Éditeur(s) : Ieee-inst Electrical Electronics Engineers Inc
Résumé : The synthetic aperture radar (SAR) Doppler centroid has been used to estimate the scatter line-of-sight radar velocity. In weak to moderate ocean surface current environment, the SAR Doppler centroid is dominated by the directionality and strength of wave-induced ocean surface displacements. In this paper, we show how this sea state signature can be used to improve surface wind retrieval from SAR. Doppler shifts of C-band radar return signals from the ocean are thoroughly investigated by colocating wind measurements from the ASCAT scatterometer with Doppler centroid anomalies retrieved from Envisat ASAR. An empirical geophysical model function (CDOP) is derived, predicting Doppler shifts at both VV and HH polarization as function of wind speed, radar incidence angle, and wind direction with respect to radar look direction. This function is used into a Bayesian inversion scheme in combination with wind from a priori forecast model and the normalized radar cross section (NRCS). The benefit of Doppler for SAR wind retrieval is shown in complex meteorological situations such as atmospheric fronts or low pressure systems. Using in situ information, validation reveals that this method helps to improve the wind direction retrieval. Uncertainty of the calibration of Doppler shift from Envisat ASAR hampers the inversion scheme in cases where NRCS and model wind are accurate and in close agreement. The method is however very promising with respect of future SAR missions, in particular Sentinel-1, where the Doppler centroid anomaly will be more robustly retrieved.
Ieee Transactions On Geoscience And Remote Sensing (0196-2892) (Ieee-inst Electrical Electronics Engineers Inc), 2012-07 , Vol. 50 , N. 7 , P. 2901-2909

Droits : 2012 IEEE
http://archimer.ifremer.fr/doc/00088/19896/17554.pdf
DOI:10.1109/TGRS.2011.2174998
http://archimer.ifremer.fr/doc/00088/19896/

Éditeur(s) : ESA Publication
Résumé : Satellite remote sensing has emerged as an essential and necessary observing system to acquire global information about the state of the ocean. Complemented with in situ observing networks, the ultimate goals are to be able to make accurate estimates of selected key sets of geophysical variables, with the intention of either making operational predictions across time and spatial boundaries, or advancing fundamental knowledge through development of empirical relationships and theoretical models. For satellite oceanography, improvements are then constantly being sought in our understandings of the geophysical processes, the sensor physics, the electromagnetic and microwave properties and interactions at the complex air-sea interface. Challenges appear as unlimited as the variety of sea surface dynamics and boundary layer meteorological conditions with their broad range of spatial and temporal scales across the globe. To face these challenges, numerous efforts took places over the passed decade to build an ever-increasing quality, quantity, duration and integration of ocean observations. In parallel, simulation capabilities largely improved. All these efforts are then all critically calling for improved methodologies to better structure the wealth of information that is made readily accessible. This latter aspect is a very demanding new component for future multidisciplinary scientific research. Major innovations to consolidate sensor data repositories, to automate tailored queries, to extract, reveal and quantify relationships will then closely associate computer science developments and applied statistics with comprehensive theoretical and experimental thematic studies.
Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (ESA Publication), 2010

Droits : info:eu-repo/semantics/openAccess
http://archimer.ifremer.fr/doc/00029/14046/11241.pdf
DOI:10.5270/OceanObs09.pp.12
http://archimer.ifremer.fr/doc/00029/14046/