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Long-Period Seafloor Seismology and Deformation under Ocean Waves
Abstract
The deformation of the seafloor under loading by long-period ocean waves raises vertical component noise levels at the deep seafloor by 20 to 30 dB above noise levels at good continental sites in the band from 0.001 to 0.04 Hz. This noise substantially limits the detection threshold and signal-to-noise ratio for long-period phases of earthquakes observed by seafloor seismometers. Borehole installation significantly improves the signal-to-noise ratio only if the sensor is installed at more than 1 km below the seafloor because the deformation signal decays slowly with depth. However, the vertical-component deformation signal can be predicted and suppressed using seafloor measurements of pressure fluctuations observed by differential pressure gauges. The pressure observations of ocean waves are combined with measurements of the transfer function between vertical acceleration and pressure to predict the vertical component deformation signal. Subtracting the predicted deformation signal from pressure observations can reduce vertical component noise levels near 0.01 Hz by more than 25 dB, significantly improving signal-to-noise ratios for long-period phases. There is also a horizontal-component deformation signal but it is smaller than the vertical-component signal and only significant in shallow water (<1-km deep). The amplitude of the deformation signal depends both on the long-period ocean-wave spectrum and the elastic-wave velocities in the oceanic crust. It is largest at sedimented sites and in shallow water.
... For on-land seismic stations, it occurs when a strong wind blows over a station or high-amplitude atmospheric pressure waves, such as Lamb waves from the Hunga-Tonga eruption (Anthony et al. 2022), pass over a station. For stations Page 10 of 22 Tanimoto and Anderson Progress in Earth and Planetary Science (2023) 10:56 on the ocean floor, it occurs when oceanic infragravity waves pass over a station on the seafloor (Crawford et al. 1991;Webb and Crawford 1999) or when the ocean currents at the sea bottom change the sea-bottom pressure significantly. In all cases, the time interval of quasi-static deformation can be identified by monitoring the coherence between pressure and seismic data because coherence should become high when pressure loading is the cause of the deformation. ...
... The importance of quasi-static deformation has been recognized in at least two phenomena. The first case is the seafloor observation with co-located pressure and seismic instruments (Crawford et al. 1991;Webb et al. 1991;Webb and Crawford 1999). The second is the onland observation with co-located pressure and seismic instruments (e.g., Sorrells 1971;Sorrells et al. 1971;Sorrells and Goforth 1973;Tanimoto and Wang 2018 The same pressure amplitude results are plotted against the distance from the Hurricane Center. ...
... A similar situation was also noted for the seafloor observation of co-located pressure and seismic sensors (Crawford et al. 1991;Webb et al. 1991;Webb and Crawford 1999). In this case, highly coherent time intervals occurred when the ocean infragravity waves passed over a seafloor seismic station (Webb et al. 1991). ...
It is now established that the primary microseism, the secondary microseisms, and the hum are the three main components of seismic noise in the frequency band from about 0.003 Hz to 1.0 Hz. Monthly averages of seismic noise are dominated by these signals in seismic noise. There are, however, some temporary additional signals in the same frequency band, such as signals from tropical cyclones (hurricanes and typhoons) in the ocean and on land, stormquakes, weather bombs, tornadoes, and wind-related atmospheric pressure loading. We review these effects, lasting only from a few hours to a week but are significant signals. We also attempt to classify all seismic noise. We point out that there are two broad types of seismic noise, the propagating seismic waves and the quasi-static deformations. The latter type is observed only for surface pressure changes at close distances. It has been known since about 1970 but has not been emphasized in recent literature. Recent data based on co-located pressure and seismic instruments clearly show its existence. Because the number of phenomena in the first type is large, we propose to classify all seismic noise into three categories: (1) propagating seismic waves from ocean sources, (2) propagating seismic waves from on-land sources, and (3) quasi-static deformation at ocean bottom and on land. The microseisms and the hum are in the first category although there are differences in the detailed processes of their excitation mechanisms. We will also classify temporary signals by these categories.
... Data from seafloor pressure gauges can be used to measure the ocean waves and predict the vertical component of the noise from wave loading. Webb and Crawford (1999), Kuo et al. (2014), , and An et al. (2020) show most of the wave loading noise can be removed from the vertical component data using seafloor pressure data enabling detection of small amplitude seismic phases with good signal to noise in the ocean wave loading band. The wave loading noise has often been called the "compliance signal" and the transfer function between seafloor deformation and the pressure signal within the ocean wave band can be used to determine the elastic properties of subseafloor magma chambers (Crawford et al., , 1998Zha et al., 2014) and sediments. ...
... The coherence between the Z component of both the shielded and isolated sensor with seafloor pressure approaches 1 at frequencies below 0.1 Hz reflecting that seafloor vertical deformation driven by ocean wave loading controls long period noise levels at the shallow seafloor. Webb and Crawford (1999) and Kuo et al. (2014) show how measurements of seafloor pressure can be used to predict and remove ocean wave loading noise from the vertical 8 of 17 component. We first calculate the transfer function between pressure and vertical displacement and then apply this transfer function to the pressure data to predict and remove the wave loading from the Z components from both the shielded and isolated sensor vertical components resulting in up to 35 dB reduction in noise levels below 0.1 Hz for both sensors (Figure 6). ...
We show large “shields” can significantly reduce horizontal component noise levels for ocean bottom seismometers by shielding the seismic sensors from shaking due to ocean currents. However, at short period (<1 s) some noise from vibration or rocking of the shield under current can partly couple through the ground causing peaks in the noise spectra. Deformation of the seafloor under ocean wave loading (“compliance”) raises noise levels at long period (>5 s) for both vertical and horizontal components at shallow water sites. Pressure gauge data is now routinely used to predict and remove this source of noise on vertical component data. We have developed horizontal pressure gradient (HPG) gauges to measure and remove this source of noise from horizontal component data. The combination of HPG data and shielding enables low noise long period seismic observations at otherwise very noisy shallow seafloor sites.
... The location of the OBS on the seafloor makes it vulnerable to interference from waves and bottom current noise, particularly long-period noise (Duennebier & Sutton, 1995;Webb & Crawford, 1999). Seismometer tilt can cause some noise from the horizontal component to leak into the vertical record, which can obstruct subsequent earthquake research (Bell et al., 2015;Crawford, 2000). ...
... It is known that the horizontal recordings of oceanbottom seismometers (OBSs) are noisy. At low frequencies (<0.1 Hz), the noise is generally attributed to currents tilting the instrument, which we called tilt noise (Crawford, 2000;Webb & Crawford, 1999). Current-induced tilt noise is caused by seafloor currents flowing past the instrument and in eddies spun off the back of the instrument (Crawford, 2000). ...
The data collected by ocean-bottom seismometers are unique compared to that of land seismic stations and require preprocessing before use. In this study, we focus on preprocessing seismic data obtained from a passive-source experiment in the Mariana subduction zone conducted by the Institute of Deep-Sea Science and Engineering, Chinese Academy of Sciences from 2018 to 2019. We outline the steps involved in preprocessing the data, including time correction using the ocean background noise cross-correlation function, tilt correction using a transfer function, and orientation correction based on seismic wave polarization. Our results show that the maximum clock drifting was ∼4 s on two stations (K06 and K20), while the rest of the station waveforms have clock drifting of less than 2 s. Among stations, only the K06 station is tilted, and the tilt angle is 19.82˚. We use the P-wave and Rayleigh wave polarization methods to determine the orientation. Our results indicate that the error in the result obtained using the P-wave polarization method is less than that of the Rayleigh wave polarization method. Additionally, we address the advantages and disadvantages of these preprocessing techniques. Our goal is to offer a comprehensive overview of the preprocessing process, to assist beginners in the field, and to serve as a foundation for future research in passive-source ocean-bottom seismometers.
... OBS data usually contain noises that are not present in land seismic records, since the seafloor environment generally has higher noise levels in the long-period seismic band. Previous work has shown that for OBS vertical component data, there are two main noise sources: one is tilt noise resulting from variable ocean-bottom currents tilting the instrument and causing horizontal noise to be recorded by the vertical component; the other is compliance noise resulting from the vertical movements of seafloor due to sea bottom pressure changes resulting from infragravity waves (Crawford & Webb, 2000;Webb & Crawford, 1999). The similarity of tilt noise on vertical and horizontal components, and the similarity of compliance noise on the vertical component and the differential pressure gauge (DPG) suggest that both noises on the vertical component can be largely removed by estimating spectral transfer functions (Bell et al., 2014). ...
We develop a 3‐D isotropic shear velocity model for the Alaska subduction zone using data from seafloor and land‐based seismographs to investigate along‐strike variations in structure. By applying ambient noise and teleseismic Helmholtz tomography, we derive Rayleigh wave group and phase velocity dispersion maps, then invert them for shear velocity structure using a Bayesian Monte Carlo algorithm. For land‐based stations, we perform a joint inversion of receiver functions and dispersion curves. The forearc crust is relatively thick (35–42 km) and has reduced lower crustal velocities beneath the Kodiak and Semidi segments, which may promote higher seismic coupling. Bristol Bay Basin crust is relatively thin and has a high‐velocity lower layer, suggesting a dense mafic lower crust emplaced by the rifting processes. The incoming plate shows low uppermost mantle velocities, indicating serpentinization. This hydration is more pronounced in the Shumagin segment, with greater velocity reduction extending to 18 ± 3 km depth, compared to the Semidi segment, showing smaller reductions extending to 14 ± 3 km depth. Our estimates of percent serpentinization from VS reduction and VP/VS are larger than those determined using VP reduction in prior studies, likely due to water in cracks affecting VS more than VP. Revised estimates of serpentinization show that more water subducts than previous studies, and that twice as much mantle water is subducted in the Shumagin segment compared to the Semidi segment. Together with estimates from other subduction zones, the results indicate a wide variation in subducted mantle water between different subduction segments.
... Using teleseismic S-wave limits the use of high-frequency waveforms in the R-ACF. The low-frequency component is not used in the vertical nor pressure component to avoid the effect of compliance noise and/or tilt noise on the seafloor (e.g., Webb & Crawford, 1999). Also, since the travel time of the P-wave is much shorter than the travel time of the S-wave in the high-Vp/Vs sediment layer, the choice of low-frequency waveforms for R-ACF and high-frequency waveforms for Z-and P-ACF helps to constrain P-and S-wave velocity structures in a similar resolution. ...
This study presents an approach to better characterize the P‐wave and S‐wave velocity structure of the seafloor sediment layer using ocean bottom seismometers. The presence of low‐velocity seafloor sediment layers influences the observed seismic record at the seafloor over a broad frequency range, such that detailed knowledge of this sediment structure is essential to predict its effect on teleseismic records. We use the radial component of teleseismic P waves and autocorrelation functions of the radial, vertical, and pressure components of teleseismic P and S waves to obtain sediment layer models using the Markov chain Monte Carlo approach with parallel tempering. Synthetic tests show that the body waves constrain the P‐ and S‐wave impedances and travel times and the P‐ to S‐wave velocity ratio of the sediment layers. The proposed method resolves thin layers at a high resolution, including the uppermost thin (∼50 m to a few hundred meters) low S‐wave velocity layer. Real data applications at sites across the Pacific Ocean that are coincident with previous in situ studies demonstrate the effectiveness of this method in characterizing the seafloor sediment unit. The sediment models characterized by this new approach will allow us to more accurately predict and correct the effects of sediment layers in generating P‐ and S‐wave reverberations.
... currents' effects from other sources, such as infragravity waves, because their impacts are intertwined (Webb & Crawford, 1999). ...
The ocean‐bottom currents are believed to be largely responsible for the high noise level in ocean bottom seismograph (OBS) data, in particular on the horizontal components. Due to the lack of in‐situ experiments and measurements, the generation mechanism and characteristics of the current‐induced noise are still poorly understood. In this paper, we designed an experiment to explore the features of current‐induced noise. A sensor module from a typical passive‐source OBS was installed in a water flume that can produce controllable steady water flows. We measured and analyzed the recorded noise with changing current velocities, with and without shielding. With other noise sources, such as infragravity waves precluded, this experiment demonstrates that the currents can generate low‐frequency noise, particularly <0.1 Hz. The noise level depends on the current velocity as well as the frequency. While the current‐induced noise affects the horizontal components significantly, its impacts on the vertical component appear negligible. The experiment shows that current‐induced noise has a dominant direction approximately perpendicular to the currents, a pattern consistent with an actual OBS on the flank of Mariana Trench, where the current direction is supposed to be along the trench. Shielding the sensor module with a plastic casing can substantially suppress the noise, indicating that shielding is a practical, low‐cost scheme to reduce the current‐induced noise.
Applications of machine learning in seismology have greatly improved our capability of detecting earthquakes in large seismic data archives. Most of these efforts have been focused on continental shallow earthquakes, but here we introduce an integrated deep-learning-based workflow to detect deep earthquakes recorded by a temporary array of ocean-bottom seismographs (OBSs) and land-based stations in the Tonga subduction zone. We develop a new phase picker, PhaseNet-TF, to detect and pick P- and S-wave arrivals in the time-frequency domain. The frequency-domain information is critical for analyzing OBS data, particularly the horizontal components, because they are contaminated by signals of ocean-bottom currents and other noise sources in certain frequency bands. PhaseNet-TF shows a much better performance in picking S waves at OBSs and land stations compared to its predecessor PhaseNet. The predicted phases are associated using an improved Gaussian Mixture Model Associator GaMMA-1D and then relocated with a double-difference package teletomoDD. We further enhance the model performance with a semi-supervised learning approach by iteratively refining labelled data and retraining PhaseNet-TF. This approach effectively suppresses false picks and significantly improves the detection of small earthquakes. The new catalogue of Tonga deep earthquakes contains more than 10 times more events compared to the reference catalogue that was analyzed manually. This deep-learning-enhanced catalogue reveals Tonga seismicity in unprecedented detail, and better defines the lateral extent of the double-seismic zone at intermediate depths and the location of 4 large deep-focus earthquakes relative to background seismicity. It also offers new potential for deciphering deep earthquake mechanisms, refining tomographic models, and understanding of subduction processes.
Cross-correlating continuous seismic data is a commonly employed technique to extract coherent signals to image and monitor the subsurface. However, due largely to site effects and poorly characterized noise sources in oceanic environments, its application to ocean-bottom seismometer (OBS) recordings often requires additional processing. In this contribution, we propose a method to improve the quality of the retrieved surface waves from OBS data and characterize the noise sources. We first cluster the pre-stack noise cross-correlation functions (NCFs) based on a sequencing algorithm, followed by selectively stacking those consisting of coherent and stable signals that are consistent with predicted surface-wave arrival times. Synthetic tests show that the sequenced NCFs can be used to recover the spatial and temporal distribution of noise sources. Applying the method to an OBS array offshore California increases the signal-to-noise ratios of the obtained Rayleigh waves. In addition, we find that the annual temporal distribution of selected NCFs with frequencies ranging from 0.04 to 0.1 Hz is nearly homogeneous during the recording period. In contrast, many NCFs excluded for stacking are temporally clustered. This method has the potential to be applied to other OBS recordings or possibly onland deployments, thus helping to obtain high-quality surface waves and to analyze temporal noise source characteristics.
Cycles of stress build-up and release are inherent to tectonically active planets. Such stress oscillations impart strain and damage, prompting mechanically loaded rocks and materials to fail. Here, we investigate, under uniaxial conditions, damage accumulation and weakening caused by time-dependent creep (at 60, 65, and 70% of the rocks’ expected failure stress) and repeating stress oscillations (of ± 2.5, 5.0 or 7.5% of the creep load), simulating earthquakes at a shaking frequency of ~ 1.3 Hz in volcanic rocks. The results show that stress oscillations impart more damage than constant loads, occasionally prompting sample failure. The magnitudes of the creep stresses and stress oscillations correlate with the mechanical responses of our porphyritic andesites, implicating progressive microcracking as the cause of permanent inelastic strain. Microstructural investigation reveals longer fractures and higher fracture density in the post-experimental rock. We deconvolve the inelastic strain signal caused by creep deformation to quantify the amount of damage imparted by each individual oscillation event, showing that the magnitude of strain is generally largest with the first few oscillations; in instances where pre-existing damage and/or the oscillations’ amplitude favour the coalescence of micro-cracks towards system scale failure, the strain signal recorded shows a sharp increase as the number of oscillations increases, regardless of the creep condition. We conclude that repetitive stress oscillations during earthquakes can amplify the amount of damage in otherwise mechanically loaded materials, thus accentuating their weakening, a process that may affect natural or engineered structures. We specifically discuss volcanic scenarios without wholesale failure, where stress oscillations may generate damage, which could, for example, alter pore fluid pathways, modify stress distribution and affect future vulnerability to rupture and associated hazards.
The generation and propagation of infragravity waves (frequencies nominally 0.004-0.04 Hz) are investigated with data from a 24-element, coherent array of pressure sensors deployed for 9 months in 13-m depth, 2 km from shore. The high correlation between observed ratios of upcoast to downcoast energy fluxes in the infragravity (FIGup/FIGdown) and swell (Fswellup/Fswelldown) frequency bands indicates that the directional properties of infragravity waves are strongly dependent on incident swell propagation directions. However, FIGup/FIGdown is usually much closer to 1 (i.e., comparable upcoast and downcoast fluxes) than is Fswellup/Fswelldown, suggesting that upcoast propagating swell drives both upcoast and downcoast propagating infragravity waves. These observations agree well with predictions of a spectral WKB model based on the long-standing hypothesis that infragravity waves, forced by nonlinear interactions of nonbreaking, shoreward propagating swell, are released as free waves in the surf zone and subsequently reflect from the beach.The radiated free infragravity waves are predicted to be directionally broad and predominantly refractively trapped on a gently sloping shelf. The observed ratios FIGsea/FIGshore of the seaward and shoreward infragravity energy fluxes are indeed scattered about the theoretical value 1 for trapped waves when the swell energy is moderate, but the ratios deviate significantly from 1 with both low- and high-energy swell. Directionally narrow, shoreward propagating infragravity waves, observed with low-energy swell, likely have a remote (possibly trans-oceanic) energy source. High values (up to 5) of FIGsea/FIGshore, observed with high-energy swell, suggest that high-mode edge waves generated near the shore can be suppressed by nonlinear dissipation processes (e.g., bottom friction) on the shelf.
During the French pilot experiment OFM/SISMOBS (April 22-May 20,
1992) in the Atlantic Ocean, two sets of Guralp CMG-3 broadband
seismometers were successfully installed and recovered. The first set,
OFP (Observatoire Fond de Puits: Borehole Observatory), was installed
inside the DSDP borehole 396B at 296m below the seafloor and the second
one, OFM (Observatoire Fond de Mer: Ocean Bottom Observatory), on the
sea bottom close to the hole at a depth of 4450 m. A first analysis
showed that the broadband seismic noise (5 sps) on the seafloor had the
same magnitude as compared with the long period seismic noise (1 sps)
recorded at SSB, a continental station of the GEOSCOPE network. The
noise recorded in the borehole was disappointedly high. The seismic data
obtained during the experiment have been reanalyzed and it is shown that
the seismic noise in the borehole is decreasing significantly with time
whereas the instrument on the seafloor displays normal variations. A
long term experiment (at least one month) is necessary to assess the
final noise in the borehole.
Most of our understanding of the Earth's interior has been derived from measurements from global seismic networks, although no network has ever been truly “global” because some 71% of the Earth's surface is underwater. The resulting gaps in coverage produce a biased and incomplete image of the Earth. Work has begun toward establishing permanent observatories on the deep seafloor, although the technical difficulties remain severe. Will these stations be useful, and where and how shall they be established? Data from seafloor observatories will be of poorer quality than continental site data because the sea surface is an important and local source of broadband noise. This noise is derived from wind and waves through direct forcing at long periods and by nonlinear coupling to elastic waves at short periods. Our understanding of the generation and propagation of seismic noise and of wind and wave climatology can be used to predict the temporal and geographical variability of the noise spectrum and to assess likely sites for permanent seafloor observatories. High noise levels near 1 Hz may raise detection limits for short-period, teleseismic arrivals above mb = 7.5, limiting the usefulness of many seafloor sites. Noise levels in deep boreholes will be 10 dB quieter than those at the seafloor, but sensors buried short distances below the seafloor may also provide comparable noise levels and fidelity. The retrieval of data from permanent seafloor observatories remains an unsolved problem, but long-term temporary arrays of ocean bottom seismometers are now being used in regional scale experiments using earthquakes as sources. Such experiments are likely to be less successful in the Pacific basin than in either the Indian Ocean or North Atlantic Ocean because of higher noise levels.
A pressure gauge configured to respond to the difference between the ocean pressure and the pressure within a confined volume of compressible oil is found to be especially useful for detecting pressure fluctuations in the frequency range from a few millihertz to a few hertz. In the middle of the range its noise level is lower than any other known gauge. The limitation of the gauge at the lower frequency limit is caused by unpredictable thermal expansion in the confined oil and at the upper limit by thermal agitation noise in the resistance of the strain gauge transducer. The gauge is insensitive to acceleration and tilting. Measurements with this gauge on the deep seafloor show two principal features in the spectrum of pressure fluctuations. At frequencies below 0.03 Hz there is evidence of pressures generated directly by long surface gravity waves. Above 0.11 Hz the pressures associated with microseisms are predominant. Between 0.03 and 0.11 Hz there is a spectral gap where the pressure level dr...
Pressure fluctuations from two sites on the deep sea floor separated by a distance of 32 km were found to be partially coherent at frequencies between .001 Hz and .015 Hz. The pressure fluctuations in this range are caused by surface gravity waves which are of sufficiently long wavelength that significant coherence exists. No coherence is detected at lower frequencies because temperature fluctuations disturb the reference in the pressure gauge, while at higher frequencies the surface gravity wave induced pressure fluctuations are sharply attenuated through the ocean. The real part of the coherency as a function of frequency resembles a Jo Bessel function of argument kr (r is the distance between the sites and k is the magnitude of the wavenumber as determined by the surface gravity wave dispersion relation). The imaginary part of the complex coherency is smaller than the real part over most of the surface gravity wave band. The coherency is well modeled if the surface gravity wave field is assumed to be isotropic, but other models for the directional spectrum which require a very broad distribution in direction of propagation fit equally well. Narrow beam width models fit the data poorly.
The static deformation of an elastic half-space by surface pressure is reviewed. A brief mention is made of methods for solving the problem when the medium is plane stratified, but the major emphasis is on the solution for spherical, radially stratified, gravitating earth models. Love-number calculations are outlined, and from the Love numbers, Green's functions are formed for the surface mass-load boundary-value problem. Tables of mass-load Green's functions, computed for realistic earth models, are given, so that the displacements, tilts, accelerations, and strains at the earth's surface caused by any static load can be found by evaluating a convolution integral over the loaded region.
We use records from the Project IDA modified LaCoste gravimeters to investigate ground noise at. frequencies from 1 to 10 mHz. At most sites the level between 2 and 10 mHz is nearly flat and close to 2 × 10 ⁻¹⁸ m ² s ⁻³ Much higher values which are observed at island and coastal stations are due to loading by waves trapped along the shore. Data from the superconducting gravimeter at Piñon Flat Geophysical Observatory show that the noise power increases as ƒ −2.7 for frequencies between 1 and 0.001 mHz.
Microseisms are seismoacoustic waves excited by nonlinear interactions of ocean waves and are evident in the band 0.1 to 5 Hz in measurements of pressure or displacement spectra from the deep seafloor. A remarkable uniformity in microseism amplitudes is observed at the seafloor, despite many orders of magnitude variation in the amplitude of ocean waves overhead. This paper looks at how a balance is established between the excitation of microseisms under large source regions and the dissipation of this energy within a waveguide formed by the ocean, crust, and upper mantle. The excitation functions and dissipation of modes within ocean models are calculated to determine the "equilibrium microseism spectrum" of displacement or pressure for which local excitation is balanced by local dissipation. Efficient propagation of energy within the ocean waveguide also acts to make deep ocean microseism observations homogeneous.
The first results from a deployment of four instruments on the floor of the Beaufort Sea in March 1990 are presented. The instruments recorded pressure fluctuations in the band from 0.0005 to 8 Hz during a 2‐week period. The pressure spectra derived from these measurements show very low energy in the microseism peak near 0.1 Hz in comparison with measurements from the Pacific or Atlantic seafloor. The microseism band shows a series of spectral peaks and valleys likely associated with the modes of the ocean–seafloor Rayleigh wave waveguide. The shape of the microseism peak is remarkably stable during the experiment although the amplitude varies by about 10 dB. The signals are very coherent between adjacent instruments and suggest propagation in the microseism band from a source in the Gulf of Alaska. The pressure spectra rise rapidly toward lower frequency below 0.02 Hz, but Arctic spectra are less energetic than spectra from sites on either Pacific or Atlantic seafloors at all frequencies. The long period energy appears to be related to flexural‐gravity waves on the oceansurface. The pressure measurements predict amplitudes for these waves in general agreement with previous tilt and displacement measurements made on the ice.
Small diurnal and semidiurnal gravity tides are seen at the South Pole because of the loading by and attraction of the ocean tides. These data provide a check on the quality of ocean-tide models, especially in the southernmost ocean, which has historically been the most lacking in tidal data. Ocean-tide models developed in the 1980's did not predict the gravity tides at this location very well. Recently-developed models based on the Topex/Poseidon altimetric data and improved hydrodynamical modeling agree much better with the observations, provided that the tides beneath the ice shelves are included. The level of agreement at this remote location suggests that, loads from very local tides aside, the new generation of ocean-tide models can predict the loading tides to very high accuracy.