Global Prediction of non-tidal ocean mass variability induced by atmospheric forcing with a barotropic ocean tide model

Global models of the ocean mass anomaly play an important role in processing space geodetic observations. Most importantly, high-frequency variability of the sea surface height (and the associated surface mass) can degrade altimetric and gravimetric observations, due to their observation characteristics. Therefore, background models are typically used to avoid aliasing of high-frequency signal content. Ocean dynamics is significantly driven by baroclinic dynamics, especially on long-time scales. However, barotropic ocean models have been successfully used to predict high-frequency (~sub-monthly) sea surface dynamics and mass variability (e.g., Carrère and Lyard, 2003; Schindelegger et al., 2018).

Here, we present simulations of non-tidal sea surface height dynamics with the barotropic ocean model TiME (Tidal model forced by ephemerides), which was originally designed to study ocean tides and adapted to simultaneous tidal and non-tidal forcing (Sulzbach et al., 2021). The model possesses several characteristics that are beneficial for global storm surge simulations : (i) a truly global domain ; (ii) the computation of the non-local effect of self-attraction and loading at each time step ; (iii) dissipation by parameterized baroclinic processes, i.e., topographic wave drag ; (iv) simultaneous forcing by the Tide-Generating potential as well as atmospheric pressure and wind stress. The model's versatility allows us to study the influence of the above-mentioned features on the accuracy of the prediction of non-tidal ocean mass variability. Among all considered effects, the influence of (ii) is especially pronounced, as it is sensitive to the spatial extent of the ocean mass anomaly, which can change significantly in time and space for non-tidal processes.

Multiple years of sea surface height data were computed and transformed to Stokes coefficients. Comparison of the results with geodetic observations (e.g., tide gauge data) shows consistent validation and significant improvements when considering tidal/non-tidal interactions, self-attraction and loading, and optimized mechanical energy dissipation by topographic wave drag.