EOT20: a global ocean tide model from multi-mission satellite altimetry

EOT20 is the latest in a series of empirical ocean tide (EOT) models derived using residual tidal analysis of multi-mission satellite altimetry at DGFI-TUM. The amplitudes and phases of 17 tidal constituents are provided on a global 0.125∘ grid based on empirical analysis of seven satellite altimetry missions and four extended missions. The EOT20 model shows significant improvements compared to the previous iteration of the global model (EOT11a) throughout the ocean, particularly in the coastal and shelf regions, due to the inclusion of more recent satellite altimetry data as well as more missions, the use of the updated FES2014 tidal model as a reference to estimated residual signals, the inclusion of the ALES retracker and improved coastal representation. In the validation of EOT20 using tide gauges and ocean bottom pressure data, these improvements in the model compared to EOT11a are highlighted with the root sum square (RSS) of the eight major tidal constituents improving by ∼ 1.4 cm for the entire global ocean with the major improvement in RSS (∼ 2.2 cm) occurring in the coastal region. Concerning the other global ocean tidal models, EOT20 shows an improvement of ∼ 0.2 cm in RSS compared to the closest model (FES2014) in the global ocean. Variance reduction analysis was conducted comparing the results of EOT20 with FES2014 and EOT11a using the Jason-2, Jason-3 and SARAL satellite altimetry missions. From this analysis, EOT20 showed a variance reduction for all three satellite altimetry missions with the biggest improvement in variance occurring in the coastal region. These significant improvements, particularly in the coastal region, provide encouragement for the use of the EOT20 model as a tidal correction for satellite altimetry in sea-level research. All ocean and load tide data from the model can be freely accessed at https://doi.org/10.17882/79489 (Hart-Davis et al., 2021). The tide gauges from the TICON dataset used in the validation of the tide model, are available at https://doi.org/10.1594/PANGAEA.896587 (Piccioni et al., 2018a).

Impact of the stochastic model of the ocean tides on GRACE monthly gravity field solutions

<p><span>I</span><span>n </span><span>GRACE data </span><span>processing</span><span> </span><span>t</span><span>he geophysical </span><span>background </span><span>models, which are needed to compute </span><span>the </span><span>monthly gravity field solutions, </span><span>usually </span><span>e</span><span>nter as</span><span> error-free. </span><span>This</span><span> </span><span>means that model errors could influence and distort the gravity field solution</span><span>.</span></p><p><span>The geophysical models </span><span>which influence the solution the most</span><span> a</span><span>re</span><span> the </span><span>atmosphere and ocean dealiasing product (AOD1B) and the ocean tide model. </span><span>In this presentation we focus on the </span><span>ocean tide model and on incorporati</span><span>ng</span><span> </span><span>its </span><span>stochastic information </span><span>in data processing</span><span>. </span></p><p><span>We use </span><span>the FES2014 ocean tide model presented as a spherical harmonic expansion till degree and order 180. The information about its uncertainties and the correlations between different spherical harmonics is provided by the research unit NEROGRAV (New Refined Observations of Climate Change from Spaceborne Gravity Missions). In a first step, the stochastic properties of the tide model are considered to be static and are expressed as variance-covariance matrices (VCM) of the spherical harmonics of the 8 main tidal waves till degree and order 30. The incorporation of this stochastic information is done by setting up the respective ocean tide harmonics as parameters to be solved for. Since ocean tides cannot be freely estimated within monthly GRACE solutions, the provided VCMs for the 8 tidal waves are used for constraining the tidal parameters.</span></p><p><span>T</span><span>his procedure was used to compute monthly gravity field solutions for the year 2007. For a comparison, we computed also monthly gravity fields without taking into account the stochastic information on ocean tides. In this contibution we present and discuss the first results of this comparison.</span></p>

Implementation of the barotropic tide in oceanic circulation models. Current tests with the NEMO model

<p>This study proposes a new methodology for implementing the barotropic tide in an ocean general circulation model (OGCM). The assumptions underlying this methodology are that the best barotropic tide solutions are computed by specialized models and that the fields that should be accurately reproduced by the OGCM are the transport fields from the specialized tide model. The target/reference solution for the OGCM is thus the projection of the tide model on the OGCM grid, for each tidal harmonic.</p><p>The proposed methodology involves little change of the OGCM modeland yields almost exactly the reference solution, with a cost that is belowmost of the current methodologies. It relies on the modification of the tidepotential, or more accurately, on the replacement of all terms associatedwith the tide (tide potential, self attraction and loading, tide dissipation,  ...) by a general tide forcing term in the barotropic momentum equationwhich is calculated from the –known- reference solution.</p><p>The tide forcing terms can be tricky to calculate as they depend on details of the OGCM numerical schemes (for both temporal and spatial operators). A general procedure, automatically adapting the chosen schemes, is proposed for their calculation, so that the procedure is independent of the model.  </p><p>Tests with academic configurations are first proposed to validate the methodology and its implementation, and the OGCM is chosen to be the NEMO (Nucleus for European Modelling of the Ocean) model.</p><p>A global ¼° configuration with realistic bathymetry and with FES tide solutions (Finite Element Solution) are then performed. Current tests show that when FES solutions are crudely interpolated on the NEMO grid, the methodology exactly reproduces the FES fluxes, but the associates NEMO SSH is very noisy in regions where FES has high resolution. This problem is currently addressed. To get rid of this problem, fluxes must be carefully integrated along each grid cell, so that the reproduced SSH is exactly an average of the FES SSH within the NEMO grid cell. Hopefully, we will be able to present final –clean- solutions at the conference.</p>

Determination of Coastal Sea Level Heights around Taiwan by improved GNSS Reflectometry

<p>Rapid sea level rise, a severe consequence of global warming, could significantly damage the lives and properties of numerous human beings living in low-lying coastal areas. Therefore, realizing and monitoring coastal sea level variations are of great importance for human society. Conventionally, sea level heights are measured by using tide gauges; however, the records are contaminated by vertical land motions which are difficult to be separated. Recently, Global Navigation Satellite System Reflectometry (GNSS-R) technology has been proved to effectively monitor the coastal sea level changes from GNSS signal-to-noise ratio (SNR) data. However, the generation of detrended SNR ( SNR) depending on different satellite elevation angle intervals via a quadratic fitting, considerably influences the accuracy of sea level retrievals. Moreover, the quadratic fitting cannot perfectly describe the trend of SNR data. Therefore, we proposed a method combining ensemble empirical mode decomposition (EEMD) and ocean tide model to compute SLHs. EEMD can decompose the original SNR data into several intrinsic mode functions (IMFs) corresponding to specific frequencies. Then, Lomb-Scargle Periodogram (LSP) is applied to calculate the dominant frequency of the IMF with maximum spectral power. EEMD is not only suitable for dealing with nonlinear and nonstationary data but also eliminates the mode mixing problem of empirical mode decomposition (EMD) by adding white noises. In addition, we set an empirical SLH interval from ocean tide model as a quality control. In this study, the existing GNSS stations at the coasts of Taiwan are used to examine the proposed approach and then compare the results with those from the traditional quadratic fitting. Finally, the measurements from co-located or nearby traditional tide gauges are served as ground truth to evaluate the accuracy and stability of the mentioned methods.</p>