1. GOCE in Ocean Modelling and the GOCINO project.
P. Knudsen, DTU Space,
M.-H. Rio, CLS,
J. Johannessen, NERSC,
K. Haines, U of Reading,
D. Lea, UK Met Office,
D. Anderson, ECMWF.

2. GOCINO – GOCE in Ocean Modelling
The GOCINO project is a Specific Support Action supported by EU FP6.
GOCINO contributed to reach the pre-operational capability in ocean modelling for GMES utilizing data from GOCE.
Duration: 2½ years (June 07 – Nov 09).
5 Partners (DTU, CLS, NERSC, UREADES, UK Met)

3. Main GOCINO Objectives:
Dissemination of the scientific results from the EU FP-5 RTD project “Geoid and Ocean Circulation in the North Atlantic – GOCINA”,
Apply GOCINA products and recommendations to develop strategies for implementation of GOCE products in operational ocean models together with the ECMWF, TOPAZ, FOAM, MERCATOR, and MFS operational centres,
Disseminate and transfer the implementation strategies for further implementation of GOCE data into the marine component of GMES.

4. Summary: GOCINA Geoid and Ocean Circulation In the North Atlantic
was an EU FP5 project:
For joint exploitation of ENVISAT
and GOCE in ocean circulation
studies:
Climate modeling
Operational assimilation
& The GOCINA project team: P1-DNSC: Knudsen, Andersen, Forsberg, Vest, Olesen, Föh, P2-NMA: Solheim, Omang, P3-UEDIN: Hipkin, Hunegnaw, P4-UREADES: Haines, Bingham, Drecourt, P5-NERSC: Johannessen, Drange, Siegismund, P6-CLS: Hernandez, Schaeffer, Rio, Larnicol

5. GOCINA:
The Individual components: MSS, geoid, and MDT, have been improved.
Combination solutions
Impact studies
Recommendations
MSS = Geoid + MDT

6. Compare and Combine Components
Composite MDT
KMS04 – NAT04
Error fields
+-40 cm
10 cm
25 cm

7. GOCINA - Impact analyses:
The impact of using the new improved MDT on ocean modelling were analysed.
Altimetry were referenced to the new MDT and – together with the error estimates – assimilated into
FOAM
MERCATOR, and
TOPAZ
operational systems.

8. GOCINA: Impact on Ocean Modelling: Ocean circulation / transport
Changes in flow of % were found
Changes in heat transport of about 30 % were found
Improved transports – increased agreement with drifter observations
Climate prediction
Decreased model northward net heat transport through the straits
Per Knudsen

9. Impact on Heat Transport (TW)
Per Knudsen

10. GOCINA: Recommendations: Integration of GOCE in Ocean Modelling:
Generic algorithms have been developed
Integration of GOCE and altimetry
Validation:
Best possible regional fields for validation of GOCE:
Geoid, MSS, and MDT
Gravity gradient tensor
Diagonal components of the gravity gradient tensor for the total field (radial component Γzz)
Per Knudsen

11. Development of strategies:
Apply GOCINA products and recommendations to develop strategies for implementation of GOCE products in operational ocean models together with the ECMWF, TOPAZ, FOAM, MERCATOR, and MFS operational centres including revision of the
Recommendations on combining GOCE gravity models and a Mean Sea Surface to derive a Mean Dynamic Topography model,
Recommendations on assimilation of altimetry into numerical ocean models using the GOCE MDT.

12. Computation of MDT:
Recommendations on combining GOCE gravity models and a Mean Sea Surface to derive a Mean Dynamic Topography model were based on
GOCINA recommendations,
Results from ESA activities on GOCE User Toolbox developments:
User requirements
Algorithm specification
GUT v1 implementation
Tutorials

13. The GUT Tutorials
The GUT Tutorials is a document that help the user by:
Describing the GOCE products,
Describing procedures for using GOCE products for Geodesy, Oceanography and Solid Earth studies,
Defining workflows for a variety of tasks,
Showing examples.
More info at

14. GUT - Primary WorkFlows
Defines the defaults we recommend “Novice” Users to follow

15. Workflow example Workflow 1a Input Data:
EIGEN-GRACEGL4S SH coefficients
(reference ellipsoid=GRIM
Tide system=FREE )
Output Reference ellipsoid: TP
Output tide system: Mean Tide
Degree/order of expansion: 40 m
Options:
Output Grid : regular, ½°resolution grid

16. Workflow example Workflow 1b Input Data:
EIGEN-GRACEGL4S error covariance matrix of SH coefficients
(reference ellipsoid=GRIM
Tide system=FREE )
Output Reference ellipsoid: TP
Output tide system: Mean Tide
Degree/order of expansion: 50
Options:
Output Grid : regular, ½°resolution grid mm

17. Workflow example Workflow 3a Input Data: MSSCLS01
EIGEN GL04S GRACE Geoid
Options:
Filter Type: Gaussian
Filter width=400 km cm
+ my_filter_matrix.fic

18. Assimilation of altimetry/GOCE MDT:
Recommendations on assimilation of altimetry into numerical ocean models using the GOCE MDT were based on
GOCINA recommendations
Improving assimilation scheme considering observation and model biases and error covariance information:

19. Bias examples:
Observation bias, in m for the NEMO operational models (19 August 2009) ¼ degree global.

20. Bias examples:

21. Deliveables:
A series of strategies for including GOCE assimilation in the operational models of ECMWF, TOPAZ, FOAM, MERCATOR, and MFS have been completed in a close collaboration with those centres.
A website for dissemination of GOCINO results has been set up:

22. Status: The ECMWF model system:
Altimeter data assimilation was included for the first time in April 2006 in the operational ECMWF System 3 seasonal forecasting system.
ECMWF may still need to adopt the altimeter bias correction scheme to deal with any large scale discrepancy due to model errors.
ECMWF plan to operationally implement a system based on NEMOVAR.
ECMWF will thoroughly test any assimilation scheme using a GOCE based MDT.

23. Status: The TOPAZ model system:
The assimilation system in TOPAZ3 relies on an Ensemble Kalman Filter (EnKF) and the HYCOM ocean model. Experiments have showed that the efficiency of the EnKF assimilation in taking up the MDT biases.
In view of the strategy for assimilating GOCE derived MDT the TOPAZ3 system will be employed.
For the analyses of the observation errors and the geoid error covariance an ensemble of GOCE based MDTs will be generated.

24. Status: The FOAM model system:
Recently the observation bias method has been introduced. The full bias code, including model biases, has not yet been implemented operationally, however.
With respect to implementation of a GOCE MDT the work has started at the Met Office on testing the 3D-Var NEMOVAR assimilation scheme within the FOAM system.
Within the timescales for producing GOCE based MDT it is likely that the testing of NEMOVAR for operational implementation include testing a GOCE MDT at the same time.

25. Status: The MERCATOR model system:
The strategy developed at MERCATOR for assimilating the future GOCE data consists in combining spatial and in-situ data so as to estimate the ocean Mean Dynamic Topography
Data from the GOCE mission will allow resolving the geoid at spatial scales down to 100km with centimetric accuracy. Further combination with in-situ data is needed. In this combination step, the covariance error information from the GOCE data will be very useful.
The assimilation scheme from the MERCATOR system does not need at the moment the MDT covariance error information.

26. Status: The MFS model system:
A 3D-VAR assimilation scheme has been recently developed to be integrated into the MFS forecasting system.
The strategy is based on the assumption that the error in the MDT field appears in the assimilation system as a temporally constant and spatially variable observational bias. At the present time, no covariance information is used.
When available (together with the GOCE geoid information), it will be used for constructing the MDT.

27. Conclusions:
A series of reports based on the results obtained in the GOCINA project with a special focus on assimilation of GOCE into operational models were completed.
A series of strategies for including GOCE assimilation in the operational models of ECMWF, TOPAZ, FOAM, MERCATOR, and MFS have been completed in a close collaboration with those centres.
A website for dissemination of GOCINO results has been set up.
The operational centres are prepared to use GOCE data.