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Ocean Surface Topography from Space
Observatory and Research on extreme PHEnomena over the Oceans (ORPHEO)


Yves Quilfen - (LOS IFREMER)

  Bertrand Chapron
Nicolas Reul
Jean Tournadre
Jean François Piolle
Fabrice Ardhuin
Pierre Queffeulou


Observatory and Research on extreme PHEnomena over the Oceans (ORPHEO)
Jason-1 and -2 SSH anomalies for orbits oriented in the hurricane Igor cross-track direction. The red (blue) anomalies correspond to higher (lower) sea level by comparison with the previous 10-day cycle (current orbit day given at the top of each orbit). The scale is indicated in the upper left corner. The blue line displays the IGOR track with day number given at 12Z. The dotted black line gives the location of the Amazon/Orinoco plume as determined from the SMOS salinity measurements.
Thanks to satellite-based observations, extreme weather events such as tropical cyclones or explosive mid-latitude storms and polar lows can be more commonly reported, directly analyzed (e.g. Quilfen et al., 2010, 2011, Reul et al., 2012) or indirectly characterized (Ardhuin et al., 2009, Collard et al, 2009; Delpey et al., 2010). These measurements are critical for short term forecasting, but also offer means to better question the role of extreme conditions for the state of ocean at local and global scales, and effects on ocean circulation and ocean heat transport. Energy inputs in the region of intense storm tracks are indeed thought to represent the main kinetic energy sources necessary to maintain the deep ocean stratified and to strengthen ocean stirring processes. As already demonstrated by radiometers onboard the DMSP satellite series, WindSat, TRMM, AMSR-E and now SMOS (i.e. Reul et al., 2012), as well as by scatterometers onboard the ERS, ADEOS, QuikScat and METOP satellites, unprecedented synoptic observations of surface wind and atmospheric water content are now possible and are revealing the storm structures with impressive details. Satellite estimates don't necessarily provide direct measurements of geophysical parameters and can suffer from limitations linked to the sensors characteristics, but the combined use of sensors helps to build methods to retrieve geophysical content.

For instance, while certainly limited by its relatively coarse across-track sampling, the altimeter dual frequency radar cross section measurements have been demonstrated to provide very valuable information. Altimeter signals can be processed using specialized algorithms to retrieve the surface wind speed and significant wave height, along with the rain rate in extreme weather events (Quilfen et al., 2006). Winds up to 50 m/s have been estimated in hurricanes using altimeter measurements, to open new perspectives for estimation of extreme event intensity (Quilfen et al., 2011). These observations can thus help to more accurately evaluate the amount of momentum transferred from extreme weather events to the ocean. The resulting intense currents and surface waves excited under hurricane conditions are then associated to local intense cooling, density changes and large sea surface height anomalies, all aspects generally systematically well revealed and observed in the hurricane wakes (Reul et al., in preparation). The large surface waves can further locally modify the air-sea momentum flux, particularly impact the drag coefficient, and contribute to so-called Coriolis-Stokes forcings. Away from the extreme events, the radiated swell fields may then eventually cover a full ocean basin, and have a lifetime that can extend over few days according to the swell propagation properties to allow multiple observations (e.g. Delpey et al., 2010).

In this project, we then intend to further elaborate on these previous results to explore in depth these combined capabilities to observe and quantitatively characterize extreme events. From a sensor physics point of view, special attention will be given to more thoroughly understand and model of foam characteristics (coverage and thickness) which strongly impact the passive and active measurements under very high wind conditions. In particular, the SMOS L-band radiometer with its large swath coverage is actually the least affected by heavy precipitations to provide more quantitative insights about extremes (Reul et al., 2012). Moreover, between the altimeter and SAR sea state measurements, the methodology already developed (Collard et al., 2009) will then be extended to more precisely provide valuable information to describe the sea state structures in the wake, near the center, and ahead of the storm, to better characterize the intensity near the intense generation area.

Finally, in combination with other sensors and numerical models, the available time series of wind and wave measurements obtained from different satellite platforms since the beginning of the nineties, will be used to analyze these data to characterize the variability in the most intense surface wind and associated wave fields. The link between changes in the mean fields with changes in storms distribution characteristics will then be more closely investigated and assessed.

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