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

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Summary

This study uses the ensemble Kalman filter (EnKF) with satellite data to reconstruct ocean swell fields. The EnKF method shows good spatial-temporal consistency for simulating swells from distant storms.

Keywords:
EnKFparameter sensitivitypseudo SAR observationswell field reconstruction

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Area of Science:

  • Oceanography
  • Remote Sensing
  • Geophysics

Background:

  • Swell propagation models based on geometric optics effectively simulate swells from distant storms.
  • Satellite observations provide large datasets of basin-traversing swells induced by mid-latitude storms.
  • Routine reconstruction of swell fields from irregularly sampled satellite data requires further investigation.

Purpose of the Study:

  • To apply the ensemble Kalman filter (EnKF) for reconstructing ocean swell fields using pseudo SAR satellite observations.
  • To compare EnKF results with buoy data and polynomial regression.
  • To analyze the influence of EnKF parameters on swell field estimation.

Main Methods:

  • Utilized 3-h interval pseudo SAR observations within an ensemble Kalman filter (EnKF) framework.
  • Reconstructed swell fields in an ocean basin.
  • Validated results against in situ buoy measurements and compared with polynomial regression.

Main Results:

  • The EnKF demonstrated strong spatial-temporal consistency in reconstructing far-field swell propagation.
  • EnKF performance was validated against in situ measurements.
  • Sensitivity analysis explored the impact of different EnKF parameter sets.

Conclusions:

  • EnKF is a robust method for reconstructing swell fields from satellite data, particularly in far-field scenarios.
  • Satellite-derived swell data can complement in situ and wave re-analysis datasets.
  • Parameter sensitivity analysis is crucial for future swell field data assimilation.