Modeling gravimetric signatures of third-degree ocean tides and their detection in superconducting gravimeter records
Sulzbach, R.; Wziontek, H.; Hart-Davis, M.; Dobslaw, H.; Scherneck, H.-G.; Van Camp, M.; Omang, O.C.D.; Antokoletz, E.D.; Voigt, C.; Dettmering, D.; Thomas, M. (2022). Modeling gravimetric signatures of third-degree ocean tides and their detection in superconducting gravimeter records. Bulletin Géodésique 96(5): 35. https://dx.doi.org/10.1007/s00190-022-01609-w
In: Bulletin Géodésique = Journal of Geodesy = Official Journal of the International Association of Geodesy. Springer: Berlin; Heidelberg. ISSN 0949-7714; e-ISSN 1432-1394, more
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| Keyword |
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| Author keywords |
Tidal modeling; Degree-3 tides; Superconducting gravimetry; Tide gaugedata; Tidal analysis |
| Authors | | Top |
- Sulzbach, R.
- Wziontek, H.
- Hart-Davis, M.
- Dobslaw, H.
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- Scherneck, H.-G.
- Van Camp, M., more
- Omang, O.C.D.
- Antokoletz, E.D.
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- Voigt, C.
- Dettmering, D.
- Thomas, M.
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| Abstract |
We employ the barotropic, data-unconstrained ocean tide model TIME to derive an atlas for degree-3 tidal constituents including monthly to terdiurnal tidal species. The model is optimized with respect to the tide gauge data set TICON-td that is extended to include the respective tidal constituents of diurnal and higher frequencies. The tide gauge validation shows a rootmean-square (RMS) deviation of 0.9-1.3 mm for the individual species. We further model the load tide-induced gravimetric signals by two means (1) a global load Love number approach and (2) evaluating Greens-integrals at 16 selected locations of superconducting gravimeters. The RMS deviation between the amplitudes derived using both methods is below 0.5 nGal (1 nGal = 0.011 nm/S-2) when excluding near-coastal gravimeters. Utilizing ETERNA-x, a recently upgraded and reworked tidal analysis software, we additionally derive degree-3 gravimetric tidal constituents for these stations, based on a hypothesis-free wave grouping approach. We demonstrate that this analysis is feasible, yielding amplitude predictions of only a few 10 nGal, and that it agrees with the modeled constituents on a level of 63-80% of the mean signal amplitude. Larger deviations are only found for lowest amplitude signals, near-coastal stations, or shorter and noisier data sets. |
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