the case of P. oceanica we had to face the opposite problem: the quality (in terms of resolution) of the information on seagrass distribution is generally very high compared to the environmental data available over large scale in marine domains (e.g. global bathymetry data). The high resolution application and the model transfer (from calibration areas to North African coast) was possible taking advantage of Ocean Color products: the probability of presence of the species in a given area was modelled using a binomial generalized linear model as a function of the bathymetry and some water characteristics mainly obtained from satellite data. Full resolution (c.a. 300m) Medium Resolution Imaging Spectrometer (MERIS) sensor imagery have been processed in order to extract a set of environmental variables to be coupled to seagrass distribution in the areas used to calibrate the model and for the whole North Africa coast (i.e. model application area). For the period 2003-2011 we processed data of: 1) the diffuse attenuation coefficient 2) coloured dissolved organic matter 3) Particle backscatter at 443nm; 4) Euphotic depth, estimated considering the coefficient of extinction of light; 5) Euphotic depth/ depth ratio, combining the estimation of euphotic depth with the bathymetry. Other variables have been resampled at MERIS full resolution, like data obtained from Moderate Resolution Imaging Spectroradiometer (MODIS; Sea Surface Temperature and Photosynthetically Available Radiation) or by model simulation (e.g. water salinity). The fitted model suggests that water transparency plays a major role, but also other variables, such as salinity and sea surface temperature, are important at larger spatial scales in explaining meadows distribution. The availability of high resolution time-series of input data allowed us to apply the validated model to the whole NA coast. Using model predictions to identify areas with suitable conditions for P. oceanica, it was possible to develop a robust indicator of potential habitat use and to define baseline reference conditions, necessary for the assessment of Good Environmental Status in Mediterranean coastal waters. This work shows how the Ocean and Land Colour Instrument (OLCI) within the Sentinel-3 mission can be exploited - thanks to the way opened by MERIS - to carry out the operational monitoring needed for the implementation of the UNEP MAP and EU MSFD Ecosystem Approach to the integrated management of land, water and living resources.

EUMETSAT is a global operational satellite agency at the heart of Europe and the operator of the Sentinel-3 satellite and its Marine Payload Data Ground Segment. Sentinel-3 marine data encompass ocean colour products used by the Copernicus Marine Environment Monitoring Service and the users worldwide. For EUMETSAT, ocean colour parameters are new and necessitate new outlook to meet user needs. Fisheries, aquaculture, health, shipping, water supply and tourism are just a few industries increasingly relying on ocean colour observations to monitor marine biogeochemistry, marine resources, eutrophication, sedimentation, harmful algal blooms, and water quality. Ocean colour is also an essential climate variable. Timescales for most of these applications are much longer than the standard near‐real time (NRT) operational paradigm and even the NRT applications need accurate and stable long‐term time series to extract anomalies that typically are at the detection limit of the space technology as well as natural marine variability. Copernicus Marine Services, nations obliged by EC’s Good Environmental Status directives, and users worldwide critically rely on the quality of operational ocean colour data. There is also an increasing need to resolve marine biogeochemistry at ever higher spatial and temporal scales, thus consistent multi-mission time series and diurnal observations from geostationary sensors are in focus. This presentation will concentrate on addressing operational ocean colour needs for the future.