Abstract

Abstract. This study presents the evaluation of the performances of satellite altimeter missions by comparing the altimeter sea surface heights with in situ dynamic heights derived from vertical temperature and salinity profiles measured by Argo floats. The two objectives of this approach are the detection of altimeter drift and the estimation of the impact of new altimeter standards that requires an independent reference. This external assessment method contributes to altimeter calibration–validation analyses that cover a wide range of activities. Among them, several examples are given to illustrate the usefulness of this approach, separating the analyses of the long-term evolution of the mean sea level and its variability, at global and regional scales and results obtained via relative and absolute comparisons. The latter requires the use of the ocean mass contribution to the sea level derived from Gravity Recovery and Climate Experiment (GRACE) measurements. Our analyses cover the estimation of the global mean sea level trend, the validation of multi-missions altimeter products as well as the assessment of orbit solutions.Even if this approach contributes to the altimeter quality assessment, the differences between two versions of altimeter standards are getting smaller and smaller and it is thus more difficult to detect their impact. It is therefore essential to characterize the errors of the method, which is illustrated with the results of sensitivity analyses to different parameters. This includes the format of the altimeter data, the method of collocation, the temporal reference period and the processing of the ocean mass solutions from GRACE. We also assess the impact of the temporal and spatial sampling of Argo floats, the choice of the reference depth of the in situ profiles and the importance of the deep steric contribution. These analyses provide an estimation of the robustness of the method and the characterization of associated errors. The results also allow us to draw some recommendations to the Argo community regarding the maintenance of the in situ network.

Highlights

  • Since the early 1990s, several satellite missions have been equipped with altimeters allowing the estimation of sea level anomalies (SLAs) and the monitoring of mean sea level (MSL)

  • This illustrates that the estimation of the altimeter absolute drift is possible thanks to the combined used of Argo and Gravity Recovery and Climate Experiment (GRACE) data, but it is affected by significant uncertainties related to the estimation of the different ocean mass solutions

  • The in situ dynamic heights derived from the Argo network can be used as an independent reference for the analysis of the relative mean sea level temporal evolution, and for the detection of the impact of new altimeter standards or products used to calculate the sea surface heights

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Summary

Introduction

Since the early 1990s, several satellite missions have been equipped with altimeters allowing the estimation of sea level anomalies (SLAs) and the monitoring of mean sea level (MSL). The relative comparison of these data sets with Argo measurements shows that in the Bay of Bengal the use of the new altimeter release leads to a reduced variability (−1 cm2) of the SLA minus DHA differences (not shown) and a slightly greater correlation and a reduced root mean square (rms) of the differences with the in situ reference (see Table 1) All these illustrations clearly demonstrate that the Argo in situ measurements are a valuable tool to detect altimeter drift and to assess the impact of a new altimeter standard or product, regarding the long-term evolution of the mean sea level or its variability, at global or regional scales. At last, concluding remarks are provided on the method uncertainty and the results allow us to draw some recommendations for the Argo community regarding the maintenance of the in situ network

Altimetry
Sensitivity of the method
Format of altimeter data
Error of collocation
Impact of the temporal reference period
Impact of the GRACE data set and associated errors
Impact of the temporal sampling of the Argo floats
Impact of the spatial sampling of the Argo network
Reference depth of Argo profiles
Impact on the global and regional coverage
Impact on the global MSL trend estimation
Impact of the deep steric contribution
Findings
Conclusions
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