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Sensors 2016, 16(12), 2000; doi:10.3390/s16122000

Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter

1
Qingdao Collaborative Innovation Center of Marine Science and Technology, College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China
2
Institut Telecom/Telecom Bretagne, UMR LabSTICC, Technopôle Brest-Iroise, Brest 29280, France
3
Collecte Localisation Satellites, Brest 29280, France
4
Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266100, China
*
Author to whom correspondence should be addressed.
Academic Editor: Changzhi Li
Received: 21 May 2016 / Revised: 19 October 2016 / Accepted: 11 November 2016 / Published: 25 November 2016
View Full-Text   |   Download PDF [9502 KB, uploaded 25 November 2016]   |  

Abstract

The swell propagation model built on geometric optics is known to work well when simulating radiated swells from a far located storm. Based on this simple approximation, satellites have acquired plenty of large samples on basin-traversing swells induced by fierce storms situated in mid-latitudes. How to routinely reconstruct swell fields with these irregularly sampled observations from space via known swell propagation principle requires more examination. In this study, we apply 3-h interval pseudo SAR observations in the ensemble Kalman filter (EnKF) to reconstruct a swell field in ocean basin, and compare it with buoy swell partitions and polynomial regression results. As validated against in situ measurements, EnKF works well in terms of spatial–temporal consistency in far-field swell propagation scenarios. Using this framework, we further address the influence of EnKF parameters, and perform a sensitivity analysis to evaluate estimations made under different sets of parameters. Such analysis is of key interest with respect to future multiple-source routinely recorded swell field data. Satellite-derived swell data can serve as a valuable complementary dataset to in situ or wave re-analysis datasets. View Full-Text
Keywords: pseudo SAR observation; EnKF; swell field reconstruction; parameter sensitivity pseudo SAR observation; EnKF; swell field reconstruction; parameter sensitivity
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Wang, X.; Tandeo, P.; Fablet, R.; Husson, R.; Guan, L.; Chen, G. Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter. Sensors 2016, 16, 2000.

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