Concluding Remarks

The chapter provides only a very brief summary of ocean remote sensing measurement principles. More information can be found in Fu and Cazenave (2001), Robinson (2004) and Martin (2004) books.

Satellite data play a fundamental role for operational oceanography. They are mandatory to constrain ocean models through data assimilation and they provide directly useable data products for applications. Over the past 10 years, new and improved data sets and products needed by the modeling and data assimilation systems and for applications have been developed. Accuracy and timeliness of products have been improved. This has resulted in a larger and more systematic assimilation of satellite data into ocean models. Sampling and error characteristics, measurement content must be well understood, however, for a proper use in ocean models. In-situ data are also mandatory to calibrate, validate and complement satellite observations.

There are still a series of advances in satellite oceanography that are expected to impact operational oceanography and its applications:

• Continuous data processing improvements are needed so that data sets and products evolve according to requirements from modeling and data assimilation systems (including error characterization).

• New satellite missions for SSS (SMOS, Aquarius) and gravity (GOCE) and high resolution altimetry (SWOT) will likely have a major impact on operational oceanography.

• Better management of the huge amount of data coming from various instruments is needed. We need to exploit the data in an efficient way. New tools to search, process and visualize data from different sources are required.

• We are not fully exploiting the information content of satellite observations. Most observations are not yet sufficiently explored and used in ocean models. Synergy between observations (satellite, in-situ), models and new theories should be developed further. This is needed, in particular, to better exploit the high resolution information in satellite observations (e.g. Isern-Fontanet et al. 2006).

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