Copernicus Marine Environment Monitoring Service (CMEMS) Service …marine.copernicus.eu/wp-content/uploads/2017/06/CMEMS... · 2017-06-29 · Copernicus Marine Environment Monitoring

Copernicus Marine

Environment Monitoring

Service (CMEMS) Service

Evolution Strategy:

R&D priorities

Version 3

June 2017

Document prepared by the CMEMS Scientific and

Technical Advisory Committee (STAC) and

reviewed/endorsed by Mercator Ocean

CMEMS SERVICE EVOLUTION STRATEGY: R&D PRIORITIES June 2017 0 0

Table of content

1 Introduction ........................................................................................................................ 1

2 Scientific and technical backbone of CMEMS .................................................................... 3

3 Key drivers of the Service Evolution and related R&D priorities ....................................... 4

4 R&D areas and required developments ............................................................................. 7

4.1 Circulation models for the global ocean, regional and shelf seas ................................... 7

4.2 Sub-mesoscale - mesoscale interactions and processes .................................................. 8

4.3 Coupled ocean-marine weather information, surface currents and waves .................. 10

4.4 New generation of sea-ice modelling ............................................................................ 11

4.5 modelling and data assimilation for marine ecosystems and biogeochemistry ........... 12

4.6 Seamless interactions between CMEMS and coastal systems ...................................... 13

4.7 Coupled ocean-atmosphere models with assimilative capability .................................. 15

4.8 Ocean climate products, indicators and scenarios ........................................................ 16

4.9 Observation technologies and methodologies .............................................................. 17

4.10 Observing systems: impact studies and optimal design .............................................. 19

4.11 Advanced assimilation for large-dimensional systems ................................................ 20

4.12 High-level data products and big data processing ....................................................... 21

5 The service evolution roadmap for 2021 and beyond ..................................................... 23

5.1 The targeted CMEMS service in and after 2021 ............................................................ 23

5.2 Tier-3 R&D marine projects of interest to CMEMS ........................................................ 25

5.3 Tier-2 R&D marine projects selected by CMEMS ........................................................... 27

5.4 Service evolution roadmap and milestones until 2021 ................................................. 28

6 Appendices ....................................................................................................................... 29

6.1 Service Evolution Strategic documents .......................................................................... 29

6.2 CMEMS Service Evolution call 21-SE-CALL1 selected projects ...................................... 29

6.3 CMEMS Service Evolution: R&D calls for Global MFc .................................................... 35

6.4 Report from the Copernicus Coastal Workshop ............................................................ 36

6.4.1 Context and workshop objectives ........................................................................... 36

6.4.2 Main outcomes and recommendations .................................................................. 36


1 INTRODUCTION

The Copernicus Marine Environment Monitoring Service (CMEMS) provides regular and

systematic reference information on the physical state, variability and dynamics of the ocean

and marine ecosystems for the global ocean and the European regional seas. This capacity

encompasses the description of the current ocean situation, the variability at different

spatial and temporal scales, the prediction of the ocean state a few days to weeks ahead

(forecast), and the provision of consistent retrospective data records for recent decades

(reprocessed observations and re-analyses). CMEMS provides a sustainable response to

European user needs in four areas of benefits: (i) maritime safety, (ii) marine resources, (iii)

coastal and marine environment, (iv) weather, seasonal forecast and climate. A major

objective of the CMEMS is to deliver and maintain a competitive and state-of-the-art

European service responding to public and private intermediate user needs, and thus

involving explicitly and transparently these users in the service delivery definition.

A Delegation Agreement1 has been signed between the European Commission and Mercator

Ocean for the CMEMS implementation during the 2015-2021 period. It mandates the

development and maintenance of a Service Evolution Strategy (see also section 6.1) in order

to respond to new needs and take advantage of improved methodologies. This strategy is

the mechanism by which lessons and knowledge derived during the past, as well as new

research results, are used to guide change and/or a potential service upgrade in the

subsequent phases.

The Service Evolution Strategy is maintained on the basis of direct feedbacks from users,

scientific and technical gaps analysis of emerging and existing user requirements, and the

potential to improve the Core Service elements. At the same time, the Service Evolution

Strategy identifies research needs that can guide external (e.g. H2020) and internal (CMEMS)

R&D priorities. Consistent updates of the Service Evolution Strategy and its R&D priorities

are made on an annual basis.

This document is the second update of the R&D roadmap which identifies the essential

Science and Technological (S&T) developments needed for the evolution of CMEMS during

the 2015-2021 period. Different categories of activities are conducted, with different time

horizons, players and objectives:

long-term objectives (Tier-3, beyond 2 years up to ~10 years), corresponding to the

long-term evolution of the CMEMS framework;

1 See http://www.copernicus.eu/sites/default/files/library/CMEM_TechnicalAnnex_PUBLIC.docx.pdf

http://marine.copernicus.eu/wp-content/uploads/2017/03/CMEMS-High-Level-Service-Evolution-Strategy-FV-September-20-2016.pdf

http://www.copernicus.eu/sites/default/files/library/CMEM_TechnicalAnnex_PUBLIC.docx.pdf


mid-term objectives (Tier-2, 1 – 2 year cycle) addressed by dedicated R&D project

teams, for implementing and assessing major scientific upgrades of the service during

Phase-I (2015-2018) and mostly Phase-II (2018-2021) (see technical annex of the

Delegation Agreement);

short-term objectives (Tier-1, several months to 1 year cycle) with activities for

addressing issues requiring fast responses for rapid implementation within the

existing phases of CMEMS.

Long-term R&D activities, although implemented in a different framework, are as crucial as

short and mid-term activities for the sustainable evolution of the Service. The short and mid-

term activities are addressed both through internal CMEMS activities and open R&D calls,

while long-term activities are promoted in the framework of external projects (e.g. Horizon

2020 or other European and national R&D programmes).


2 SCIENTIFIC AND TECHNICAL

BACKBONE OF CMEMS

The backbone of the CMEMS relies on an architecture of production centres both for

observations (Thematic Assembly Centres – TACs) and modelling/assimilation (Monitoring

and Forecasting Centres – MFCs) and a Central Information System (CIS). The CMEMS

architecture for the phase 2 (2018-2021) consists of:

Eight Thematic Assembly Centres (TACs), including six “space” TACs organized by ocean variables (sea surface topography, ocean colour, sea surface temperature, sea ice, waves, and winds), one TAC for in situ observations, and one TAC for multi-observations (combining both in situ and satellite observation). TACs gather observational data and generate elaborated products, e.g. multi-sensor data products, derived from these observations. TACs are fed by operators of space and in situ observation platforms and infrastructures; the detailed operational requirements for space and in situ observation data were initially specified in the Marine Core Service Strategic Implementation Plan (Ryder, 2007 “GMES Fast Track Marine Core Service, Strategic Implementation Plan, Final version 24/04/2017”).

Seven Monitoring and Forecasting Centres (MFCs), distributed according to the

marine area covered (Figure 1, including Global Ocean, Arctic Ocean, Baltic Sea,

North Atlantic West Shelf, North Atlantic Iberia-Biscay-Ireland area, Mediterranean

Sea and Black Sea). MFCs generate model-based products on the ocean physical and

biogeochemical states, including forecasts, analyses and reanalyses.

A Central Information System (CIS), encompassing the management and

organization of the CMEMS information and products, as well as a unique User

Interface.

TACs, MFCs and CIS contractors for the phase 2 of CMEMS (04/2018-04/2021) will be

selected following a call for tender that will be issued during the 2nd semester of 2017.

Figure 1. Regions covered by CMEMS.


3 KEY DRIVERS OF THE SERVICE

EVOLUTION AND RELATED R&D PRIORITIES

The guidelines to identify the R&D activities to be organized within Copernicus or in

coordination with the service are motivated by several key drivers:

Requirements from core users in the four main areas of benefit as recalled in the

Introduction, accounting for both existing needs and needs likely to emerge in the

future;

Requirements from the CMEMS production centres based, in particular, on their 3-6

year R&D plans, considering the limitations in the daily service due to knowledge or

technological gaps identified to elaborate the products;

Requirements motivated by the development of Copernicus downstream services;

Requirements from European and international programmes dealing with Earth

observations, operational oceanography and Copernicus; notably GODAE OceanView,

the Copernicus Integrated Ground Segment (IGS) and GEOSS (Global Earth

Observation System of Systems);

Outcomes of EU projects implemented under the Space theme (R&D to enhance

future GMES applications in the Marine and Atmosphere areas), such as MyWave,

OSS2015, E-AIMS, OPEC and SANGOMA or under FP7 and H2020 projects (e.g.

JERICO, PERSEUS, AtlantOS).

Additional drivers that reflect a more strategic view for the service evolution are also taken

into account, such as:

EU directives implemented to regulate activities in the Marine sector (e.g., Marine

Strategy Framework Directive, Maritime Spatial Planning);

New scientific and technological opportunities in the next 5-10 years, regarding both

satellite (e.g. the Sentinels suites) and in situ observations (e.g. plans for the global

BGC-Argo extension), modelling and assimilation capabilities, new communication

and data processing technologies, etc.

The need to maintain competitiveness w.r.t. international players in operational

oceanography, as keeping a high-level know-how and innovation capacity will be

strategic to attract new users;

Forthcoming activities involving Copernicus developments in the framework of other

European (e.g. EMODnet, EuroGOOS, EOOS) and global initiatives or programmes


(e.g. the Global Ocean Observing System in the context of GEOSS, GEO Blue Planet,

GODAE OceanView);

The Sustainable Development Goals (SDG) defined as part of the UNEP 2030 Agenda

(especially SDG 14 - Conserve and sustainably use the oceans, seas and marine

resources for sustainable development);

Outcomes of the 21st Conference of the Parties (COP21) to the UNFCCC (United

Nations Framework Convention on Climate Change) including the need for a global

stocktake to support emission agreements.

The constant dialogue with user communities as outlined above helped in identifying

overarching themes for the Service Evolution, focusing on:

i. A better description of ocean biogeochemical and ecosystem parameters in

particular to support reporting on marine environmental status in the regional

European seas, as required by the Marine Strategy Framework Directive (MSFD);

ii. The production of consistent ocean and wave information/products resulting

from the coupling between the ocean state, the atmosphere, surface wave

dynamics and other air-sea interface processes;

iii. A better interface between the CMEMS and coastal monitoring services

operated by Member States or private groups: this will require an improved

processing of satellite and in situ observations in the coastal zone as well as the

provision of suitable connectivity and boundary conditions between the Marine

Service and the national coastal systems;

iv. A better monitoring and description of the ocean state and its variability,

requiring the preparation and release of annual Ocean State Reports describing

the state of the global ocean and the European regional seas, in particular for

supporting the Member States in their assessment obligation;

v. A better assessment of the quality of CMEMS products, which requires

continuous upgrade of observation infrastructures and improved data

information and access services.

Moreover, it is identified that one overarching driver for service evolution remains a

continuous enhancement of modelling, data assimilation and forcing techniques at both

the air-sea interface and lateral boundaries (coasts, open boundaries), in order to exploit

the considerable investment in recent and upcoming observation technologies (e.g. SAR,

SARin, SWOT, CFOSAT) and observation infrastructures.

These priorities provide guidelines to the short, medium and longer term developments

outlined in section 4 below. The proposed R&D roadmap was established following an

analysis of R&D priorities by the CMEMS Scientific and Technical advisory committee (STAC)

set up to assist Mercator-Ocean for the CMEMS implementation.

This version (V3) released in June 2017 provides an update of R&D priorities and develops

the Service Evolution roadmap and plans for the coming years. It takes into account, in

particular, revised 3-year and 6-year evolution plans from the present CMEMS TACs and


MFCs, past and on-going H2020 Copernicus projects (service evolution, downstream)

referred to in section 5, and outcomes of the first call for tenders for CMEMS Service

Evolution (section 6). In the prospect of proposals to be submitted in response to the second

CMEMS SE call (fall 2017), it is recommended to carefully consider the scope of on-going

Tier-2 or Tier-3 projects in order not to duplicate research and developments efforts already

addressed by other project teams.


4 R&D AREAS AND REQUIRED

DEVELOPMENTS

In this section, the 12 R&D areas required to support the service evolution guided by user

needs are described. The required developments are categorized in terms of time horizons

(short- to mid-term, and long-term) and expected objectives. The developments with short-

to mid-term objectives refer to R&D activities that are expected to deliver significant results

in less than 2 years, while longer-term activities are thought to need more than 2 years to

bear results that will impact the service. The sections addressing R&D priorities of the 4

over-arching themes that emerged from the strategic analysis made by the STAC are

organized as follows: ocean circulation modelling, mesoscale and other interactions, ocean-

wave and ocean-ice coupling (sections 4.1 to 4.4), biogeochemistry and ecosystems in the

marine environment (section 4.5), interactions with the coastal ocean (section 4.6) and

ocean-atmosphere coupling, reanalysis and indicators, and climate change (sections 4.7 and

4.8). Finally, sections 4.9 to 4.12 correspond to cross-cutting activities and methodologies

that will benefit the 4 overarching themes.

4.1 CIRCULATION MODELS FOR THE GLOBAL OCEAN, REGIONAL AND SHELF

SEAS

Expected evolutions

To support Copernicus marine users and decision-makers there will be an increasing demand

for model information on fine spatial scales, higher frequencies and with a more complete

representation of dynamical processes of the turbulent ocean. This is relevant to all areas

from the open ocean where the dynamics are significantly impacted by mesoscale eddies, to

transition areas connecting coastal and shelf seas and to critical regions (e.g. straits,

boundary layers) requiring high topographic resolution. Numerical models will be needed

with increased resolutions to represent the dynamics captured by existing and future Earth

Observation platforms (e.g. high-resolution wide-swath altimetry, geostationary sensors,

direct estimations of surface currents, high resolution sea surface temperature (SST), etc.)

and consistent with improved estimates of fluxes of freshwater and suspended matter at the

coast.

Required developments with short- to mid-term objectives

Development of advanced physical parameterizations, numerical schemes and

alternative grids to improve the performance of ocean models resolving the

mesoscale and smaller scales;


Adaptation of multi-scale and seamless downscaling/nesting capabilities to achieve

kilometric to sub-kilometric resolution over specific areas;

Better resolution of surface currents (0-20 m depth) and higher-frequency processes

(e.g. tides) including their effects (e.g. rectification) and associated uncertainties on

the circulation and on the transport of tracers;

Adaptation of forcing methods with consistent physical parameterizations that

benefit the fine scales (fronts, filaments) of surface ocean patterns;

Improved capability in 3D storm surge forecasting for global and regional models, in

particular new strategies to incorporate atmospheric surface pressure data, tidal

forcing and coupled ocean-wave-atmosphere effects;

New strategies and algorithms to solve the model equations efficiently on next

generation computing systems: this should result in code performance improvements

on most intensive HPC applications, which is crucial to sustain operational

production;

Development of empirical or other atmospheric modelling techniques to improve the

spatial and temporal resolution of atmospheric forcing.

Required developments with longer-term objectives

Modelling issues related to multi-scale and multi-physics and in particular model

nesting and unstructured grids;

Development of non-hydrostatic ocean models to represent the full evolution of fine-

scale oceanic structures in the three spatial dimensions;

Understanding of fine scale processes to guide the development of global ocean

analyses and forecasts at increased resolution and complexity (e.g. including

representations of tidal physics, mixing and wave-current interactions).

4.2 SUB-MESOSCALE - MESOSCALE INTERACTIONS AND PROCESSES

Expected evolutions

Our knowledge on the relationships between the physical, chemical and biological processes

in the upper ocean is continuously improving. This is essential for understanding and

predicting how the ocean and the marine ecosystems respond to ocean dynamics and

changes in atmospheric forcing. Advection, mixing and enhanced vertical velocities

associated with mesoscale and sub-mesoscale oceanic features such as fronts, meanders,

eddies and filaments are of fundamental importance for the exchanges of heat, fresh water

and for biogeochemical tracers between the surface and the ocean interior, but also for

exchanges between the open oceans and shelf seas, and between the pelagic ocean and the

benthos.

The challenges associated with mesoscale (20-300 km, Rossby numbers < 1, and time scales

from weeks to a few months) and sub-mesoscale variability (between 1-20 km, Rossby and

Richardson numbers O(1), and time scales from minutes to a few days) require high-


resolution observations (both in situ and satellite) and multi-sensor approaches. Accordingly,

multi-platform synoptic experiments have to be designed in areas characterized by intense

density gradients and strong mesoscale activity to monitor and establish the vertical

exchanges associated with mesoscale and sub-mesoscale structures and their contribution

to upper-ocean interior exchanges. In situ systems, including ships, profilers and drifters

should be coordinated with satellite data to provide a full description of the physical and

biogeochemical variability and will be combined with resolution numerical simulations.

Focus should be made on a range of scales (15-100 km) traditionally not resolved by

conventional altimeters but in which the wide swath altimeter SWOT will make an

unprecedented contribution. At the same time, the realistic representation of the

generation and evolution of such processes in numerical ocean models remains very

challenging due to the chaotic nature of the oceanic flow, making direct model-data

comparisons at the smallest scales problematic.


Predictability studies to assess the feasibility of developing open ocean and

coastal/regional seas’ forecasts with lead-time of a few days to weeks, together with

assessment of likely prediction skill;

Methods to assess the relative impact of sub-mesoscales and internal waves on sea

surface height and in situ observations;

Methods to account for turbulence-submesoscale interactions into numerical

models, topographic interactions at small scales, mixing induced by internal waves

and other interacting processes between internal waves and submesoscale eddies;

Development of new metrics adapted to the increased resolution in both

observations/products and models.


Synthesis from multidisciplinary field experiments and numerical studies to assess (i)

systematic error in ocean models induced by sub-mesoscale dynamics, (ii) impact of

vertical exchanges associated with mesoscale and sub-mesoscale structures, and (iii)

operational products in specific areas;

Process studies focused on physical-biological interactions at sub-mesoscale,

implications for biogeochemistry, productivity, export, ecosystem structure and

diversity;

Improved understanding of vertical exchanges associated with oceanic mesoscale

and sub-mesoscale features (e.g. fronts, meanders, eddies and filaments) through

the combined use of in situ, satellite data and numerical models;

Assess the impact of solving the ocean dynamics at kilometric scales on the role of

ocean on climate (e.g. vertical exchange of heat and carbon, representation of

overflows).


4.3 COUPLED OCEAN-MARINE WEATHER INFORMATION, SURFACE CURRENTS

AND WAVES

Expected evolutions

The most important ocean weather parameters delivered by CMEMS are ocean currents,

temperature (in particular in the near-surface layer of the ocean), sea ice, sea level, waves

and surface winds. For several marine and coastal applications, information on surface

parameters, including total and non-tidal currents and waves, is highly important. One

example is the off-shore industry, where information on wave height and period are

fundamental in the decision making (e.g. when ocean platforms need to be evacuated during

violent storms). Everyday activities along the coasts heavily depend on wave information.

Information on surface waves is also an essential input to the risk analysis in storm flood

events.

Waves are a bridge between the ocean and the atmosphere. Therefore, surface fluxes and

winds used to drive the wave and ocean circulation should be consistent. The quality of

wave forecasts and analyses is strongly linked with the quality of the wind forcing. Waves

are also an important mixing agent with an active role in erosion and resuspension

processes.

In 2012, the EU funded project MyWave was established to lay the foundation for a future

Service that also includes ocean waves. Additional efforts funded under the 1st CMEMS SE

call are underway to support the production of more consistent ocean-marine weather

information, including information on surface waves. However, the two-way coupling

between ocean and wave processes has to be further developed and improved.


Improved methods for analysing and predicting upper ocean currents;

Improved processing methods to retrieve wave and surface currents (total and non-

tidal) information from the relevant satellite data, such as wave height based on

altimeters (e.g. Sentinel 3) and wave information from SAR (e.g. Sentinel 1) and

CFOSAT;

Improved processing methods to retrieve wave information (including integrated

parameters such as significant wave height) from in situ platforms (buoys, moorings,

HF radars, etc);

Developments to implement fully coupled ocean-wave models in which both

components will exchange information at high frequency, and development of

coupling parameterizations (bulk parameterizations for instance), both in the open

ocean and near the shoreline;

Investigations of wave model error dependencies on swell parameters (usually

source of the largest errors) and improved parameterizations;

Improved wave modelling near the ice edge and in ice-infested waters.



Improved modelling of extreme and rogue waves ;

Implementation of advanced techniques to assimilate data into fully coupled ocean-

wave-atmosphere model systems;

Improved characterisation of the uncertainties in coupled ocean-wave analyses and

forecasts.

4.4 NEW GENERATION OF SEA-ICE MODELLING

Expected evolutions

There is evidence of a number of shortcomings in modelling the coupled ocean-sea-ice-

atmosphere system at high latitudes that continue to limit the quality of operational

products delivered to users (both real-time as well as reanalyses). The 10 km to 100 km wide

Marginal Ice Zone where ocean waves and sea ice processes are coupled is expected to

widen in a warmer Arctic, but is still not well represented, neither in data nor in operational

models. Additionally, products for fisheries (having a very strong economic value) depend on

several qualities of both physical models (mixing, horizontal and vertical advection of larvae)

and primary and secondary production models.

Some shortcomings are inherent to the traditional viscous-plastic sea-ice rheology (and

elastic-viscous-plastic as well) used in the current sea-ice models, deformations of sea ice

being not correctly represented and in turn the velocity of sea ice drift being also incorrect.

The ability to assimilate sea ice drift is also impaired by such model biases. In addition, the

inclusion of more non-linear, chaotic processes are expected to become increasingly

challenging for assimilation methods, in a context where more observations will be delivered

from space, especially through the Sentinel suite.


New methods designed to assimilate satellite sea ice observations, such as the type

and thickness of sea ice and more detailed information available from SAR imagery,

together with impact assessments;

Sea-ice models based on a more realistic rheology (for instance rheological models

based on solid mechanics rather than fluid mechanics and their inclusion into

operational models);

Improved coupling between ocean waves and sea-ice processes ;

Improved physical modelling of mixing below sea ice;

Improved sea ice thermodynamics that will include effects of surface melt ponds;

Coupling with snow models to account for ageing of snow and blowing snow;

Development of a new generation of sub-kilometer scale dynamic sea ice models

able to resolve ice floes.



Representation of biological cycles in sea ice, including optical properties of sea ice

and vertical migration of nutrients in sea ice;

Specific development for modelling of the Marginal Ice Zone, taking into account the

heterogeneity in sea ice coverage and coupling effects with ocean and atmosphere

and waves at fine scales;

Developments on sea-ice models and data assimilation targeted to initialize coupled

ocean-atmosphere and sea-ice forecasts for a wide range of time scales.

4.5 MODELLING AND DATA ASSIMILATION FOR MARINE ECOSYSTEMS AND

BIOGEOCHEMISTRY

Expected evolutions

Users of the future CMEMS will benefit from the gradual improvement of models and tools

to monitor the biogeochemical state of the ocean and marine ecosystems in ocean basins

and marginal seas, using model-data integration and assimilation methodologies. This will

require very significant strengthening of the observation system of the “green” ocean

component at a range of scales, including in regional and coastal seas. In addition to the

Sentinel suite, the potential of future satellite sensors (e.g. imagers from geostationary

satellites) should induce a breakthrough in the monitoring of coastal areas and the land-

ocean interface. Moreover, monitoring the concentration and distribution of pollutants will

be essential for predicting ecosystem responses to pollution. Other challenges on the marine

component of the carbon/greenhouse gases cycles will also require significant R&D effort as

significant gaps in monitoring tools also exist in this area.

During the past years, a suite of EU funded projects have developed the processing of

remote-sensing data for open ocean and coastal waters (see section 5) as well as prototype

ecological marine forecast systems for ocean basins and European seas (Atlantic, Baltic,

Mediterranean and Black Seas) which include hydrodynamics, lower and higher trophic

levels. More recent projects funded under the 1st CMEMS Service Evolution R&D call will

deliver further advances for multi-platform biological data assimilation, data assimilation of

phytoplanctonic functional types and delivery of ecosystem enriched products. There is an

expectation that the integrated Atlantic Ocean observing system will increase the number

and quality of in situ observations on chemistry, biology and ecology over the next decade. A

co-evolution of the data use in assessment and predictive models holds great potential for

new products and users.

It is required that results from these projects as well as similar advances in the field be

transferred to CMEMS in order to consolidate the core ecosystem component of the service.



Improved modelling and assimilation capabilities for the representation of ocean

biogeochemistry and the marine food web from primary production to higher trophic

levels (plankton to fish), including estimations of uncertainty;

Relationships between optical properties and biomass for direct assimilation of

optical properties into biogeochemical models;

Improving CMEMS monitoring (i.e. products derived from satellite and in situ

observations) and modelling products to better support aquaculture management

applications;

Improved pH and carbon monitoring and forecasting: carbonate system

observations, modelling and assessment at regional and global scales;

Methods to generate operational products in addition to standard (T, S, Chl, –

oxygen, pH, nutrients, light, plankton biomass) in support of predictive habitat

forecasts, for ecological status and fisheries modelling and risk assessment (e.g.

invasive species, harmful algal blooms, marine protected area planning);

Multi-objective assimilation capabilities, e.g. combining state and parameter

estimation, combining ocean colour and sub-surface data from BGC-Argo, gliders

and other relevant ecological observations especially in regional seas;

Demonstration of consistent interfacing (nesting, downscaling) between open ocean

biogeochemical models and regional/coastal ecosystem models and downstream

applications;

Standardized validation methods for ecosystem model products/variables

(particularly related to non-assimilated observations/variables).


Improved description of benthic-pelagic coupling on short-term (seasonal) and long-

term (decadal) scales; identification of the impact of initial conditions;

Improved methodologies for supplying operational information on sources of

nutrients and pollution/chemicals to the oceans;

Develop a system for routine model estimates of the dose and direct and indirect

effects of pollution on communities of algae, zooplankton and fish larvae.

4.6 SEAMLESS INTERACTIONS BETWEEN CMEMS AND COASTAL SYSTEMS

The coastal monitoring services operated by Member States or private groups will form an

important and strategic group of users of the CMEMS. These activities will enhance the

socio-economic value of CMEMS by contributing to the MSFD, spatial planning and other

downstream applications (offshore operations, coastal engineering, habitat monitoring,

aquaculture, harmful algal bloom monitoring, adaptation and mitigation to climate change).

Downscaling also includes the integration of coastal stations, and the role of CMEMS

regional products is also to fill gaps between coastal observatories.


However, the “one-way” vision of a core service delivering information to downstream users

without feedback to upstream providers has a number of limitations since the coastal strip

should also be considered as an “active” boundary layer that influences the open ocean

region connected to coastal areas. Scientifically, interactions between land, littoral, shelf,

regional and abyssal seas are still a major unknown, poorly characterized and modelled. It is

therefore needed to develop the CMEMS in such a way as to enable more efficient

interfacing with a large variety of coastal systems describing the physical and

biogeochemical coastal ocean states and ecosystems. Future operational circulation models

implemented in the open ocean in CMEMS should enable more flexible coupling with a

variety of model codes and regional configurations specifically customized for coastal

dynamics and benefiting from user experience and practices, including those interfaced with

near-shore, estuary models and hydrological models, unstructured grid models in areas that

require very high resolution with good representation of topographic features.

These issues have been explored in a number of recent EU-funded and national projects,

relying on the coordinating role of EuroGOOS with the objective to consolidate, integrate

and further develop existing European coastal and regional operational observing and

forecasting systems into an integrated pan-European system targeted at detecting

environmental and climate changes, predicting their evolution, producing timely and quality

assured forecasts, and providing marine information services (including data, information

products, knowledge and scientific advices). In the ongoing H2020 CEASELESS project for

instance, it will be demonstrated how the new Sentinel measurements will support the

development of a coastal dimension in Copernicus by providing an unprecedented level of

resolution, accuracy and continuity with respect to present products.

Furthermore, it also becomes timely to explore the possible connections between the

CMEMS and the Copernicus Land monitoring service as coastal users will rely on information

from both services. Therefore, an expert workshop was recently organized by EEA and

Mercator Ocean with the objective to better address user needs in the coastal zone (see

section 6.4). The required developments listed below are partly inspired from the main

conclusions of this expert workshop.


Improved and standardised inputs of freshwater flows and associated river inputs of

particulate and dissolved matter and homogenised river forcing approaches in global,

regional and coastal models;

Improve the interfaces/interactions between coastal monitoring and modelling

systems and CMEMS;

Comprehensive impact studies of CMEMS boundary conditions on coastal systems

(physics, biology) and their applications (e.g. MSFD);

Data assimilation and ensemble forecasting improvements to better serve the coastal

applications;


Development of flexible interfaces between regional and coastal models, including

near-shore and estuarine models and with the capability to connect structured and

unstructured grids.


Adoption of robust standards to ensure compatibility between CMEMS and

downstream systems;

Connection and coupling with land hydrology models.

4.7 COUPLED OCEAN-ATMOSPHERE MODELS WITH ASSIMILATIVE CAPABILITY

Expected evolutions

While coupled ocean-atmosphere models have been developed for a while in the context of

climate research and weather forecasting, the MFC systems in CMEMS are currently based

on a “forcing mode” approach (except for the GLO-CPL forecasting system) in which the

ocean is driven by surface momentum, heat and freshwater fluxes computed using specified

atmospheric information at fairly coarse space-time resolution. This could be an issue due to

the different scales of variability in the atmosphere and ocean systems. In particular, the lack

of feedback at fine scales between ocean and atmospheric models leads to inconsistencies

and has implications for the practical forecasting capability of regional and coastal

environments. Furthermore, the existence of observations at the ocean-atmosphere

interface is an opportunity to introduce assimilation constraints into coupled models,

especially for regional/coastal applications of interest to Copernicus users.


Advanced assimilation methods targeted to provide improved estimations of upper

ocean properties consistent with sea-surface observations and air-sea fluxes;

Representation of diurnal variability and cool skin layer in forced ocean and coupled

ocean-atmosphere models;

Consistent numerical schemes to improve the representation of ocean-wave-

atmosphere interactions for regional oceanic applications;

Use of ocean wave spectra to determine contributions to boundary layer momentum

fluxes.


Novel ocean forcing approaches that may include simplified atmospheric boundary

layer dynamics and ocean feedbacks at high spatial resolution;

Analyses of impacts and feedbacks resulting from coupling between ocean,

atmosphere and waves on the surface ocean dynamics and biology, including in the

case of extreme events;

Facilitate collaboration with the atmospheric community for exploitation of the

surface observations common to the coupled ocean-sea-ice-atmosphere interface,


such as surface winds, surface currents, SST, waves, radiative, freshwater and heat

flux components, sea-ice concentration, sea-ice thickness and sea-ice temperature;

Multivariate data assimilation into fully coupled ocean-wave-atmosphere dynamical

systems.

4.8 OCEAN CLIMATE PRODUCTS, INDICATORS AND SCENARIOS

Several CMEMS systems produce analyses and reanalyses or multi-year reprocessed

observations that describe ocean variability and changes. Ocean Monitoring Indicators (OMI)

can be derived from these products for tracking ocean mechanisms and/or climate modes

and trends, much as we use global greenhouse gas (GHG) concentrations to follow

anthropogenic effects, and globally averaged SST to monitor warming. CMEMS is developing

OMIs for monitoring the ocean state at global and European scales (see the CMEMS Multi-

Year Product Strategy Plan, section 6.1).

Many users are also interested in future trends and evolution of the marine environment

under different climate scenarios. Earth system and climate model predictions (seasonal to

decadal) and longer-term projections based on GHG scenarios, together with comprehensive

ocean reanalyses, can be used to infer possible changes in the ocean state at regional and

coastal levels, including biogeochemical and other aspects of the marine environment (e.g.,

related to harmful algal blooms and other marine extreme events). In the field of ecology,

our scientific understanding of ecosystems has matured to a point that we may be able to

produce potential scenarios based on our knowledge of potential future change in the

physical system (e.g. water quality, coral bleaching).

Such outcomes require the production of improved ocean reanalyses and multi-year

reprocessed observations suitable for climate change detection, with reduced systematic

errors and improved dynamical and physical consistency and realism. Reanalyses product

quality delivered by the CMEMS will have to be monitored on a continuous basis, using

proven, verifiable and robust methodologies that can be agreed upon with external partners

(see section 6.1). This activity can rely on standard metrics (e.g. as defined in the

international GODAE Ocean View framework) or on new approaches.

These activities will contribute to the Ocean State Reports delivered by CMEMS, and will also

benefit from the development of the Copernicus Climate Change Service (C3S) line.


Development of methods for inferring the future state (from seasons to decades) of

the marine environment (physics and biogeochemistry) at regional and coastal scales,

as well as changes in ecosystems, based on climate model predictions and

projections (and associated tests for quality and reliability);

Development of Ocean Monitoring Indicators based on CMEMS and other products;

specific needs include indicators (i) for the physical ocean state, variability and

http://marine.copernicus.eu/wp-content/uploads/2017/03/CMEMS-MYP_StrategyPlan_final_20170314_v2.pdf



change monitoring (ii) for the health of the ocean (e.g. acidification, deoxygenation,

eutrophication), (iii) for fishery and aquaculture management and (iv) for other

applications such as maritime transport, marine renewable energy, coastal zone

management;

Framework for coordination / intercomparisons with international community efforts

(EuroGOOS, GODAE OceanView, CLIVAR, CMIP activities …);

Methods to ensure quality, homogeneity and robust uncertainty measures in long-

term time-series reconstructed from data or model reanalyses.


Development of methods for inferring the future state (from seasons to decades) of

the marine environment (physics and biogeochemistry) at regional and coastal scales,

as well as changes in ecosystems, based on climate model predictions and

projections (and associated tests for quality and reliability) [continued].

4.9 OBSERVATION TECHNOLOGIES AND METHODOLOGIES

Expected evolution

The observing system, which today provides regular and systematic data on the physical

state and dynamics of the ocean and marine ecosystems, is expected to evolve in several

directions during the next years:

The global in situ component, through coordinated programmes such as Argo and its

extensions (deep ocean, polar seas and BGC), Atlantos in the Atlantic and TPOS2020

in the Pacific Ocean , is expected to more systematically collect data on new chemical

and biogeochemical state variables (oxygen, bio-optical properties, nutrients, pH) in

addition to conventional temperature and salinity profiles, and to increase the

sampling of the deep (below 2000 m) and ice-covered seas;

The European regional and coastal seas will be monitored through more

coordinated, multi-sensors and multi-parameter networks including HF radars,

cabled structures, fixed platforms, ferry boxes, surface drifters, gliders, and other

new technologies, e.g. undertaken under EuroGOOS, EMODnet, the EOOS (European

Ocean Observing System) initiative and other projects (e.g. JERICO-Next, AtlantOS);

The space component will rely on a mixture of operational (e.g. the Sentinel suite)

and exploratory missions, providing sea-level (both along-track and wide-swath),

geoid information, SST, ocean colour, surface salinity, surface wind and currents,

wave properties and sea-ice parameters;

New capabilities are expanded to sample a variety of scales through multi-platform

observing systems that include more and more autonomous platforms with multi-

disciplinary sensors;

Observations delivered through Copernicus or in cooperation with other initiatives

will increase, especially those dedicated to validation measurements following


agreed protocols (e.g. ESA protocols, quality assurance framework for Earth

observation guidance);

Ocean observing systems will be multi-purpose and have multiple uses, observing the

ocean at multiple scales and from the coastal to the open ocean, delivering quality

controlled data to science and society.

New multi-platform and multi-disciplinary approaches combining both in situ (e.g. gliders,

Argo, ships, drifters, fixed platforms) and satellite observations at high resolution will be

needed to resolve a wide range of temporal and spatial scales, to monitor key regions or

processes for the ocean state and its variability and to fill gaps in our knowledge connecting

physical processes to ecosystem response (e.g. BGC Argo, TPOS2020, Atlantos, GOOS). In

addition, there is a huge potential to more efficiently access/use data from different

industrial platforms, including off shore power stations.

The core data set assimilated in CMEMS real-time models or multi-year reanalysis systems

include SST, sea-level anomalies and T/S profiles (almost systematically), sea-ice

concentration (whenever possible), and chlorophyll concentration (occasionally). In addition

to consolidating the assimilation of such data, a broader list of parameters should be

integrated into monitoring and forecasting systems within the next 3-10 years.


Improved processing of Sentinel 1, 2, 3 data for coastal ocean products and

applications;

Adaptation of existing quality-control methods to new observing system

components, both in situ (for instance new biogeochemical parameters) and satellite,

with a focus on Sentinel observations and future exploratory missions (e.g. CFOSAT,

SWOT); advancement and adoption of international calibration and quality-control

procedures;

Developments of advanced protocols for real-time quality checking and automated

flagging procedures that are more consistent with nowcast/forecast information

delivered by MFCs;

More consistent processing and assembly of data from different, heterogeneous

observation platforms and sensors for estimating derived quantities (e.g. sea-ice

products, surface currents, mixed-layer depth, primary production, nutrients from

temperature, salinity and O2 vertical profiles etc.);

Incremental development of assembly centres to include more observations relevant

to coastal waters but also of interest to the monitoring of regional seas.


Exploitation of new technologies and platforms to more systematically observe pH

and pCO2 in ocean basins ;

Adaptation of assembly centres procedures to take advantage of new sensors,

communication technologies and unification of procedures, protocols, access and

download systems across assembly centres.


4.10 OBSERVING SYSTEMS: IMPACT STUDIES AND OPTIMAL DESIGN

Expected evolutions

Regarding future observing systems (from space or in situ), the best possible basis is

required in the design and exploitation of observation networks and satellite constellations.

This goal can be ideally achieved through impact and design studies (Observing System

Experiments – OSEs; Observing System Simulation Experiments - OSSEs) and dedicated

process experiments and pilots. OSEs and OSSEs represent a useful investment when

expanding an existing observing system, defining a new one, or preparing the assimilation of

new data types, or data with improved resolution/accuracy. They are also required for

design studies to re-assess the sampling of the present in situ networks, define the required

extensions, and prepare the assimilation of new in situ data types considering the synergies

with satellite observations. Such approaches enable a consistent approach to the

assessment of the impact of observation data, assimilation techniques and analysis/forecast

systems, the definition and operation of space missions (upstream and downstream) and in

situ networks.

The existing TAC and MFC capabilities provide an excellent opportunity to develop a new

functionality within the CMEMS, and conduct impact studies and observing system design

based on rigorous and objective methodologies. This functionality will consolidate the link

between CMEMS and the data providers by formalizing recommendations on future

observing systems. In return, improving the design of future observing systems will be of

great benefit to CMEMS itself given the likely impact on the products quality.


Adaptation of tools and diagnostic methods such as Degrees of Freedom Signal (DFS)

and Forecast System Observation Impact (FSOI) to measure the impact of

observations into ocean monitoring and forecasting systems;

Adaptation of assimilation interfaces (e.g., observation operators) to new satellite

sensors: wide-swath altimetry, ocean colour, SST from Sentinels, surface currents …;

Development of more robust methodologies (i.e. to ensure results as independent as

possible from model and error assumptions) and automatic tools to conduct impact

studies (including the OSE class);

Impact studies of new observation data types or products for ocean analyses,

forecasts and reanalyses (e.g. SSS from space, Sea Ice thickness from Cryosat and

SMOS, surface current data sets, BGC-Argo, HF Radars, etc.);

Network studies that will provide guidance to deployments: this includes identifying

critical ocean observation points and regions where the benefit to forecast skill and

ocean analyses and reanalyses can be maximized.


Design studies to re-assess the sampling of the present-day in situ T/S network (Argo

including BGC-Argo, ships, buoys, moorings);


Guidance to the in situ observation communities on how to optimize observing

strategies and the synergies with Sentinel and future wide-swath altimetry missions

(SWOT), complementing the ongoing AtlantOS effort.

4.11 ADVANCED ASSIMILATION FOR LARGE-DIMENSIONAL SYSTEMS

Expected evolutions

The operational suites implemented in the CMEMS MFCs essentially rely on traditional

assimilation methods inherited from the Kalman filter or the 3DVAR approach including

simplifications and adaptations to make them tractable with large-dimensional systems.

Today, only the Arctic MFC has explicitly implemented the EnKF to propagate the spread of

an ensemble of likely states between successive updating steps, though several other MFCs

intend to implement ensemble approaches in the future (Global, Mediterranean, Baltic

MFCs, Figure 1).

The current trend in oceanic and atmospheric data assimilation is a move toward

probabilistic methods inherited from the Bayesian estimation framework, as reflected in a

variety of activities conducted in recent projects (e.g. FP7 SANGOMA), or reported in

workshops (e.g., GODAE Ocean View task teams) and conferences (WMO symposium on

Data Assimilation).

At CMEMS level, it becomes urgent to take advantage of these developments in order to

(i) further develop the assimilation methods to enable implementation into systems

involving different components (coupling with atmosphere, biology, biogeochemistry,

cryosphere, etc.), (ii) improve the coupling between assimilative systems with different

target resolutions and different assimilation parameterizations, (iii) implement an effective

production of probabilistic information as needed by users to support decision-making, and

(iv) improve the physical consistency of ocean state estimations, ensuring that the small-

scale dynamics simulated by ocean models is in balance with the larger scales captured by

the observing systems.

In the NEMO framework (most MFCs systems are based on NEMO), a new assimilation

component has been implemented in the reference version that includes several modules

(observation operators, linear-tangent and adjoint of the circulation model, incremental

updating schemes) to facilitate coupling with various assimilation systems. It is also planned

to include an ensemble simulation mode in future versions of NEMO. Other efforts on

modular software development have also been initiated in European institutions, such as the

Object-Oriented Prediction System (OOPs) project at ECMWF. A convergence between these

parallel efforts is expected in order to ensure an effective implementation of these

developments into the large-scale systems based on NEMO.


Metrics for ocean analysis/reanalysis and forecasting produced using ensemble

techniques;


Development and application of advanced assimilation methods, including to identify

and understand model bias and forcing errors, with a focus on ocean reanalyses;

Adaptations of ensemble-based assimilation/forecasting systems, and development

of new techniques to increase the range and amount of observations assimilated into

MFCs (e.g. ocean currents, ice thickness, ocean colour), making best use of

Copernicus Sentinel missions;

Common developments on assimilation modules to connect models and assimilation

kernels shared between different MFCs;

Extension of conventional assimilation schemes to include image data information

(SST, Ocean Colour) in addition to pixel data;

Efficient methods to account for complex observation and modelling error structures

(incl. non-Gaussian errors) in assimilation algorithms;

Adaptation of analysis schemes to process different spatial and temporal scales

during the analysis stage;

Adaptation of analysis schemes to preserve the consistency of non-observed

quantities such as vorticity, diffusion, vertical velocity, passive tracers etc.;

Verification methods and intercomparison protocols (rank histograms, Continuous

Rank Probability Score, …) suitable to assess the reliability of ensembles in

probabilistic assimilation systems;

Inverse methods that will incorporate simplified balance relationships (e.g.

geostrophic and vorticity balance, omega equation) to ensure physically consistent

products.


Development of data assimilation tools for coupled models (ocean-atmosphere

including waves, physics-biogeochemistry, ocean-shelf models), including consistent

coupled initialization approaches and flux correction schemes at interfaces;

Developments of software infrastructure that can accommodate different

assimilation methods and facilitate the sharing of algorithms and optimization of

computer codes (models, assimilation schemes) on HPC.

4.12 HIGH-LEVEL DATA PRODUCTS AND BIG DATA PROCESSING

Expected evolutions

CMEMS needs to enrich its offer with improved accessibility and quality controlled data, in

agreement with scientific community standards. Users are also requesting advanced data

products that should rely on more complex processing of measurements of essential ocean

variables at higher resolution, including the provision of composite products and their

uncertainty estimates. Those data products will feed monitoring and forecasting systems or

validate model outputs. The ESA Climate Change Initiative and the Copernicus Climate


Change Service (C3S), for instance, will deliver advanced products that will benefit the

CMEMS reanalyses production.

The methodologies in place today for merging, filtering, compressing and interpolating

observations (until now mostly based on statistical interpolation methods) will need to be

adapted to face the challenges of big data streams and observing systems that are

heterogeneous in terms of space-time sampling, resolution and accuracy. An additional issue

to address is how to take advantage of the high quality delayed mode data in order to get

improved reanalyses of the ocean state for assessing changes and updating climatologies.


New high resolution ocean colour products from Sentinel 2 and synergy with Sentinel

3 OLCI products;

Development of advanced data products merging different type of observations

through multivariate analysis (e.g. for chlorophyll, surface currents, ice drift and ice

thickness);

Reprocessing of existing data sets with more advanced quality control methods, to

continuously improve the ocean reanalysis effort including for detection of change;

Specific processing and mapping of data product uncertainties for both direct use,

validation purposes, and data assimilation;

Discrimination methods between steric and non-steric components in observed sea

level anomaly signals, both for data processing and assimilation into models;

Preparation of composite data products and derivation of quantities that can be used

to infer transport from tracer information, or vice versa;

New bathymetric data with very high resolution, and possibly information about

changes in ocean bottom, including impact assessment on ocean analyses and

forecasts.


Data mining and image processing techniques needed to facilitate the automatic

extraction and analysis of patterns from big data sets (produced by observing and/or

modelling systems) and to better respond to user’s needs.


5 THE SERVICE EVOLUTION ROADMAP

FOR 2021 AND BEYOND

In this section, the outline of the service framework anticipated in 2021 is described

together with the completed and ongoing Tier-3 R&D projects to be taken into account for

the definition of priorities in future calls, and the main scheduling of service evolution

projects until the end of the CMEMS implementation period. The CMEMS technical annex

provides the framework for the implementation of the CMEMS in terms of functionalities

and operational tasks.

The 12 R&D areas developed in the previous section should be covered in such a way as to

ensure that CMEMS can evolve towards the targeted service lines foreseen for 2021 and

after. While the 12 R&D areas are all relevant and essential at present to reach the

objectives initially defined for the CMEMS, priorities are re-adjusted periodically according to

updates of user requirements, the status of scientific developments achieved within and

outside the CMEMS community, and to the high level CMEMS evolution strategy.

5.1 THE TARGETED CMEMS SERVICE IN AND AFTER 2021

The CMEMS is currently designed to deliver products to users in four main domains of

application:

i. marine safety, which requires information at very high resolution in focused areas all

over the globe to support marine operations, marine weather forecasting, sea ice

forecasting, combating oil spill, informing ship routing and search and rescue

operations, and all activities requesting offshore operations;

ii. marine resources, with applications to the sustainable management of living marine

resources, through fisheries and aquaculture;

iii. coastal and marine environment, with applications that require good knowledge of

environmental status in coastal areas in terms of physical, chemical and biological

components and their variability;

iv. weather, seasonal forecasting and climate, with needs for accurate information near

the surface and sub-surface ocean, on a daily or shorter time basis, in real time and

delayed mode.

With respect to the existing CMEMS offer and based on existing and future user needs, the

following evolutions of the service in terms of technical and scientific content of its products

are proposed:

http://copernicus.eu/sites/default/files/library/CMEM_TechnicalAnnex_PUBLIC.docx.pdf


Staying a world-leading reference source of information for operational players in the

marine domain through improved product consistency (especially of reprocessed

time series and reanalyses), quality accuracy and assessment, multi-data approach

with scientific inter-calibration and assessment;

Improving the physical information content of CMEMS products by increasing

resolution in space and time of models and observations, adding the representation

of physical processes, going towards more coupled systems (ocean circulation –

waves – sea ice – atmosphere – biogeochemistry – ecosystems) to produce

consistent estimates of the full ocean state;

Improving assimilation schemes, in particular for biogeochemical data, taking

advantage of the considerable investment in observation infrastructure and increase

of data flow, especially through the Sentinel constellation that will be in place in 2021

in tandem with the in situ component; these techniques should also take into

account new HPC architectures and computing facilities available in 2021;

Meeting the “marine biology” demand and reach the level of excellence CMEMS has now for the “marine physics”. This also includes providing more information on biogeochemistry and higher trophic levels (from plankton to fish) to better support fisheries management, living resources protection, sustainable exploitation of marine biomass;

Enhancing ocean climate and ocean health monitoring (physics and biogeochemistry

including O2 and pH), supported by the release of annual Ocean State Reports2,

informed by annual analyses of the state of the global ocean and the European

regional seas, in particular for supporting the Member States in their assessment

obligation;

Assessing past and future climate change impacts on the ocean environment: transform the high level CMEMS expertise on the ocean physical, biogeochemical states, ocean health and ecosystems, into a strong assessment capacity on the ocean climate, propose assessment capacity and what-if scenarios, including projections of the ocean state (physical, biogeochemical, ecosystems) at regional scales from weeks to decades for climate change scenarios;

Supporting coastal area monitoring by Member States through the provision of

suitable interfaces and boundary conditions by CMEMS for efficient EU leverage for

supporting coastal environment knowledge and economy. Co-production and

operation between the CMEMS and the national coastal systems should be

encouraged, with adaptations at the level of coastal seas benefiting from user

experience and practices (see also section 6.4).

2 The first issue of the Ocean State Report is available here (doi: 10.1080/1755876X.2016.1273446). See also

section 6.1 for the CMEMS Multi-Year Product Strategy Plan.

http://www.tandfonline.com/doi/full/10.1080/1755876X.2016.1273446


These objectives will have to be covered by CMEMS Tier-2 projects (see below) and 3-6 years

R&D plans of the TACs/MFCs. The CMEMS technical annex identifies additional service lines

more specifically motivated by Member States’ requirements.

The CMEMS service is operated today in an overarching framework that includes other

Copernicus services, such as the Atmosphere service (CAMS, ECMWF), Land service (CLMS,

EEA, JRC), Emergency service (EMS, JRC), Security service (EMSA, FRONTEX, SATCEN) and

Climate Change service (C3S, ECMWF), as well as a community of new users consolidated

through dedicated user uptake calls. This landscape will smoothly modify the profile of

capabilities and users and service needs, including new users at the intersection between

different Copernicus services. However at present, existing R&D projects and service

priorities largely align with the Marine Service overarching objectives.

5.2 TIER-3 R&D MARINE PROJECTS OF INTEREST TO CMEMS

This section provides a status of Tier-3 (i.e., long-term objectives) R&D projects that are

identified in 2017 as relevant for the CMEMS service evolution.

Completed projects

A number of projects, including those implemented under the Space theme in 2012, have

been completed in 2014/2015:

E-AIMS: improved European contribution to the international Argo observing system

in support to scientific and operational challenges for in situ monitoring of the world

ocean.

MyWave: preparation of the scientific grounds for a wave component of the marine

service.

OSS2015: consolidation of biogeochemical products, information and services based

on models, in situ and satellite observations.

OPEC: improvement of operational services for biochemistry and ecological

parameters at time scales from days to decades, with a focus on ecological status of

coastal and shelf seas.

SANGOMA: preparation of the new generation of stochastic data assimilation

methods for ocean physical and biological model applications.

Ongoing and newly decided EU projects

HIGHROC: FP7 project (2014-2017) to conduct R&D necessary for the next

generation of coastal water products and services from ocean colour space-borne

data by giving an order of magnitude improvement in both temporal and spatial

resolution;

JERICO-NEXT: H2020 project (2015-2018) which aims at providing a solid and

transparent European network for operational services delivering high quality

environmental data and information products related to marine environment in

European coastal seas;

http://copernicus.eu/sites/default/files/library/CMEM_TechnicalAnnex_PUBLIC.docx.pdf

http://www.copernicus.eu/main/services


AtlantOS: H2020 project (2015-2019) which aims at optimising and enhancing the

integrated observing systems in the Atlantic Ocean (northern and southern basins),

with a focus on in situ platforms and considering European as well as non-European

projects (TPOS in the tropical Pacific, and SOOS in the southern ocean) and partners.

IntarOS: a new H2020 project (2016-2020) to build up an integrated and unified

holistic monitoring system for the different parts of the Arctic, including tools for

integration of data from atmosphere, ocean, cryosphere and terrestrial sciences.

ODYSSEA: H2020 project (~2017-2021) downstream of CMEMS to develop, operate

and demonstrate an interoperable and cost-effective platform that fully integrates

networks of observing and forecasting systems across the Mediterranean basin,

addressing both the open sea and the coastal zone.

SPICES: H2020 project (2015-2018) which aims at developing new methods to

retrieve sea ice parameters from existing satellite sensors to provide enhanced

products for polar operators and prediction systems.

CEASELESS: H2020 project (2016-2019) that will demonstrate how the new Sentinel

measurements can support the development of a coastal dimension in Copernicus.

CoReSyf: H2020 project (2016-2019) that aims at supporting the development of

coastal research through satellite data by creating an online platform delivering Earth

observation data for coastal water monitoring.

A variety of new projects supporting mainly the development of downstream services are

also of potential interest to the evolution of the CMEMS (e.g., AQUA-USERS, SAFI, SWARP,

BASE-platform, EO4life, EONav, Copernicus App Lab, CYANOLAKES, EOMORES, SPACE-O and

MARINE-O EO-1 &2 projects) and should be monitored to some extent by CMEMS experts.

R&D gaps for future H2020 calls

The guidance document published by the EC in 2015 (“Research needs of Copernicus

operational services”) identified 4 key actions needed to implement the CMEMS over the

period of 2014-2020, taking into account evolving user needs and technological

developments.

These 4 key actions (that were based on the first version of this roadmap) are associated to

the following scientific and technical challenges:

1. Solving ocean dynamics at kilometric resolution,

2. Designing future observing systems and related assimilation methods,

3. Developing seamless information chains linking dynamics, biogeochemistry and

ecosystem essential variables,

4. Seamless interactions between CMEMS and coastal monitoring systems.

The table below shows that a number of H2020 projects recently implemented will address

some of these challenges (mainly action 2 and 4), while other actions [(1) and (3)] are still

needed to meet the objectives.

https://www.google.fr/search?q=european+commision+guidance+document+Research+needs+of+Copernicus+operational+services&ie=utf-8&oe=utf-8&client=firefox-b&gfe_rd=cr&ei=CWsZWcW-GYvBaIrqk8AC

https://www.google.fr/search?q=european+commision+guidance+document+Research+needs+of+Copernicus+operational+services&ie=utf-8&oe=utf-8&client=firefox-b&gfe_rd=cr&ei=CWsZWcW-GYvBaIrqk8AC


1. Solving ocean dynamics at km resolution

2. Designing future observing systems and related assimilation methods

AtlantOS, Jerico-NEXT, IntarOS, SPICES, CEASELESS

3. Developing seamless chains linking dynamics, biogeochemistry and ecosystem

4. Seamless interactions between CMEMS and coastal monitoring systems

CEASELESS

5.3 TIER-2 R&D MARINE PROJECTS SELECTED BY CMEMS

This section provides an overview of the Tier-2 (i.e., medium-term objectives) R&D projects

that were selected for the CMEMS Service Evolution call 21-SE-CALL1 released in autumn

2015. An outline of the 12 selected project including project participants and abstracts can

be found online and in section 6.2.

The 2015 CMEMS R&D Service Evolution call included 5 lots:

Ocean circulation, ocean-wave and ocean-ice coupling (3 projects selected):

proposals funded under this theme are mainly addressing sub-mesoscale processes

(R&D area 4.2), ocean-wave (R&D area 4.3) and ocean-sea ice coupling (R&D area

4.4).

Marine ecosystems and biogeochemistry (3 projects selected): the funded projects

cover several R&D objectives identified under area 4.5, specifically modelling of

higher trophic levels in ecosystems and data assimilation capabilities.

Links with coastal environment (2 projects selected): one project addresses

upscaling issues under R&D area 4.6, while the other focuses on regional data

assimilation and ensemble forecasting;

Ocean-Atmosphere coupling and climate (1 project selected): the project focuses on

the momentum exchange across the ocean-atmosphere interface in regional ocean

prediction systems and the value of providing CMEMS products from ocean-wave

systems that are fully coupled with an atmospheric component relative to those

running in forced mode (R&D area 4.7);

Cross-cutting developments on observation, assimilation, and product quality

improvement (3 project selected): proposals funded under this theme address (i)

satellite SST assimilation with a proper account of the diurnal cycle, (ii) the

integration of existing European high-frequency radar operational systems into the

CMEMS, and (iii) synergistic use of satellite and in situ data to infer the state of the

upper ocean and associated flux of tracers and energy at fine scale.

A preliminary review of the projects took place in early 2017 to identify if all projects were

on track and to assess in advance the range of results of potential interest for the Tier-1

work plan. For the next call for tenders to be released in August 2017, priorities should be

targeted towards the R&D areas and objectives not covered so far or complementary to the

http://www.mercator-ocean.fr/en/mercator-ocean/copernicus/service-evolution/


on-going R&D projects; they should also take into account results and recommendations

from on-going R&D projects.

5.4 SERVICE EVOLUTION ROADMAP AND MILESTONES UNTIL 2021

The CMEMS R&D roadmap until 2021 will be implemented as illustrated below. In addition

to programmatic aspects, a number of milestones relevant to the service evolution R&D will

complement the roadmap, e.g. the Copernicus Marine Week to be held in Brussels (25-29

September 2017).

At Tier-2 level, the 12 CMEMS R&D projects selected in early 2016 (from the fall 2015 21-SE-

CALL1) will terminate at the end of Phase 1, so as to provide guidance to the Tier-1 R&D

work plans that will have to be developed in the TACs/MFCs tenders covering phase 2. The

second Tier-2 CMEMS call for tenders (66-SE-CALL2), to be released in August 2017, will

mainly impact the CMEMS after 2021: this will set a clear programmatic constraint on the

definition of the long-term CMEMS strategy for the post 2021 period.

At Tier-3 level, ongoing H2020 projects are expected to deliver results of interest to CMEMS,

but not before 2018. The newly EU-funded projects (e.g. under the Space EO-3-2016) are

expected to provide elements for the future CMEMS period starting in 2021.

http://www.copernicusmarineweek.eu/


6 APPENDICES

6.1 SERVICE EVOLUTION STRATEGIC DOCUMENTS

The CMEMS Service Evolution strategy is described in the CMEMS High-Level Service Evolution Strategy document1.

Two other documents provide specific details on the CMEMS Strategies for product quality assessment and monitoring and multi-year reprocessed and reanalysis products.

These documents have been prepared by Mercator Ocean with the support of the CMEMS STAC.

6.2 CMEMS SERVICE EVOLUTION CALL 21-SE-CALL1 SELECTED PROJECTS

ARCTICMIX. IMPACT OF ADDITIONAL CONTRIBUTIONS TO THE VERTICAL MIXING FOR THE

SIMULATION OF ARCTIC OCEAN AND SEA-ICE STATES

PI: Fabrice Ardhuin (CNRS/LOPS).

Co-Is: Camille Lique (IFREMER), Claude Talandier (CNRS), Mickael Accensi (IFREMER), Marion Huchet (CNRS).

Abstract: The Arctic Ocean is experiencing some rapid transformations, including a fast shrinking of the sea-ice cover, with potential impact on global ocean and climate. A seasonally ice-free Arctic would allow new prospects for socio-economic activities in the region. Understanding and forecasting these changes thus requires an accurate model simulation of the Arctic ocean and sea-ice states. Yet, most Arctic models are largely biased, and vertical mixing has been identified as a key parameter controlling the realism of the ocean and sea-ice states. Here, we propose to evaluate the effect of the implementation in a high-resolution model of different sources of vertical mixing (namely, the surface waves, tide, and double diffusive mixing) on the simulation of ocean and sea-ice state. The surface wave contribution will be implementing following previous work on the waves impact in ice-free regions, and on-going studies on the impact of waves on sea-ice rheology in the marginal sea-ice zone, and the characterization of the potential feedback on the sea-ice melt via the ocean mixing. All model developments and the evaluation of the impact of different mixing parameterizations resulting from this project will be directly applicable to the global NEMO ORCA12 configuration used by CMEMS.

DIMUP. DIAGNOSE, INTERPRET, MONITOR UPPER OCEAN CIRCULATION: NOVEL DATA

SYNERGIES VIA DYNAMICAL EXPLORATION

PI and organization: Fabrice Collard (Ocean Data Lab).

Co-Is: Lucile Gaultier (Ocean Data Lab), Erwan Hascoët (Ocean Data Lab).



http://marine.copernicus.eu/wp-content/uploads/2017/03/CMEMS-PQ-StrategicPlan-v1.6-1.pdf

http://marine.copernicus.eu/wp-content/uploads/2017/03/CMEMS-PQ-StrategicPlan-v1.6-1.pdf


http://marine.copernicus.eu/science-learning/service-evolution/about-stac/

http://marine.copernicus.eu/science-learning/service-evolution/about-stac/


Steering committee: Aurélien Ponte (IFREMER), Patrice Klein (IFREMER), Joe LaCasce (Univ.

Oslo), Bertrand Chapron (IFREMER), Vladimir Kudriavtsev (Univ. St Petersburg).

Abstract: The main objectives of this proposal are to develop and apply innovative methods

that infer, from satellite and in situ observations, the state of the upper ocean and

associated horizontal and vertical fluxes of tracers and energy. These methods leverage an a

priori knowledge of the dynamics (embedding in a quasi-geostrophic mesoscale eddy field

topped by a turbulent mixed-layer) whose validation, in terms of spatio-temporal scales and

background environmental conditions, represent the cornerstone of the proposal. This

project directly addresses the R&D priority 4.6 (“Sub-mesoscale- mesoscale interactions and

processes”) of the CMEMS Service Evolution Strategy, and will contribute to the R&D priority

4.2 (“From big data streams to high-level data products “) through the development of new

products and physical diagnostics. Several very high resolution basin scale numerical

simulations have recently suggested the strong dynamical impact of fine scale (below the

Rossby deformation radius) ocean processes. In this context, we propose to thoroughly

assess the role and observability of these fine scales by an approach combining remote

sensing, realistic high-resolution modelling and idealized dynamical models. This effort will

provide CMEMS with dedicated practical tools and improved products to better resolve

these scales.

GREENUP. GREEN MATRIX UPLOADED: A NEW ECOSYSTEM VARIABLE FOR MARINE

RESOURCES SECTOR

PI and organization: Patrick Lehodey (CLS).

Co-Is: Pedro Afonso (IMAR), Mark Payne (DTU).

Abstract: The objective of the present project is to extent the CMEMS products catalogue by developing a new product covering a key ecosystem component at the mid-trophic level, i.e. the micronekton, to better address the Marine Resources area of benefit. Indeed, providing both real time and hindcast simulation of micronekton distributions produced from CMEMS physical (temperature, currents) and biogeochemical (primary production, euphotic depth) existing products would assist in the development of new management tools by various research and fisheries organisations and would pave the way for new approaches to the management and monitoring of marine resources. The work will consist firstly in developing and set up the micronekton model for the north Atlantic ocean, to produce demonstration products that will then be used within two Use Cases.

INCREASE. INNOVATION AND NETWORKING FOR THE INTEGRATION OF COASTAL RADARS

INTO EUROPEAN MARINE SERVICES

PI and organization: Julien Mader (AZTI).

Co-Is: Anna Rubio (AZTI), Ainhoa Caballero (AZTI), Luis Ferrer (AZTI), Antonio Novellino (ETT), Giuseppe Manzella (ETT), Paolo D’Angelo (ETT), Marco Alba (ETT).


Abstract: The accurate monitoring of surface transport, which is inherently chaotic and depends on the details of the surface velocity field at several scales, is key for the effective integrated management of coastal areas, where many human activities concentrate. This has been the driver for the growth of coastal observatories along the global ocean coasts. Among the different measuring systems, coastal High Frequency Radar (HFR) is the unique technology that offers the means to map ocean surface currents over wide areas (reaching distance from the coast of over 100km) with high spatial (a few kms or higher) and temporal resolution (hourly or higher). Consequently, the European HFR systems are playing an increasing role in the overall operational oceanography marine services. Their inclusion into CMEMS is crucial to ensure the improved management of several related key issues as Marine Safety, Marine Resources, Coastal and Marine Environment, Weather, Climate and Seasonal Forecast. In this context, INCREASE will set the necessary developments towards the integration of the existing European HFR operational systems into the CMEMS, following four main objectives: (i) Provide HFR quality controlled real-time surface currents and key derived products ; (ii) Set the basis for the management of historical data and methodologies for advanced delayed mode quality-control techniques; (iii) Boost the use of HFR data for improving CMEMS numerical modelling systems; and (iv) Enable an HFR European operational node to ensure the link with operational CMEMS.

MASSIMILI. DEVELOPMENT OF A BIOGEOCHEMICAL MULTI-DATA ASSIMILATION SCHEME TO

INTEGRATE BIO-ARGO DATA WITH OCEAN COLOUR DATA INTO CMEMS-MFCs

PI and organization: Gianpiero Cossarini (OGS).

Other members of the proposing team: Stefano Salon (OGS), Heloise Lavigne (OGS), Laura Mariotti (OGS), Fabrizio D’Ortenzio (UPMC-LOV), Vincent Taillandier (UPMC-LOV), Alexandre Mignot (UPMC-LOV).

External experts: Christel Pinazo (MIO), Clément Fontana (Geoid-Ocean).

Abstract: In MASSIMILI we aim to develop a multi-data assimilation framework to integrate Bio-Argo data with ocean colour data into the biogeochemical modelling systems of the CMEMS MFCs. We will start by qualifying the multi-data and multivariate biogeochemical datasets (Bio-Argo and ocean colour) to be used by the assimilation scheme. Then we will develop the numerical components of a new multi-data scheme which assimilates chlorophyll, nitrate and oxygen in the frame of the 3DVAR variational scheme already implemented in the biogeochemical component of the CMEMS MED-MFC. Finally, we will assess the impacts of the new multi-data assimilation scheme to the CMEMS biogeochemical products following a protocol of different tests, by adopting new skill performance metrics specifically developed in the project to validate the multi-data assimilation with selected observational datasets. The proposed activities of MASSIMILI will benefit the users by increasing the quality of the CMEMS biogeochemical products with a better quantification of the model errors. We will also contribute to the capacity building for CMEMS TACs and MFCs involved in biogeochemical multi-data use and assimilation. Further, MASSIMILI will provide feedback/suggestions on the efficiency/performances of the existing and future Bio-Argo networks.


MEDSUB. UNDERSTANDING MESO AND SUBMESOSCALE OCEAN INTERACTIONS TO IMPROVE

MEDITERRANEAN CMEMS PRODUCTS

PI and organization: Simon Ruiz (CSIC / IMEDEA)

Co-Is: Ananda Pascual (CSIC/IMEDEA), Antonio Sanchez-Roman (CSIC/IMEDEA), Evan Mason (CSIC/IMEDEA), Joaquin Tintoré (SOCIB), Mélanie Juza (SOCIB), Baptiste Mourre (SOCIB).

Abstract: The objective of this project is to contribute to the improvement of CMEMS products based on new understanding of the fine-scale ocean circulation. To achieve the objective, a multi-platform approach, combining in situ and satellite data in synergy with numerical models, is proposed. The underlying scientific goal is to enhance our knowledge of 2D/3D (including vertical exchanges) mesoscale and submesoscale processes and their interactions at different scales. The project focuses on the Mediterranean Sea, characterized by intense meso and submesoscale features (e.g fronts, meanders, eddies and filaments), and where the team has a broad experience. Main actions of the project include (1) to analyze CMEMS MFCs and TACs products and (2) to assess and validate CMEMS products using high-resolution multi-platform observations (glider, drifters, ship CTD, ADCP, Argo, etc) from recent field experiments. Particular attention will be devoted to providing feedback to the MFCs. The benefit for CMEMS will be the evaluation of model products from Monitoring and Forescasting Centers (MFCs) and in situ and satellite Thematic Assembly Centers (TACs), to assess their capacity to investigate meso and submesocale processes. Finally, a set of recommendations will emerge to improve CMEMS products, with particular emphasis on the 2D/3D ocean circulation at meso and submesoscale.

OWAIRS. OCEAN-WAVE-ATMOSPHERE INTERACTIONS IN REGIONAL SEAS

PI and organization: Huw Lewis (Met Office)

Other members of the proposing team: Chris Harris, Andy Saulter, Juan Castillo Sanchez, Tamzin Palmer (Met Office).

Abstract: Focused research through ocean, wave and atmospheric science disciplines will improve the representation of momentum exchange across the ocean-atmosphere interface in regional ocean prediction systems. This study objectives are: • Improve the consistency of ocean and wave prediction systems within CMEMS between those derived from either “forced”, partially or fully “coupled” modes, • Examine the sensitivity of ocean-wave-atmosphere feedbacks to model physics and system resolution choices, • Demonstrate the value of providing CMEMS products from ocean-wave systems that are fully coupled with an atmospheric component relative to those running in forced mode.

This project will deliver technical developments to NEMO interface routines and case study evaluations focused on the North-West Shelf. The research builds on unique modelling capability and a fully self-consistent and flexible evaluation framework with which to run traceable experiments. Following this work the CMEMS community will have available an enhanced ocean model infrastructure and demonstration of a more robust methodology for


assessing forced and fully coupled prediction systems. Improved understanding and evidence of the impacts of closer coupling will be delivered. These will inform future system configuration choices. Developments will readily translate into CMEMS service evolution across MFCs, improving the quality of information provided to users.

SCRUM. STOCHASTIC COASTAL/REGIONAL UNCERTAINTY MODELLING:

SENSITIVITY, CONSISTENCY AND POTENTIAL CONTRIBUTION TO CMEMS ENSEMBLE DATA

ASSIMILATION

PI and organization: Sarantis Sofianos (Univ. of Athens). Other members of the proposing team: Vassilios Vervatis (Univ. of Athens), Pierre De Mey (CNRS/LEGOS), Nadia Ayoub (CNRS/LEGOS). External expert involved: George Triantafyllou (HCMR), Charles-Emmanuel Testut (Mercator Ocean). Abstract: The proposed work aims at strengthening CMEMS in the areas of regional/coastal ocean uncertainty modelling, Ensemble consistency verification, and Ensemble data assimilation. The work is based on stochastic modelling of ocean physics and biogeochemistry, in the context of coastal/regional Ensemble Data Assimilation (EDA) forecasting systems, and includes novel Ensemble consistency verification methods. The work is designed for the Service Evolution framework within “Lot 3: links with coastal environment”. In a first step, we will use stochastic modelling to generate Ensembles describing uncertainties in coastal/regional domains. In a second step, we will introduce and test two methodologies aimed at checking the consistency of the above Ensembles with respect to TAC data and arrays. In addition, we wish to showcase the use of those Ensemble-modelled uncertainties in a pilot data assimilation exercise, and contribute to the CMEMS DA team guidance in support of upcoming decisions regarding the evolution of regional/coastal data assimilation schemes in CMEMS. SOSSTA. STATISTICAL-DYNAMICAL OBSERVATION OPERATOR FOR SST DATA ASSIMILATION

PI and organization: Andrea Storto (CMCC).

Co-Is: Gerasimos Korres (HCMR), Sam Pimentel (TWU), Nadia Pinardi (CMCC), Isabelle Mirouze (CMCC), Eric Jansen (CMCC), Francesca Macchia (CMCC).

Abstract: Advancing capability to effectively assimilate satellite observations of SST with proper account of diurnal cycle together with thermo-dynamical coupling with near-surface ocean state is highly relevant to increasing accuracy of ocean analysis and prediction.

To ensure benefits of advanced SST assimilation in the future for diverse operational systems, as well as to enhance capacity to make optimal assessments of impact of current and future satellite SST observations in step with progress in the ocean satellite observing, it is desirable to investigate more efficient approaches. The objective of this project is to develop and test a new technique for producing dynamically-based but highly efficient


statistical observation operators for assimilation of daily satellite SST observations that could be easily implemented with any data assimilation technique. The technique consists of application of statistical method of canonical correlation analysis to joint data from a process model of near surface ocean thermo-dynamics and the corresponding satellite retrievals of SST from different sensors. This approach may streamline the progress toward improving the SST-DA in different operational DA systems in CMEMS, enriching overall DA technology available in CMEMS in support of improving the capacity to perform optimal assessments of SST observation impacts.

TOSCA. TOWARDS OPERATIONAL SIZE-CLASS CHLOROPHYLL ASSIMILATION

PI and organization: Stefano Ciavatta (PML).

Co-Is: Robert Brewin, Susan Kay, Benjamin Taylor (PML).

Abstract: This project will evolve the capability of CMEMS to monitor and simulate biogeochemical indicators of the health of European shelf-seas, by developing the first system assimilating ocean colour data of size-class chlorophyll (SCC) into pre-operational ecosystem models. This project goes beyond state-of-the-art operational models, which assimilate ocean colour data of total chlorophyll, and which are currently challenged by simulating reliably the phytoplankton groups and their biogeochemical and ecological feedbacks. The new assimilation system will be an upgrade to the operational model in use at the CMEMS North West Shelf (NWS) Monitoring and Forecasting Centre (MFC). Firstly, a new algorithm will produce time series of SCC in the NWS; secondly, an operational assimilation system will be upgraded to assimilate SCC; thirdly, the new system will be applied to produce a quality- assessed pre-operational reanalysis of biogeochemical indicators in the NWS. We expect the approach to be exportable to other CMEMS MFCs and to support CMEMS in assessing the state of the ocean. Ultimately, by enhancing CMEMS capability to monitor and simulate biogeochemical indicators, this project will evolve both the ability of end-users to achieve their requirements and marine policy to safeguard marine ecosystems through cutting-edge CMEMS products.

UPSCALING. PROPAGATING INFORMATION BACK FROM COASTAL/REGIONAL MODELS TO

CMEMS

PI and organization: Alexander Barth (Univ. of Liège).

Co-Is: L. Vandenbulcke (Seamod/SC Jailoo).

Abstract: Many high-resolution (regional and coastal) models use CMEMS forecast as boundary conditions. However, no feedback mechanism is presently implemented in the CMEMS-MFCs to benefit from the high-resolution forecasts.

In this proposal, part of the nested models forecasts are extracted, and assimilated as pseudo-observations in the basin-scale model. The procedure is called upscaling. It is cheap (data assimilation is performed anyway in the basin-scale models), but very beneficial as a form of nesting feedback is realized. From the basin-scale MFC point-of-view, the nested


models can be interpreted as «measurement devices» complementing too-sparse (real) observations. The MFCs will also benefit from data assimilation of local and/or ultra-high-resolution observations (e.g. SST) by the nested models. By improving the basin-scale model, in time, through more consistent open sea boundary conditions, the nested models will also be improved. In this project, the upscaling procedure will be tried out using NEMO in the Mediterranean Sea and its North-Western basin.

WAVE2NEMO. COUPLED OCEAN-WAVE MODEL DEVELOPMENT IN FORECAST ENVIRONMENT

PI and organization: Joanna Staneva (HZG).

Co-Is: Oyvind Breivik (MetNo), Luigi Cavaleri (CNR), Victor Alari (TUT).

Abstract: This proposal deals with improving the coupling between ocean circulation model systems and wave models in a forecast environment. The proposed activity will focus on the implementation of a coupled system in the operational short-term forecasting framework taking advantage of the developments in the frame of MyWave and MyOcean projects and supported by regional operating forecasting systems. The proposal aims at further development of the NEMO ocean model and the forcing which will explicitly include: the effect of waves from wave models on the upper ocean dynamics; providing to the CMEMS forecast services software for additional parameters which have to be exchanged between waves and hydrodynamic models; improved validation methods by retrieved wave information from satellite data and in situ platforms; demonstrating the interaction of waves and currents at small scales both in the middle of oceans and near the shoreline. Most of the CMEMS target fields – marine safety, marine resources, marine environment and forecasting – will directly benefit from the proposed R&D work proposed here. Thus, it is expected that the proposal will make connections to CMEMS in order to support the future production of more consistent ocean-marine weather information including also surface waves, as often requested by users.

6.3 CMEMS SERVICE EVOLUTION: R&D CALLS FOR GLOBAL MFC

Three calls were opened in 2016 to answer specific needs of the high-resolution global

forecasting system of CMEMS. Projects are now on-going.

CALL 22-GLO-HR Lot 1: Global ocean modelling

The objective is to improve the global high-resolution configuration currently used in the

Global MFC, which is based on the NEMO community model in a global 1/12° configuration

(e.g. parametrizations, numerical schemes, effective resolution). Another objective is to

prepare the evolution of CMEMS global forecasting systems towards stochastic approaches.

CALL 22-GLO-HR Lot 2: High-Resolution ocean, waves, atmosphere interactions

The objective is to improve high-resolution (mesoscale) ocean/atmosphere interaction in the

high-resolution global analysis and forecasting system run by the GLO MFC, by coupling the

ocean model to an atmospheric boundary layer model. A further step is to couple this

system with a global wave model.


Call 36-GLO-HR Lot 1: Assimilation of biogeochemical ocean data on a global scale

The objective is to assimilate biogeochemical data, as a priority from satellite observations

but also from in situ data in the global MFC biogeochemical model (PISCES coupled to

NEMO) using a stochastic approach.

Call 36-GLO-HR Lot 2: Separation of scales in Ocean data assimilation at the global scale

The objective is to propose a data assimilation method which can be used to process

different spatial and temporal scales during the analysis stage, which are compatible with

the Mercator Océan Assimilation System (SAM2) based on the reduced order SEEK filter.

6.4 REPORT FROM THE COPERNICUS COASTAL WORKSHOP

Evolution of Copernicus Marine and Land Services to better handle the coastal zone

Summary and main outcomes of an expert workshop held on December 13 & 14, 2016 in Brussels

6.4.1 Context and workshop objectives

The workshop was organized by EEA and Mercator Ocean as a first step to analyse mid-term (2018-2020) and long term (post 2021) priorities for the evolution of the Copernicus Marine (CMEMS) and Land (CLMS) service to better address user needs in the coastal zone. The workshop was a first step to address the complex issue of users/services in the coastal areas and interfaces between core/European and downstream services. Several Marine and Land Copernicus service coastal experts, representatives of coastal monitoring systems, representatives of the private sector and PIs of European projects related to coastal services participated to the workshop.

6.4.2 Main outcomes and recommendations

Improving the monitoring and forecasting of coastal zones building on Copernicus Marine and Land services and making the best use of existing and future Copernicus satellite observations is both needed and feasible. This requires both a significant evolution of Copernicus Marine and Land core European services and a strengthening of the links with downstream coastal monitoring activities organized both in the public (member states) and private sectors. The workshop identified several important gaps or areas of improvements. A series of short-term/mid-term actions and recommendations were identified. They take into account the necessary delineation between core and downstream activities. The main recommendations can be summarized as follows:

Better processing (i.e. specific algorithms) of satellite observations is required to improve the quality of coastal products. This could be organized as part of the evolution of CLMS and CMEMS from 2018 onwards. This applies, in particular, for CMEMS to ocean colour products in the coastal zone (Sentinel 3 and Sentinel 2, MSG/SEVERI).


New satellite products to better characterize the state of the coastal zone (e.g. coastline, coastal erosion) and its evolution (e.g. on seasonal to annual basis) should be proposed.

Improved Digital Elevation Models (DEM) and Bathymetries are basic core requirements for the coastal zone.

New satellite data/products are also required for the Regional Seas Conventions (e.g. Barcelona Convention/Mediterranean). Many neighbourhood policies, the MSFD and MSP Directives rely on the availability of such data.

Based on an analysis of existing capabilities and requirements from other Copernicus services (in addition of CMEMS and CLMS) (e.g. emergency, C3S), the need to extend the marine and land service activities to the monitoring and forecasting of all major EU rivers (river outflows, nutrient and sediment loading) should be analysed. By extension other linkages between land related and sea related parameters should be explored.

Similarly, the monitoring, short and long-term prediction of sea level close to the coasts should be improved. This is required for a wide range of applications (flooding, coastal erosion, coastal zone management).

Stronger interfaces between CMEMS and downstream coastal marine monitoring systems should be developed. This includes harmonization and standardization issues (e.g. formats, quality assessment methods, documentation, data distribution) and of the use of consistent and improved bathymetry, atmospheric forcing and river inputs.

Pilot studies should be conducted for representative sub-regional/local coastal areas spanning the relevant fields (physical, biological) of the coastal marine environment (cf CMEMS User Uptake activities).

Links/interfaces with EMODnet portals and activities (e.g. bathymetry, seabed habitats, chemistry) should be reinforced.

Products from national/member states coastal monitoring systems could be made available through CMEMS, CLMS or Copernicus (e.g. DIAS) data portals (coproduction EU & Member States).

Copernicus could include in the longer run core/common/generic coastal activities to support the development of coastal downstream services and strong operational interfaces with the Copernicus Marine and Land services (e.g. short-term/mid-term R&D on modelling, data assimilation and coupling, satellite observations and products from Sentinels, in situ data gathering and processing).

Capacity building and development of best practices are also very important for the coastal zone monitoring activities developed by member states and local authorities. This is an area where a European approach would be beneficial.

Documents

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