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 root-mean-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 \(= 0.01 \frac{\text {nm}}{\text {s}^2}\)) 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.

我们使用正压、数据无约束的海潮模型 TimeE 来推导 3 度潮汐成分的图谱，包括每月到三日潮汐物种。该模型针对潮汐仪数据集 TICON-td 进行了优化，该数据集被扩展为包括昼夜和更高频率的相应潮汐成分。验潮仪验证显示单个物种的均方根 (RMS) 偏差为 0.9–1.3 毫米。我们通过两种方法进一步模拟负载潮汐引起的重力信号：（1）全局负载洛夫数方法和（2）在 16 个选定的超导重力仪位置评估格林积分。使用这两种方法得出的幅度之间的 RMS 偏差低于\(0.5 \ \) nGal ( \(1 \ \) nGal\(= 0.01 \frac{\text {nm}}{\text {s}^2}\) ) 当不包括近岸重力仪时。利用最近升级和重新设计的潮汐分析软件 ETERNA-x，我们还根据无假设波分组方法为这些站点推导了 3 级重力潮汐成分。我们证明了这种分析是可行的，产生的幅度预测只有几个 10 nGal，并且它在平均信号幅度的 63-80% 的水平上与建模成分一致。较大的偏差仅在最低幅度信号、近岸台站或较短且噪声较大的数据集上发现。