Abstract's details

Wavelet analysis of Altika measurements

Jean-Christophe Poisson (CLS, France)


Pierre Thibaut (CLS, France); Duc Hoang (CLS, France); François Boy (CNES, France); Amandine Guillot (CNES, France); Nicolas Picot (CNES, France)

Event: 2014 Ocean Surface Topography Science Team Meeting

Session: Quantifying Errors and Uncertainties in Altimetry data

Presentation type: Type Oral

Contribution: PDF file


The SARAL/AltiKa Satellite has been successfully launched on February 25, 2013. It embarks the first radar altimeter in Ka-band. The AltiKa instrument is a Low Resolution Mode altimeter as on Jason or Envisat. As for the previous missions, the on-ground waveform retracking algorithm uses a Brown model. However, it has already been shown that backscattering heterogeneities in the disc-shaped-footprint (e.g. sigma0 blooms, rain cells or others) can induce strong perturbations of the sea level anomaly (SLA) measurements. The result of these pollutions is manifested by a "spectral hump" on the SLA power spectrum. Given that the spectral hump is due to transient backscattering phenomena, we propose to analyze altimetry signals using the continuous wavelet transform which appears to be much more relevant in this context.
In the framework of the PEACHI project (Prototype for Expertise on AltiKa, for Coastal, Hydrology and Ice, project funded by CNES) dedicated to the study of AltiKa measurements and to the improvement of the products, a continuous wavelet transform tool (CWT) is developed and implemented to compute the corresponding wavelet power spectrum at each 40Hz AltiKa measurement. This algorithm is based on the exploitation of the slope of the trailing edge of the waveform (which is clearly linked to the properties of the scatterers in the waveform footprint). A simple thresholding processing on the computed power spectral density, make possible the location and the editing of the most corrupted measurements. Then, depending on the chosen threshold and using other parameters like the Integrated liquid Water Content (deduced from the colocalized radiometer measurements) or like the level of the thermal noise in the waveforms, rain cells and sigma0 blooms can be discriminated and rain rate can be estimated.

Oral presentation show times:

Room Start Date End Date
Ballroom Thu, Oct 30 2014,09:00 Thu, Oct 30 2014,09:15
Jean-Christophe Poisson