Preprints
https://doi.org/10.48550/arXiv.2602.01416
https://doi.org/10.48550/arXiv.2602.01416
02 Apr 2026
 | 02 Apr 2026
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Convolution Based Techniques for Computing Self Attraction and Loading in MOM6

Anthony Chen, He Wang, Brian Arbic, and Robert Krasny

Abstract. Self Attraction and Loading (SAL), which includes the deformation of the solid Earth under the load of the ocean tide and the self-gravitation of the so-deformed Earth as well as of the ocean tides themselves, is an important term to include in numerical models of the ocean tides. Computing SAL is a challenging problem that is usually tackled using spherical harmonics. The spherical harmonic approach has several drawbacks which limit its accuracy. In this work, we propose an alternative technique based on a spherical convolution. We implement the convolution technique in the Modular Ocean Model, version 6, and demonstrate that it allows for more accurate tides when measured against tidal datasets based upon satellite altimetry. The convolution based SAL reduces the error by reducing spurious oscillations associated with the Gibbs phenomenon. These oscillations are large in coastal regions under the traditional spherical harmonic approach.

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Anthony Chen, He Wang, Brian Arbic, and Robert Krasny

Status: open (until 28 May 2026)

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Anthony Chen, He Wang, Brian Arbic, and Robert Krasny
Anthony Chen, He Wang, Brian Arbic, and Robert Krasny
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Latest update: 02 Apr 2026
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Short summary
Self Attraction and Loading (SAL) is an important force that affects many oceanic motions, including tides. Computing SAL is challenging and ocean models neglected to include the impacts of SAL for a long time. Recent work has proposed a method for incorporating the effects of SAL, but the method has several limitations that limit the accuracy. This work proposes an alternative method. Tests of this new method in an ocean model indicate that it reduces the amount of error in the modeled tides.
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