D.I. Lysaker, O.C.D. Omang , D. Solheim ESA Living Planet Symposium, Bergen 30. June 2010

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Geostrophic Surface Currents in the Northern North Atlantic revealed by GOCE, Gravity Anomalies and MSSH

D.I. Lysaker, O.C.D. Omang, D. Solheim

ESA Living Planet Symposium, Bergen 30. June 2010

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This presentation shows an example of how to use geodetic data in climate studies

Gravity + MSSH

Geostrophic ocean

surface currents

Direct

Synthetic

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Ocean circulation may be estimated if height above geoid is known

Ocean Circulation and Transport between the North Atlantic and the Arctic Sea

www.science.nasa.gov

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OCTAS -Ocean Circulation and Transport between the North Atlantic and the Arctic Sea

Courtesy Kourosh Ghazavi

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Oceanographic models

• Salinity• Temperature

OCCAM

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Two methods for estimating geostrophic surface currents

• Direct– MDT obtained using LSC

– Combine MSSH and gravity data

• Synthetic– MDT derived by subtracting a regional

gravimetric geoid from a MSSH model

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Direct method uses LSCCross-covariance

between observations y and signal x

Error covariances

Auto-covariance of observations

a-priori signal variance matrix

Covariance matrix for the measurement noise

MDT

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Synthetic method

MDT = MSSH – N + e

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Data used in the direct and synthetic method

MSSH (OCTAS06v3/DNSC08)

Gravity data

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Gravity coverage is not complete in our test area … fill with gravity data from altimetry

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Both models give a lot of features

Combined model (MSSH and g)

Direct model(MSSH and N)

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Geodetic model has smaller features than oceanographic model

Geodetic model (MSSH-N)Oceanographic model (OCCAM)

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Synthetic model fits drifter data better

Average: 10.5 cm/s

Standard deviation: 9.3 cm/s

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Combination model and drifter data

Average: 11.2 cm/s

Standard deviation: 9.8 cm/s

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OCCAM fits better with drifter data

Model Mean Stdsubtracted (cm/s) (cm/s)

MDT_octas06 11.1 9.8

MDT_dnsc08 11.2 9.8

SMDT_octas06 11.3 16.9

SMDT_dnsc08 10.5 9.3

OCCAM 8.5 8.0

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Mooring data

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Drifter data fits as good/bad with mooring data as combination model

Model Mean Stdsubtracted (cm/s) (cm/s)

MDT_octas06 8,6 5,3

MDT_kms04 7,7 5,5

MDT_dnsc08 5,4 2,7

SMDT_octas06 10,1 5,2

SMDT_kms04 14,4 8

OCCAM 7,3 4,4

drifter 7,9 6,7

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• Using geodetic data reveals smaller features than oceanographic models

• Redistribution of water is due to change in climate

– Gravity observations may contribute to monitor this change

Conclusions