Sentinel‐3 A&B radar altimeters yield sea surface height measurements in both a high‐precision Synthetic Aperture Radar Mode (SARM), and a Pseudo‐Low Resolution Mode (PLRM). We stacked repeat cycles from both missions and in both modes to compare their resolution of small seamounts. Stacking entailed removing non‐geoidal heights and height errors, testing for consecutive measurements over ocean, aligning to common locations at 1 km intervals along a synthetic track, and forming a median height profile. These profiles are available from the National Centers for Environmental Information (NCEI) data repository. Global maps show that, over the oceans, the median height is usually derived from more than 49 cycles, and the typical error in an individual PLRM measurement is approximately 1.9 times greater than an individual SARM measurement. We applied a seamount detection bandpass filter to the median profiles and compared their spectral resolution to that of the Satellite for ARgos and AltiKa (SARAL) AltiKa mission. Small seamounts are similarly resolved by Sentinel‐3 A&B SARM data and by the SARAL/AltiKa data.

The CNES/ISRO altimetric satellite SARAL/AltiKa was launched in February 2013 and since then has provided useful data for various scientific and operational applications in oceanography, hydrology, cryospheric sciences and geodesy. However, a Reaction Wheel problem forced relaxation of the repeatability constraint on the satellite's orbit, which has been drifting slowly since July 2016. Beyond the expected contributions of this mission and its very good integration into the objectives of the constellation of altimetric satellites, it has become more and more apparent that specific contributions and innovations related to the main specification of SARAL/AltiKa, that is to say the use of the Ka-band, have clearly emerged. The advantages of the Ka-band are in short the reduction of ionosphere effects, the smaller footprint, the better horizontal resolution and the higher vertical resolution. A drawback of the Ka-band is the attenuation due to water/water vapor in case of rain and the resulting loss of data. The main objective of this paper is to highlight the specific advances of the Ka-band in different scientific and technical fields and to show why they are promising for the future and open the way to several missions or mission projects. Although unplanned initially, the fine coverage of the Drifting Phase brings some interesting openings especially for geodesy and hydrology applications.

Seamounts can be habitats and hazards to submarine navigation, and their distribution reveals the volcanic history of the oceans. As only a few percent of ocean floor has been sounded, seamount distribution must be mapped by satellite altimetry. Wessel (doi:10.1029/2000JB000083) looked at data from an earlier generation of altimeter technology and suggested that all seamounts 2 km and taller had been found, but there might be as many as 50,000 seamounts between 1–2 km tall that were not yet found. The AltiKa altimeter delivers more precise sea level measurements at a higher along-track sampling rate than previous altimeters. These data resolve small seamounts not previously resolvable (Smith, doi:10.1080/01490419.2015.1014950), particularly if repeat-track profiles are “stacked” and band-pass filtered (Marks and Smith, doi:10.1007/s11001-016-9293-0). These two studies looked at only a few isolated locations where multibeam acoustic depth sounding surveys were available for “ground truth” for tuning a band-pass filter to detect the small seamount geoid signal. In the new work we present here we have stacked 32 repeat cycles of SARAL AltiKa data world-wide, and band-pass filtered the stacks, to yield 75,208 potential seamount locations distributed between +/- 81.5 latitude throughout the global ocean. These locations are detected as local maxima in the filtered geoid at least 2 cm above background and with a full-width at half-maximum (FWHM) at least 4 km wide. Of these, 4824 detections were over multibeam surveys. We assign a proxy seamount height to each by subtracting the regional SRTM30 depths from the multibeam depths. These proxy heights follow a Poisson statistical distribution similar to that which fits acoustic bathymetry profiles over seamounts (Jordan et al., doi:10.1029/JB088iB12p10508). We are currently investigating how to derive proxy heights from anomaly amplitude and FWHM, optimizing the trade-off between false negative and false positive detections, and whether it is possible to identify potential seamounts that may pose hazards to submarine navigation.

The SARAL AltiKa radar altimeter measured sea surface height along ground tracks that were regularly revisited by repeating cycles. We devised an automated method of “stacking” the repeat cycles that aligns them to common positions along a model track, selects segments that pass quality criteria, removes the non‐geoidal height and height error from each repeat profile, and calculates the median height profile. This procedure reinforces geoid signals while reducing measurement noise and height signals produced by ocean dynamics. A seamount detection filter applied to the median profiles reveals 75,208 possible small seamounts along AltiKa ground tracks globally. Of these, 4824 are located over multibeam surveys. Seamount heights estimated by subtracting regional depths from the multibeam depths follow a Poisson statistical distribution that suggests at least 84% are less than 2 km tall. A 1 km along‐track sampling of the stacked repeat cycles is available from the National Centers for Environmental Information (NCEI) data repository.

An assessment of ocean depth knowledge underneath commercial airline routes shows just how much of the seafloor remains "terra incognita."

We present a technique of stacking repeat cycles of satellite altimeter sea surface height profiles that lowers the noise and improves the resolution of small seamounts. Our approach differs from other studies because it uses the median (not the mean) of the stacks, which suppresses outliers. Seamounts as small as 720 m tall are easily detected in stacked 40 Hz AltiKa data profiles, and a 500 m tall seamount is perceptible. Noise variance decreases with an increase in the number of cycles stacked, and RMS noise dips below 2 cm when 11 or more cycles are stacked. Coherence analyses between geoid height and bathymetry show that full wavelengths down to about 10 km can be resolved. Comparisons of study areas with and without seamounts find that signal from small seamounts lies in the ~10–28 km waveband. A simple Gaussian band-pass filter based on the seamount waveband passes signals that can be used in seamount detection studies. Such studies may find seamounts <2 km tall that are predicted to be abundant on the ocean floor.

General Bathymetric Chart of the Oceans (GEBCO) has released the GEBCO_2014 grid, a new digital bathymetric model of the world ocean floor merged with land topography from publicly available digital elevation models. GEBCO_2014 has a grid spacing of 30 arc sec and updates the 2010 release (GEBCO_08) by incorporating new versions of regional bathymetric compilations from the International Bathymetric Chart of the Arctic Ocean, the International Bathymetric Chart of the Southern Ocean, the Baltic Sea Bathymetry Database, and data from the European Marine Observation and Data network bathymetry portal, among other data sources. Approximately 33% of ocean grid cells (not area) have been updated in GEBCO_2014 from the previous version, including both new interpolated depth values and added soundings. These updates include large amounts of multibeam data collected using modern equipment and navigation techniques, improving portrayed details of the world ocean floor. Of all nonland grid cells in GEBCO_2014, approximately 18% are based on bathymetric control data, i.e., primarily multibeam and single-beam soundings or preprepared grids which may contain some interpolated values. The GEBCO_2014 grid has a mean and median depth of 3897m and 3441 m, respectively. Hypsometric analysis reveals that 50% of the Earth's surface is composed of seafloor located 3200m below mean sea level and that similar to 900 ship years of surveying would be needed to obtain complete multibeam coverage of the world's oceans.

The General Bathymetric Chart of the Oceans (GEBCO) is an international body of experts that develops bathymetric datasets and products that are made available for public use. Among these products is the International Hydrographic Organization (IHO) and the Intergovernmental Oceanographic Commission (IOC) GEBCO Cook Book that provides the international community with a set of procedures for processing and analysing bathymetry data. Landsat 8 was launched in February 2013. The imagery from this new multispectral satellite is free and publicly available. This paper discusses updates in the IHO-IOC GEBCO Cook Book chapter on using Landsat imagery to derive bathymetry.

On the morning of 8 March 2014, Malaysia Airlines flight MH370, from Kuala Lumpur to Beijing, lost contact with air traffic control shortly after takeoff and vanished. While the world waited for any sign of the missing aircraft and the 239 people on board, authorities and scientists began to investigate what little information was known about the plane's actual movements.

Incorporating new altimeter data from CryoSat-2 (30 months), Envisat (18 months), and Jason-1 (7 months) satellites into an updated marine gravity field yields significant reduction in noise and improved resolution. Compared to an older gravity field that did not include the new altimeter data, incoherent power is reduced globally by approximately 2.9 dB at 15 km, 1.6 dB at 20 km, and 1.0 dB at 25 km wavelengths. Coherence analyses between the updated gravity and recent multibeam surveys distributed throughout the world’s oceans shows an average increase of ~0.023 in mean coherence in the 20–160 km waveband, with the biggest increase (>0.08) over fast spreading ridges and smallest (<0.02) over slow spreading ridges and continental shelves. The shortest wavelength at which coherence is above 0.5 decreased globally by ~2 km wavelength, with the biggest decrease (>3.5 km) over fast spreading ridges and smallest (<1.5 km) over slow spreading ridges and continental shelves. In the Clipperton fracture zone area these improvements result in seamounts that are more accurately located, the detection of smaller seamounts, and the expression of north–south trending abyssal hill fabric. As more altimeter data from the ongoing satellite missions are incorporated into future gravity field updates, finer-scale details of the seafloor will continue to emerge.

We compute the radially symmetric coherence between multibeam bathymetry and satellite gravity grids in 25 areas distributed around the world. In contrast to previous studies employing one-dimensional analysis of data along profiles, our results cannot be biased by unseen off-track topography. The mean coherence averaged over the 20–160 km waveband, and the shortest wavelength at which coherence is above 0.5, vary with tectonic setting. Seamounts and slow spreading ridges have high (>0.7) mean coherence down to ~20 km wavelength, other spreading ridges and trenches have intermediate (0.5–0.7) coherence down to ~20–30 km wavelength, and continental shelves have low (<0.5) coherence at all wavelengths. In the areas with highest mean coherence, the shortest wavelength at which coherence is above 0.5 decreases as mean depth decreases. The filter employed in the bathymetric prediction method of Smith and Sandwell (J Geophys Res 99(B11):21803–21824, 1994) selects the most coherent parts of the bathymetry and gravity spectrum.

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We analyze errors in the global bathymetry models of Smith and Sandwell that combine satellite altimetry with acoustic soundings and shorelines to estimate depths. Versions of these models have been incorporated into Google Earth and the General Bathymetric Chart of the Oceans (GEBCO). We use Japan Agency for Marine-Earth Science and Technology (JAMSTEC) multibeam surveys not previously incorporated into the models as “ground truth” to compare against model versions 7.2 through 12.1, defining vertical differences as “errors.” Overall error statistics improve over time: 50th percentile errors declined from 57 to 55 to 49 m, and 90th percentile errors declined from 257 to 235 to 219 m, in versions 8.2, 11.1 and 12.1. This improvement is partly due to an increasing number of soundings incorporated into successive models, and partly to improvements in the satellite gravity model. Inspection of specific sites reveals that changes in the algorithms used to interpolate across survey gaps with altimetry have affected some errors. Versions 9.1 through 11.1 show a bias in the scaling from gravity in milliGals to topography in meters that affected the 15–160 km wavelength band. Regionally averaged (>160 km wavelength) depths have accumulated error over successive versions 9 through 11. These problems have been mitigated in version 12.1, which shows no systematic variation of errors with depth. Even so, version 12.1 is in some respects not as good as version 8.2, which employed a different algorithm.