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The height of the mean sea surface above the reference ellipsoid is a time independent reference model that can be removed from radar altimeter measurements to isolate the oceanographic signals.  This document explains how the CLS mean sea surface model is updated at short wavelengths using the 30-years of sea surface slope measurements that have been archived and computed at Scripps Institution of Oceanography.  The data are available at https://topex.ucsd.edu/pub/ .

AbstractSea 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.

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 (15 m) 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 >20 km 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 90 m. We find higher than expected power in the 3–20 km wavelength band where geoid and ocean signals should be small. This artificial power is caused by the projection of 2-D surface waves with ∼300 m wavelengths into longer wavelengths (5–10 km) 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.

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 bymapping 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 aswell 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.

Our understanding of plate boundary deformation has been enhanced by transient signals observed against the backdrop of time-independent secular motions. We make use of a new analysis of displacement time series from about 1,000 continuous Global Positioning System (GPS) stations in California from 1999 to 2018 to distinguish tectonic and nontectonic transients from secular motion. A primary objective is to define a high-resolution three-dimensional reference frame (datum) for California that can be rapidly maintained with geodetic data to accommodate both secular and time-dependent motions. To this end, we compare the displacements to those predicted by a horizontal secular fault slip model for the region and construct displacement and strain rate fields. Over the past 19 years, California has experienced 19 geodetically detectable earthquakes and widespread postseismic deformation. We observe postseismic strain rate variations as large as 1,000 nstrain/year with moment releases equivalent up to an Mw6.8 earthquake. We find significant secular differences up to 10 mm/year with the fault slip model, from the Mendocino Triple Junction to the southern Cascadia subduction zone, the northern Basin and Range, and the Santa Barbara channel. Secular vertical uplift is observed across the Transverse Ranges, Coastal Ranges, Sierra Nevada, as well as large-scale postseismic uplift after the 1999 Mw7.1 Hector Mine and 2010 Mw7.2 El Mayor-Cucapah earthquakes. We also identify areas of vertical land motions due to anthropogenic, natural, and magmatic processes. Finally, we demonstrate the utility of the kinematic datum by improving the accuracy of high-spatial-resolution 12-day repeat-cycle Sentinel-1 Interferometric Synthetic Aperture Radar displacement and velocity maps.

The pace of scientific discovery is being transformed by the availability of 'big data' and open access, open source software tools. These innovations open up new avenues for how scientists communicate and share data and ideas with each other and with the general public. Here, we describe our efforts to bring to life our studies of the Earth system, both at present day and through deep geological time. The GPlates Portal (portal.gplates.org) is a gateway to a series of virtual globes based on the Cesium Javascript library. The portal allows fast interactive visualization of global geophysical and geological data sets, draped over digital terrain models. The globes use WebGL for hardware-accelerated graphics and are cross-platform and cross-browser compatible with complete camera control. The globes include a visualization of a high-resolution global digital elevation model and the vertical gradient of the global gravity field, highlighting small-scale seafloor fabric such as abyssal hills, fracture zones and seamounts in unprecedented detail. The portal also features globes portraying seafloor geology and a global data set of marine magnetic anomaly identifications. The portal is specifically designed to visualize models of the Earth through geological time. These space-time globes include tectonic reconstructions of the Earth's gravity and magnetic fields, and several models of long-wavelength surface dynamic topography through time, including the interactive plotting of vertical motion histories at selected locations. The globes put the on-the-fly visualization of massive data sets at the fingertips of end-users to stimulate teaching and learning and novel avenues of inquiry.

The Mw 7.2 El Mayor-Cucapah (EMC) earthquake ruptured a complex fault system in northern Baja California that was previously considered inactive. The Cerro Prieto Geothermal Field (CPGF), site of the world's second largest geothermal power plant, is located approximately 15 km to the northeast of the EMC hypocenter. We investigate whether anthropogenic fluid extraction at the CPGF caused a significant perturbation to the stress field in the EMC rupture zone. We use Advanced Land Observing Satellite interferometric synthetic aperture radar data to develop a laterally heterogeneous model of fluid extraction at the CPGF and estimate that this extraction generates positive Coulomb stressing rates of order 15 kPa/yr near the EMC hypocenter, a value which exceeds the local tectonic stressing rate. Although we cannot definitively conclude that production at the CPGF triggered the EMC earthquake, its influence on the local stress field is substantial and should not be neglected in local seismic hazard assessments. Key Points Geothermal energy production causes surface subsidence and crustal stressingProduction at CPGF generates positive Coulomb stresses in EMC rupture zoneAnthropogenic stresses exceed the tectonic loading rate at EMC hypocenter

El Mayor-Cucapah earthquake occurred on 4 April 2010 in northeastern Baja California just south of the U.S.-Mexico border. The earthquake ruptured several previously mapped faults, as well as some unidentified ones, including the Pescadores, Borrego, Paso Inferior and Paso Superior faults in the Sierra Cucapah, and the Indiviso fault in the Mexicali Valley and Colorado River Delta.We conducted several Global Positioning System (GPS) campaign surveys of preexisting and newly established benchmarks within 30 km of the earthquake rupture. Most of the benchmarks were occupied within days after the earthquake, allowing us to capture the very early postseismic transient motions. The GPS data show postseismic displacements in the same direction as the coseismic displacements; time series indicate a gradual decay in postseismic velocities with characteristic time scales of 66 ± 9 days and 20 ± 3 days, assuming exponential and logarithmic decay, respectively. We also analyzed interferometric synthetic aperture radar (InSAR) data from the Envisat and ALOS satellites. The main deformation features seen in the line-of-sight displacement maps indicate subsidence concentrated in the southern and northern parts of the main rupture, in particular at the Indiviso fault, at the Laguna Salada basin, and at the Paso Superior fault. We show that the near-field GPS and InSAR observations over a time period of 5 months after the earthquake can be explained by a combination of afterslip, fault zone contraction, and a possible minor contribution of poroelastic rebound. Far-field data require an additional mechanism, most likely viscoelastic relaxation in the ductile substrate. ©2014. American Geophysical Union.

Seismic moment accumulation rate is a fundamental parameter for assessing seismic hazard. It can be estimated geodetically from either fault‐based modeling, or strain rate‐based calculations, where fault‐based models largely depend on the rheological layering and the number of faults. The strain‐rate method depends on an unknown (Kostrov) thickness used to convert strain rate into moment rate. In Part 1 of this study, we use three published fault‐based models from southern California to establish the value of the Kostrov thickness such that the total moment from the strain‐rate approach, calculated from the fault model‐predicted strain rate, matches the fault‐based approach. Constrained thickness estimates of 7.3, 9.7, and 11.5 km (6.4–13.0 km, including uncertainties) suggest that the 11 km value used in previous studies may be too large and a lower value may be more accurate. In Part 2 we use calibrated values of Kostrov thickness, along with the latest compilation of GNSS velocity data, to partition moment rate into on‐fault and off‐fault moment rate, where off‐fault varies from 32%–43% of the total moment rate. The largest uncertainty is related to the method used to interpolate sparse GNSS data. Lastly, we compare our estimates of total moment rate (mean: 2.13 ± 0.42 × 1019 Nm/yr) with the historical seismic catalog. Results suggest that including uncertainties in Kostrov thickness brings fault‐based geodetic moment rate closer to the seismic moment release (particularly when aseismic afterslip is accounted for), while the (uncertain) values of off‐fault moment rate push geodetic moment rates to be larger than seismic moment rates. Plain Language Summary: One commonly‐used method of evaluating the future earthquake potential of a known fault is to estimate the moment rate accumulating along that fault. In other words, one can estimate how much earthquake energy is accumulating over time, caused by the forces that propel plate boundary motion along fault systems. Two ways to do this are: (a) using detailed fault models of plate boundary motion, which are constrained by satellite‐based measurements of surface motion or (b) using those satellite‐based measurements directly through the estimation of regional strain rate. Here, we investigate the uncertainties present in the latter method by comparing previously published estimates of fault‐based moment rate, with their equivalent strain rate‐based versions. We estimate uncertainties related to the strain‐rate based method, which can lead to an over‐ or under‐estimation of earthquake potential on a given fault system. In addition, we explore the off‐fault moment rate accumulation in southern California which can help identify areas of enhanced moment accumulation and thus increased seismic hazard. Key Points: Previously published fault‐based models can constrain a Kostrov thickness range of 6.4–13.0 km, including uncertaintiesDifferences between strain rate moment estimates and fault‐based estimates suggest 32%–43% off‐fault moment rate in southern CaliforniaThe largest uncertainty in estimating moment rate from strain rate is the degree of smoothing used to estimate strain from geodetic data [ABSTRACT FROM AUTHOR]

GMTSAR is an open source (GNU General Public License) InSAR processing system designed for users familiar with Generic Mapping Tools (GMT). The code is written in C and will compile on any computer where GMT and NETCDF are installed. The system has three main components: 1) a preprocessor for each satellite data type (e.g., ERS, Envisat, and ALOS) to convert the native format and orbital information into a generic format; 2) an InSAR processor to focus and align stacks of images, map topography into phase, and form the complex interferogram; 3) a postprocessor, mostly based on GMT, to filter the interferogram and construct interferometric products of phase, coherence, phase gradient, and line-of-sight displacement in both radar and geographic coordinates. GMT is used to display all the products as postscript files and kml-images for Google Earth. A set of C-shell scripts has been developed for standard 2- pass processing as well as image alignment for stacking and time series. ScanSAR processing is also possible but requires a knowledgeable user. Users are welcome to contribute to this effort.

Author(s): Dan Bassett (corresponding author) [1]; David T. Sandwell [1]; Yuri Fialko [1]; Anthony B. Watts [2] The March 2011 Tohoku-oki earthquake was only the second giant (moment magnitude M [...]