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ABSTRACT We measure maximum amplitudes in the time domain on recordings of the 2019 Ridgecrest earthquake sequence to convert ground-motion amplitudes to source spectra. To do this, we modify Richter’s local magnitude relation to measure frequency-dependent empirical amplitude-decay curves and station corrections for a series of narrowband time-domain filters. Peak displacement amplitude in each frequency band is used to construct the displacement spectrum. After correction for attenuation, we determine corner frequency and moment from the resulting source spectra. By this approach, we measure moment magnitudes reliably to as small as ML 1.0. We find stress drop increases with both depth and magnitude and discuss whether this could be an artifact through assumptions about the source, path, and site. 

Abstract Earthquake location programs employ diverse approaches to address the challenges posed by incomplete knowledge and simplified representation of complex Earth structures. Assessing their reliability in location and uncertainty characterization remains challenging as benchmark datasets with known event locations are rare, and usually confined to particular sources, such as quarry blasts. This study evaluates eight earthquake location methods (GrowClust, HypoDD, Hypoinverse, HypoSVI, NonLinLoc, NonLinLoc_SSST, VELEST, and XCORLOC) through a controlled synthetic computational experiment on 1000 clustered earthquakes based on the setting of the 2019 Ridgecrest, California, earthquake sequence. We construct a travel-time dataset using the fast-marching method and a 3D velocity model extracted from the Community Velocity Model, supplemented with a von Karman perturbation to represent small-scale heterogeneity, and including elevation effects. Picking errors, phase availability, and outliers are introduced to mimic difficulties encountered in seismic network monitoring. We compare the location results from eight programs applied to the same travel-time dataset and 1D velocity structure against the ground-truth locations. For this aftershock sequence, our results reveal the superior accuracy and precision of differential time-based location methods compared to single-event location methods. The results validate the significance of compensating for deviations from assumed 1D velocity structure either by path or site correction modeling or by cancellation of unmodeled structure using differential arrival times. We also evaluate the uncertainty quantification of each program and find that most of the programs underestimate the errors. 

Abstract Deep and abyssal layer decadal temperature trends from the mid‐1980s to the mid‐2010s are mapped globally using Deep Argo and historical ship‐based Conductivity‐Temperature‐Depth (CTD) instrument data. Abyssal warming trends are widespread, with the strongest warming observed around Antarctic Bottom Water (AABW) formation regions. The warming strength follows deep western boundary currents transporting abyssal waters north and decreases with distance from Antarctica. Abyssal cooling trends are found in the North Atlantic and eastern South Atlantic, regions primarily ventilated by North Atlantic Deep Water (NADW). Deep warming trends are prominent in the Southern Ocean south of about 50°S, the Greenland‐Iceland‐Norwegian (GIN) Seas and the western subpolar North Atlantic, with cooling in the eastern subpolar North Atlantic and the subtropical and tropical western North Atlantic. Globally integrated decadal heat content trends of 21.6 (±6.5) TW in the deep and 12.9 (±1.8) TW in the abyssal layer are more certain than previous estimates. 

Abstract Many natural faults are believed to consist of velocity weakening (VW) patches surrounded by velocity strengthening (VS) sections. Numerical studies routinely employ this framework to study earthquake sequences including repeating earthquakes. In this laboratory study, we made a VW asperity, of lengthL, from a bare Poly(methyl methacrylate) PMMA frictional interface and coated the surrounding interface with Teflon to make VS fault sections. Behavior of this isolated asperity was studied as a function ofL(ranging from 100 to 400 mm) and the critical nucleation length, , which is inversely proportional to the applied normal stress (2–16 MPa). Consistent with recent numerical simulations, we observed aseismic slip for  < 2, periodic slip for 2 <  < 6, and non‐periodic slip for 10 < . Furthermore, we compared the experiments whereLwas contained by VS material to standard stick‐slip events whereLwas bounded by free surfaces (i.e.,L = the total sample length). The free surface case produced ∼10 times larger slip during stick‐slip events compared to the contained fault ruptures, even with identical . This disparity highlights how standard, complete‐rupture stick‐slip events differ from contained events expected in nature, due to both the free surface conditions and the heterogeneous normal stress along the fault near the free ends, as confirmed by Digital Image Correlation analysis. This study not only introduces the Teflon coating experimental technique for containing laboratory earthquake ruptures, but also highlights the utility of as a predictive parameter for earthquake behavior. 

Abstract Earthquakes are rupture-like processes that propagate along tectonic faults and cause seismic waves. The propagation speed and final area of the rupture, which determine an earthquake’s potential impact, are directly related to the nature and quantity of the energy dissipation involved in the rupture process. Here, we present the challenges associated with defining and measuring the energy dissipation in laboratory and natural earthquakes across many scales. We discuss the importance and implications of distinguishing between energy dissipation that occurs close to and far behind the rupture tip, and we identify open scientific questions related to a consistent modeling framework for earthquake physics that extends beyond classical Linear Elastic Fracture Mechanics. 

Abstract Earth’s energy imbalance (EEI) is a fundamental metric of global Earth system change, quantifying the cumulative impact of natural and anthropogenic radiative forcings and feedback. To date, the most precise measurements of EEI change are obtained through radiometric observations at the top of the atmosphere (TOA), while the quantification of EEI absolute magnitude is facilitated through heat inventory analysis, where ~ 90% of heat uptake manifests as an increase in ocean heat content (OHC). Various international groups provide OHC datasets derived from in situ and satellite observations, as well as from reanalyses ingesting many available observations. The WCRP formed the GEWEX-EEI Assessment Working Group to better understand discrepancies, uncertainties and reconcile current knowledge of EEI magnitude, variability and trends. Here, 21 OHC datasets and ocean heat uptake (OHU) rates are intercompared, providing OHU estimates ranging between 0.40 ± 0.12 and 0.96 ± 0.08 W m⁻²(2005–2019), a spread that is slightly reduced when unequal ocean sampling is accounted for, and that is largely attributable to differing source data, mapping methods and quality control procedures. The rate of increase in OHU varies substantially between − 0.03 ± 0.13 (reanalysis product) and 1.1 ± 0.6 W m⁻² dec⁻¹(satellite product). Products that either more regularly observe (satellites) or fill in situ data-sparse regions based on additional physical knowledge (some reanalysis and hybrid products) tend to track radiometric EEI variability better than purely in situ-based OHC products. This paper also examines zonal trends in TOA radiative fluxes and the impact of data gaps on trend estimates. The GEWEX-EEI community aims to refine their assessment studies, to forge a path toward best practices, e.g., in uncertainty quantification, and to formulate recommendations for future activities. 

ABSTRACT We present initial findings from the ongoing Community Stress Drop Validation Study to compare spectral stress-drop estimates for earthquakes in the 2019 Ridgecrest, California, sequence. This study uses a unified dataset to independently estimate earthquake source parameters through various methods. Stress drop, which denotes the change in average shear stress along a fault during earthquake rupture, is a critical parameter in earthquake science, impacting ground motion, rupture simulation, and source physics. Spectral stress drop is commonly derived by fitting the amplitude-spectrum shape, but estimates can vary substantially across studies for individual earthquakes. Sponsored jointly by the U.S. Geological Survey and the Statewide (previously, Southern) California Earthquake Center our community study aims to elucidate sources of variability and uncertainty in earthquake spectral stress-drop estimates through quantitative comparison of submitted results from independent analyses. The dataset includes nearly 13,000 earthquakes ranging from M 1 to 7 during a two-week period of the 2019 Ridgecrest sequence, recorded within a 1° radius. In this article, we report on 56 unique submissions received from 20 different groups, detailing spectral corner frequencies (or source durations), moment magnitudes, and estimated spectral stress drops. Methods employed encompass spectral ratio analysis, spectral decomposition and inversion, finite-fault modeling, ground-motion-based approaches, and combined methods. Initial analysis reveals significant scatter across submitted spectral stress drops spanning over six orders of magnitude. However, we can identify between-method trends and offsets within the data to mitigate this variability. Averaging submissions for a prioritized subset of 56 events shows reduced variability of spectral stress drop, indicating overall consistency in recovered spectral stress-drop values. 

These transect organized radargrams were collected as part of the Center for Oldest Ice Exploration (COLDEX) Science and Technology Center (https://www.coldex.org) in the 2022/23 (CXA1) airborne reconnaissance field season. The raw 3 TB data is deposited at the USAP data center at https://doi.org/10.15784/601768. Flight organized data with additional processing by the University of Kansas to remove electromagnetic interference can be found at the Open Polar Radar server (https://www.openpolarradar.org). The science goal was to characterize the ice sheet between Antarctica's Dome A and Amundsen Scott South Pole Station, to locate sites of interest for the drilling of an ice core with ages spanning the mid-Pleistocene. The radar was deployed on Balser C-FMKB, and flown at ranges of up to 800 km from South Pole Station at velocities of 90 m/s and typical altitude above ground of 600 m. Other instruments included a UHF array system provided by the University of Kansas, a gravity meter, a magnetometer, a laser altimeter, and multiple global navigation satellite systems receivers. The radar data is used for finding ice thickness, bed character, englacial structure and surface assessment. Dataset organization Transects are provided a P/S/T nomenclature, organized by the Project they are flying in, the acquisition System (typically named after the aircraft) and the Transect within the Project. Transects were collected in preplanned systems with the following parameters: CLX radials (CLX/MKB##/R###), attempting to emulate flow lines from Dome A and radiating (in the EPSG:3031 polar stereographic projection) from easting 965 km northing 385 km, with a separation of 0.25 degrees. CLX corridor (CLX/MKB##/X###) rotated from the EPSG:3031 polar stereographic projection at -150 degrees and separated by 10 km in the Y direction and 3.75 km in the X direction CLX2 corridor (CLX2/MKB##/X###) rotated from the EPSG:3031 polar stereographic projection at -150 degrees and separated by 2.5 km in its Y direction and 2.5 km in its X direction SAD corridor (SAD/MKB##/X###|Y####) designed to characterize the Saddle region near South Pole approximately perpendicular to the flow lines, rooted from the EPSG:3031 polar stereographic projection at -73.8 degrees and separated by 2.5 km in its Y direction and 2.5 km in the its X direction Untargeted transit lines used the name of the expedition (CXA1) as the project, and used the flight and the increment within the flight to name the Transect (eg (CXA1/MKB2n/F10T02a). Processing These data represent range compressed VHF radargrams as collected and analyzed in the field. The data are from the MARFA radar system, a 60 MHz ice penetrating radar system that has operated in several different guises over the years. MARFA operates with a 1 microsecond chirp with a design bandwidth of 15 MHz, allowing for ~8 range resolution. The record rate after onboard stacking is 200 Hz. High and low gain channels are collected from antennas on each side of the aircraft. In ground processing, the data were stacked 10x coherently to reduce range delayed incoherent surface scattering, and then stacked 5 times incoherently to improve image quality. In this preliminary processing, the effective resolution of deep scattering is several hundred meters due to range ambiguities at depth. Data format These data collection represents georeferenced, time registered instrument measurements (L1B data) converted to SI units. The data format are netCDF3 files, following the formats used for NASA/AAD/UTIG's ICECAP/OIB project at NASA's NSIDC DAAC (10.5067/0I7PFBVQOGO5). Metadata fields can be accessed using the open source ncdump tool, or c, python or matlab modules. A Keyhole Metadata Language (KML) file with geolocation for all transects is also provided. See https://www.loc.gov/preservation/digital/formats/fdd/fdd000330.shtml for resources on NetCDF-3, and https://nsidc.org/data/IR2HI1B/versions/1 for a description of the similar OIB dataset. Acknowledgements This work was supported by the Center for Oldest Ice Exploration, an NSF Science and Technology Center (NSF 2019719). We thank the NSF Office of Polar Programs, the NSF Office of Integrative Activities, and Oregon State University for financial and infrastructure support, and the NSF Antarctic Infrastructure and Logistics Program, and the Antarctic Support Contractor for logistical support. Additional support was provided by the G. Unger Vetlesen Foundation.