P. Y. Le Traon

An Improved Mapping Method of Multisatellite Altimeter Data

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 me...

Mesoscale Mapping Capabilities of Multiple-Satellite Altimeter Missions

Abstract The purpose of this paper is to quantify the contribution of merging multiple-satellite altimeter missions to the mesoscale mapping of sea level anomaly (H), and zonal (U) and meridional (V) geostrophic velocities. A space/time suboptimal interpolation method is used to estimate the mean and standard deviation of the H, U, and V mapping errors (as a percentage of signal variance) for different orbit configurations. Only existing or planned orbits [TOPEX/Poseidon (T/P), Jason-1, ERS-1/2–ENVISAT, Geosat–GFO] are analyzed. Jason-1 and T/P orbits are assumed to be interleaved. A large number of simulations are performed, including studies of sensitivity to a priori space scales and timescales, noise, and latitude. In all simulations, the Geosat orbit provides the best sea level and velocity mapping for the single-satellite case. In most simulations, the Jason-1–T/P orbit provides the best two-satellite mapping. However, the gain from an optimized two-satellite configuration (Jason-1 + T/P) compared t...

Can We Merge GEOSAT Follow-On with TOPEX/Poseidon and ERS-2 for an Improved Description of the Ocean Circulation?

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.

Using Topex/Poseidon Data to Enhance ERS-1 Data

Abstract This paper presents a relatively straightforward method for efficiently reducing the ERS-1 orbit error using Topex/Postidon data. The method is based on a global minimization of Topex/Poscidon-ERS-1 (TP-E) dual crossover differences. The TP-E crossover differences give an estimate of the ERS-1 radial orbit error almost directly, leading to a geometric estimation of orbit error. Smoothing cubic-spline functions are then used to obtain a continuous estimation of the orbit error over time. The splines can also be adjusted to minimize the ERS-1-ERS-1 (E-E) crossover differences. This allows a better estimation of the orbit error, especially poleward of 66° where no TP-E crossovers are available. The method was successfully applied to the final TP and ERS-1 datasets [i.e., the TP GDRs (geophysical data records) and the ERS-1 OPRs (ocean products)]. The authors used one full 35-day ERS-1 cycle and five TP cycles concurrent with ERS-1 data. Only crossovers with time differences lm than 5 days are used i...

Use of a High-Resolution Model to Analyze the Mapping Capabilities of Multiple-Altimeter Missions

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...

Effects of Global Mean Atmospheric Pressure Variations on Mean Sea Level Changes from TOPEX/Poseidon

Abstract The authors used meteorological pressure fields from the European Centre for Medium-Range Weather Forecasts to calculate a mean global pressure to serve as a reference for an improved inverse barometer correction of altimeter data. These global pressure fields, available every 6 h on a ½ degree grid, enabled the extraction of the dominant mean pressure signals. Then, the effect of an improved inverse barometer correction on TOPEX/Poseidon mean sea level variation was estimated. Different low-pass smoothings of global mean pressure were used with cutoff frequencies ranging from (40 to 2 days)−1. Best results were obtained with the (2 days)−1 cutoff frequency, which was then used for an improved inverse barometer correction. The improved correction reduces the standard deviation of mean sea level variations (relative to an annual cycle and slope) by more than 20% when compared with standard inverse barometer correction and no correction at all. It also slightly reduces the variance of sea surface h...

Velocity Mapping Capabilities of Present and Future Altimeter Missions: The Role of High-Frequency Signals

Abstract A detailed analysis of the velocity field mapping capabilities from existing and future multiple altimeter missions is carried out using the Los Alamos North Atlantic high-resolution model. The velocity mapping errors on the instantaneous fields and on 10-day averaged fields are systematically computed for all analyzed configurations. The T/P+ERS (Jason-1+ENVISAT) mapping error on the velocity remains acceptable (20%–30%) relative to the ocean signal. Mapping errors of 10-day averaged fields are twice as small, which shows that this configuration has a good potential for mapping lower frequencies of the velocity field. Compared to T/P+ERS, T/P+Jason-1 has a smaller error by about 20%–30% mainly because it is less sensitive to the aliasing of high-frequency signals. The mapping errors are twice as small with a three interleaved Jason-1 configuration. One of the main findings of this study is the role of high-frequency signals that strongly limit the velocity mapping accuracy. The high-wavenumber h...

Mapping the Oceanic Mesoscale Circulation: Validation of Satellite Altimetry Using Surface Drifters

Abstract This study aims to show that Lagrangian surface drifters are a suitable means of validating the mapping of oceanic mesoscale circulation by satellite altimetry. Tests are done using Geosat data to simulate drifter trajectories in the Azores-Madeira area. Multivariate objective analysis is then done to estimate the dynamic topography and its associated formal error using the velocity measurements obtained along drifter trajectories. This dynamic-topography field is compared with the reference field as given by Geosat data. Sensitivity to drifter number and energy level is studied. It is shown that with 25 drifters in a 500-km × 500-km area, the dynamic topography is obtained to within a formal accuracy of around 10%–20%. The difference between the estimated and reference fields is below 2 cm rms. These errors are smaller than the mapping errors induced by the space-time sampling of ERS-1 or TOPEX-POSEIDON satellites. According to these preliminary results, surface drifters are an efficient tool fo...

Empirical Correction of XBT Data

AbstractThe authors use a collocation method between XBT and CTD/Ocean Station Data (OSD; including bottle cast and low-resolution CTD) from World Ocean Database 2005 (WOD2005) to statistically correct the XBT fall rate. An analysis of the annual median bias on depth shows that it is necessary to apply a thermal correction, a second-order correction on the depth, as well as a depth offset representing measurement errors during XBT deployment. Data were separated into several categories: shallow and deep XBTs and below or above 10°C of vertically averaged ocean temperatures (in the top 400 m). Also, XBT measurements in the western Pacific between 1968 and 1985 were processed separately because of large regional biases. The estimated corrections deviate from other published estimates with some large variations in time of both linear and curvature terms in the depth corrections, and less time variation of the temperature correction for the deep XBTs. This analysis of heat content derived from corrected XBTs ...

Analysis of Errors Due to Polynomial Adjustment of Altimeter Profiles

Abstract Among the various sources of error on altimetric sea surface height variability, the orbit error has the largest amplitude. However, since orbit error is mostly at long wavelengths, it can theoretically be distinguished from the mesoscale signal, characterized by wavelengths of a few hundred kilometers. The most commonly used technique to subtract this long-wavelength error is polynomial adjustment (zero, first or second degree) over distances of a few thousand kilometers. This paper examines the error on estimating the polynomial, which directly impacts the mesoscale signal obtained after the adjustment. We demonstrate how it can be estimated in theory and how it varies according to the spatial and energetic mesoscale characteristics (variability level, nonhomogeneities). These results are checked against simulated data and validated using actual Geosat data. The error is far from negligible: for a first-degree fit over 1500 km or a second-degree fit over 2500 km, its amplitude is typically 30% ...