1. Improved Satellite Altimeter data dedicated to coastal areas :
Validation over the Northwestern Mediterranean Sea
(MAP team)
Jérôme Bouffard
Y. Ménard, L. Roblou, F. Birol, F. Lyard, R. Morrow

2. Context Are altimeter data valuable in coastal areas ?
Longitude
Latitudes
Gulf of
Genoa
Altimetric tracks:
- Topex/poseidon
- Envisat
- jason 1
- GFO
Tide gauges:
LPC
Current
Corsica
Channel
Gulf of Lion
Catalan Sea
Ligurian Sea
Balear islands
Algerian Bassin
Liguro Provencal Catalan (LPC) current
Complex small mesoscale dynamics (Send, 1999)
LPC Instability + meanders (Conan and Millot, 1995)
Seasonnal variability (Millot 1991)
Western Mediterranean Sea
Are altimeter data valuable in coastal areas ?
How to improve altimeter data in coastal areas?

3. Available data Standard distributed data: Improved coastal data:
AVISO regional along-track product: DT-(M)SLA “Upd”
Features:
Standard editing
MOG2D Global (w+P) + FES2004 (tide) corrections
Along-track sampling every 7km (~ 1HZ)
Large scale and orbit error reduction (Le Traon et Ogor, 1998)
Improved coastal data:
Margins Altimetry Projects (MAP) : Xtrack SLA (see Lyard et al OSTST 2007)
Features:
Specific editing and correction re-building
MOG2D -Medsea (w+P) + MOG2D-Medsea (tide) corrections
High resolution sampling every 350 or 700 m (~ 10HZ/ 20 HZ)

4. Impact of the processing features
Example at the Nice TG

5. Comparisons at the Nice TG:
% of RMS explained: Impact of regional de-aliasing corrections
Correlation: 0.78
Residual RMS: 3.9 cm
RMS explained: 37%
MAP-Xtrack Medsea
Regional de-aliasing
Nice TG
Correlation: 0.75
Residual RMS: 4.1 cm
RMS explained: 33%
Nice TG % 10 40
MOG2D Medsea (Regional configuration) significantly improves the consistency beween the altimeter and the Nice tide gauge time series.
Global de-aliasing
MAP-Xtrack Global

6. Comparisons at the Nice TG:
% of RMS explained: Impact of the data editing methodology
Correlation: 0.78
Residual RMS: 3.9 cm
RMS explained: 36%
MAP-xtrack Medsea
HF no editing
Nice TG
Standard editing
Correlation: 0.81
Residual RMS: 3.7 cm
RMS explained: 40%
Nice TG
MAP-Xtrack Medsea HF
Specific editing
The specific data editing methodology allows to decrease the noise in the altimeter time series % 10 40

7. Comparisons at the Nice TG:
% of RMS explained: Impact of the High Frequency sampling
Correlation: 0.78
Residual RMS: 3.9 cm
RMS explained: 37%
MAP-Xtrack Medsea
1HZ sampling
Nice TG
Correlation: 0.81
Residual RMS: 3.7 cm
RMS explained: 40%
Nice TG
MAP-Xtrack Medsea HF
HF sampling % 10 40
The high frequency sampling allows to go closer to the coast

8. Comparisons of the Map-Xtrack data with a regional standard product
Example at the Nice Tide Gauge

9. Comparisons at the Nice TG:
Number of data MAP-Xtrack Medsea HF vs DT-(M)SLA Upd
Nice TG
Nice TG
115
125
115
125
MAP
product
AVISO
product
MAP-Xtrack Medsea HF
DT-(M) SLA Upd
The MAP-Xtrack processing allows to recover more data far and close to the coast

10. Comparisons at the Nice TG:
% of RMS explained: MAP-Xtrack Medsea HF vs DT-(M) SLA Upd
Nice TG
Nice TG
LPC 1 2
Correlation: 0.74
% of RMS explained: 32.9
Correlation: 0.79
% of RMS explained: 38.4
Correlation: 0.79
% of RMS explained: 36.5
Correlation: 0.81
% of RMS explained: 40.4
MAP
product
AVISO
product
MAP-Xtrack Medsea HF
DT-(M) SLA Upd
Better statistical results for the the Xtrack-HF data
Detection of small coastal spatial structure: are they physically reallistic ?
Are they Linked with the LPC dynamics ?

11. Hovmuller plots of across track geostrophic velocity anomalies (TP track-222 in 2001)
LPC current
Close to the LPC and to the coast:
The two signals are well phased:
The altimetric signal has a lower amplitude:
Intrinsic seasonal variability of the LPC is shifted toward the steric signal.
cm/s
Time
Eddy ?
Meander ?
August
January
Far from the LPC:
Dephasing between the two signals:
the Offshore and the coastal don’t « see » the same dynamics (eddy ?) .
The altimetric and TG signals have equivalent amplitude:
 The steric effect is a large wavelenght signal 2
Time
latitude
offshore
Coast
Aviso product
MAP product

12. Comparisons of the Map-Xtrack data with a regional standard product
Example at the Sete Tide Gauge

13. Comparisons at the Sète TG:
Number of available data MAP-Xtrack Medsea HF vs DT-(M) Upd 95
120 95
120
MAP
product
Aviso
product
MAP-Xtrack Medsea HF
DT-(M) SLA Upd
MAP-Xtrack medsea HF processing allows to recover more data far and close to the coast

14. Comparisons at the Sète TG:
% of RMS explained: MAP-Xtrack Medsea HF vs DT-(M) SLA Upd
Correlation: 0.84
% of rms explained: 45.6
Correlation: 0.77
% of rms explained: 35.9
Sète TG
Sète TG % % 10 40 10 40
Correlation: 0.89
% of rms explained: 52.8
Correlation: 0.79
% of rms explained: 38.9
MAP
product
Aviso
product
MAP-Xtrack Medsea HF
DT-(M) SLA Upd
Better statistical results for the the Xtrack-HF data
Stronger improvement than at Nice TG

15. Comparisons of the Map-Xtrack data with a regional standard product
Mean statistics at Tide gauges over the whole area
Tide Gauges

16. Multi-satellite: Mean Statistics at TGs
Topex / Poseidon
MAP
Number of data
Distance to
TGs (km)
Correlation
RMS difference
(cm)
% of RMS
explained
Xtrack 99 61
0.83
3.7
44 %
DT-(M) SLA 90 73
0.77
4.4
34 %
Jason 1
Xtrack
Std. editing 39 50
0.82
3.9
43 %
DT-(M) SLA 39 60
0.75
4.8
34 %
GFO
Xtrack
Std. editing
+ orbit adjust. 39 59
0.81
3.9
39 %
DT-(M) SLA 38 69
0.80
4.2
36 %

17. Meridional dirrection M3 tide gauge (Senetosa)
Crossover
Envisat 257
Jason85
Envisat 258
Jason44
Envisat 588
GFO 257
Jason 44
Jason 85
Crossover points
Meridional dirrection
Ligurian Sea
Corsica Channel
In-situ
station
Comparisons with the normalized transport
(from in-situ data)
Multi-satellite crossover geostrophic velocities
Ellipses of geostrophic velocity anomalies at altimetric crossovers
See also poster Bouffard et al, «A view from multi-mission satelite altimetry over the coastal ocean: a study in the Ligurian Sea and the Corsica channel. » (OSTST 2007)
SSH absolute bias at M3 tide gauge, Jason-1 pass 085
Mean=0.1046m
Std dev=0,0252m
Jason-1 pass 222
Jason-1 pass 085
M3 tide gauge (Senetosa)
CAL/VAL at the Senetosa Tide Gauge
Sea level anomalies comparisons in the Bay of Biscay along Jason-1 ground track 137 (July-August 2004).
Blue: altimeter data
Red: Symphonie coastal model
Good agreements on instantaneous sea levels
Satisfying correlation for synoptic scales and meso-scales dynamics
Altimeter data exhibit short scales processes not represented in the model simulations
See also Roblou et al, « x-track a new processing tool for altimetry in coastal oceans »
Correlation SYMPHONIE model elevations – altimetry SLA: TOPEX + GFO
Sea level anomalies comparisons in the Mediterranean Sea along Multi-satellite ground track ( ).
See also Bouffard et al, « Improved Altimetry in the Northwestern Mediterranean : Comparison of Ocean Dynamics with a Regional Circulation Model »
Correlation SYMPHONIE model elevations – altimetry SLA: Jason + GFO
Correlation SYMPHONIE model elevations – altimetry SLA: Jason + GFO + Envisat
2001
2002
2003
0.7
0.9
Conclusion
Processings
Specific editings allow to eliminate spurious data and improve the quality of coastal altimetric products
Regional de-aliasing models strongly improves altimetric data
High frequency along track sampling allow to highlight small spatial dynamical processes
Comparisons with a standard product
More coastal data with the MAP processings
Closer to the coastline
Better quality of the altimetric data
Applications
Validation of Regional 3D models
Cal/Val
Monitoring of transport in marginal areas