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P. Y. Le Traon
,
G. Dibarboure
, and
N. Ducet

Abstract

The contribution of merging multiple-satellite altimeter missions to the mapping of sea level is analyzed from a North Atlantic high-resolution (1/10°) numerical simulation. The model is known to represent the mesoscale variability quite well and offers a unique opportunity for assessing the mapping capability of multiple-altimeter missions. Several existing or planned orbits [TOPEX/Poseidon (T/P), Jason-1, ERS-1/2–ENVISAT, GEOSAT-GFO] are analyzed, and Jason-1 and T/P orbits are assumed to be interleaved. The model sea level anomaly fields are first subsampled along T/P, ERS, GFO, and Jason-1 tracks and a random noise of 3-cm rms is added to the simulated altimeter data. A suboptimal mapping method is then used to reconstruct the 2D sea level anomaly from alongtrack data and the reconstructed fields are compared with the reference model fields. Comparisons are performed in the North Atlantic and over a complete year. These results confirm the main conclusions of the Le Traon and Dibarboure study based on formal error analysis. There is, in particular, a large improvement in mapping capability when going from one to two satellites. Mapping errors (in percentage of the signal variance) are, however, larger than the ones derived from formal error analysis (by a factor between 1.5 and 2) and do not decrease as rapidly. This is mainly due to the high-frequency (periods < 20 days) and high-wavenumber signals of the Los Alamos model, which cannot be resolved with any of the analyzed multiple-satellite configurations.

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G. Dibarboure
,
P. Y. Le Traon
, and
N. Galin

Abstract

Sea surface height (SSH) measurements provided by pulse-limited radar altimeters are one-dimensional profiles along the satellite's nadir track, with no information whatsoever in the cross-track direction. The anisotropy of resulting SSH profiles is the most limiting factor of mesoscale SSH maps that merge the 1D profiles.

This paper explores the potential of the cross-track slope derived from the Cryosphere Satellite-2 (CryoSat-2)'s synthetic aperture radar interferometry (SARin) mode to increase the resolution of mesoscale fields in the cross-track direction. Through idealized 1D simulations, this study shows that it is possible to exploit the dual SARin measurement (cross-track slope and SSH profile) in order to constrain mesoscale mapping in the cross-track direction.

An error-free SSH slope allows a single SARin instrument to recover almost as much SSH variance as two coordinated altimeters. Noise-corrupted slopes can also be exploited to improve the mapping, and a breakthrough is observed for SARin errors ranging from 1 to 5 μrad for 150-km-radius features in strong currents, and 0.1–0.5 μrad for global mesoscale.

Although only limited experiments might be possible with the error level of current CryoSat-2 data, this paper shows the potential of the SAR interferometry technology to reduce the anisotropy of altimeter measurements if the SARin error is significantly reduced in the future, and in particular in the context of a prospective SARin demonstrator optimized for oceanography.

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P. Y. Le Traon
,
F. Nadal
, and
N. Ducet

Abstract

Objective analysis of altimetric data (sea level anomaly) usually assumes that measurement errors are well represented by a white noise, though there are long-wavelength errors that are correlated over thousands of kilometers along the satellite tracks. These errors are typically 3 cm rms for TOPEX/Poseidon (T/P), which is not negligible in low-energy regions. Analyzing maps produced by conventional objective analysis thus reveals residual long-wavelength errors in the form of tracks on the maps. These errors induce sea level gradients perpendicular to the track and, therefore, high geostrophic velocities that can obscure ocean features. To overcome this problem, an improved objective analysis method that takes into account along-track correlated errors is developed. A specific data selection is used to allow an efficient correction of long-wavelength errors while estimating the oceanic signal. The influence of data selection is analyzed, and the method is first tested with simulated data. The method is then applied to real T/P and ERS-1 data in the Canary Basin (a region typical of low eddy energy regions), and the results are compared to those of a conventional objective analysis method. The correction for the along-track long-wavelength error has a very significant effect. For T/P and ERS-1 separately, the mapping difference between the two methods is about 2 cm rms (20% of the signal variance). The variance of the difference in zonal and meridional velocities is roughly 30% and 60%, respectively, of the velocity signal variance. The effect is larger when T/P and ERS-1 are combined. Correcting the long-wavelength error also considerably improves the consistency between the T/P and ERS-1 datasets. The variance of the difference (T/P–ERS-1) is reduced by a factor of 1.7 for the sea level, 1.6 for zonal velocities, and 2.3 for meridional velocities. The method is finally applied globally to T/P data. It is shown that it is tractable at the global scale and that it provides an improved mapping.

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P. Y. Le Traon
,
Y. Faugère
,
F. Hernandez
,
J. Dorandeu
,
F. Mertz
, and
M. Ablain

Abstract

Merging Geosat Follow-On (GFO) with TOPEX/Poseidon (TP) and ERS-2 altimeter data has the potential to improve the mapping of sea level and ocean circulation variations. This can be achieved, however, only if measurement errors and inconsistencies between the different missions are sufficiently reduced. In this paper, it is shown how to get consistent sea surface heights from the three missions using the most precise mission (TP) as a reference. A new technique is then used to estimate a GFO mean profile. This allows consistent sea level anomalies (SLAs) to be extracted from GFO, TP, and ERS-2. SLA data are then merged with a mapping technique that takes into account noise and residual long wavelength errors. Thanks to these techniques, it is shown that GFO can be combined with TP and ERS-2 and that the combination provides a significant improvement in the description of the mesoscale circulation.

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P. Y. Le Traon
,
P. Klein
,
Bach Lien Hua
, and
G. Dibarboure

Abstract

In high-eddy-energy regions, it is generally assumed that sea level wavenumber spectra compare well with quasigeostrophic (QG) turbulence models and that spectral slopes are close to the expected k −5 law. This issue is revisited here. Sea level wavenumber spectra in the Gulf Stream, Kuroshio, and Agulhas regions are estimated using the most recent altimeter datasets [the Ocean Topography Experiment (TOPEX)/Poseidon, Jason-1, the Environmental Satellite (Envisat), and the Geosat Follow-On]. The authors show that spectral slopes in the mesoscale band are significantly different from a k −5 law, in disagreement with the QG turbulence theory. However, they very closely follow a k −11/3 slope, which indicates that the surface quasigeostrophic theory (SQG) is a much better dynamical framework than the QG turbulence theory to describe the ocean surface dynamics. Because of the specific properties of the SQG theory, these results offer new perspectives for the analysis and interpretation of satellite data.

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M.-I. Pujol
,
G. Dibarboure
,
P.-Y. Le Traon
, and
P. Klein

Abstract

An Ocean System Simulation Experiment is used to quantify the observing capability of the Surface Water and Ocean Topography (SWOT) mission and its contribution to higher-quality reconstructed sea level anomaly (SLA) fields using optimal interpolation. The paper focuses on the potential of SWOT for mesoscale observation (wavelengths larger than 100 km and time periods larger than 10 days) and its ability to replace or complement altimetry for classical mesoscale applications. For mesoscale variability, the wide swath from SWOT provides an unprecedented sampling capability. SWOT alone would enable the regional surface signal reconstruction as precisely as a four-altimeter constellation would, in regions where temporal sampling is optimum. For some specifics latitudes, where swath sampling is degraded, SWOT capabilities are reduced and show performances equivalent to the historical two-altimeter constellation. In this case, merging SWOT with the two-altimeter constellation stabilizes the global sampling and fully compensates the swath time sampling limitations. Benefits of SWOT measurement are more important within the swath. It would allow a precise local reconstruction of mesoscale structures. Errors of surface signal reconstruction within the swath represent less than 1% (SLA) to 5% (geostrophic velocities reconstruction) of the signal variance in a pessimistic roll error reduction. The errors are slightly reduced by merging swath measurements with the conventional nadir measurements.

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J. A. Johannessen
,
P.-Y. Le Traon
,
I. Robinson
,
K. Nittis
,
M. J. Bell
,
N. Pinardi
, and
P. Bahurel

In response to the joint European Commission and European Space Agency initiative to establish by 2008 a system for Global Monitoring for Environment and Security (GMES), the Marine Environment and Security for the European Area (MERSEA) Strand-1 Project was executed to assess and demonstrate the capacity of present monitoring and forecasting systems. The study area covered the North Atlantic, with its northwest European shelf seas, and the Mediterranean. By integrating of existing satellite observations with data from in situ measurement networks and ocean models, daily mean products and forecasts from four core data assimilation systems (~1 0 km resolution) were compared and distributed through an Open-source Project for a Network Data Access Protoco (OPeNDAP) server from1 June 2003 to 31 May 2004.Moreover, downscaling to high-resolution (1–5 km) models was used for specific applications to harmful algal bloom, eutrophication, and oil spill monitoring in the Baltic, North Sea, Irish Sea, Iberian coastal shelf seas, and the Aegean Sea. The lessons learned from this project are reported here.

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