Global Barotropic Tide Modeling Using Inline Self-Attraction and Loading in MPAS-Ocean

• Main Authors: Barton, Kristin N., Pal, Nairita, Brus, Steven R., Petersen, Mark R., Arbic, Brian K., Engwirda, Darren, Roberts, Andrew F., Westerink, Joannes J., Wirasaet, Damrongsak, Schindelegger, Michael
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Graduate School of Oceanography, University of Rhode Island 2022
• Subjects: numerical ocean modeling; E3SM; barotropic tides; surface tides; self-attraction and loading; MPAS-Ocean; Geological Sciences; Science; Arctic
• Online Access: https://hdl.handle.net/2027.42/175240; https://doi.org/10.1029/2022MS003207

We examine ocean tides in the barotropic version of the Model for Prediction Across Scales (MPAS-Ocean), the ocean component of the Department of Energy Earth system model. We focus on four factors that affect tidal accuracy: self-attraction and loading (SAL), model resolution, details of the underlying bathymetry, and parameterized topographic wave drag. The SAL term accounts for the tidal loading of Earth’s crust and the self-gravitation of the ocean and the load-deformed Earth. A common method for calculating SAL is to decompose mass anomalies into their spherical harmonic constituents. Here, we compare a scalar SAL approximation versus an inline SAL using a fast spherical harmonic transform package. Wave drag accounts for energy lost by breaking internal tides that are produced by barotropic tidal flow over topographic features. We compare a series of successively finer quasi-uniform resolution meshes (62.9, 31.5, 15.7, and 7.87 km) to a variable resolution (45 to 5 km) configuration. We ran MPAS-Ocean in a single-layer barotropic mode forced by five tidal constituents. The 45 to 5 km variable resolution mesh obtained the best total root-mean-square error (5.4 cm) for the deep ocean (> $ > $1,000 m) M2 ${mathrm{M}}_{2}$ tide compared to TPXO8 and ran twice as fast as the quasi-uniform 8 km mesh, which had an error of 5.8 cm. This error is comparable to those found in other forward (non-assimilative) ocean tide models. In future work, we plan to use MPAS-Ocean to study tidal interactions with other Earth system components, and the tidal response to climate change.Plain Language SummaryOver the next century, climate change impacts on coastal regions will include floods, droughts, erosion, and severe weather events. The Department of Energy (DoE) is funding the Integrated Coastal Modeling Project to understand these potential risks better. In this paper, we implement tides in the DoE ocean model. Tides themselves respond to climate change, altering coastal flooding risk assessments. We explore the ...