Ocean

We studied the changes of total suspended matter (TSM) distribution in Estonian coastal sea with special focus on Paldiski harbor at the Pakri Bay. Pakri Bay is environmentally sensitive area:  most of the bay is covered by Natura 2000 Special Protection Area. The purpose of current study was to examine the suitability of remote sensing data to detect the turbidity differences caused by dredged sediments and to evaluate the impact of monthly mean dredging amount to the surface TSM concentration retrieved from satellite images.

The MERIS (Medium Resolution Imaging Spectrometer) Full Swath Geo-located (FSG) products with 300m resolution from years 2006-2010 were used. Images were processed using Case II Regional (C2R) and Free University of Berlin (FUB) processors available in BEAM software. Validation with in situ measurements showed that both processors represent the changes in TSM concentration adequately. C2R processors showed better statistics (R2= 0.61, root mean square error = 0.82 mg l^–1, SD = 0.77 mg l^–1, mean bias = –0.28 mg l^–1) compared to the FUB processor.

For analysis of environmental impact we calculated the differences between monthly mean maps from dredging period (2008) versus non dredging period (monthly mean 2006-2010). A threshold TSM concentration value of >2.26 mg l^–1 difference from background TSM was defined as a criterion for dredging impact detection for Pakri Bay. The area of dredging-induced turbidity was between 0.56 and 1.25 km² and did not reach the environmentally sensitive NATURA 2000 region adjoining Paldiski South Harbour.

The Baltic Sea is an optically complex water body where a number of MERIS products did not perform with the accuracy and stability desired. There is a strong need for in situ data to improve the performance of atmospheric correction algorithms as well as water quality products when OLCI data becomes available. In the BONUS FerryScope project, two ferries hosting a traditional ferrybox (Chl-a fluorescence, phycocyanin fluorescence, temperature, turbidity, salinity) were equipped with Rflex autonomous hyperspectral reflectance measurement systems. This allows collecting water quality and reflectance data simultaneously and to produce a large number of matchups required for cal/val of satellite products. The data are made freely accessible in near real time. SIOPs of Baltic Sea waters have been studied in various projects. Based on these data we have created modelled spectral libraries (look-up tables, LUT) for the open Baltic Sea waters and more extreme near-coastal waters. These spectral libraries can be used directly in the interpretation of satellite data using procedures like SIOCS, but the modelled LUT can also be used to test empirical remote sensing algorithms. The in situ data infrastructure for the open Baltic Sea will be accompanied by a bio-optical profiling buoy in Estonian coastal waters. The buoy will have sophisticated optical instrumentation on board (e.g. backscattering, absorption, and attenuation meters) that will provide IOP data to complement reflectance. Thus, an unsurpassed volume of in situ and modelled optical data will be available to tackle algorithm development and product validation in the optically challenging Baltic Sea.

Sentinel-3 will provide two key features to the improvement of sea level variability studies:

1) high density of repeated tracks

2) Delay/Doppler processing

This study investigates the benefits from these two features considering previous missions, i.e. Envisat for 1) and Cryosat-2 for 2).

The high density of repeated tracks increases the detection of spatial variation in the sea level variability at a sub-regional scale. This is evident in the North-Sea/Baltic Sea transition zone, where the ALES coastal reprocessing of Envisat data highlighted significant variations of the annual signal of the sea level in a 50-100 Km scale.

The Delay/Doppler processing was already performed in the frame of CS-2. The analysis of the sea level estimations in the Indonesian Seas demonstrates that CS-2 is able to decrease by roughly 1 cm the high-rate noise of sea level estimation within 50 km of the coast, when compared to the ALES-reprocessed Envisat dataset. 

The increase in the standard deviation of the monthly sea level from CS-2 compared to Envisat (phase B) might be related to the peculiar ground-track followed by CS-2, which repeat every 369 days and do not follow the ground-tracks of previous altimetry missions. If this is proved, it will demonstrate the strong need for an accurate mean sea level, achievable by means of repeated tracks in Sentinel-3.

Aquaculture is one of the world's fastest growing food sectors with increasing economic importance. Like many other sectors, marine farming uses natural resources and may affect the environment if not properly managed and monitored.  However, for healthy, high-quality and environmentally-sustainable farming of marine seafood, clean waters are crucial. Remote sensing offers the means to monitor water quality in near-real time and in a continuous manner which could help aquaculture enterprises in their daily management. Moreover, historical water quality information may provide important information for site selection. The needs of seafood producers in terms of water quality parameters have been carefully investigated within the EU-funded FP7 project AQUA-USERS, which has the goal to provide the aquaculture industry with timely information based on satellite data and innovative optical in-situ measurements; currently a range of products (e.g., chlorophyll, Kd_490, suspended solids) are evaluated for different marine regions in Europe. In this study we present the results derived for the Danish case 2 waters of the Baltic Sea, targeting the Danish aquaculture industry.

We tested three neural network-based processors: i) FUB/WeW version 2.2 designed for European coastal waters, ii) MERIS Case 2 Regional (C2R) version 1.6.2 for case 2 waters and iii) CoastColour version 2 developed for highly turbid waters. With these processors we retrieved chlorophyll a (Chl-a), the diffuse attenuation coefficient (Kd_490) and total suspended matter (TSM) from Envisat-MERIS data for 2007, 2009 and 2011. The derived indicators were then compared with in situ data from the Danish national monitoring program (OverfladevandsDAtabasen ODA) collected over the same period.

Due to the complexity of the Baltic Sea, standard algorithms often do not perform very well. Therefore we also evaluated if a calibration would better represent the special regional conditions and could therefore improve the results.

In this work we will present the results of the comparative analysis and provide an outlook summarising expected benefits for the European aquaculture industries with bio-optical information from Sentinel-3.

The Arctic Ocean is a challenging region for tidal modeling, because of its complex and not well-documented bathymetry, together combined with the intermittent presence of sea ice and the fact that the in situ tidal observations are rather scarce at such high latitudes. As a consequence, the accuracy of the global tidal models decreases by several centimeters in the Polar Regions. In particular, it has a large impact on the quality of the satellite altimeter sea surface heights in these regions (ERS1/2, Envisat, CryoSat-2, SARAL/AltiKa and the future Sentinel-3 mission).

Better knowledge of the tides would improve the quality of the high latitudes altimeter sea surface heights and of all derived products, such as the altimetry-derived geostrophic currents, the mean sea surface and the mean dynamic topography. In addition, accurate tidal models are highly strategic information for ever-growing maritime and industrial activities in this region.

NOVELTIS and DTU Space are currently working on the development of a regional, high-resolution tidal atlas in the Arctic Ocean. In particular, this atlas will benefit from the assimilation of the most complete satellite altimetry dataset ever used in this region, including Envisat and SARAL/AltiKa data up to 82°N and the CryoSat-2 reprocessed data between 82°N and 88°N. The combination of all these satellites will give the best possible coverage of altimetry-derived tidal constituents. The available tide gauge data will also be used either for assimilation or validation.

This paper presents the deficiencies and needs of the global tidal models in the Arctic Ocean as identified using the CryoSat altimetry data, and the on-going work to develop an improved regional tidal atlas in this region.

Sea level is a very sensitive index of climate change and variability. Sea level integrates the ocean warming, mountain glaciers and ice sheet melting. Understanding the sea level variability and changes implies an accurate monitoring of the sea level variable at climate scales, in addition to understanding the ocean variability and the exchanges between ocean, land, cryosphere, and atmosphere. That is why Sea Level is one of the Essential Climate Variables (ECV) selected in the frame of the ESA Climate Change Initiative (CCI) program. It aims at providing long-term monitoring of the sea level ECV with regular updates, as required for climate studies. After a first phase (2011-2013), the program has started in 2014 a second phase of 3 years. The objectives of this second phase are to involve the climate research community, to refine their needs and collect their feedbacks on product quality, to develop, test and select the best algorithms and standards to generate an updated climate time series and to produce and validate the Sea Level ECV product. This will better answer the climate user needs by improving the quality of the Sea Level products and maintain a sustain service for an up-to-date production. To this extent, the ECV time series has been extended and it now covers the period 1993-2013, with the 2014 additional year available by the end of 2015.

We will firstly present the main achievements of the ESA CCI Sea Level Project. On the one hand, the major steps required to produce the 21 years climate time series are briefly described: collect and refine the user requirements, development of adapted algorithms for climate applications and specification of the production system. On the other hand, the product characteristics are described as well as the results from product validation, performed by several groups of the ocean and climate modeling community. At last, the work plan and key challenges of the second phase of the project are described, including the development of new algorithms that will be used for the 2016 reprocessing of the two decades of altimeter measurements.

With thesatellite altimetrymissions, the global mean sea level (GMSL) has been calculated on a continual basis since January 1993. 'Verification' phases, during which the satellites follow each other in close succession (TOPEX/Poseidon--Jason-1, thenJason-1--Jason-2), help to link up these different missions by precisely determining any bias between them. The global mean sea level (MSL) deduced from these 3 altimetric missions provides a global rate of 3.2 mm/yr from 1993 to 2013 applying the post glacial rebound (see the MSL page of the AVISO website http://www.aviso.altimetry.fr/en).

Within the ESA Climate Change Initiative program, the users requirements have been collected and for the users of the Sea Level ECV, it is crucial to know as much as possible the errors impacting the MSL calculation in order to analyze the MSL variations and in fine to interpret correctly the geophysical mechanisms underlying these variations. The characterization of these errors was performed over the whole altimetric period separating several time scales as the long-term evolution (mean sea level trend), but also the inter-annual and periodic signals.

However, it will also be very useful to provide the confidence envelop (or error envelop) of the global MSL time series in order to know the exact error level at each time step.  In this paper, we propose to describe in details the approach developed to compute this confidence envelop. We will also present the results obtained and how to interpret them. This work will be of great value in order to prepare the use of the future Sentinel-3 altimeter measurements.

Since the first altimeter missions and the improvements performed in the accuracy of sea surface height measurements from 1992 onwards, the importance of global quality assessment of altimeter data has been increasing. Global Cal/Val studies are usually performed by the analysis of internal consistency and cross-comparison between all missions. In this study, the steric and mass contributions to the sea level provided by Argo profiling floats and the Gravity Recovery And Climate Experiment (GRACE) mission respectively are used as independent sources of comparison to analyze the altimetry errors.

Argo profiling floats are spread out over almost the global open ocean since 2004. However, they measure temperature and salinity vertical profiles, providing only the steric contribution to the total sea level content measured by altimeters. The missing mass contribution is derived from the GRACE data set from 2003 onwards.

The comparison is performed with the first objective of detecting global and regional altimeter mean sea level drifts. A second goal is to assess the impact of new altimeter standards (orbit, geophysical corrections, ground processing) and new versions of altimeter merged products such as the 2014 AVISO reprocessing or the Sea Level CCI data set. We also focus our work on sensitivity analyses of the method of comparison to various parameters. In particular, we determine to which extent the altimeter quality assessment is affected by a different pre-processing of altimeter data, a sub sampling of the Argo network and a change of the reference depth used to compute Argo dynamic heights. This approach will be adapted to assess the performances of Sentinel-3 altimeter mission.

Until now, the Global MSL indicator has been computed from the TOPEX/Jason “reference missions” only. They are all on the same ground-track (TOPEX ground track with a 9.91-day cycle). The first advantage of these continuous records is that the oceanic variability is sampled on the exact same way for the 3 missions. The second advantage are the “calibration phases” between TOPEX and Jason-1 (9 months in 2002), and between Jason-1 and Jason-2 (9 months in 2008) which are necessary for an accurate computation of the relative sea-level bias (Leuliette, et al., 2004).
However, the Sentinel-3 mission is expected to be launched in 2015. One of the main objectives is to measure sea surface topography for environmental and climate monitoring. Therefore, it could be possible to change the orbit of reference in the future to compute the MSL evolution: Sentinel-3 could replace Jason-2 or Jason-3 missions.
In this study, the impact of this change on the relative bias uncertainty and its consequences on the Global and regional MSL trend uncertainties have been estimated. In a second time, the impact of oceanic variability sampling between the Sentinel-3 and the historical TOPEX ground tracks has been analyzed. Both parts lead to the conclusion that it is essential -as long as possible- to use altimeters on TOPEX historical ground track for the computation of a long and accurate Global and regional Mean Sea Level record.

Many spaceborne sensors are deployed to image the ocean in the visible portion of the spectrum. The colour of the sea, or more presisely the spectral water-leaving radiance, gives us information about the concentration of water constituents, e.g., chlorophyll, coloured dissolved organic matter, or suspended mineral matter. The bidirectional nature of the upwelling radiance just beneath the water surface and the interaction of this radiance with the air-sea interface depend on the viewing- and Sun-geometry and surface waves. If we consider wave elevation and wave shadowing effects, perceptible deviations of the transmittance and reflectance of the air-water interface occur at low Sun (zenith angle of more than 60°) in comparisson with wind-depending wave slope statistics. The inclusion of appropriate wind and wave data, i.e., wave heights and periods, can help to reduce uncertainties related to the Fresnel-reflecting ocean surface – in particular for large solar zenith angles. This especially regards remote sensing of ocean colour at high latitudes and atmospheric correction. 

 A reliable MSS that includes high-latitude regions within the 82 degree parallel is required for the Sentinel-3 data processing. In this presentation we present the new DTU15MSS which is an update of the DTU13MSS with more years of Cryosat-2

 Cryosat-2 offers a unique dataset in the Arctic Ocean for testing SAR altimetry with nearly five years of high-resolution SAR altimetry. In the Arctic Ocean older conventional altimetry satellites (ERS-1/ERS-2/Envisat) have only been able to provide sparse data for the past 20 years.

Here we present the development of the DTU13MSS in the Arctic being the latest release of the global high resolution mean sea surface from DTU Space based on 4 years/repeat of Cryostat-2.

 The analysis shows that Laser Altimetry from the ICESat satellite being the basis of DTU10 and DTU13MSS between 82 and 86N is now obsolete for mean sea surface determination.

 The study also highlight the problems of integrating altimetry from various modes (LRM, SAR and SAR-in altimetry as well as the problems relating to the fact that the averaging period of Cryosat-2 is adjacent to the 20 years (1993-2012) period used to develop DTU13MSS.

Evaluation of the new MSS is performed and comparison with existing MSS models is performed to evaluate the impact of these updates into MSS computation 

Cryosat-2 offers the first ever possibility to perform coastal altimetric studies using SAR-Interferometry as well as SAR altimetry. With this technological leap forward Cryosat-2 is now able to observe sea level in very small water bodies and also to provide coastal sea level very close to the shore.

 We perform an investigation into the retrieval of sea surface height and sea state around Denmark comparing various physical retrackers for the 2010-2014 period. These regions have been chosen as the coastal regions around Denmark falls within the SAR mask and the coastal regions of Greenland falls in under the SAR-in mask employed on Cryosat-2. The coastal region around Denmark is a test region of the EU sponsored project LOTUS in which the impact of the increased along-track resolution of the SAR is investigated.

With the increased spatial resolution of Cryosat-2 SAR we provide valuable sea level observations within the Straits around Denmark which are crucial to constrain the waterflow in and out of the Baltic Sea. 

Autonomous systems like BOUSSOLE, MOBY, Aeronet-OC and Smartbuoys have been used for validation and calibration of moderate resolution ocean colour imagery, as they typically provide a matchup per cloud-free scene, adding up to hundreds of matchups over a satellite’s lifetime.
Here we present the use of high spatial resolution data from Landsat-8 to assess spatial variability within one moderate resolution pixel (e.g. 300 m for Sentinel-3/OLCI) at a number of validation sites. The Landsat imagery allows the description of moderate resolution sub-pixel variability at validation sites, both in terms of natural variability and in terms of the impacts of the measuring structure itself on the TOA radiance observed by the satellite. As the structures are reflective in the NIR and SWIR, the atmospheric correction, which typically uses bands at these wavelengths for aerosol correction, may be contaminated. Furthermore, impacts of structures on hydrodynamics and hence suspended sediment concentration and marine reflectance, have been observed in shallow and tidally influenced regions.
Natural variability in suspended sediment concentrations in coastal areas can be enormous, and the mean average value observed in a moderate resolution pixel does not necessarily correspond well to the in situ measurement: in situ turbidimeters typically measure a few cm³ of water, and above-water radiometers integrate over several square meters, while a 300 m satellite pixel averages the signal from 90.000 m². Using high resolution imagery, areas with significant spatial variability within the moderate resolution pixel can be delineated. This opens up possibilities for attaching an uncertainty to the in situ-satellite matchup based on location alone.

The European Space Agency project GlobCurrent (http://www.globcurrent.org) is investigating the potential of satellite data to provide operational surface current estimates. One part of this project is to investigate the use of ocean colour images in the derivation of these estimates. Attempts to automatically estimate surface current velocities from satellite optical image data have often struggled with the data occlusion due to cloud cover, the complex evolution of features and the degradation of their surface signature through atmospheric effects. Simple image matching techniques such as the Maximum Cross Correlation (MCC) tend to fail due to these effects. With increasingly more rapid repeat times, new satellite constellations (such as Sentinel-3A and 3B)and higher resolution data becoming available, MCC may emerge as a viable method for ocean current estimation from ocean colour features. Here we present the results of applying the MCC technique to data from the Geostationary Ocean Color Instrument (GOCI), aboard the Korean Communication, Ocean, and Meteorological Satellite. Using the 2012 data archive we examine the robustness of i) the approach to time intervals ranging from 1 to 7 hours, and ii) using different satellite products such as water-leaving radiance or derived parameters such as chlorophyll concentration. These estimates of surface currents are evaluated using in situ High Frequency (HF) radar systems located in the Tsushima Strait between Korea and Japan.

Sea Surface Temperature (SST) is an Essential Climate Variable (ECV) for which there are observations since 1850. Because of its importance for climate, weather forecasting and oceanography SST observations from space have been made by dedicated instruments, for example ATSR-1 on board ERS-1 from August 1991 and its successor instruments ATSR-2 and AATSR, on board ERS-2 and ENVISAT respectively. All three ATSRs have provided 20 years of high quality global SST observations. Indeed, due to their well calibrated blackbodies and dual view capability, ATSRs produce more accurate SST measurements than any other satellite instrument or in general in situ instruments such as drifting buoys, although spatially averaged. However the need for a dual view, which permits the minimisation of atmospheric effects, is accompanied by the necessity of a narrow swath width (at least in comparison to other satellite cross-track scanning radiometers). The CCI SST project is an effort to produce a complete and homogeneous dataset of SST designed specifically with the climate quality criteria in mind (i.e. high accuracy, precision and stability). Although, CCI contains data from both ATSRs and AVHRRs, in order to overcome the low spatial coverage of the former, here only CCI observations (version 1.1) from ATSRs are considered in order to facilitate the comparison with the precursor ARC SST dataset also created using the ATSRs. However, the comparison between CCI and ARC is not straightforward as there are two main differences. Firstly, the method for the skin SST retrieval differs, with ARC using retrieval coefficients calculated from radiative transfer simulations, while CCI uses optimal estimation retrieval for ATSR-2 and AATSR (but retrieval coefficients for ATSR-1, the same as ARC). Secondly, the ARC dataset is provided at a spatial resolution of 0.1o, while CCI has a finer resolution of 0.05o. Results show that the current version of CCI does not yet match the quality of ARC SST retrievals when comparing with drifting buoys. In comparison to ARC, CCI daytime retrievals have a larger bias in the tropics, while for night-time retrievals the CCI bias is higher at mid-latitudes. Similarly, the standard deviation of CCI against buoys is higher than the respective ARC values both for daytime and night-time retrievals by about 0.1 K. This is consistent with the results from the three way error analysis using collocated SST observations from drifting buoys, ATSRs and TMI/AMSR-E retrievals. Finally, the uncertainties provided in the ARC dataset are in general more consistent than the uncertainties provided with the CCI data.

The Southern Ocean is a remote but important component of the Earth system. As a result of its unique geography, the region has a profound influence on global ocean circulation and climate. The Southern Ocean provides the principal connections between the Earth’s ocean basins and controls the connection between the deep and upper layers of the global overturning circulation, thereby regulating the storage and transport of heat, carbon, and other properties that influence climate and global biogeochemical cycles. Additionally, the Southern Ocean contributes more to the ocean storage of the excess heat and carbon added to the Earth-atmosphere system by human activities than any other latitudinal band. There is less known about the radiative and physical properties of the Southern Ocean than the Arctic Ocean due to the difficulty of traveling to this region for frequent data collection and less availability of remotely sensed data. The latter is especially needed to inform an effective response to the challenges of climate change, sea-level rise, ocean acidification and the sustainable use of marine resources.

To achieve this, enhanced understanding of the Southern Ocean community’s data use and desires are essential. The Southern Ocean Satellite Requirements Report summarizes survey results on satellite data requirements and needs for monitoring changes in the biological, geophysical, and biogeochemical regimes in the Southern Ocean (across all temporal/spatial scales). This survey was initiated by the Southern Ocean Observing System (SOOS), the Climate and Cryosphere Project (CliC), and World Meteorological Organization’s Polar Space Task Group (WMO PSTG) to collect information on current satellite uses from the scientific and operational communities who depend on reliable monitoring services. The survey also addressed data needs for specific missing ocean parameters and provided user recommendations on where the focus should be directed to resolve gaps. The key motivation of the survey and report was to provide the satellite data providers with a strong, consolidated "user voice" on Southern Ocean satellite data requirements for use when planning future satellite missions. This is the first comprehensive summary of Southern Ocean space-based monitoring needs created to ensure sustained and enhanced Southern Ocean data coverage. The unification of scientific, commercial, societal and operational motivations is required because improvements in satellite data for monitoring will be crucial in providing the required interannual to decadal time series. The outcome of this report will be used as the first baseline document guide for the WMO PSTG, the Scientific Community for Antarctic Research (SCAR), and other relevant operational and scientific communities.

Using in situ and remote-sensing data, we have characterized the spatial, seasonal and inter-annual variations of Chl-a (a proxy indicator of phytoplankton biomass) in Rufiji Delta/Mafia Channel in Southern Tanzania and we have investigated the influence of environmental factors on the phytoplankton variations. In-situ measurements of Chl-a, Sea Surface Temperature (SST), salinity, pH and nutrients have been collected in December 2012 along 49 stations near the mouths of the delta. Remote-sensing observations of Chl-a and SST were obtained from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua and Advanced Very High Radiometer Resolution (AVHRR) sensors respectively for the period from January 2003 to December 2012. The standard global empirical algorithm MODIS OC3 was applied to retrieve Chl-a concentration. The correlation between MODIS OC3 and in-situ Chl-a concentrations was significant (R2=0.75, p<0.05), indicating good agreement between the two streams of observations. Analysis of the spatial distribution of satellite Chl-a revealed high concentrations of Chl-a off the Rufiji coast (>10mgm-3) and low concentration towards the central parts of the Mafia Channel (<1mgm-3). Seasonal cycles of Chl-a were characterized by minimum concentrations during dry season (lowest value of 0.6mgm-3 was observed in December 2006) and maximum concentration in wet season (highest value of 1.5mg m-3 was observed in May 2003). Annual mean Chl-a concentrations from satellite data for Rufiji Delta/Mafia Channel showed a decrease during the decade 2003- 2012 and a significant correlation was found between the seasonal variations of Chl-a and Rufiji river discharge.

The ESA S3-4Sci project POCO (Pools of Carbon in the Ocean) is designed to examine, evaluate, improve and implement algorithms for estimating pools of carbon in the ocean from satellite data, and to evaluate their readiness for use in climate-change studies. This project will run for 2 years and will compare methods used by ecosystem modellers to convert between carbon and chlorophyll, to assess whether any of these approaches can be adapted for application in remote sensing. We will compare satellite-based outputs with those derived from models, and interpret the differences according to the underlying assumptions in the models, and with respect to the environmental driving variables, such as temperature, light and nutrients. The analyses will serve to evaluate satellite outputs as well as to explore possibilities for improving them on the basis of insights garnered from the comparison. This study is also seen as a vehicle to engage the user community, especially the ecosystem-modelling community, in discussion about how OC-CCI products currently available and value-added products generated from this project can help address hitherto unresolved issues in marine ecosystem modelling.

With global population expansion, the demand for high-quality protein is rising dramatically, and fish farming is gaining importance to ensure food security. Aquaculture is the fastest growing food production sector worldwide. Environmental conditions determine the growth and health of the produced species, while the production often releases large amounts of nutrients to the surrounding environment.

To support the growth of efficient and sustainable aquaculture production, the FP7 project AQUA-USERS aims at providing the aquaculture industry with user-relevant and timely information based on the most up-to-date satellite data and innovative optical in-situ measurements. The key purpose is to develop a web portal and mobile application that bring together satellite information on water quality and temperature with in-situ observations as well as relevant weather prediction and met-ocean data. A decision support system underlying the applications will link this information to a set of user-determined management decisions.

AQUA-USERS is a highly user-driven project with a user board consisting of companies and organisations from 5 countries representing different European aquaculture production systems. Together with the user board, the project partners will demonstrate the applicability of the developed methods and tools in three case studies dealing with site characterisation and selection based on historic satellite data, operational management using in-situ measurements and operational management using near real-time satellite data in combination with in-situ measurements.

In the first year, the project concentrated on user requirements, method development and technical preparation and implementation. Particular focus was on developing new and improved methods for making EO data useful for the aquaculture industry. For the study areas, a full archive of MERIS full resolution data has been processed with regionally adapted and validated algorithms for water quality parameter retrieval. Together with an archive of sea surface temperature data based on a number of different sensors, these data will serve as a basis for site characterisation and selection.

Based on satellite and in-situ data, a method has been established to derive indicators for potential benefits and risks for aquaculture production based on biogeochemical variables. To improve the detection of harmful algal blooms with optical methods, two approaches have been pursued: training a detection algorithm with multi-spectral satellite images of known blooms of certain species and modelling of hyperspectral HAB data based on laboratory instruments. We intend to apply these methods in a near real-time case study on operational aquaculture management using OLCI in 2016. 

New Sentinel generation products will provide a chance to investigate spatial and temporal scales not considered before. This applies in particular to coastal areas where the variety of processes and scales require such a level of resolution and continuity. The combination of numerical models, satellite images and observational "in-situ" data offer the possibility to enhance predictions and investigate geophysical processes near the land sea border. Experiences in Catalan shelf (North East Spanish Mediterranean coast) have revealed the convenience of high resolution products in areas where there is a multiplicity of scales and sharp variations. The effects of wave-current interactions, wave response under highly variable winds, upwelled cold water due to cross-shelf winds or along-shelf sea-level gradients are examples where present remote sensing products are useful but still inaccurate. The coastal zone requirements and current limitations of satellite products will be discussed to illustrate the need to enhance predictions in coastal areas and investigate the coupled (meteo-ocean) physical processes there occurring.

The coming launch of Sentinel-3 requires a large effort of the world ocean-colour community to ensure a high quality of the radiative measurements and derived geophysical products collected by the Ocean Land Colour Imager sensor (OLCI). Here we propose a number of activities that are, or will be, taking place in the Arctic and Sub-Arctic marine environments of Canada to support the calibration and validation of OLCI products, as well as the development of new bio-optical algorithms. A Canadian consortium made of universities (Takuvik/Université  Laval-CNRS, Université de Québec à Rimouski) and a private company (Arctus) intends to develop an archive of in situ measurements of remote sensing reflectance and bio-optical parameters at different locations, including a tethered buoy in the Saint-Lawrence River with high frequency sampling and several cruises located in the Canadian Arctic (Baffin bay, Canadian Archipelago and Beaufort Sea) that will take place in the coming years. In addition, effect of sea-ice on the water-leaving signal will be studied using radiative transfer simulations and a correction scheme will be proposed. A new approach for data fusion between high- (e.g., landsat-8 and sentinel-2) and moderate- resolution (MODIS) will be presented to emphasize possible new applications of OLCI.

The Climate Change Initiative (CCI) is the response of the European Space Agency (ESA) to the need for climate-quality satellite data, with the goal of providing stable, long-term, satellite-based Essential Climate Variable data products. The ESA Ocean Colour CCI focuses on the production of water-leaving reflectance, chlorophyll concentration and inherent optical properties from ESA's MERIS (2002-2012) and NASA's SeaWiFS (1997 - 2010) and MODIS (2002-present) sensor archives. Water-leaving reflectances have been band-shifted and merged from the three sensors, from which chlorophyll concentration and inherent optical properties were subsequently calculated. The in situ database used for validation of the second version of CCI products is presented here. The in situ data were obtained from several sources, span the years 1997 to 2012, and have a global distribution. Observations of the following variables were compiled: remote sensing reflectance, concentration of chlorophyll-a, inherent optical properties and the diffuse attenuation coefficient. Data were obtained from the following sources: MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GEPCO. The data were acquired via the open internet services or from agreements with data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. Apart from data reductions during quality control and conversion to standard variables, minimum changes were made on the original data. Metadata of each in-situ measurement (original source, cruise or experiment, principal investigator) were propagated throughout the work and made available in the final table. The final result is a merged table tuned for validation of satellite-derived ocean colour products and available in a text-format. This was an attempt to gather, standardise and merge several sets of high-quality bio-optical in-situ data. Such an in situ database, if maintained and extended to Sentinel-3 years, would form a useful tool for validation of OLCI data.

ESA's sea level CCI project recognised the Arctic as one of its two main challenges during Phase 2. This is because the Arctic provides a complex spatially heterogeneous surface, with a mix of open ocean, ice floes, leads and polynyas which together produce complex waveforms not consistent with the simple Brown model used for ocean retracking. As sea-ice may provide a strong reflecting surface only tens of centimetres different from sea level, it is vital that techniques be improved to discern which measurements are truly from the ocean surface. Major work in this field was led by Seymour Laxon and colleagues at UCL/CPOM, who developed methods based on a binary classification of waveforms into ice floes and leads, with different retracking algorithms to derive geophysical information from each class. Within the context of the sea level CCI, PML and CLS have investigated further approaches to classification and evaluated the results by comparison with other remote-sensing datasets. Envisat altimeter data has provided the primary test dataset, as it covers the high Arctic latitudes whilst having simultaneous coverage by MERIS and AATSR. Through the VICTORIA project we acquired access to thermal and optical imagery which give high-resolution (~1km) views on the ice cover. Even high-resolution imagery is available from SAR data, although observations from the on-board instrument, ASAR, cannot be simultaneous with the solely nadir-viewing altimeter. Together these thermal optical and radar imagery allow us to evaluate the efficacy of any altimeter waveform classification scheme. Further techniques are being investigated that consider multiple waveforms at once to recognise the hyperbolic trajectories in waveform space of the signal emanating from strongly reflecting leads and to use only the observations from direct nadir. Finally these classification and retracking strategies will be brought together to generate monthly maps of Arctic sea level.

As part of the SEOM Sentinel 3 for Science Ocean Colour program, an innovative product based on a robust algorithm that has been used for several sensors during the past will be developed for the daily PAR estimation from ENVISAT/MERIS and S3/OLCI and compared to existing in situ data and to Level 3 daily, weekly and monthly equivalent products derived from SeaWiFS, MODIS Aqua and Terra and GOCI. Several original methods for correcting known issues like the diurnal variation of cloudiness will be implemented in a baseline version of the algorithm, and complemented with secondary, experimental quantities like the UV irradiance below or above the sea surface or the spectral PAR. A simple method will also be developed for assessing the daily PAR uncertainty on a pixel basis. A demonstration data set of one year from MERIS will be disseminated quite early in the project to the user community in order to get their feedback and to draw some recommendations during a workshop that will be organized in the second year of the project. The user’s community will be stimulated by an example of application of this new PAR product to the Primary Production estimation from MERIS and Sentinel 3.

With the new suite of sensors arriving with Sentinel, the challenge for scientists is to break out of the single sensor mentality and think synergistically. However, then the task is to source many different sets of data, correctly apply the latest state-of-the art algorithms, and to co-display these very different perspectives. To facilitate this, ESA has sponsored the project <> to create an "Earth Observation supersite" with a first demonstration over the Agulhas Current region. This two-year project, from Nov 2014 to Oct 2016, shall provide once completed a single point for accessing and displaying all the relevant satellite data for this area (including available Sentinels) using image tile pyramids to allow rapid display and zooming.

The Agulhas Current region has been chosen as the pilot area for the supersites concept, because it is an exciting and dynamically energetic area, with strong current, large thermal and ocean colour contrasts, and has been a useful test-bed for new innovative techniques such as sunglint records of sea surface roughness and SAR Doppler imaging of part of the surface velocity field.

The Ocean Virtual Laboratory is being constructed as an open source software platform including a web-based client (http://bit.ly/1zCkmkl) and a pre-processing and web server. These points make it ideal as a discovery tool for individual researchers in both developing and developed nations who lack the resources to hold large volumes of data or large processing capabilities themselves.

Processing plugins will be provided for various key tasks such as removing speckle from SAR images, locating thermal fronts and filling in gaps within data. An API will allow anyone with some Python scripting knowledge, to develop their own processing plugins. The features present in multiple images can be contrasted by overlaying with varying degrees of transparency

The SSALTO/DUACS system produces, as part of the CNES/SALP and MyOcean projects, high quality multimission altimetry Sea Level products for oceanographic applications, climate forecasting centers, geophysic and biology communities... These products consist in directly usable and easy to manipulate Level 3 (along-track cross-calibrated SLA) and Level 4 products (multiple sensors merged as maps or time series) and are available in global and  regional version (Mediterranean Sea, Arctic, European Shelves …).

With the integration of HY-2A data in 2014, the Near Real Time system now merges data from 4 satellites. In parallel of the constellation management, on April 2014, the entire catalogue was significantly upgraded with impacts on scientific content and format, improving the quality and accessibility of the products. Besides, a full reprocessing of the whole altimetry time series has been performed allowing us to make available a set of 21 years of homogeneous along–track and map products.

In 2015, we are now starting a new step. The launch of Sentinel-3 will not only contribute to the robustness of the operational Sea Level service but the processing of the sea level could also be improved to fully exploit the advanced technology of this new sensor. This paper will present the main perspectives for the SSALTO/DUACS Sea level products in the coming years.

 

 

 

Multisensor image fusion is the process of combining relevant information from two or more satellite images into a single image. In remote sensing applications, the increasing availability of space borne sensors gives a motivation for different image fusion algorithms. Several situations in image processing require high spatial and high spectral resolution in a single image. Most of the available equipment is not capable of providing such data convincingly. Image fusion techniques allow the integration of different information sources. The fused image can have complementary spatial and spectral resolution characteristics. However, the standard image fusion techniques can distort the spectral information of the multispectral data while merging.

Many methods exist to perform image fusion. The very basic one is the high pass filtering technique. Later techniques are based on Discrete Wavelet Transform, uniform rational filter bank, and Laplacian pyramid.

The data fusion will be applied to data from MSI/Sentinel2 and OLCI/Sentinel3. In the visible range MSI measures radiance with 10 m resolution at 490, 560 and 665 nm; with 20 m resolution at 705 nm; and with 60 m resolution at 443 nm. In the visible range OLCI measures with 300 m spatial resolution at 400, 412, 443, 490, 510, 560, 620, 665, 673, 681, 708 nm. The data from the visible from both sensors will be fused to get products with values of remote sensing reflectance wavelengths of OLCI and with spatial resolution of 20 m. In addition to the standard fusion methods the Neural Network approach will be developed, tested and applied.

The results of the fusion will be utilized in the multi-spectral MCC and feature tracking algorithms to identify weak ocean currents as well as for retrieval of water quality parameters including chlorophyll-a, suspended mineral matter and dissolved organic carbon in coastal Case-II waters.

Ocean colour sensors onboard satellites allow for global monitoring of chlorophyll-a (Chl a) concentrations in case 1 surface waters. Case 2 waters, for example Belgian Water, are more difficult to measure using optical remote sensing. The Marine Strategy Framework Directive (MSFD), which lays out parameters for monitoring the coastal and offshore waters in Europe uses chlorophyll-a (CHL) concentration, specifically the chlorophyll-a 90 percentile (CHL-P90) to determine the eutrophication status. Additionally, the Water Framework Directive (WFD) assesses the health of river basins in Europe and coastal waters up to the first nautical mile from the coast. The primary method of acquiring data is through in situ measurements. However, the in situ monitoring program that is in place are sparse and do not adequately cover the spatial and temporal dynamics in the region.

The problem of enhancing the temporal resolution and spatial resolution of data is interesting for the monitoring and management of Belgian waters, especially in the context of the MSFD and the WFD. In a region that is highly dynamic in both time and space, affected by tides and often hidden by cloud cover, a multi-sensor approach to chlorophyll-a measurement is needed.

In this paper, a multi-sensor approach to the remote sensing of Chlorophyll-a will be assessed for Belgian waters. The primary advantage of a multi-sensor approach is that there is more information for users of remote sensing data. This approach is also important for validation of remote sensing products of coarse resolution. Due to the high variability in time and space for this region, matchups between remotely sensed measurements and in situ measurements may be misleading. The error introduced by sampling at a coarse spatial resolution can be estimated by sampling at a higher resolution. We compare the abilities of current remote sensing sensors like MODIS to the Sentinel-2 and -3 satellite missions on given subsets of remotely sensed data. We use the statistical properties, such as mean, standard deviation and range, of the chlorophyll-a measurements for each of the sensors as criteria for this comparison. For each sensor, an error assessment of Chl-P90 is determined. In this way, the uncertainty can be estimated for each of the sensors as well as in situ measurements.

The OLCI sensor aboard Sentinel-3 is a sensor suited to remote sensing measurements in this highly dynamic region. Images from this sensor will be available daily. The sensor is designed for global biological and biogeochemical oceanography. Sentinel-2, although not designed for oceanographic purposes will be useful for measurements in Belgian Waters. Sentinel-2 has greater spatial resolution than Sentinel-3 but more coarse temporal resolution, however it is believed that meaningful chlorophyll measurements will be obtained from the Sentinel-2 MSI sensor. Synergy between Sentinel-3 and Sentinel-2 will enable a greater understanding of the submesoscale dynamics which will help strengthen monitoring and management programs.

References:

Gohin, F., Saulquin, B., Oger-Jeanneret, H., Lozac'h, L., Lampert, L., Lefebvre, A., ... & Bruchon, F. (2008). Towards a better assessment of the ecological status of coastal waters using satellite-derived chlorophyll-a concentrations. Remote Sensing of Environment, 112(8), 3329-3340.

Malenovský, Z., Rott, H., Cihlar, J., Schaepman, M. E., García-Santos, G., Fernandes, R., & Berger, M. (2012). Sentinels for science: Potential of Sentinel-1,-2, and-3 missions for scientific observations of ocean, cryosphere, and land. Remote Sensing of Environment, 120, 91-101.

Micronekton organisms (typical size of 2-20 cm, or even smaller organisms capable to swim) are both the prey of large ocean predators, and themselves also predators of eggs and larvae of many species from which most fishes. The micronekton biomass concentration is therefore a key explanatory variable that is usually missing in ecosystem models to understand individual behaviour and population dynamics of large oceanic predatorsthat are either targeted by fisheries (tuna, swordfish, marlin, etc.) or strictly controlled in by-catch (bluefin tuna, sharks), or fully protected (marine turtles, seabirds, marine mammals).

In that context, the OSMOSIS (Ocean ecoSystem Modelling based on Observations from Satellite and In-Situ data) project aims at demonstrating the feasability and prototyping an integrated system going from the synergetic use of many different variables (Sea level, Earth Marine geoid, Sea Surface Salinity, Sea Surface Temperature, Ocean color) measured from space to the modeling of the distribution of micronektonic organisms. In this paper, we present how data from CRYOSAT, GOCE, SMOS, ENVISAT, together with other non-ESA satellites and in-situ data, can be merged to provide the required key variables needed as input of the micronekton model: the 3D description of the ocean state (Temperature and currents), the primary production and the euphotic depth. Also, first micronekton density maps obtained in the Southern Indian and Pacific Ocean by forcing the model with the OSMOSIS input fields are presented and discussed.

For all nadir altimetry missions, the quality of the orbit ephemerides is crucial for the computation of the Sea Surface Height (SSH). Impacting mostly large scales, spatially and temporally, the errors attributed to the orbit are worth being quantified and analyzed precisely.

Conversely, to assess evolutions of the orbit computation, having a realistic knowledge of the impact on the SSH quality efficiently completes the intrinsic orbit based diagnosis. Indeed, it provides an external reference (the SSH) to benchmark different orbit solutions and to detect remaining weaknesses with a very fine precision.

In the past, those studies already showed their usefulness. For instance, they enabled to detect (and solve) imprecisions in the gravity field modeling in the orbit computation with an impact of 10to20% of the Mean Sea Level trend estimation depending on the missions.
Combining many calval tools and skills, these studies use mono-mission and multi-missions diagnosis as well as in situ database comparisons.

This work illustrates the mutual benefits of such activities between both orbit and altimetry communities and how Sentinel 3 could/should keep contributing to these studies.

The operational meteorological satellites of EUMETSAT have since long provided high quality remote sensing observations of the oceans, driven by the needs of meteorology. The Ocean and Sea Ice Satellite Application Facility consortium, is dedicated to deriving relevant satellite data products, on behalf of EUMETSAT. EUMETSAT has also entered international cooperative programmes to extend its marine products and services with e.g. the Jason and Sentinel-3 missions.

 

The marine products and services of EUMETSAT strive to provide common responses to the needs of meteorology and other applications such as operational oceanography, environmental monitoring and climate monitoring. The new Copernicus marine products constitute an important event in the continuous evolution and improvement of those services. Looking forward to future evolutions of its satellites, an overview of the marine products and services of EUMETSAT will be given, highlighting the complementarity of the marine products from Sentinel-3 and those from the other contributing missions.

The Sentinel-3 SRAL/MWR surface topography mission will serve primarily the marine operational users but will also allow the monitoring of sea ice and land ice, as well as inland water surfaces, using novel observation techniques.

A two-channels microwave radiometer (S3-MWR, 23.8 and 36.5 GHz) is combined to the altimeter in order to correct the altimeter range for the excess path delay resulting from the presence of water vapour in the troposphere. The radiometer will perform measurements of brightness temperatures in both bands interpolated at the location of the altimeter footprint. The wet tropospheric correction is retrieved from both brightness temperatures and altimeter backscattering coefficient to take into account the surface roughness using an empirical method based on neural networks. The same type of algorithm is used to retrieve the other microwave radiometer parameters (water vapor content, cloud liquid water content, the atmospheric attenuation of the altimeter backscattering coefficient in Ka band).

This presentation will focus on the specificities of S3-MWR, with respect to other radiometers, in terms of instrumental architecture, raw measurements processing and retrievals of geophysical parameters. Regarding these latter, the classical retrieval approach applied with success on Envisat and a new approach for the in-flight calibration inspired by the work performed on SARAL/AltiKa CNES/JPL microwave radiometer will be combined to insure the best performance. Finally, we will also present the first results of a one dimensional variational method for the retrieval of the wet tropospheric correction, a promising algorithm which could offers yet unreachable performances on heterogeneous surfaces such as coast areas, hydrological targets or land and sea ice surfaces.

The series of Sentinel satellites mark a major step forward in the collection of Earth Observation data with the commitment to a series of spacecraft and sensors to construct long time series of data suitable for both climate applications and widespread operational use. Amongst its many sensors, Sentinel-3 will carry a delay Doppler altimeter, providing global high-resolution data for the first time.

 

Cryosat-2 mission already embarks a delay Doppler altimeter with the primary objective of measuring accurate sea level over sea ice. The Cryosat-2 altimeter is operated almost continuously over ocean, mainly in Low Resolution Mode (like conventional pulse-limited altimetry sensors).  In order to support the Sentinel-3 mission preparation, SAR acquisitions have been regularly performed over large oceanic zones.

 

Boy et al (2012, 2013) developed dedicated SAR retracking processing for ocean and showed that the results obtained over a full year of data were very promising. On the one hand, this technique appears to be mature enough to replace LRM mode in order to retrieve mesoscale signal. On the other hand, very compelling results have been obtained in the shortest scales below 80 km where the SAR provides more accurate data.

 

The present work complements the results obtained in the frame of the ESA project Cryosat Plus For Ocean (CP4O). Under ESA and CNES coordination, these efforts allowed validating two different retracking algorithms over a test data set of two months, over limited areas (Equatorial Pacific and North Atlantic). The present study shows some results obtained on a longer time series with a two year CPP SAR data record. This data set represents a major achievement in the understanding of the SAR mode altimetry (Raynal et al in prep).

 

Data quality has been assessed through different metrics that are presented here. We analyse more deeply the main features to check the reliability and the improvements of the SAR processing (noise reduction, increased along track spatial resolution, check of the dependencies that may induce geographically correlated errors, continuity with LRM processing...).

 

All the lessons learned with the extensive use of Cryosat-2 data will benefit to the ocean validation activities conducted in the frame of the Mission Performance Centre (the altimetry component). This will specifically help us in fine tuning the Sentinel-3 ground processing algorithms dedicated to Delay Doppler processing and the SAMOSA retracking.

All these efforts will result in achieving a seamless transition between LRM and SAR altimetry techniques and fulfilling the operational needs for assimilating sea level in operational forecast models, especially for the Marine Copernicus Service.

On the other hand, the Sentinel-3 SAR mode observations of sea level shall provide for the first time at global scale a data record with an improved accuracy, paving the way for high resolution altimetry and for a better observation of small scale ocean dynamics.

Coastal areas and shelf seas provide goods and services to humankind, such as fisheries, aquaculture, tourism and climate regulation. Assimilation of ocean colour data into marine models can support the understanding and operational prediction of anthropic and climate impacts on these crucial ecosystems. Data assimilation is a technique that merges models and satellite data, potentially leading to improvements in the biogeochemical estimates obtained separately from simulations and observations from space.

The objective of this work is to assess the benefits of assimilating Ocean Colour provided by ESA’s Climate Change Initiative (ESA CCI-OC) into a marine ecosystem model of the northwest European shelf sea.  

The ecosystem model couples a physical (POLCOMS) and a biogeochemical model (ERSEM). The ocean colour data were assimilated by using the Ensemble Kalman filter (EnKF) algorithm. The assimilative simulation was run in a decadal reanalysis of the biogeochemistry in the years 1997-2009. Independent in situ monitoring data of chlorophyll, nutrients, dissolved oxygen, temperature and salinity were used to evaluate skill metrics of the assimilation performance, i.e. root mean square error, bias, Pearson correlation.

Assimilation of ocean colour improved markedly the model simulation and forecast of chlorophyll. The assimilative simulation had also some skill in reproducing the spatial-temporal patterns of other model variables not observed from space, e.g. oxygen, nitrate and silicate. However, nutrients remained overestimated in some areas of the shelf. The analysis of the simulated biogeochemical processes showed that the northwest European shelf is a net sink for atmospheric CO₂. This holds for the largest part of the region, and takes account of the inter-annual variability of the CO₂ fluxes, as well as of the errors associated to the model estimates.  Biological processes provided a major contribution to the carbon in-gassing into the shelf sea ecosystem.

Some features of the assimilated CCI-OC product were crucial for achieving the above results, i.e. the relatively high spatial coverage of the data and the pixel-by-pixel characterization of their errors.

Assimilation of satellite ocean colour data into marine ecosystem model can support the current scientific and policy efforts to enhance the understanding and operational capabilities for the sustainable management of marine ecosystems. This work contributes to ESA CCI-OC and EU FP7 Project “Operational Ecology”, which aimed to develop a (pre)operational forecasting system of marine ecosystem indicators, based on satellite data assimilation, for downstream applications in all the European regional seas. 

Primary production by phytoplankton is the most important process of our aquatic biosphere, since nearly all life in the ocean and in inland waters depends on phytoplankton. Thus, the temporal and spatial occurrence of phytoplankton is most critical for the food web in the aquatic environment. For environmental science primary production is a key process to be monitored. However, there is no method available to directly determine the requested quantity, i.e. the net or gross primary production per square meter water surface and day, rather it is necessary to determine a number of parameters and then compute PP. Some of these critical parameters, in particular their spatial and temporal distribution, can be determined by remote sensing. The S3-mission is of particular importance for this task. Within the frame of the project Scientific Monitoring (WIMO) we are going to utilize the following variables, which can be derived from OLCI data in our PP model: phytoplankton chlorophyll concentration, the spectral downwelling irradiance attenuation coefficient or the penetration depth of light (PAR).

The algorithms to determine these variables are based on the Coastcolour project of ESA, furthermore the water temperature will be derived from SLSTR.

To compute the vertical profile of PAR a spectral model is used, since in our coastal waters the wavelengths with maximum transmittance changes with the composition and concentration of water water constituents. The P versus I parameters, which describe the production as a function of light per unit of biomass and which cannot be measured by remote sensing, have been determined for the North Sea during ship cruises. Other variables, which are needed, are the water depth or the depth of the upper mixed layer and the cloud cover statistics.

A key question will be the uncertainty of the PP estimations. To address this issue we have analyzed the uncertainty range of each of the critical parameters and then determined the sensitivity of the overall model.

So far this scheme has been tested with MERIS data. These results will be shown. The extended potential of the S3 mission will be discussed.

The Laboratory for Earth Observations and Analyses at ENEA runs a measurement site dedicated to climate in the central Mediterranean, the Station for Climate Observations on the island of Lampedusa (35.5°N, 12.6°E; http://www.lampedusa.enea.it).  The Station is operational since 1997, and measurements, carried out also in collaboration with different international Institutes, are mainly dedicated to atmospheric parameters and contribute to several global networks (GAW/WMO; NOAA Cooperative air sampling network; AERONET; ICOS, etc.). 

The marine section of the observatory has been recently developed within the framework of the RITMARE Italian Project.  An elastic beacon type of buoy has been designed and built, and will be installed in Spring 2015 at a site about 2 miles West of Lampedusa (35.5°N, 12.47°E).  The primary scientific objectives for the instrumented buoy are: to investigate air sea interactions in the central Mediterranean; to study the surface energy budget; to characterize the oceanic optical properties, and to investigate links with the carbon cycle.  In the perspective of the Sentinel 3 mission, this site will be available as a cal/val facility for satellite observations of the sea environment.  Data collected by the instruments onboard the buoy will be also used to validate operational oceanographic model forecast.  A first set of sensors was acquired, and laboratory tests are ongoing.

The marine section will integrate the exisiting infrastructure for atmospheric measurements. Routine observations at the site include:  meteorological parameters; greenhouse gases (CO₂, CH₄, N₂O, SF₆, CFCs, HFCs, HCFCs); aerosol optical properties (optical depth at several wavelengths and derived quantities); aerosol vertical distribution; temperature and humidity vertical profiles; cloud cover and optical properties; column water vapour and liquid water path; spectral surface irradiances from the UV to the near IR; broadband IR irradiances; direct and diffuse radiation components in different bands; surface ozone; total column ozone; PM10 concentration and chemical composition at the daily scale; black carbon; atmospheric aerosol deposition, etc.

The Baltic Sea, known to be one of the biggest estuarine environments is also a major industrial area that is under high anthropogenic pressure. In this highly active sea area it is important to have a good understanding of the oceanographic characteristics (circulation, stratification, sea level etc.) for better management of pollution, fisheries, shipping etc. The general circulation pattern in this sea area is known to consist of small eddies and meso-scale features, the statistical average of which results in a cyclonic circulation scheme. So far our understanding of the hydrodynamics of the Baltic Sea have been greatly influenced by simulations of ocean models, that reproduces the major hydrodynamic features fairly well, however they still posses some inconsistencies especially with simulating the circulation and stratification structure. Model results have also shown that semi-persistent pattern at different temporal and spatial scales are known to play an important role in the surface circulation. As a result there still remain many gaps in our understanding of the variability and structure of the oceanographic characteristics of the surface layer. Thus the intention of this study is to utilise the past and present satellite data from various sources with model results and in-situ observations to compare, verify and thus better understand some of the surface hydrodynamics of the Baltic Sea.

The focus will be on the Gulf of Finland (one of the sub-basins of the Baltic Sea, located in the eastern section).  So far using simulated Eulerian velocity obtained from the Rossby Centre Ocean model (RCO) and in-situ measurements based on surface drifters the surface circulation pattern of the Gulf of Finland  have shown some interesting results that depended on the time-scale that data were investigated. For instance model simulations show for long time scales (5 years) an anti-cyclonic gyre existing in the central Gulf of Finland and on a short time scale (weekly) occurrences of across-gulf transport. Whilst both model and in-situ observation show evidences of seasonal trends. The idea is to now use the overlapping areas from the model simulations, observed data and satellites, to investigate the surface circulation and stratification at varying time scales to better understand some of the patterns that may exist.

The incorporation of satellite data plays a key role in complimenting the existing model and in-situ data. Whilst the satellite data may be limited in its spatial and temporal resolution, it is believed that using radar altimetry data from several missions such as the ENVISAT, ERS, Sentinels and other third party missions would lead to identifying some of the seasonal and long term patterns, with salinity data from the Soil Moisture and Ocean Salinity (SMOS) mission complimenting some of these results. 

To overcome the short-comings of current multi-spectral PFT products (supplying either knowledge on dominant groups or size fractions only, data products with strong linkage to a-priori-information) and PhytoDOAS data products (with only low temporal and spatial coverage),this ESA SEOM project's objective is a substantial improvement of retrieving phytoplankton groups with defined accuracy and good spatial and temporal coverage. This shall be done by developing a synergistic product which contains the Chl-a (biomass) of several PFT by using complementary information from multi- and hyper-spectral satellite ocean colour data. This algorithm can be later applied to produce a synergistic PFT product from TROPOMI (on Sentinel-5-Precursor, Sentinel-4, Sentinel-5) and OLCI (on Sentinel-3). 

To enlarge the coverage and to reduce the uncertainty of the PFTs and total Chl-a satellite products, as a ESA-ESRIN funded Sentinel for science synergy research and development (SY-4SCI Synergy R & D) study focusing on PFTs we will

 review available PFT algorithms based on hyper- and multi-spectral datasets;

develop an improved PFT algorithm by the synergistic use of low spatial resolution hyper-spectral data (i.e. SCIAMACHY) with high spatial multi-spectral data (i.e. MERIS). This can be later adapted to TROPOspheric Monitoring Instrument (TROPOMI, on Sentinel-5Precursor) and Ocean and Land Colour Instrument (OLCI, on Sentinel-3) measurements.

perform a sensitivity study, based on radiative transfer calculations, to determine the band-set needed by multi-spectral instruments (e.g. OLCI) to retrieve PFTs based on hyper-spectral data (now SCIAMACHY, future TROPOMI) PFT algorithms

provide a scientific roadmap for future Chl-a and PFT retrievals from ocean colour (multi- and / or hyper-spectral) data

The project started at the end of 2014 and we will show first results obtained within the study.

CoastColour algorithms and processing chain with MERIS and OLCI

The ESA DUE CoastColour Project has developed a new 3-step approach for regional processing of ocean colour data. The L1P step consists of radiometric and geometric system corrections, and top-of-atmosphere pixel classificaiton including cloud screening, sun glint risk masking or detection of floating vegetation. The second step includes the atmospheric  correction and is providing the L2R product, which comprises marine reflectances with error characterisation and normalistion. The third step is the in-water processing which produces IOPs, attenuation coefficient and water constituent concentrations. Because of the high optical variability of coastal waters, a new bio-optical model has been developed, and a combination of different in-water algorithms using an optical water type classification is performed.

The new 5-component bio-optical model decomposes the water absorption into absorption due to phytoplankton, and two exponentially decreasing absoption components with a steep and flat spectral exponent. LIkewise the scattering is modelled through an exponential, with two components of a spectral flat (white) scattering component and spectrally steep component. In the inversion process, the spectral slope of absorption and scattering is found by the neural net technique as a combination of these components.

Each of these steps will benefit from the additional bands on OLCI. The 5 component bio-optical model will already be used in the standard ESA processing of OLCI, and also part of the pixel classification methods will be part of the standard products. Other algorithm adaptation are in preparation.

On-demand processing service for tailored coastal processing

However, the advantage of the CoastColour approach is the highly configurable processing chain which allows (a certain) adaptation to the individual characteristics of the area of interest. This flexibility is made available to data users through the CoastColour on-demand processing service. The complete global MERIS Full and Reduced Resolution data archive is accessible, covering the time range from 17. May 2002 until 08. April 2012, which is almost 200TB of in-put data available online.

The main advantages and features of the Calvalus On-Demand Processing System

No need to download large pre-defined product sets but tailored to a region of interest individually

The system enables generation of specific product level data sets (L1P, or L2R or L2W) according to user's needs.

Specification of selected time periods, regions, and processing parameters.

Choice between Full or Reduced Resolution input data sets.

Building own processing chains by using the outputs of one processing step as the inputs for a subsequent step.

The selected data are processed automatically on the Calvalus cluster located at Brockmann Consult. The results are made available for download via HTTP and ftp.

The CoastColour on-demand processing is a big success used by many users worldwide. Continuation of the service for Sentinel 3 OLCI is a challenge but worth to be undertaken.

The validation of both Ocean and Land Colour Instrument (OLCI) data and Sea and Land Surface Temperature Radiometer (SLSTR) in theMediterranean Seais a crucial task for the actual use of the new Sentinel-3 (S3) products. The COSIMO 2015 Cruise, which will take place in March-April, 2015, on the R/V Minerva Uno, is a pre-launch multidisciplinary survey (first of a series of surveys) that will contribute to quantify the uncertainties of S3 data products  for both open (Case I) and coastal (Case II) waters in the Mediterranean Sea. This will be pursued by setting up a comprehensive matchup dataset including satellite and field measurements of relevant water parameters such as: chlorophyll-a (Chl) and total suspended matter (TSM) concentrations, remote sensing reflectance, inherent optical properties (IOPs) of optically significant constituents, and sea surface temperature (SST). Specific application of the in situ measurements may include the development of  Mediterranean-adapted algorithms for OC S3 data products.

The COSIMO 2015 oceanographic cruise will be meanly dedicated to the collection of in situ measurements of bio-geochemical and sedimentologic tracer concentrations along the western Adriatic coastal plume during the maximum fluvial runoffs phase. The area of investigation and the chosen period are justified by the actual scarcity of biogeochemical and sedimentological data related to coastal waters and river plumes (Case II waters) during the stage of maximum river runoff in the Adriatic region. This will increase the existing IOP data in theMediterranean and allow for improving the Chl:Carbon ratio estimates and, in particular, Chl:TSM estimates. The in situ sampling will benefit of real time satellite data products of SST, Chl concentration, seawater diffuse attenuation coefficient as well as by the use of hull thermo-salinometers and F-LIDAR  to qualify the water types. The research is part of the CNR-ISAC activities within the MyOcean/Copernicus project, which are dedicated to the development of a high-quality ocean color datasets to be assimilated in numerical ecological models for operative oceanography services.

The Cruise will naturally support the validation of skin SST retrievals fromSLSTR, VIIRS and MODIS data products as well as the reconstruction the diurnal sea surface temperature variation in theMediterranean Sea, which has a large impact on the basin’s heat budget and climate.

Climate change is arguably the greatest environmental challenge for the twenty-first century. Ocean colour is the only marine Essential Climate Variable (ECV) able to map a biological field: chlorophyll concentration, an index of abundance of phytoplankton, a key factor in the Earth’s carbon cycle.

However, the finite lifetime of individual ocean-colour sensors, and the differences in their characteristics, increase the difficulty of creating a long-term, consistent, ocean-colour time series that meets the requirements of climate studies. This is the goal of Ocean Colour Climate Change Initiative (OC-CCI), a European Space Agency programme.  These data are crucial for the scientific community in general and modellers in particular.

OC-CCI has recently produced a time series of satellite-based ocean-colour products at the global scale, merging data from three sensors: SeaWiFS, MODIS-Aqua and MERIS, while attempting to reduce inter-sensor biases. 

In this work we present a comparison between the OC-CCI chlorophyll-a product and pre-cursor satellite derived datasets, both single missions (SeaWiFS, MODIS-Aqua and MERIS) and merged products (GlobColour and MEaSUREs). 

Several statistical parameters, such as the correlation coefficient, bias, unbiased root mean square difference and mutual information are computed for each time step of the data records.

Our results demonstrate that the OC-CCI product increases the number of global observations, in relation to other pre-cursor satellite-derived Chl product per month. OC-CCI product was generally most similar to the single-mission products.

Relationships between OC-CCI and other precursors did not change significantly during a 5-year common period (2003 to 2007), and, on average, the root-mean-square differences between log-transformed chlorophyll-a concentration are below or equal to 0.11.

Further, when considering the variability that could arise when merging data from different sources, it is shown that the OC-CCI product is more stable in time than other multi-mission initiatives studied here. 

 This work is a contribution to the European Space Agency OC-CCI project (principal investigator - Dr Shubha Sathyendranath from Plymouth Marine Laboratory, United Kingdom).

 

In this paper, we  present the results of a classification study of Adriatic waters which was carried out using a clustering procedure combining quantile smoothing and an agglomerative clustering algorithms. The smoothing function includes a seasonal term, thus allowing one to classify areas according to “similar” seasonale evolution, as well as according to “similar” trends. This methodology, which is here applied for the first time to Ocean Colour data, is more robust with respect to other classical methods, as it does not require any assumption on the probability distribution of the data. This approach was applied to the classification  of an eleven year long time series, from January 2002 to December 2012,  of monthly values of  Chlorophyll a concentrations covering the whole Adriatic Sea. The data set was made available by ACRI (http://hermes.acri.fr) in the frame work of the GlobColour Project (http://www.globcolour.info). Data were obtained by calibrating Ocean Colour data provided by different satellite missions, such as MERIS, SeaWiFS and MODIS.

          The results clearly show the presence of North-South and West-East gradient in the level of Chlorophyll, which is consistent with literature findings. Furthermore, it also highlights the presence of a more pronounced seasonality along the Northern Italian coast, probably driven by the nutrients apportioned by river discharges. This analysis could provide a sound basis for the identification of “water bodies” and of  Chlorophyll a thresholds which define their Good Ecological Status, in terms of trophic level, as required by the implementation of the Marine Strategy Framework Directive. At present, such thresholds are selected on the basis of mean values, without taking trend and seasonality into account.

The forthcoming availability of Sentinel-3 OLCI data, in continuity of the previous missions, and with perspective of more than a 15-year monitoring system, offers a real opportunity of expansion of our study as a strong support to the implementation of both the EU Marine Strategy Framework Directive and the UNEP-MAP Ecosystem Approach in the Mediterranean.

Storm surges are one of the deadliest and most dangerous natural hazards, and in light of recent events such as Sandy in the USA and Haiyan in the Philippines there is an increasing interest in the modelling and forecasting of these phenomena. Earth Observation data from satellites have an important role to play in storm surge monitoring and forecasting, but the full uptake of these data by the users must be actively promoted.

 

Since 2011, the eSurge project (funded by the European Space Agency through its Data User Element (DUE) programme), has worked to support the improvement of surge forecasting through the increased use of satellite data. The project contributes towards an integrated approach to storm surge, wave, sea-level and flood forecasting, as part of a wider optimal strategy for building an improved forecast and warning capability for coastal inundation. It also serves as a showcase for the use of the advanced capabilities of ESA and other satellite data for storm surge applications. The project is led by CGI (UK), with NOC (UK), DMI (Denmark), UCC (Ireland) and KNMI (Netherlands) as scientific partners.

 

eSurge makes available a database of Earth Observation and in situ measurements for past surge events , which is publicly available, and has been used for many applications. Critical data types are scatterometry (for wind direction), altimetry (for sea level) and wave measurements, and we show examples of how each can be used for real applications.

 

By nature, storm surges are a phenomena that apply in the coastal zone, and hence are a natural target for the new field of coastal altimetry, which by its nature directly measures the total water level envelope (TWLE), one of the key quantities required by storm surge applications and services. It can also provide important information on the wave field in the coastal strip, which helps the development of more realistic wave models that in turn can be used to improve the forecast of wave setup and overtopping processes. Within eSurge an improved retracking technique has been developed, the Adaptive Leading-Edge Sub-waveform algorithm or ALES. This algorithm rejects some of the artefacts typically affecting the altimeter waveforms in the coastal zone, making possible an accurate retrieval of the water level and significant wave height.

 

A key part of eSurge has been to provide a demonstration near real time (NRT) service of selected data types, including altimetry. In particular, for several regions (such as the European seas and the Indian Ocean coastline) SAR altimetry from Cryosat has been provided. This provides a test case of how altimetry from Sentinel-3 could be used in a future operational system. We present examples of how altimetry has captured significant surge events in European Seas. We also outline how a new technique, developed by DMI, for blending such altimeter data with tide gauge measurements has the potential to improve operational surge forecasting models.  At the present time the usefulness of this method is limited by the number of altimeter passes available, but once Sentinel-3 spacecraft are operationally this situation will significantly improve.

 

Finally, although there are many groups studying storm surge forecasting, there has been a lack of a community to facilitate networking between such groups. eSurge has initiated such networks, which could form the basis of a storm surge community that can engage with Sentinel 3, and more widely with the Copernicus programme, giving consolidated recommendations. 

The Gulf of Cadiz (Southwestern Iberian Peninsula) and the Strait of Gibraltar (the choke point between Africa and Europe connecting the Atlantic Ocean and the Mediterranean Sea) are being used to validate altimeter information coming from past (RA-2 Envisat) and present (SIRAL Cryosat-2) ESA missions. These regions represent a valuable opportunity to validate future (SRAL Sentinel-3) altimeter mission too.

In this contribution we first describe in detail the observing systems available in the two pilot areas. These include a wide range of in-situ instruments (pressure/radar tide gauges, directional/scalar buoys) deployed in a long-term basis by Spanish Institutions (Puertos del Estado, University of Cadiz, Instituto Español de Oceanografía). This ensures a high-quality ground-truth dataset of ocean parameters (sea level, significant wave height, etc.) which is being utilized already for the validation of past, present and future altimeter data, for instance in the framework of the ALCOVA and VOCALS3 projects.

We then present some of the results obtained in the study areas in terms of validation of altimeter-derived sea level data coming from RA-2 Envisat and SIRAL Cryosat-2 against the in-situ measurements, and we discuss the extension of the developed techniques to Sentinel-3.

In most coastal waters a manifold of factors in the water and atmosphere determines the top of atmosphere radiance spectra, many more than we can derive inversely from the spectra. These factors include various water constituents with different optical properties, different aerosols, the vertical structure, the horizontal inhomogeneity etc. In some cases high concentrations of one water constituent may fully mask the optical influence of others and the importance of a factor may change along gradients of concentrations pixel by pixel. In addition water constituents with high absorption coefficients may also reduce the water leaving radiance so that the signal/noise ratio with respect to the top of atmosphere radiance becomes very poor.

This complexity of factors determines the accuracy of a single component of a pixel and how well the product at this pixel can be utilized for scientific applications or environmental monitoring.

The described issue requires that uncertainties have to be estimated pixel by pixel and delivered to the user along with the data product. But also strategies have to be developed to reduce uncertainties by selecting appropriate algorithms and conversion factors and by realistic assumptions of influencing factors, which cannot be derived from the reflectance spectra itself, e.g. by auxiliary data and existing knowledge of the area or water type, which can help to exclude or reduce ambiguities. The user has also to develop strategies how to utilize only the data of those pixels, which satisfy his requirements.

In this presentation we will present the OLCI algorithms for coastal water products including the calculation of uncertainties and flags and discuss different options in the form of examples how to improve the utilization of the products for different types of optically complex waters.

ESA’s upcoming satellite Sentinel-3 will provide continuity for altimeter and optical medium spatial resolution imagery, with high temporal resolution. The aim is to ensure continuity to ENVISAT observations, as well as MODIS and SeaWiFS. Sentinel-3 will carry the OLCI sensor (Ocean and Land Color Instrument), a multispectral medium resolution instrument planned for Ocean Color observation designed to minimise sun-glint and composed with 21 spectral bands. In comparison to the latter sensors, Sentinel-3 includes two new spectral bands in the NIR spectrum for the aerosol retrieval required to perform an accurate atmospheric correction a new band in the red region, which represents a peak in of the plankton bloom centered at 673.75 nm.

The objective of this study is to evaluate the performance of the upcoming multispectral sensor by comparing OLCI reflectance, obtained from hyperspectral satellite imagery processing, with synchronous MERIS data. Selected satellite observations, acquired on 11/01/2012 over northern Adriatic Sea basin, show turbidity patterns due to wave-generated resuspension of sediments during intense wind stress conditions, which caused variation in water column turbidity.

Ocean Color parameters were estimated from the OLCI reflectance and spatial patterns of Total Suspended Matter (TSM), generated from both OLCI and MERIS reflectances, were used to interpret the sediment resuspension event. Results suggests that performances of OLCI spectral configuration may improve the estimation of Ocean Color parameters which can lead to generate more accurate products for water quality monitoring, especially for time series analysis and proper integration with modelling methods.

The altimeter significant wave height (SWH) and the surface wind speed measurements are of considerable importance for weather prediction either for assimilation or verification. The ESA CryoSat-2 Fast Delivery Ocean Level 2 (FDM) is not an exception and therefore validation of this product is required.  The FDM SWH data demonstrated good quality. The assimilation experiments proved that the data are useful as far as wave data assimilation is concerned.

More investigation was carried out using the SAR data from Cryosat, which is similar to Sentinel-3 altimetry products, showed that the SAR data are of goo quality as well. Still more investigations will be carried out and the results will be shown.  

Monitoring sediment fluxes patterns in coastal area, like dispersion, sedimentation and resuspension processes, is a relevant topic for scientists, decision makers and natural resources management. Time series analysis of Earth Observation (EO) data may contribute to the understanding and the monitoring of processes in sedimentary depositional marine environment, especially for shallow coastal areas.

ESA’s upcoming satellite Sentinel-3 will feature the OLCI sensor (Ocean and Land Color Instrument) to provide optical multispectral medium resolution imagery, with high spectral and temporal resolution (2-3 days). The aim is supply operational services for the monitoring of land, coastal and marine environments, ensuring continuity to MERIS, MODIS and SeaWiFS observations.

The objective of this study is to show the ability of optical medium resolution imagery in interpreting the evolution of sediment resuspension from seafloor in coastal areas during intense wind forcings. Steady Bora wind events in northern Adriatic Sea basin during winter 2011 provoked considerable wave-generated resuspension of sediments, which caused variation in water column turbidity. Available ENVISAT MERIS cloud free observations acquired during the study period have been used to trace turbidity in the water column, generated by river plumes and resuspended sediments. MERIS L1b data have been processed using CoastColour v2 processors and BEAM software. The generated L2 products have been binned to a L3 300 m regular grid, in order to perform time series analysis maintaining the spatial features detail. Total Suspended Matter (TSM) and maximum signal depth (Z90_max) products were selected to analyze superficial circulation patterns and the evolution of sediment resuspended and transported throughout the Bora events. Maximum signal depth, which indicates the water depth from which 90% of the reflected light comes from, was used to evaluate the evolution of sediment concentration in the water column and has been recognized to be not only a relevant parameter to interpret the dynamics of sediment fluxes, but also a requirement to improve contribution of EO data assimilation in numerical modeling.

Results show how EO time series analysis can be a powerful tool to monitor high energy forcing events in shallow coastal areas, providing precise spatial and temporal patterns to interpret the evolution of sediment fluxes. This suggest that Sentinel-3 sensor will be suitable for the monitoring of sediment dynamics in shallow coastal environments. Moreover, up-to-date algorithms for geophysical parameters estimation were found to be capable of satisfying the requirements for data assimilation in numerical modeling.

Considerable progress has been made during the past decade in measuring sea level change globally and regionally, and in understanding the climate-related causes of observed changes. New challenges have been identified in terms of observations, modelling and impact studies in coastal regions where spatial and temporal variability of the sea level as well as the underlying ocean dynamics,differ significantly from open ocean.

A long-term satellite-based monitoring of the sea level Essential Climate Variable as required for climate studies is provided by the ESA Climate Change Initiative Sea Level Project (SLCCI). Amongst the various CCI activities for validation and sea level trend verification, a regional study assess the quality of the Fundamental Climate Data Record (FCDR) over the German Bight and the Mediterranean Sea. These are ideal test regions, where reliable and long time-series of in-situ sea level and geodetic stations allow a good characterization of the error and comparison of signal and error with the Essential Climate Variable (ECV) regional solution.

 

Our first objective is to characterize the altimetry errors and to improve some corrections to extract the climate signals at the coast (trend). The altimeter data are validated in both regions against geodetic-referenced in-situ data, referred to the Earth’s reference ellipsoid GRS80 via the Global Navigation Satellite System (GNSS). In the second part of the study we will highlight the importance of carrying out multidisciplinary studies to understand and discriminate causes of current sea level changes, integrating the various factors that interfere at local scale (as climatic component, atmospheric and oceanographic processes, ground subsidence, etc.).

 

The Northern Adriatic Sea is presently the area, within the Mediterranean Sea, where river plumes show the most significant influence as several rivers (Po, Adige, Brenta and Tagliamento rivers) produce almost a single freshwater plume that can influence the sub-basin and the whole basin.

In February 2014 we carried out a research voyage to characterize the spatial and temporal variability in optical properties and composition of particulate and dissolved matter in the Northern Adriatic Sea. We measured bulk and apportioned inherent optical properties (IOPs) as well as apparent optical properties (AOPs), biogeochemical properties and particle size distribution, during the tidal cycle. We observed a significant variability in the shape and amplitude factors controlling the inherent optical properties (IOPs) spectral shapes.

To accurately retrieve particulate and dissolved matter IOPs as well as concentrations, we applied algorithms designed to resolve the IOPs and AOPs variability to MODIS imagery acquired during the research voyage. The results of the adaptive inversion approach (Brando et al., 2012) will be compared with class-based approaches for deriving optical water type specific inversion algorithms (e.g. Melin et al., 2011; Vantrepotte et al., 2012).

The proposed method has then been applied to the MODIS time series. Spatial and temporal patternes in the IOPs and AOPs will be discussed.

This study reports the use of significant wave height product, derived from radar altimeter on board of OSTM/Jason-2 satellite, during last winter (DJF 2014) storms at the Northeast region of theAtlantic Ocean, including a large area between Azores and the West Iberian coast.

Altimeter wave height data is important for wave model data assimilation and also to support marine forecasts. In the present paper a comparison with European Centre for Medium-Range Weather Forecasts (ECMWF) wave model (WAM) is undertaken and the results highlight the importance of the use of altimetry data in an operational way.

In summary, and despite the limitations of altimeter data for operational marine forecasts, mainly the incapability of providing a synoptic overview, the results illustrate the benefits of the use of wave height product, particularly in ocean regions with lack of observations, where real-time satellite altimeter data can be used to support the short-range ocean forecast.

Remote sensing by advanced radar active and passive methods provide better discrimination and higher resolution in complex geophysical flows. In the ocean, and even more so, in the coastal zone,where turbulent flow is generated in the ocear surface either  by waves, wind or/and local currents.  The conditions of the medium are highly non-homogeneous, and in the presence of a pollutant the SAR  detects many topological features[1,2]. New techniques are used for the subsequent analysis, of more than 2000 Images provided by the ESA ERS1/2, ASAR, ENVISAT, RADARSAT and other European , Canadian and Russian Satellites. We shall concentrate and provide statistics, as well as describing some events detected by several satellites and with additional cruise observations and measurements [4-9] in  the North-west Mediterranean Sea area  between  1996 and  2012.

Also the structure of the flows are presented using self-similar traces that may be used to parametrize mixing at both limits of the Rossby Deformation Radius scale. RL Results show the ability to identify different SAR signatures and at the same time provide calibrations for the different local configurations of vortices, spirals, Langmuir cells, oil spills and tensioactive slicks that eventually allow predicting the self-similar structure of the turbulence.[3,4]

It is noteworthy that such complex coastal field-dependent behavior is strongly influenced by stratification and rotation of the turbulence spectrum is observed only in the range smaler than local RL. The measures of diffusivity from buoy or tracer experiments are used to calibrate the behaviour of different tracers and pollutants, both natural and man-made in the NW Mediterranean Sea [4,5]. Thanks to different polarization and intensity levels in satellite imagery can be used to distinguish between natural and man-made sea surface features due to their distinct self-similar and fractal as a function of spill parameters, environmental conditions and history of both oil release and weather conditions.

Environmental factors determine [6,7] spreading, drift and weathering of oil on the sea surface, but  note that coastal turbulence becomes helical influenced by the wind field. This means that the one-point correlation functions of  the flow velocity. On the other hand helical and stratified turbulence is also modified by the intermittency and by the maximum fractal dimension, [5,8], which is related to the energy spectrum of the flow. Using all the available information it is possible to investigate the spatial variability of the horizontal eddy diffusivity K(x,y).[2,9] This information would be very important when trying to model numerically the behaviour in time of the oil spills [10,4] At smaller scale there is a strong dependence of horizontal eddy diffusivities with the Wave Reynolds number as well as with the wind stress measured as the friction velocity from wind profiles measured at the coastline.[11,12]

[1] Redondo, J.; Matulka, A.M.; Carrillo, J. (2010) Vortex decay in stratified flows. Topical Problems of Fluid Mechanics 2010. Praga, AS. pp. 127-130.

[2] Castilla R., Redondo J.M., Gamez P.J. and Babiano A. (2007), Non Linear Processes in Geophysics, 14, (2007) pp. 139.

[3]  J. M. Redondo, J. H. Fernando and S. Pares (1995) Cloud entrainment by internal or external turbulence, Mixing in geophysical flows, J. M. Redondo and O. Metais (Eds), CIMNE, Barcelona (1995) pp. 379-392.

[4] Sekula E., Redondo J. M. (2008)"The structure of turbulent jets, vortices and boundary layer: Laboratory and field observations", Il Nuovo Cimento, Vol. 31, N. 5, pp. 893 ‐ 907

[5]   Platonov A., Carillo A., Matulka A., Sekula E., Grau J., Redondo J. M., Tarquis A. M. (2008) Multifractal observations of eddies, oil spills and natural slicks in the ocean surface", Il Nuovo Cimento, Vol. 31 C, N. 5‐6, pp. 861‐880.

[6] Redondo J.M. (1996) Vertical microstructure and mixing in stratified flows. Advances in Turbulence VI. Eds. S. Gavrilakis et al.(1996), pp. 605-608.

[7] Redondo J.M.(2001) Mixing efficiencies of different kinds of turbulent processes and instabilities, Applications to the environment” in Turbulent mixing in geophysical flows. Eds. Linden P.F. and Redondo J.M., pp. 131-157.

[8] Nicolleau, F.C.G.A.; Cambon, C.; Redondo, J.M.; Vassilicos, J.C.; Reeks, M.; Nowakowski, A.F. (Eds.)(2011) New Approaches in Modeling Multiphase Flows and Dispersion in Turbulence, Fractal Methods and Synthetic Turbulence. ERCOFTAC Series.

[9] Fraunie P., Berreba S. Chashechkin Yu.D., Velasco D. and Redondo J.M. (2008) Large eddy simulation and laboratory experiments on the decay of grid wakes in strongly stratified flows. Il Nuovo Cimento C 31, 909-930.

[10] Matulka, A., López, P., Redondo, J. M., and Tarquis, A.(2014) On the entrainment coefficient in a forced plume: quantitative effects of source parameters, Nonlin. Processes Geophys., 21, 269-278.  

[11] Castilla R., Oñate E. and Redondo J.M. (2007) Models, Experiments and Computations in Turbulence. CIMNE, Barcelona, 255.

[12] M.O. Bezerra, M. Diez, C. Medeiros, A. Rodriguez, E. Bahia., A. Sanchez and J.M. Redondo (1998) Study on the influence of waves on coastal diffusion using image analysis. Applied Scientific Research 59,.191-204.

Marine environment provides a number of important benefits and services to people. Coastal areas are essential to the Indian Ocean Commission (IOC) countries economic, cultural and environmental health. Unfortunately the sustained delivery of these marine ecosystem services is threatened by a growing variety of human activities. Climate change and associated oceanographic and weather changes are increasing the risks posed to the coastal environment of the IOC member states. The products developed by the Mauritius Oceanography Institute in the framework of the Monitoring for Environment and Security in Africa (MESA) programme for the Indian Ocean Commission region is dedicated to using Earth Observation and in-situ data to support the information requirements and decision-making processes for Marine Resources Management and the Monitoring of the Coastal Environmentin the South West Indian Ocean region. By using Sea Surface Temperature and Chlorophyll images, Potential Fishing Zones may be identified. To be able to map potential fishing grounds is important for resource management and also of benefit to pelagic fishermen. Physical processes such as waves, currents, temperature and sea surface height affect biological productivity and have a strong influence on the coastline.

Observation of the ocean’s physical properties from space coupled with in-situ data help to better understand and describe these oceanographic parameters.  Operational marine information from wave data buoys can be very useful in the monitoring, prevision and mitigation of oceanographic risks such as sea level rise, swells and storm surges that may lead to coastal hazards.

 

The two services being developed in the context of the Indian Ocean Commission (IOC) THEMA “Marine and Coastal Management” are illustrated with examples of the different products and the targeted users.  The IOC THEMA goals and activities are also highlighted.

 

Keywords: Marine and Coastal Management, Marine Resources Management, Potential Fishing Zones, Physical Oceanography variables, Climate Change.

CMIP5 pre-industrial simulations are examined to assess the ability in reproducing the El Niño and Atlantic dipole variability in the Tropical Atlantic Ocean. We present results of  Principal Component Analysis (PCA) and Non linear Principal Component Analysis (NLPCA) on the ERSST data set from the NOAA and  few models of CMIP5 model ensemble. It is observed that the first NLPCA modes explain marginally more of the total data variance than do the PCA modes. Our results show that a modest number of models were able to capture correctly the meridional mode (Atlantic dipole). NLPCA shows that the spatial distribution of the El Niño pattern signature in model HadGEM2-AO compares reasonably well with the observed features but with sign reversal.

The advent of delay/Doppler altimetry has represneted a major step forward on altimetry. One of the by product of this technique, i.e. the delay/Doppler stack, has so far been largely overlooked for scientific applications due to the fact that the estimation of geophysical products starts mainly at the multi-looked echoes.

However, the stack contains very valuable information that can be used in a wide variety of applications. For instance, in coastal altimetry, the stack can be geo-referenced in order to mitigate the land contamination effect.

In this paper we intend to show the performances of this technique by correlating SAR altimetry data in coastal areas with third parties independent sources.