Altimeter Signal-to-Noise for Deep Ocean Processes in Operational Systems

Abstract

The ocean signal for this study is the sea surface height due to the slowly varying (greater than 5-day) ocean processes, which are predominantly the deep ocean mesoscale. These processes are the focus of present assimilation systems for monitoring and predicting ocean circulation due to ocean fronts and eddies and the associated environmental changes that impact real time activities in areas with depths greater than about 200 m. By this definition, signal-to-noise may be estimated directly from altimeter data sets through a crossover point analysis. The RMS variability in crossover differences is due to instrument noise, errors in environmental corrections to the satellite observation, and short time period oceanic variations. The signal-to-noise ratio indicates that shallow areas are typically not well observed due to the high frequency fluctuations. Many deep ocean areas also contain significant high frequency variability such as the subpolar latitudes, which have large atmospheric pressure systems moving through, and these in turn generate large errors in the inverse barometer correction. Understanding the spatial variations of signal to noise is a necessary prerequisite for correct assimilation of the data into operational systems.

Keywords:

• satellite altimetry
• Jason-1
• TOPEX/Poseidon
• ERS
• GFO
• near real time
• sea surface height
• mesoscale features
• data assimilation

Acknowledgments

Two reviewers provided valuable comments that significantly improved this manuscript. This work was sponsored by the SPAWAR project “Altimeter Data Fusion Center Support” and the NRL project “Slope to Shelf Energetics and Exchange Dynamics.” This article is NRL paper contribution number NRL/JA/7320/04/0009.