Reduction of spatially structured errors in wide-swath altimetric satellite data using data assimilation

Show simple item record Metref, Sammy Cosme, Emmanuel Le Sommer, Julien Poel, Nora Brankart, Jean-Michel Verron, Jacques Gómez Navarro, Laura 2020-01-23T09:20:19Z 2020-01-23T09:20:19Z
dc.description.abstract [eng] The Surface Water and Ocean Topography (SWOT) mission is a next generation satellite mission expected to provide a 2 km-resolution observation of the sea surface height (SSH) on a two-dimensional swath. Processing SWOT data will be challenging because of the large amount of data, the mismatch between a high spatial resolution and a low temporal resolution, and the observation errors. The present paper focuses on the reduction of the spatially structured errors of SWOT SSH data. It investigates a new error reduction method and assesses its performance in an observing system simulation experiment. The proposed error-reduction method first projects the SWOT SSH onto a subspace spanned by the SWOT spatially structured errors. This projection is removed from the SWOT SSH to obtain a detrended SSH. The detrended SSH is then processed within an ensemble data assimilation analysis to retrieve a full SSH field. In the latter step, the detrending is applied to both the SWOT data and an ensemble of model-simulated SSH fields. Numerical experiments are performed with synthetic SWOT observations and an ensemble from a North Atlantic, 1/60◦ simulation of the ocean circulation (NATL60). The data assimilation analysis is carried out with an ensemble Kalman filter. The results are assessed with root mean square errors, power spectrum density, and spatial coherence. They show that a significant part of the large scale SWOT errors is reduced. The filter analysis also reduces the small scale errors and allows for an accurate recovery of the energy of the signal down to 25 km scales. In addition, using the SWOT nadir data to adjust the SSH detrending further reduces the errors.
dc.format application/pdf
dc.relation.isformatof Reproducció del document publicat a:
dc.relation.ispartof Remote Sensing, 2019, vol. 11, num. 11, p. 1-21
dc.rights cc-by (c) Metref, Sammy et al., 2019
dc.subject.classification 00 - Ciència i coneixement. Investigació. Cultura. Humanitats
dc.subject.classification 6 - Ciències aplicades
dc.subject.other 00 - Prolegomena. Fundamentals of knowledge and culture. Propaedeutics
dc.subject.other 6 - Applied sciences. Medicine. Technology
dc.title Reduction of spatially structured errors in wide-swath altimetric satellite data using data assimilation
dc.type info:eu-repo/semantics/article
dc.type info:eu-repo/semantics/publishedVersion 2020-01-23T09:20:19Z
dc.rights.accessRights info:eu-repo/semantics/openAccess

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