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Mesoscale turbulence in the ocean and synergy of variables: merging of SMOS and Aquarius SSS maps using new, non-parametric methods
|Autor:||Turiel, Antonio ; Umbert, Marta ; Hoareau, Nina ; Ballabrera-Poy, Joaquim ; Font, Jordi|
|Fecha de publicación:||3-dic-2012|
|Editor:||American Geophysical Union|
|Citación:||AGU Fall Meeting: OS21E-1798 (2012)|
|Resumen:||Remote sensing platforms onboard satellites provide synoptic maps of ocean surface and thus an accurate picture of many processes taking place in the ocean at mesoscale and sub-mesoscale levels mainly can be gained. Since the first ocean observation satellites these images has been exploited to assess ocean processes; however, extracting further dynamic information from remote sensing maps generally implies a higher degree of processing complexity, involving the use of numerical models and assimilation schemes. A critical variable for the understanding the climate system is Sea Surface Salinity (SSS). The arrival of SMOS and Aquarius missions has given us access to SSS in a regular basis. However, those images still suffer of many acquisition and processing issues, what precludes gaining a complete picture of ocean surface dynamics. In order to favor the oceanographic exploitation of SMOS and Aquarius maps new filtering schemes need to be devised. During the last years a new branch of image processing techniques applied to ocean observation has arisen with force, namely multiscale/multifractal analysis. Different scalars submitted to the action of the ocean flow develop an identical inner structure (multifractal structure) that can be revealed by means of the appropriate analysis tools (singularity analysis). These tools allow for instance to characterize surface currents from snapshots of different scalars (Turiel et al, Ocean Sciences, 2009). In this work we go further away, with the introduction of a new method to blend different types of scalar in a single map of improved quality. The method does not imply the introduction of any parameter, nor relies in any numerical model, but in the assumption that the action of the oceanic flow leads to the same multifractal structure in any ocean variable. The method allows, for instance, to use the multifractal structure coming from SST images to improve the quality of SSS maps (as illustrated in the figure). It can also be applied to merge SMOS and Aquarius maps to increase the quality and spatial coverage. http://http://www.smos-bec.icm.csic.es/|
|Descripción:||AGU Fall Meeting 3–7 December 2012, San Francisco, California|
|Versión del editor:||http://fallmeeting.agu.org/2012/eposters/eposter/os21e-1798/|
|Aparece en las colecciones:||(ICM) Comunicaciones congresos|
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