This dataset provides data for four third-degree tidal constituents used in the publication of Sulzbach et al (2022). The tidal constituents provided are the 3M1, 3M3, 3N2 and 3L2 for 134 globally distributed stations. The tide information, such as the nodal modulations of these tides, are taken from Table 1 and Table S2 of Ray (2020). These tidal constants are estimated using the GESLA dataset (Woodworth et al 2014) following the approach presented in Piccioni et al (2019). This record is an add-on to the full TICON dataset (https://doi.org/10.1594/PANGAEA.896587), using exactly the same data format and pre-processing.These steps include using tide gauge data that contains at least ten years of continuous data. Further, the dataset is restricted to only contain open ocean tide gauges by limiting it to a mean surrounding depth of tide gauges to be deeper than 500 meters in a 2-degree radius and excluding stations not native to the ocean domain of the employed tidal model TiME. Duplicate and closely neighbouring tide gauges, found within a 0.2-degree radius, are also removed from the dataset. This resulted in the availability of the four tidal constants for 134 tide gauges.The results are stored in one tab-separated text/ASCII file with 13 columns:1. Latitude of the tide gauge station2. Longitude of the tide gauge station3. Constituent name4. Amplitude (in cm)5. Phase (in degrees)6. Standard deviation of the amplitude (in cm)7. Standard deviation of the phase (in degrees)8. Percentage of missing observations9. Total number of observations analyzed10. Length of the maximum temporal gap found in the time series in days11. Date of the first observation12. Date of the last observation13. Code that corresponds to the original source of the recordTICON is a useful and easy-to-handle data set for tide model validation and allows the users to select the records according to the different criteria most suitable for their purposes. The options span from the choice of a geographical region to the use of single constituents or time periods.