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Ensemble-Based Data Assimilation of Significant Wave Height from Sofar Spotters and Satellite Altimeters with a Global Operational Wave Model
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  • Isabel Houghton,
  • Stephen Gregory Penny,
  • Christie Hegermiller,
  • Moriah Cesaretti,
  • Camille Teicheira,
  • Pieter Bart Smit
Isabel Houghton
Sofar Ocean

Corresponding Author:isabel.houghton@sofarocean.com

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Stephen Gregory Penny
Sofar Ocean
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Christie Hegermiller
Sofar Ocean Technologies
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Moriah Cesaretti
Sofar Ocean
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Camille Teicheira
Sofar Ocean
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Pieter Bart Smit
Sofar Ocean
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Abstract

An ensemble-based method for wave data assimilation is implemented using significant wave height observations from the globally distributed network of Sofar Spotter buoys and satellite altimeters. The Local Ensemble Transform Kalman Filter (LETKF) method generates skillful analysis fields resulting in reduced forecast errors out to 2.5 days when used as initial conditions in a cycled wave data assimilation system. The LETKF method provides more physically realistic model state updates that better reflect the underlying sea state dynamics and uncertainty compared to methods such as optimal interpolation. Skill assessment far from any included observations and inspection of specific storm events highlight the advantages of LETKF over an optimal interpolation method for data assimilation. This advancement has immediate value in improving predictions of the sea state and, more broadly, enabling future coupled data assimilation and utilization of global surface observations across domains (atmosphere-wave-ocean).
21 Jan 2023Submitted to ESS Open Archive
24 Jan 2023Published in ESS Open Archive