Back
Peer-Reviewed Research

Ensemble-based data assimilation of significant wave height from Sofar Spotters and satellite altimeters with a global operational wave model

Sofar Ocean

This paper was written by I. A. Houghton, S. G. Penny, C. Hegermiller, M. Cesaretti,  C. Teicheira, and P. B. Smit.

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).

Sofar in the News
In the News
October 23, 2023
Wayfinder delivers 8% total equivalent fuel savings on Brazil-China (BDI C14) voyages arriving in early October
In the News
October 2, 2023
What was different about the latest Advanced Naval Technology Exercise
In the News
September 25, 2023
Sofar Ocean's Superior Weather Forecasts Minimize Voyage Costs

Related Stories