| Summary: | European Geosciences Union General Assembly 2014 (EGU2014), 27 april - 2 may 2014, Vienna, Austria.-- 1 page Satellite Remote sensing measurements are used in oceanography since the mid-1970s. Thanks to satellite imagery, the research community has been able to better interpret surface structures, such as meandering fronts or eddies, which became apparent in instantaneous views of the ocean. Moreover, satellite altimeter and sea surface temperature (SST) observations evidenced the high percentage of ocean energy accumulated at the intermediate scales (tens to hundreds of km, days-weeks), i.e. the oceanic mesoscale. Today, thanks to the launch of the Soil Moiture and Ocean Salinity (SMOS) mission (2009) and the Aquarius mission (2011), we have more than four years of satellite-derived Sea Surface Salinity (SSS) observations with the objectives of improving seasonal and interannual climate prediction, ocean rainfall estimates and hydrologic budgets, and monitoring large-scale salinity events and thermohaline convection (Lagerloef, 2001). A study from Reynolds and Chelton (2010) compared six different SST products using spatial power density spectra in three regions of the ocean at different periods (January and July 2007-2008). The results showed that the spatial spectra vary geographically and temporally, and from one product to the next. Here, a similar study is presented for the first time with SSS data to help understand the spatial signature of the SSS variability and validate the different data sources. Thanks to the increased maturity of remote sensing estimations of SSS, the spatial spectra of the SSS fields provided by numerical models can now be compared with observations. In this work, we focus on the region of North Atlantic Ocean for the year of January and July of 2011 and 2012. The data used in this work come from Satellites (AQUARIUS and/or SMOS Level 2), outputs of an ocean model (NEMO-OPA, configuration DRAKKAR-NATL025), in-situ observations collected during the Barcelona World Race (BWR 2010), ...
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