monitoring the ocean from observations - euro-argo eric...guinehut, s., p.-y. le traon, g. larnicol...
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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
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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
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+ 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
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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.
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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
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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
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Armor3D - 1993-2010 reanalysis
Synthetic T’ – at 100m
Armor3D T’ Argo T’
In-situ observations – Coriolis data center
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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
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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
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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
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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
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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
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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.
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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*
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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
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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
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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)
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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)