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Ocean Motion From Space Exploit the synergy of SSH, SST and OC to estimate improved ocean surface currents

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Ocean Motion From Space Exploit the synergy of SSH, SST and OC to estimate improved ocean surface currents The needs Measuring ocean currents from space: existing approaches Limits of the altimeter system Improving altimeter currents through the merging with OC/SST data The Mercatini et al, 2010 approach The challenges Workplan

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Ocean Motion From Space The needs Ship routing Search And Rescue coastal development and management Offshore operations Maritime Pollution navigation Ice forecasting aquaculture fisheries Climate change research

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The GlobCurrent Project The GlobCurrent Project was kicked-off in October 2013. The project has a 3-years duration and is supported by the European Space Agency (ESA) under the Data User Element (DUE) programme. The overall objective of the project is to advance the quantitative estimation of ocean surface currents from satellite sensor synergy and demonstrate impact in user-led scientific, operational and commercial applications that, in turn, will increase the uptake of satellite measurements. The project is led by NERSC with expertise from four partners, i.e. IFREMER, CLS, PML, ISARDSAT

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Measuring ocean currents from space: existing approaches At the moment there is no satellite observing system that provides direct observations of the ocean surface currents. However, a large variety of active and passive remote-sensing instruments have been put into orbit in the last few decades providing continuous, global information about the ocean. This includes altimeters, scatterometers, Synthetic Aperture Radars (SAR), imaging radiometers operating at different wavelengths, spectrometers. Estimates of the surface current can be retrieved by transformation of these satellite-measured quantities based on a range of assumptions, feature tracking methods and empirical based retrieval algorithms.

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Measuring ocean currents from space: existing approaches Altimetry, by providing global, accurate and repetitive measurements of the Sea Surface Height (SSH), has been by far the most exploited system for the study of the ocean surface currents variability over the last 20 years ERS-1 ERS-2 1991-07 2000-03 1995-04 2011-07 ENVISAT2002-03 2012-04 GFO1998-02 2008-10 TOPEX1992-08 2005-10 JASON-12001-12 2013-07 JASON-22008-06 2015+ JASON-3 CRYOSAT-22010-04 2014+ SARAL2013-02 2018+ SENTINEL-3 GOCE2010 2013 GRACE2002-03 2014+

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Theoretical Courses on Altimetry October 2012 - 7 - The ocean Mean Dynamic Topography orbit hOhO hAhA =h O -h A h G The altimeter Principle Geoid E = G + h Geoid: poorly known at short scales Measured with altimetry at cm accuracy Signal of interest for oceanographers Altimeter missions repetitivity = G + Altimeter Sea Level Anomalies h P Example of Sea Level Anomaly after multimission mapping

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Theoretical Courses on Altimetry October 2012 - 8 - The ocean Mean Dynamic Topography SSALTO DUACS: computed relative to a 7 years mean profile (P=1993- 1999) In order to reconstruct the dynamic topography h from the Sea Level Anomaly h= the missing component is: The ocean Mean Dynamic Topography (MDT) for the period 1993-1999 The altimeter Principle = G + h Geoid: poorly known at short scales Measured with altimetry at cm accuracy Signal of interest for oceanographers Altimeter missions repetitivity = G + + Mean Dynamic Topography = Absolute Dynamic Topography h Altimeter Sea Level Anomalies h 93-99

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Theoretical Courses on Altimetry October 2012 - 9 - The ocean Mean Dynamic Topography MSS 9399 m GEOID (t,x,y) = G(t,x,y) + h(t,x,y) Calculating the ocean Mean Dynamic Topography: The direct method P (x,y)= P (x,y) G(x,y) MDT=MSS GEOID

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Theoretical Courses on Altimetry October 2012 - 10 - The ocean Mean Dynamic Topography (t,x,y) = G(t,x,y) + h(t,x,y) Calculating the ocean Mean Dynamic Topography: The direct method P (x,y)= P (x,y) G(x,y) MDT 9399 =MSS 9399 GEOID cm

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Theoretical Courses on Altimetry October 2012 - 11 - The ocean Mean Dynamic Topography Calculating the ocean Mean Dynamic Topography: The direct method MDT 9399 Rc=200 km Rc=300 km Rc=400 km Gaussian filter cm

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Theoretical Courses on Altimetry October 2012 - 12 - The ocean Mean Dynamic Topography MSS CLS_SHOM98 MSS OSU 95 MSS CNES_CLS_2011 MSS DTU10 MSS DNSC08 MSS CLS01 Calculating the ocean Mean Dynamic Topography: The direct method 20 years of MSS improvements

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Theoretical Courses on Altimetry October 2012 - 13 - The ocean Mean Dynamic Topography RMS differences (in cm) between geoid models and GOCE-TIM-R3 filtered at 100km (on oceans) Satellite-only geoid models 19951999200320052010 120 98 50 44 5 ModelYearMax DO Data GRIM4S4199570Geodetic satellites GRIM5S1199999Geodetic satellites CHAMP3S200314033 months of CHAMP GGM02S/ EIGEN3S 20051502 years of GRACE ITG- GRACE201 0s 20101807 years of GRACE GOCE2010- 2014 200- 250 2 months (R1) 6 months (R2) 1 year (R3) 2 years (R4) Calculating the ocean Mean Dynamic Topography: The direct method 20 years of GEOID improvements

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Theoretical Courses on Altimetry October 2012 - 14 - The ocean Mean Dynamic Topography 1995 20 YEARS OF Geoid IMPROVEMENTS: Impact on MDT determination

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Theoretical Courses on Altimetry October 2012 - 15 - The ocean Mean Dynamic Topography 1999 20 YEARS OF Geoid IMPROVEMENTS: Impact on MDT determination

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Theoretical Courses on Altimetry October 2012 - 16 - The ocean Mean Dynamic Topography 2003 20 YEARS OF Geoid IMPROVEMENTS: Impact on MDT determination

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Theoretical Courses on Altimetry October 2012 - 17 - The ocean Mean Dynamic Topography 2005 20 YEARS OF Geoid IMPROVEMENTS: Impact on MDT determination

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Theoretical Courses on Altimetry October 2012 - 18 - The ocean Mean Dynamic Topography 2006 20 YEARS OF Geoid IMPROVEMENTS: Impact on MDT determination

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Theoretical Courses on Altimetry October 2012 - 19 - The ocean Mean Dynamic Topography 2009 20 YEARS OF Geoid IMPROVEMENTS: Impact on MDT determination

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Theoretical Courses on Altimetry October 2012 - 20 - The ocean Mean Dynamic Topography 2010 20 YEARS OF Geoid IMPROVEMENTS: Impact on MDT determination GRACE: Resolution 150 km

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Theoretical Courses on Altimetry October 2012 - 21 - The ocean Mean Dynamic Topography 2010 20 YEARS OF Geoid IMPROVEMENTS: Impact on MDT determination GRACE: Resolution 125 km

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Theoretical Courses on Altimetry October 2012 - 22 - The ocean Mean Dynamic Topography 2012 20 YEARS OF Geoid IMPROVEMENTS: Impact on MDT determination GOCE: Resolution 125 km

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Theoretical Courses on Altimetry October 2012 - 23 - The ocean Mean Dynamic Topography MSS CLS01-EIGEN - GRGS.RL02 300 km 2009: 5 years of GRACE data Example in the Gulfstream Region Mean Geostrophic Velocities In-Situ mean velocities

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Theoretical Courses on Altimetry October 2012 - 24 - The ocean Mean Dynamic Topography 2009: 5 years of GRACE data In-Situ mean velocities SMO CLS01-EIGEN-GRGS 133 km Example in the Gulfstream Region Mean Geostrophic Velocities

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Theoretical Courses on Altimetry October 2012 - 25 - The ocean Mean Dynamic Topography In-Situ mean velocities MSS CLS10 - EGM-DIR-V3 100 km 2011: 1 year of GOCE data Example in the Gulfstream Region Mean Geostrophic Velocities

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Theoretical Courses on Altimetry October 2012 - 26 - The ocean Mean Dynamic Topography (u,v) At each position r and time t for which an oceanographic in-situ measurement of surface velocity u(r,t),v(r,t) is available - the in-situ data is processed to match the physical content of the altimeter measurement (geostrophic currents) - the altimeter velocity anomaly is subtracted from the in-situ velocity Computing the ocean Mean geostrophic velocities from in-situ and altimeter data (=synthetic mean velocities) cm/s SVP- Drifting buoy velocities 1993-2010 - the altimeter velocity anomaly u a (r,t),v a (r,t) is interpolated to the position/date of the in-situ data. (u a,v a )

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Mean geostrophic currents from the MDT CNES-CLS13 (Rio et al, in preparation)

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Altimetry Topex-Poseidon/Jason ERS/Envisat Multi-mission merging to obtain gridded maps of altimeter data. Final resolution of gridded products depends on the number of satellites flying at the same moment and their orbit characteristics Impact the spatial coverage capability: Spatial coverage limited to 66N/S for TP/Jason, 82N/S for ERS/Envisat Impact the spatial and temporal resolution capability Orbit inclinationRepetitivityEquatorial inter- tracks distance 6610 days315 km 98.535 days80 km Maps of surface velocities using the geostrophic approximation:

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Altimeter Constellation history Spatial resolution achieved for a 10 days temporal resolution 2 satellites 250-300km 3 satellites 150 km 4 satellites 100 km

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Time-space diagram depicting the characteristic temporal and spatial scales of the dominant surface current features in the ocean. Adapted from Chelton, (2001). The dashed lines indicate the approximate lower bounds of the space and tie scales that can be resolved in SSH fields constructed from multimission altimeter measurements (3 satellite configuration) Altimetry Limitation Spatio temporal resolution achievable Physical content of the currents: only the geostrophic component is obtained Error increases toward the coast and at high latitudes (seasonal ice coverage, limited satellite coverage)

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Measuring ocean currents from space: Use of tracer information TypeSatellite Platform(Instrument) Satellite observation Retrieval algorithms and Tools Final retrieved geophysical information IR radiometerMetOp1,2(AVHRR) ERS1-2( ATSR) ENVISAT(AATSR) EOS- Aqua/Terra/(MODIS) NOAA(AVHRR) TRMM(VIRS) MeteoSat(SEVIRI) Sentinel-3 (SLSTR) Sea surface temperature and fronts (i) Surface quasi- geostrophic assumption; (ii) MCC method Surface geostrophic current at spatial resolution of ~25km and temporal scale of about 1 to 10 days depending on clouds Feature tracking using MCC gives estimate of surface current at resolution lower that interrogation window C-band microwave radiometer Aqua-2(AMSR) DMSP (SSM/I) Coriolis (WindSat) Sea surface temperature and fronts Surface quasi- geostrophic assumption; Surface geostrophic current at spatial resolution of ~25 km and temporal scale of 1 day L-band microwave radiometer SMOS(MIRAS) SAC-D(Aquarius) Sea surface salinity and fronts Surface quasi- geostrophic assumption; Surface geostrophic current at spatial resolution of ~100 km and temporal scale > 3-10 days SpectrometerENVISAT(MERIS) EOS-Aqua/Terra(MODIS) Sentinel-3 (OLCI) Ocean color, chlorophyll A distribution and fronts MCC methodFeature tracking using MCC gives estimate of surface current

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TypeSensorModalityResolution Spatial; Temporal Coverage Spatial; Temporal Potential usage Geo- stationary SEVIRIInfrared, visible3 Km; 15 minutes Atlantic; 2002-present SST and colour feature GOCIOcean colour500m; hourly Northwest Pacific ; 2010-present Colour feature MTSATInfrared, visible4 Km; hourly Pacific; 2005-present SST and colour feature GOESInfrared, visible4 Km; hourly Pacific; 1980-present SST and colour feature PolarAVHRRInfrared1.1 km; few per day Global; 1981-present SST feature SeaWIFSOcean colour1.1 km; daily Global; 1997-2011 Colour feature ATSRInfrared1km, every 3 days1991-2011SST feature MERISOcean colour300m/1200m, every 1-2 days? 2002-2011Colour feature MODISInfrared, ocean colour 1.1 km (1 channel at 250m); daily Global; 2002-present Colour feature MCC methodology From http://ccar.colorado.edu/colors/mcc.html

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MCC methodology From http://ccar.colorado.edu/colors/mcc.html The solid boxes in the first image is the pattern to search for in the second image. The dashed boxes in the second image is the search window". The MCC method (Emery et al, 1986) is an automated procedure that calculates the displacement of small regions of patterns from one image to another. The location of the subwindow in the second image that produces the highest cross-correlation with the subwindow in the first image indicates the most likely displacement of that feature. The velocity vector is then calculated by dividing the displacement vector by the time separation between the two images.

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Limitations Cloud-cover and isothermal/isochromatic ocean surface conditions drastically limit the spatial and temporal velocity coverage provided by the MCC method. Clouds block the ocean surface in both thermal and ocean color imagery, and there are no features for the MCC method to track in isothermal/isochromatic regions. Accurate spatial alignment and coregistration of the imagery used in feature tracking is required. Consequently, the technique has been more often used in coastal regions, where landmarks are available to renavigate the satellite data. MCC techniques work well for intervals between images of 6-24 hrs, but are not so reliable for longer gaps due to evolution of the features, including rotation and shear. MCC methodology From http://ccar.colorado.edu/colors/mcc.html

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SST 1/4 (AMSR-E V5)SSH 1/3 (SSALTO/DUACS) General concept: Exploit the correlation between SST and SSH (Jones et al. 1998) : - Positive (0.2-0.6) at large scale (>1000km) - Strong (0.7) at short scales in strong gradients areas Key point of SQG theory: in the horizontal Fourier transform domain StreamfunctionSurface Density Anomalies Currents SST anomaly E-SQG Method N(z)=N eff the effective Brunt-Vaisala frequency (constant stratification assumed)

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Limitations The SQG method is valid in baroclinic instabilities areas, and strong gradients areas (ACC, Gulfstream, Kuroshio) In addition, the validity of the SQG approximation is limited to cases when the SST is a good proxy of the density anomaly at the base of the mixed layer, which effectively happens after a mixed-layer deepening period. Therefore the ideal situation for the application of this method would be after strong wind events. Limited to the retrieval of mesoscale (30-300km), not the large scale currents Isern-Fontanet et al, 2006, 2008: the reconstruction can be still improved if we exploit the synergy between SST and SSH: Courants issus de SSHCourants issus de SST E-SQG Method

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On the use of submesoscale information for the control of ocean circulations, Gaultier L., Verron J., Brankart J.M., Titaud O. and Brasseur P. Journal of Marine Systems, 2013 FSLE (in day1) derived from the geostrophic AVISO velocity first week of July, 2004 Tracer used as a dynamic informa- tion: high resolution SST images from MODIS sensor at 1 km resolution: Background velocity to be corrected: map of velocity derived from AVISO altimetric observations at 1/8 resolution : Finite-Size Lyapunov Exponents (FSLE) measure stirring in a fluid, It is a connection between sub- mesoscale dynamics and tracer stirring. FSLE is the exponential rate at which two particles separate from a distance 0 to f : Method: Modify the altimeter velocity field so as to minimize the cost function J that measures the distance between the binarized normalized gradient of SST and the binarized FSLE (u) (as a proxy of the velocity u). SST image from MODIS sensor (in C) on July 2nd, 2004 Geostrophic Velocity (in m.s1) over the SSH (in cm) on the first week of July, 2004 from AVISO.

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Ocean Motion From Space Exploit the synergy of SSH, SST and OC to estimate improved ocean surface currents SSH SST OC

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Starting point: Inverse methods (Kelly et al, 1989): Require the velocity field to obey the tracer evolution equation and inverse it for the velocity vector: c(x, y, t) is the normalized concentration of a tracer known from successive satellite observations u,v is the velocity field f(x,y,t) represents the source and sink terms Challenge: there is no contribution to tracer advection from the along-track gradient velocity, or from either components in regions of negligible gradients. -> only cross-gradient velocity information can be retrieved from the tracer distribution at subsequent times in strong gradients areas. Ocean Motion From Space Exploit the synergy of SSH, SST and OC to estimate improved ocean surface currents

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Solution from Mercatini et al, 2010 : Use a background velocity information (u bck, v bck ) so that the satellite tracer information is used to obtain an optimized blended velocity (u opt, v opt ). The authors tested the implementation of the method for the specific application of oil spill monitoring using background velocities from a numerical model. Ocean Motion From Space Exploit the synergy of SSH, SST and OC to estimate improved ocean surface currents

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Apply the methodology on successive Ocean Color and SST images using the low resolution, geostrophic altimeter velocities as background velocities. -> Altimeter velocities will be improved in term of resolution by the higher resolution information contained in the SST/OC images -> Altimeter velocities will be improved in term of physical content (ageostrophic terms) by the total velocity information derived from the SST/OC images -> The application of the method on both OC and SST images increase the overall spatial and temporal velocity coverage. In addition, ocean colour can also resolve isothermal flow, i.e. in regions where the different water masses do not have distinctive temperatures. Ocean Motion From Space Exploit the synergy of SSH, SST and OC to estimate improved ocean surface currents Our Approach

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Two main issues: Need for high spatial and temporal resolution time series of cloud free images. Visible/infrared spectral band radiometers: very high spatial resolution (0.3-1km, 4km in the case of geostationary satellites) but their availabilities are severely limited by the presence of clouds. Microwave imagers provide accurate satellite SST measurements under clouds but the spatial resolution is much lower (about 50 km). -> merging techniques to compute cloud-free images of SST and Ocean colour from the different available datasets. The drawback of these merged products is that adjacent pixels may have been actually measured at different times and from different sensors. The impact on the accuracy of the derived velocities will need to be carefully assessed. Accurate prescription of the Source and Sink terms of the evolution equation is needed in cases where the tracer evolution is not driven only by advection. SST Insolation net infrared radiation sensible and latent heat fluxes. -> These terms may be measured directly or indirectly via a Bulk Formulae. OC The main contributor to OC is phytoplankton, which is both a passive tracer transported by water circulation and an active biomass growing under favorable conditions (light, nutrients, etc.) Ocean Motion From Space Exploit the synergy of SSH, SST and OC to estimate improved ocean surface currents

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The applicability of the method will be tested using an OSSE (Observing System Simulation Experiment) based on ocean numerical modeling outputs SST test, OC test : Test a number of configurations regarding the SST and OC observing systems: different time acquisition of adjacent pixels in high resolution SST and OC merged products different parameterizations for the source and sink terms of the tracer evolution equation impact of growing time steps between two consecutive images Model outputs Nominal conf SST m Oc m U m,V m Degraded Model outputs SST test OC test MER10 Altimeter data U bck, V bck Blended Velocities U opt, V opt Ocean Motion From Space Exploit the synergy of SSH, SST and OC to estimate improved ocean surface currents

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Task 1 Gaining expertise on Sea Surface Temperature and Ocean color measurements from space Task 1.1: Bibliographical work Task 1.2: Intercomparison of merged images and Level 3 single sensor images in term of spatial/temporal resolution Task 1.3: Analysis of the different driving mechanisms of the SST and Ocean color evolution, and their relative contribution (advection versus diffusion versus ) Task 1.4: Selection of areas/periods with successive cloud free high resolution images Task 2 Observation System Simulating Experiments Task 2.1: Use of model fields to create synthetic maps of Sea Surface Temperature/Ocean color Task 2.2: Implement the MER10 methodology to create blended velocities from altimetry and synthetic SST/Ocean color images Task 2.3: Sensitivity studies Task description Ocean Motion From Space Exploit the synergy of SSH, SST and OC to estimate improved ocean surface currents

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Task 3: Implementation and testing of the method on real datasets Task3.1: Testing the method capacity of retrieving shortest scales of the geostrophic currents we will consider a study period for which four altimeters have been flying simultaneously (2002-2008) and for which therefore altimeter sea level maps (and the corresponding geostrophic velocities) have been computed using the four altimeter data measurements. Concurrent maps computed using only 2 altimeters out of the four available will be used as background velocities (with therefore a decreased spatial resolution) and the methodology will be applied using high resolution SST and OC maps. We will check that the resulting blended surface velocities compare better to the full resolution, four altimeter data based geostrophic velocities than the background velocities. Task3.2: Testing the method capacity of retrieving the ageostrophic component of the currents We will apply the methodology using the altimeter surface velocities as background for a given study period and compare the resulting blended velocities to the total velocities provided by the OSCAR (Bonjean et al, 2002) or SURCOUF (Larnicol et al, 2005) products that also include the Ekman current component. Task description Ocean Motion From Space Exploit the synergy of SSH, SST and OC to estimate improved ocean surface currents

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Task 4: Organization of the OceanMotionFromSpace workshop Task 5: Validation Task 5.1: Intercomparison to MCC methodology Task 5.2: Intercomparison to SQG methodology Task 5.3: Intercomparison synthesis Task 6: Outreach activity Task 7: Scientific paper writting Task description Ocean Motion From Space Exploit the synergy of SSH, SST and OC to estimate improved ocean surface currents

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Task 1 Task 2 Task 3 Task 4 Task 5 Task 6 2014 marsmaijuil.sept.nov. 2015 janv.marsmaijuil. 2015 End of project 31/8/2015 Soul Food Festival 15/5/2015 OceanMotionFromSpac e Workshop 15/3/2015 Project Presentation Seminar 15/3/2014 Beginning of project 1/3/2014 31/8/2015 1/1/201515/3/2015 1/1/201531/8/2015 1/9/20141/3/2015 1/4/20141/10/2014 1/3/20141/3/2015 Gantt Diagram 9 months Ocean Motion From Space Exploit the synergy of SSH, SST and OC to estimate improved ocean surface currents

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The End