ALBERT

Description: Satellite altimetry observations have provided a significant contribution to the understanding of global sea surface processes, particularly allowing for advances in the accuracy of ocean tide estimations. Currently, almost three decades of satellite altimetry are available which can be used to improve the understanding of ocean tides by allowing for the estimation of an increased number of minor tidal constituents. As ocean tide models continue to improve, especially in the coastal region, these minor tides become increasingly important. Generally, admittance theory is used by most global ocean tide models to infer several minor tides from the major tides when creating the tidal correction for satellite altimetry. In this paper, regional studies are conducted to compare the use of admittance theory to direct estimations of minor tides from the EOT20 model to identify which minor tides should be directly estimated and which should be inferred. The results of these two approaches are compared to two global tide models (TiME and FES2014) and in situ tide gauge observations. The analysis showed that of the eight tidal constituents studied, half should be inferred (2N2, ϵ2, MSF and T2), while the remaining four tides (J1, L2, μ2 and ν2) should be directly estimated to optimise the ocean tidal correction. Furthermore, for certain minor tides, the other two tide models produced better results than the EOT model, suggesting that improvements can be made to the tidal correction made by EOT when incorporating tides from the two other tide models. Following on from this, a new approach of merging tidal constituents from different tide models to produce the ocean tidal correction for satellite altimetry that benefits from the strengths of the respective models is presented. This analysis showed that the tidal correction created based on the recommendations of the tide gauge analysis provided the highest reduction of sea-level variance. Additionally, the combination of the EOT20 model with the minor tides of the TiME and FES2014 model did not significantly increase the sea-level variance. As several additional minor tidal constituents are available from the TiME model, this opens the door for further investigations into including these minor tides and optimising the tidal correction for improved studies of the sea surface from satellite altimetry and in other applications, such as gravity field modelling.

Description: Ocean tides are a vital component of global ocean circulation, with their role in the Arctic Ocean being crucial for ocean and sea ice dynamics. Recently, significant advances have been made in global ocean tide models, however, difficulties remain in the coastal regions as well as in the higher latitudes. The latter is related to the poorly resolved bottom topography, the influence of sea ice and limited regular satellite altimetry measurements. Although modelling efforts are attempting to improve our ocean tide estimates in the Arctic Ocean, the tidal in-situ network is an additional limiting factor in this region. In-situ measurements from tide gauges or ocean bottom pressure sensors are crucial sources of information that can be used to understand the spatial variability of tides as well as validate the advances made in modelled estimates. However, globally in-situ tidal constituent databases contain a limited number of observations with, for example, TICON-3 containing 111 above 60°N and 21 above 70°N with the distribution of these measurements mainly being around North America. This abstract presents the results of a concerted effort to produce a harmonised dataset of tidal constituents in the Arctic region. This dataset combines in-situ measurements from tide gauges, ocean bottom pressure sensors and GNSS reflectometry, which results in approximately 691 measurements above 60°N and 313 above 70°N with a much greater spatial distribution across the full Arctic ocean. The resultant dataset is quality assessed and compared to recent tide models to determine the reliability of the different data sources used.

Description: 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 station 2. Longitude of the tide gauge station 3. Constituent name 4. 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 observations 9. Total number of observations analyzed 10. Length of the maximum temporal gap found in the time series in days 11. Date of the first observation 12. Date of the last observation 13. Code that corresponds to the original source of the record TICON 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.

Description: This data publication represents the main outcomes of WP1.200 of Individual Project IP1 and Deliverable D1.1 of the research unit NEROGRAV. The goal of WP1.200 was the realistic representation of modern ocean tide model uncertainties in the form of empirical Variance-Covariance Matrices (VCMs) for the utilization in satellite gravimetric dealiasing. In the following, we describe the data set generation and format. A more detailed description of the processing strategy of the data set can be found in Abrykosov et al. (2021).