Nicolas Picot

The CNES_CLS11 Global Mean Sea Surface Computed from 16 Years of Satellite Altimeter Data

This article focuses on the determination and the validation of the new Mean Sea Surface from the CNES/CLS. This new model merges multiple satellite altimeters over 16 years of observations. Particular attention was paid on the analysis of the oceanic variability. Then a novel method was applied to remove this variability and to take into account different kinds of errors that affect the data. Several types of validations were performed to estimate the quality of the shortest topographic structures and to quantify the accuracy of the mean oceanic content at a larger scale.

Jason-2 in DUACS: Updated System Description, First Tandem Results and Impact on Processing and Products

For more than 13 years, the multisatellite DUACS system has been providing the altimetry community with Near Real Time and Delayed Time products ranging from reduced GDR (also known as CorrSSH) to along-track Sea Level Anomalies (SLA) and multimission Maps of Sea Level Anomalies (MSLA). A post-Jason-2 description of the DUACS system is given, with input data, processing and products, and a focus on the DT-2010 reprocessing involving a total of almost 60 years worth of altimetry data from GEOSAT to Jason-2. Less than one month after launch, Jason-2 proved to be a strong asset for multisatellite applications as it was able to replace Jason-1 as the reference mission in DUACS. Furthermore, the new Jason-2/Jason-1 tandem configuration provides an unprecedented duo for mesoscale and circulation observation. More generally, the quality of Jason-2 has a large impact in DUACS on a number of fronts: in the continuity of the reference mission for climate applications exploiting DUACS products, in the new multi-reference orbit error reduction scheme, or for new metrics derived from a Degrees of Freedom of Signal analysis applied to the multimission mapping. This paper gives an overview of the many impacts of the integration of Jason-2 into DUACS.

The SARAL/AltiKa Altimetry Satellite Mission

The India-France SARAL/AltiKa mission is the first Ka-band altimetric mission dedi-cated to oceanography. The mission objectives are primarily the observation of the oceanic mesoscales but also include coastal oceanography, global and regional sea level monitoring, data assimilation, and operational oceanography. Secondary objectives include ice sheet and inland waters monitoring. One year after launch, the results widely confirm the nominal expectations in terms of accuracy, data quality and data availability in general. Todays performances are compliant with specifications with an overall observed performance for the Sea Surface Height RMS of 3.4 cm to be compared to a 4 cm requirement. Some scientific examples are provided that illustrate some salient features of todays SARAL/AltiKa data with regard to standard altimetry: data availability, data accuracy at the mesoscales, data usefulness in costal area, over ice sheet, and for inland waters.

Jason-2 Global Statistical Assessment and Cross-Calibration with Jason-1

OSTM/Jason-2 (Ocean Surface Topography mission, named Jason-2 in this paper) satellite was successfully launched on June 20, 2008, and was put on its nominal orbit on July 4, 2008. Up to January 26, 2009, Jason-2 was flying in formation with Jason-1 only 55 seconds apart before Jason-1 was moved to its new interleaved orbit. The objectives of this paper are to assess Jason-2 data quality and to estimate the altimetry system performance from the beginning of the mission, using Geophysical Data Records (GDRs) products. Our study will focus on Jason-1/Jason-2 cross-calibration using the opportunity that the missions were on the same ground track separated by 55 seconds during the formation flight phase. This allows us to precisely assess parameter discrepancies and Sea Surface Height (SSH) consistency between both missions in order to detect geographically correlated biases, jumps or drifts. From the results presented in this paper, it is demonstrated that the Jason-2 mission fulfils the requirements of high precision altimetry, which is crucial for future oceanographic studies and applications. In particular, it allows continuation of the observation of the Mean Sea Level (MSL) variations at the same (or better) accuracy as Jason-1 and TOPEX/Poseidon, which was one of the challenges of the Jason-2 mission. Potential improvements and open issues are also identified, with the objective of still making progress in terms of altimetry data quality.

Overview and Update of the Sea State Bias Corrections for the Jason-2, Jason-1 and TOPEX Missions

We present a Jason-2 sea state bias (SSB) model from the first year of GDR products along with updates of Jason-1, TOPEX-A, and TOPEX-B solutions. Our re-evaluation of the Jason-1 SSB focused on data from the new version (C) of the GDR while for TOPEX, the updated solutions benefited from the availability of both a set of new precise orbits that are consistent with Jason-2 and an updated set of state-of-the-art geophysical corrections. Therefore, derived from homogeneous sea surface height (SSH) data to minimize geographically correlated SSH differences between missions, these empirical SSB models contribute to the consistency between Jason-2 and Jason-1 SSH data and between TOPEX and Jason-1 data during their respective tandem phase and thus to the stability of the whole altimetry system over the past 17-year period.

Relative Performance of the MLE3 and MLE4 Retracking Algorithms on Jason-2 Altimeter Waveforms

For all altimeter missions, precise estimates of geophysical parameters are obtained thanks to an algorithm called “retracking” that fits an analytical model to the measured waveforms. The Brown model provides a good representation of the return echo over deep ocean surfaces and is commonly used. Many different chains can be considered (and have already been tested) for this processing. An unweighted Least Square Estimate derived from a Maximum Likelihood Estimator (MLE) (Dumont 1985; Rodriguez 1988) is implemented in most altimeter ground processing approaches (TOPEX, Jason-1, Jason-2, and Envisat). The aim of this paper is to evaluate the performance of two retracking algorithms based on the same least square principle: The MLE3 algorithm estimates three parameters (range, significant wave height, and power) whereas the MLE4 estimates four parameters (the three previous ones and the slope of the waveform trailing edge). MLE3 was used on Jason-1 before star tracker problems occurred. The MLE4 algorithm has been used for Jason-1 Version B products and onward and for Jason-2 products from the start of the mission. Both algorithms are compared in the paper. Advantages and drawbacks of both algorithms are pointed out showing notable benefits provided by MLE4 especially for waveforms that do not conform to the Brown model.

Comparing Altimetry with Tide Gauges and Argo Profiling Floats for Data Quality Assessment and Mean Sea Level Studies

Altimeter missions have provided accurate measurements of sea surface height since 1992 not only with TOPEX/Poseidon but also with Jason-1, Envisat, and recently Jason-2. The overall quality assessment of altimeter data can be performed by analyzing their internal consistency and the cross-comparison between all missions. In this study, in situ measurements are used as an external, independent reference to enable further quality assessment of the altimeter sea level. The most up-to-date altimeter data are assessed and compared with those from tide gauges and Argo profiling floats. The first focus is on detection of global and regional drifts in altimeter sea surface height compared with in situ measurements. A second point is that the method can assess the impact of new altimeter standards (e.g., orbit solution, instrumental correction, retracking algorithm) thanks to in situ observations. Finally, the study shows how multiple and reliable altimeter products are used to detect potential anomalies in tide gauges. The results demonstrate the close link between these three steps of the method: while the detection of altimeter drifts using in situ measurements is corrected by computing new altimeter standards whose impact can then be estimated, the improved altimeter sea level time series are used as input for controlling the quality of in situ observations.

A New Estimation of Mean Sea Level in the Arctic Ocean from Satellite Altimetry

Sea level monitoring in the Arctic Ocean can provide useful information in the context of a rapid change of several parts of the Arctic climate system. Satellite altimetry systems are affected by various problems at high latitudes. As a consequence, no precise and reliable mean sea level record is available yet from altimetry products. After identifying some of the issues that affect satellite altimetry in the Arctic Ocean region, we describe the tailored processing that has been applied to along-track mono-mission altimetry data. We generate a new dataset of weekly gridded sea level anomaly fields over the Arctic region for the period spanning from 1993 to 2009 based on multisatellite altimetry missions. We demonstrate the improvements achieved by this new dataset, among which a better data coverage. The grids are used to describe some features of mean sea level variability in the Arctic Ocean both at basin-wide and local scales. The regional trend estimated for the Arctic Ocean mean sea level over all latitudes from 66°N to 82°N is 3.6 mm/yr with an uncertainty of 1.3 mm/yr (90% confidence) and without any glacial isostatic adjustment (GIA) correction applied. The record displays large inter-annual variability, but no strong correlation with climate indices was found. Spatial patterns in sea level trends and variability over the Arctic region are also investigated.

Using SARAL/AltiKa to Improve Ka-band Altimeter Measurements for Coastal Zones, Hydrology and Ice: The PEACHI Prototype

Following the successful launch of the SARAL space mission in February 2013, the reliability of the innovative AltiKa altimeter has been demonstrated for deep ocean applications, where Ka-band performances are excellent. With the objective to ensure the complementarity but also the continuity with the altimeter Level-2 products provided in the open ocean, the Prototype for Expertise on AltiKa for Coastal, Hydrology and Ice (PEACHI) project has been set up as an initiative of the French space agency, CNES, to provide a data set of research-grade Level-2 parameters that might be interesting for SARAL secondary objectives on the study of coastal dynamics, inland waters, polar oceans, or continental and sea ices. Thus, the PEACHI prototype has been developed to process and accurately tune dedicated algorithms for the assessment of Ka-band parameters, from the instrument processing to geophysical corrections. As a result, the PEACHI prototype routinely provides end users with new or improved altimeter corrections for scientific applications dedicated to mesoscale monitoring but also synergistic science.

Envisat Ocean Altimeter Becoming Relevant for Mean Sea Level Trend Studies

This article deals with the recent improvements of the Global and Regional Mean Sea Level trend using Envisat data. It focuses on the methodology based on comparison with Jason-1, Jason-2, and in situ data and shows that Envisat is now getting more reliable for MSL studies, as a comparison reference for future missions. Notably, Jason-1/Envisat comparisons enabled to detect a weakness in the orbit standard solution, now improved for all altimetric missions including Jason-2.