Impact of multiple altimeter data and mean dynamic topography in a global analysis and forecasting system

Satellite altimetry is one of the main sources of information used to constrain global ocean analysis and forecasting systems. In addition to in situ vertical temperature and salinity profiles, and Sea Surface Temperature (SST) data, Sea Level Anomalies (SLA) from multiple altimeters are assimilated through the knowledge of a surface reference, the Mean Dynamic Topography (MDT). The quality of analyses and forecasts mainly depends on the availability of SLA observations and on the accuracy of the MDT.

A series of Observing System Evaluations (OSEs) were conducted to assess the relative importance of the number of assimilated altimeters and the accuracy of the MDT in a Mercator Ocean global ¼° ocean data assimilation system. Dedicated tools were used to quantify impacts on analyzed and forecast sea surface height, and temperature/salinity in deeper layers. The study shows that a constellation of four altimeters associated with a precise MDT is required to adequately describe and predict upper ocean circulation in a global ¼° ocean data assimilation system. Compared to a 1-altimeter configuration, a 4-altimeter configuration reduces the mean forecast error by about 30%, but the reduction can reach more than 80% in Western Boundary Current (WBC) regions. The use of the most recent MDT updates improves the accuracy of analyses and forecasts to the same extent as assimilating a fourth altimeter.

Keyword(s)

Ocean, Sea level, Remote sensing, Forecast verification, skill, Operational forecasting, General circulation models

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Hamon Mathieu, Greiner Eric, Le Traon Pierre-Yves, Remy Elisabeth (2019). Impact of multiple altimeter data and mean dynamic topography in a global analysis and forecasting system. Journal Of Atmospheric And Oceanic Technology. 36 (7). 1255-1266. https://doi.org/10.1175/JTECH-D-18-0236.1, https://archimer.ifremer.fr/doc/00502/61389/

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