Monitoring the Ocean from Observations - Euro-Argo RI · Monitoring the Ocean from Observations ......

20 years of progress in radar altimetry, Venice, September 2012 - 1 -

Monitoring the Ocean from Observations

Stéphanie Guinehut Marie-Hélène Rio

Sandrine Mulet Anne-Lise Dhomps

Gilles Larnicol


Introduction Our approach :

– Consists of estimating 3D-thermohaline and current fields using ONLY observations and statistical methods

– Represents a complementary approach to the one developed by forecasting centers – based on model/assimilation techniques

– “Observation-based” component of the Global MyOcean Monitoring and Forecasting Center lead by Mercator Océan

Outline : Cooking method & ingredients Validation examples Ocean state estimates: T/S variability patterns, AMOC variability at 25°N Contribution and complementarities of the different observing system


+ MDT estimate

The principle

Global 3D Ocean State [T,S,U,V,H]

Weekly – 1993-2010 [0-1500m] 24 levels

[1/3°]

MyOcean RT/REP

The products The method The observations

altimeter, SST, winds, geoid

T/S profiles, surface drifters

Guinehut et al., 2004 Guinehut et al., 2006 Larnicol et al., 2006

Rio et al., 2011 Guinehut et al., 2012

Mulet et al., 2012


Global T/S Armor3D - Method 1

2

SLA, SST

in-situ T(z), S(z)

multiple linear regression

2

1

Armor3D T(z), S(z)

optimal interpolation

synthetic T(z), S(z)

vertical projection of satellite data (SLA, SST) combination of synthetic and in-situ profiles

T(x,y,z,t) = α(x,y,z,t).SLAsteric + β(x,y,z,t).SST’ + Tclim (x,y,z,t) S(x,y,z,t) = α’(x,y,z,t).SLAsteric + Sclim (x,y,z,t)

Guinehut, S., P.-Y. Le Traon, G. Larnicol and S. Philipps, 2004: Combining Argo and remote-sensing data to estimate the ocean three-dimensional temperature fields- A first approach based on simulated observations, J. Mar. Sys., 46 (1-4), 85-98.

Guinehut S., A.-L. Dhomps, G. Larnicol and P.-Y. Le Traon, 2012: High resolution 3D temperature and salinity fields derived from in situ and satellite observations. Accepted for publication in Ocean Sci.


Relationship between surface and subsurface fields – Calculated from historical in situ observations – Estimates now global and seasonal thanks to the Argo array

Global T/S Armor3D - Method

DH-1500m/T-100m annual correlation

Very similar structures as a function of lat. and depth for all three oceans

Except for DH-S(z) in the NH

Baroclinic structures in the tropics

Barotropic structures at high lat

Seasonal variations found between SST-T(z) in direct relation to the variation of the mixed layer depth


Armor3D - 1993-2010 reanalysis

Synthetic T’ – at 100m

SSALTO-DUACS MSLA 1/3° weekly DT - 04/07/2007 NCEP Reynolds OI-SST 1/4° daily - 04/07/2007

Arivo climatology – July – T at 100 m


Armor3D - 1993-2010 reanalysis

Synthetic T’ – at 100m

Armor3D T’ Argo T’

In-situ observations – Coriolis data center


Armor3D - Validation along the 2008 OVIDE cruise

Lherminier et al., 2007

Better estimation of the mesoscale structures (well constrained by satellite obs.)

Induce a better estimation of the large-scale signals


Armor3D - From mesoscale to large-scale signals

Lherminier et al., 2007

Temperatures anomalies from the OVIDE 2008 section

inst

anta

neou

s La

rge-

scal

e

(> 4

00 k

m)

In situ only – OVIDE

Better estimation of the mesoscale structures

Induce a better estimation of the large-scale signals

Combined field – OVIDE


Temperature variability over the 2004-2008 period (global zonal averages) :

Armor3D - Hydrographic variability patterns

Combined SCRIPPS SODA 2.2.4

2004

2008

Synthetic

2005

2006

2007 Very similar results for Synthetic/ARMOR3D/SCRIPPS

No bias introduced by the method

Very promising to study the variability of the 1993-2000 period which suffers from poor in situ measurements coverage


Temperature variability from 1993 to 2008 (global zonal averages) :

Hydrographic variability patterns

1993 1997 2001 2005

2008

1994

1995

1996

1998

1999

2000

2002

2003

2004

2006

2007


Armor3D - Hydrographic variability patterns Salinity variability over the 2004-2008 period (global zonal averages) :

ARMOR3D SCRIPPS SODA 2.2.4 Synthetic

2004

2005

2006

2007

2008

Argo obs sys mandatory

Salinity also a challenge for model solutions


Global U/V/H Surcouf3D - Method

dz)z('yρf

g)0z(u)zz(u iz

0zi ρ∂∂

+=== ∫ =

dz)z('xf

g)0z(v)zz(v iz

0zi ρ∂∂

ρ−=== ∫ =

Surcouf : Field of absolute geostrophic surface currents weekly - 1/3° (Aviso + CNES-CLS09 ¼° MDT)

Armor3D : 3D T/S fields weekly - 1/3° - [0-1500]m

Surcouf3D 3D geostrophic current fields weekly (1993-2010) 1/3° - 24 levels from 0 to1500m

Mulet, S., M.-H. Rio, A. Mignot, S. Guinehut and R. Morrow, 2012: A new estimate of the global 3D geostrophic ocean circulation based on satellite data and in-situ measurements. Deep-Sea Res. II., 77-80, 70-81, doi:10.1016/j.dsr2.2012.04.012.


Surcouf3D - Validation of the method * Parent et al., Poster : Global Eddy-Permitting

Ocean Reanalysis and Simulations of the Period 1992 to Present

2006 annual mean zonal velocities (cm/s) along a section in the Gulf Stream at 60°W

Higher values obtained in the Ekman layer than in the ocean interior, where error is less than 15%

Very similar results for the meridional component

Standard deviation of the differences between the GLORYS native and the reconstructed zonal current - % of the standard deviation of the native field

Using simulated fields from the Glorys reanalysis*


Surcouf3D - Validation of 1000-m currents Global statistics over the Atlantic outside the equator (10°S-10°N) Comparison between 3 different methods (Surcouf3D, GLORYS, Armor3D) and in-situ

observations (ANDRO) at 1000 m over the 2006/2007 period (Taylor, 2001)

skill score

Meridional component

Standard deviation (cm/s)

Sta

ndar

d de

viat

ion

(cm

/s)

● SURCOUF3D (weekly, 1/3°)

▲GLORYS = Mercator-Ocean reanalysis (weekly, 1/4°) Ferry et al., 2010

♦ Armor3D = geostrophic current with level of no-motion at 1500m (weekly, 1/3°)

● ANDRO = 1000-m currents from drifting velocities from the Argo floats (≈10days, ≈50/100km) Ollitraut et al, 2010

Results are very similar for the zonal component


Surcouf3D - Validation Comparison with GoodHope VM-ADCP observations from 14/02–17/03/2008

SURCOUF3D ADCP

Good correlation with independent in-situ obs.

Other time series to be compared

ADCP obs courtesy of S. Speich

Zonal velocities (cm/s) Meridional velocities (cm/s)

14/02/08 17/03/08


Surcouf3D - AMOC variability at 25°N

Very consistent with Bryden et al, 2005 High inter-annual variability Hard to distinguish a long-term trend

Floride Strait Transport from electrical cable

AMOC = Geost + Ekman + Florida (Surcouf3D, Bryden et al., 2005)

Ekman Transport from wind stress ERAInterim

Geostrophic Transport from 75°W to 15°W and from the surface to 1000m (Surcouf3D, Bryden et al., 2005)

Comparison with Bryden et al, 2005 (section at 24.5° from Africa to 73°W and at 26.5°N off Bahamas)

(Bryden et al,2005)


Conclusions / Perspectives

All available observations of the ocean (satellite observations of SLA, SST, geoid and in situ observations of T/S profiles and drifting buoy velocities) are merged to produce weekly 3D maps of Temperature, Salinity, SSH and horizontal velocities from the surface to 1500m depth

Observation-based products (RT, REP) are distributed as part of the MyOcean EU project

They are very useful : to study the interannual variability of the hydrographic patterns, the AMOC … to perform intercomparison exercices to study the contribution and complementarities of the different observing systems

This will be continued in the future (MyOcean, GODAE/CLIVAR/GSOP)

The relevance and accuracy of the observation-based product estimates depend strongly on the existence of a complete, homogeneous, and sustainable ocean observing system (satellite & in situ)

Monitoring the Ocean from Observations - Euro-Argo RI · Monitoring the Ocean from Observations ......

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