{"refrec":{"BRefID":352500,"RR":"<b>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.</b> (2022). Modeling gravimetric signatures of third-degree ocean tides and their detection in superconducting gravimeter records. <i>Bulletin Géodésique 96(5)</i>: 35. <a href=\"https://dx.doi.org/10.1007/s00190-022-01609-w\" target=\"_blank\">https://dx.doi.org/10.1007/s00190-022-01609-w</a>","BEntID":350207,"PublicFlag":1,"CheckedFlag":1,"wosflag":1,"vabbflag":0,"RefStringPartII":". <i>Bulletin Géodésique 96(5)</i>: 35. <a href=\"https://dx.doi.org/10.1007/s00190-022-01609-w\" target=\"_blank\">https://dx.doi.org/10.1007/s00190-022-01609-w</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":1,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"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.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Sulzbach, R. <i>et al.</i>","Englishabstract":"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. 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