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Earthquakes pose a major threat to the people of Haiti, as tragically shown by the catastrophic 2010 Mw 7.0 earthquake and more recently by the 2021 Mw 7.2 earthquake. Both events occurred within the transpressional Enriquillo–Plantain Garden fault zone (EPGFZ), which runs through the southern peninsula of Haiti and is a major source of seismic hazard for the region. Satellite-based Interferometric Synthetic Aperture Radar (InSAR) data are used to illuminate the ground deformation patterns associated with the 2021 event. The analysis of Sentinel-1 and Advanced Land Observation Satellite (ALOS)-2 InSAR data shows (1) the broad coseismic deformation field; (2) detailed secondary fault structures as far as 12 km from the main Enriquillo–Plantain Garden fault (EPGF), which are active during and after the earthquake; and (3) postseismic shallow slip, which migrates along an ∼40 km unruptured section of the EPGF for approximately two weeks following the earthquake. The involvement of secondary faults in this rupture requires adjustments to the representation of hazard that assumes a simple segmented strike-slip EPGF. This work presents the first successful use of phase gradient techniques to map postseismic deformation in a vegetated region, which opens the door to future studies of a larger number of events in a wider variety of climates.

SUMMARY Seamounts are volcanic constructs that litter the seafloor. They are important for understanding numerous aspects of marine science, such as plate tectonics, the volcanic melt budget, oceanic circulation, tsunami wave diffraction, tidal energy dissipation and mass wasting. Geometrically, seamounts come in many sizes and shapes, and for the purpose of modelling them for morphological, gravimetric or isostatic studies it is convenient to have simple analytical models whose properties are well known. Here, we present a family of seamount models that may be used in such studies, covering both the initial construction phase and later mass-wasting by sectoral collapses. We also derive realistic axisymmetric density variations that are compatible with observed first-order structure from seismic tomography studies.

Rapid melting of ice sheets and glaciers drives a unique geometry, or fingerprint, of sea-level change, including a sea-level fall in the vicinity of the ice sheet that is an order of magnitude greater than the associated global mean sea-level rise of the melt event. The detection of individual fingerprints has been challenging due to sparse sea surface height measurements at high latitudes and the difficulty of disentangling ocean dynamic variability from the signal. Efforts to date have analyzed sea level records outside the zone of major sea-level fall, where the gradients and amplitudes of the fingerprint signal are significantly lower. We predict the fingerprint of Greenland Ice Sheet (GrIS) melt using new ice mass loss estimates from radar altimetry data and model reconstructions of nearby glaciers, and compare this prediction to an independent, altimetry-derived sea surface height trend corrected for ocean dynamic variability in the region adjacent to the ice sheet. The two fields show consistent gradients across the region, with the expected strong drawdown of the sea surface toward GrIS. A statistically significant correlation between the two fields (p < 0.001) provides the first unambiguous observational detection of the near-field sea level fingerprint of recent GrIS melting in our warming world. This detection provides a robust map of the impact of ice mass flux on global oceans since the early 1990s, and validates theoretical and numerical developments in the sea level modelling community.

Satellite radar altimetry collected during a number of geodetic missions has provided a new understanding of the topography and tectonics of the deep oceans. As altimeter performance and coverage improves, smaller structures are revealed. Here we investigate the contribution of six altimeter missions that have been placed into geodetic mapping phases for more than one year. Two types of evaluations are performed. We first compare the composite (all six altimeters) grids of east and north vertical deflection to matching grids where one altimeter has been omitted evaluate their contribution versus latitude. We then estimate the noise in each altimeter by computing the median absolute deviation of the profiles with the best composite grid. Both analyses show that SARAL/AltiKa provides the greatest contribution and ERS-1 no longer provides any significant improvement. The major limitation for recovering small scale gravity features is the sea surface roughness from ocean waves. There have been steady improvements in instrumentation and processing methods that will continue into the future with higher frequency radars and interferometric swath altimeters planned for future missions.

Sea surface slope (SSS) responds to oceanic processes and other environmental parameters. This study aims to identify the parameters that influence SSS variability. We use SSS calculated from multiyear satellite altimeter observations and focus on small resolvable scales in the 30–100-km wavelength band. First, we revisit the correlation of mesoscale ocean variability with seafloor roughness as a function of depth, as proposed by Gille et al. Our results confirm that in shallow water there is statistically significant positive correlation between rough bathymetry and surface variability, whereas the opposite is true in the deep ocean. In the next step, we assemble 27 features as input variables to fit the SSS with a linear regression model and a boosted trees regression model, and then we make predictions. Model performance metrics for the linear regression model are R2 = 0.381 and mean square error = 0.010 μrad2. For the boosted trees model, R2 = 0.563 and mean square error = 0.007 μrad2. Using the hold-out data, we identify the most important influencing factors to be the distance to the nearest thermocline boundary, significant wave height, mean dynamic topography gradient, and M2 tidal speed. However, there are individual regions, that is, the Amazon outflow, that cannot be predicted by our model, suggesting that these regions are governed by processes that are not represented in our input features. The results highlight both the value of machine learning and its shortcomings in identifying mechanisms governing oceanic phenomena.

Mapping out backward motion Most deformation associated with an earthquake is, not surprisingly, in the same direction as the fault rupture. Xu et al. used satellite imaging to find areas of deformation associated with the 2019 Ridgecrest earthquake sequence that moved in the opposite direction. These regions moved in this direction because of inelastic deformation, which helped to accommodate the overall fault rupture for the sequence. The observations were possible because of improved radar imaging and are likely more common than previously believed. Science , this issue p. 605

The Mw 6.4 and Mw 7.1 Ridgecrest earthquake sequence occurred on 4 and 5 July 2019 within the eastern California shear zone of southern California. Both events produced extensive surface faulting and ground deformation within Indian Wells Valley and Searles Valley. In the weeks following the earthquakes, more than six dozen scientists from government, academia, and the private sector carefully documented the surface faulting and ground-deformation features. As of December 2019, we have compiled a total of more than 6000 ground observations; approximately 1500 of these simply note the presence or absence of fault rupture or ground failure, but the remainder include detailed descriptions and other documentation, including tens of thousands of photographs. More than 1100 of these observations also include quantitative field measurements of displacement sense and magnitude. These field observations were supplemented by mapping of fault rupture and ground-deformation features directly in the field as well as by interpreting the location and extent of surface faulting and ground deformation from optical imagery and geodetic image products. We identified greater than 68 km of fault rupture produced by both earthquakes as well as numerous sites of ground deformation resulting from liquefaction or slope failure. These observations comprise a dataset that is fundamental to understanding the processes that controlled this earthquake sequence and for improving earthquake hazard estimates in the region. This article documents the types of data collected during postearthquake field investigations, the compilation effort, and the digital data products resulting from these efforts.

Interferometric Synthetic Aperture Radar is an important tool for imaging surface deformation from large continental earthquakes. Here, we present maps of coseismic displacement and strain from the 2019 Ridgecrest earthquakes using multiple Sentinel-1 images. We provide three types of interferometric products. (1) Standard interferograms from two look directions provide an overview of the deformation and can be used for modeling coseismic slip. (2) Phase gradient maps from stacks of coseismic interferograms provide high-resolution (∼30 m) images of strain concentration and surface fracturing that can be used to guide field surveys. (3) High-pass filtered, stacked, unwrapped phase is decomposed into east–west and up–down, south–north components and is used to determine the sense of fault slip. The resulting phase gradient maps reveal over 300 surface fractures, including triggered slip on the Garlock fault. The east–west component of high-pass filtered phase reveals the polarity of the strike-slip offset (right lateral or left lateral) for many of the fractures. We find a small number of fractures that have slip polarity that is retrograde to the background tectonic stress. This is similar to observations of retrograde slip observed near the 1999 Mw 7.1 Hector Mine rupture, but the Ridgecrest observations are more completely imaged by the frequent and high-quality acquisitions from the twin Sentinel-1 spacecrafts. Determining whether the retrograde features are triggered slip on existing faults, or compliant fault deformation in response to stress changes from the Ridgecrest earthquakes, or new Coulomb-style failures, will require additional field work, modeling, and analysis.

Radar interferograms provide a map of the phase difference between the reference and repeat acquisitions modulo ${2\pi }$ . Under ideal conditions, the phase can be unwrapped to provide an absolute phase connection across the map, although there is always an unknown integer phase ambiguity (i.e., ${N2\pi }$ ) for the entire map. Here, we demonstrate a practical time series method to solve for these integer ambiguities in order to recover the absolute phase change between the first and last SAR images. An important first step is to correct the phase of each SAR image for the well-known solid earth tide, which typically produces a line of sight offset ±150 mm, as well as, trends along and across each image of ~20 mm. This tide correction significantly reduces the noise in the InSAR time series, especially at the L-band. These tidally corrected interferograms are then unwrapped and used to solve for a set of integer ambiguities that achieves phase closure when summing around loops in the stack. There is an infinite number of ambiguity combinations that achieve loop closure; thus, regularization is required. In contrast to previous studies that use a least-squares approach to find the ambiguities, we adopt an ${L}_{1}$ -norm approach to find the minimum number of ambiguity corrections needed to achieve loop closure. We note that the split-spectrum ionospheric correction can introduce ${N\pi }$ ambiguities and suggest two approaches for correcting both ${N2\pi }$ and ${N\pi }$ ambiguities.

We calibrate a technique to use repeated multibeam sidescan surveys in the deep ocean to recover seafloor displacements greater than a few meters. Displacement measurements from seafloor patches (3...

An updated global bathymetry and topography grid is presented using a spatial sampling interval of 15 arc sec. The bathymetry is produced using a combination of shipboard soundings and depths predicted using satellite altimetry. New data consists of >33.6 million multibeam and singlebeam measurements collated by several institutions, namely, the National Geospatial‐Intelligence Agency, Japan Agency for Marine‐Earth Science and Technology, Geoscience Australia, Center for Coastal and Ocean Mapping, and Scripps Institution of Oceanography. New altimetry data consists of 48, 14, and 12 months of retracked range measurements from Cryosat‐2, SARAL/AltiKa, and Jason‐2, respectively. With respect to SRTM15_PLUS (Olson et al.,), the inclusion of these new data results in a ∼1.4‐km improvement in the minimum wavelength recovered for sea surface free‐air gravity anomalies, a small increase in the accuracy of altimetrically derived predicted depths, and a 1.24% increase, from 9.60% to 10.84%, in the total area of ocean floor that is constrained by shipboard soundings at 15‐arc sec resolution. Bathymetric grid cells constrained by satellite altimetry have estimated uncertainties of ±150 m in the deep oceans and ±180 m between coastlines and the continental rise. Onshore, topography data are sourced from previously published digital elevation models, predominately SRTM‐CGIAR V4.1 between 60°N and 60°S. ArcticDEM is used above 60°N, while Reference Elevation Model of Antarctica is used below 62°S. Auxiliary grids illustrating shipboard data coverage, marine free‐air gravity anomalies, and vertical gradient gradients are also provided in common data formats.

The existing bathymetry map of the Arctic is a compilation of ship soundings and digitized contours. Due to the presence of all‐year sea ice, costly operations and political restrictions, dense and full coverage of the Arctic is not possible, leaving huge gaps between the existing surveys. In this paper, we make use of the existing Arctic bathymetry IBCAOv3 and invert Arctic bathymetry from the recent altimetric gravity model DTU17, whose accuracy is improved significantly with revised data processing strategy. The long and short wavelength components are preserved from IBCAOv3. The band‐pass‐filtering function proposed by Smith and Sandwell (1994, https://doi.org/10.1029/94JB00988) is adapted for the Arctic by reducing the cutoff wavelength. The predicted bathymetry is within 100 m on 85.8% of the grid nodes, when compared to the IBCAOv3. The consistency of the prediction is validated with two independent profiles from Healy cruises conducted in 2016 over the Chukchi Cap. A questionable valley in the IBCAOv3 is detected with gravity and at this spot, bathymetry predicted from gravity is consistent with independent multibeam soundings. The gravity‐inverted bathymetry could be combined with ship soundings for the next generation of Arctic bathymetry map.

SUMMARY Flexure and fracturing of the seafloor on the outer trench wall of subduction zones reflect bending of the lithosphere beyond its elastic limit. To investigate these inelastic processes, we have developed a full nonlinear inversion approach for estimating the bending moment, curvature and outer trench wall fracturing using shipboard bathymetry and satellite altimetry-derived gravity data as constraints. Bending moments and downward forces are imposed along curved trench axes and an iterative method is used to calculate the nonlinear response for 26 sites in the circum-Pacific region having seafloor age ranging from 15 to 148 Ma. We use standard thermal and yield strength envelope models to develop the nonlinear moment versus curvature relationship. Two coefficients of friction of 0.6 and 0.3 are considered and we find that the lower value provides a better overall fit to the data. The main result is that the lithosphere is nearly moment saturated at the trench axis. The effective elastic thickness of the plate on the outer trench slope is at least three times smaller than the elastic thickness of the plate before bending at the outer rise in agreement with previous studies. The average seafloor depth of the unbent plate in these 26 sites matches the Parsons & Sclater depth versus age model beyond 120 Ma. We also use the model to predict the offsets of normal faults on the outer trench walls and compare this with the horst and graben structures observed by multibeam surveys. The model with the lower coefficient of friction fits the fault offset data close to the trench axis. However, the model predicts significant fracturing of the lithosphere between 75 and 150 km away from the trench axis where no fracturing is observed. To reconcile these observations, we impose a thermoelastic pre-stress in the lithosphere prior to subduction. This pre-stress delays the onset of fracturing in better agreement with the data.

Author(s): Yu, Yao; Sandwell, David T; Gille, Sarah T; Boas, Ana Beatriz Villas | Abstract: SUMMARY The Ice, Cloud and land Elevation Satellite 2 (ICESat-2) laser altimetry mission, launched in September 2018, uses six parallel lidar tracks with very fine along-track resolution (15nm) to measure the topography of ice, land and ocean surfaces. Here we assess the ability of ICESat-2 ocean data to recover oceanographic signals ranging from surface gravity waves to the marine geoid. We focus on a region in the tropical Pacific and study photon height data in both the wavenumber and space domain. Results show that an ICESat-2 single track can recover the marine geoid at wavelengths g20nkm which is similar to the best radar altimeter data. The wavelength and propagation direction of surface gravity waves are sometimes well resolved by using a combination of the strong and weak beams, which are separated by 90nm. We find higher than expected power in the 3–20nkm wavelength band where geoid and ocean signals should be small. This artificial power is caused by the projection of 2-D surface waves with ∼300nm wavelengths into longer wavelengths (5–10nkm) because of the 1-D sampling along the narrow ICESat-2 profile. Thus ICESat-2 will not provide major improvements to the geoid recovery in most of the ocean.

International audience; 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.

There are two dominating approaches of modeling the marine gravity field based on satellite altimetry observations. In this study, the marine gravity field is determined in four selected areas (Northwestern Atlantic, Hawaii ocean area, Mariana Trench area, and Aegean Sea) by using exact same input datasets but different methods which are based on sea surface height (SSH) and sea surface slope (SSS), respectively. The impact of the methodology is evaluated by conducting validations with shipborne gravity observation. The CryoSat-2, Jason-1/2, and SARAL/Altika geodetic mission data (similarly 3-year-long time series) are firstly retracked by the two-pass retracker. After that, the obtained SSHs are used for the derivation of geoid undulations and vertical deflections, and then for the resulting marine gravity field separately. The validation results indicate that the SSH-based method has advantages in robustly estimating marine gravity anomalies near the coastal zone. The SSS-based method has advantages over regions with intermedium ocean depths (2000–4000 m) where seamounts and ridges are found, but obvious disadvantages when the ocean currents flow along the north–south direction (e.g., western boundary currents) or the topography features north–south directional trenches. In the deep ocean where the seafloor topography is plain and smooth, the two methods have similar accuracy.

Seafloor geodetic studies such as Global Positioning System (GPS)-Acoustic experiments often require the measurement platform on the sea surface to be positioned accurately to within a few centimetres. In this paper, we test the utility of Precise Point Positioning (PPP) for this application with two experiments. The first fixed platform experiment is a comparison between three independent processing software packages: Positioning and Navigation Data Analyst (PANDA), Global Navigation Satellite System-Inferred Positioning System and Orbit Analysis Simulation Software (GIPSY-OASIS), and the Canadian Spatial Reference System (CSRS)) and a more accurate solution based on conventional differential processing of a remote GPS station in the Aleutian Islands. The second moving platform experiment is a comparison among the three PPP software packages using 40 hours of ship navigation data collected during theRoger RevelleRR1605 cruise 170 nautical miles southwest of Palau in May 2016. We found the PPP solutions were repeatable to 5·49 cm in the horizontal components and 12·4 cm in the vertical component. This demonstrates not only that PPP is a useful tool for positioning marine platforms in remote locations, but also that modern ship navigation instruments such as the Kongsberg Seapath 330 + are suitable for seafloor geodetic application.