Noise Characteristics of Operational Real‐Time High‐Rate GNSS Positions in a Large Aperture Network

Large earthquakes are difficult to model in real‐time with traditional inertial seismic measurements. Several algorithms that leverage high‐rate real‐time Global Navigation Satellite Systems (HR‐GNSS) positions have been proposed, and it has been shown that they can supplement the earthquake monitoring effort. However, analyses of the long‐term noise behavior of high‐rate real‐time GNSS positions, which are important to understand how the data can be used operationally by monitoring agencies, have been limited to just a few sites and to short time spans. Here, we show results from an analysis of the noise characteristics of 1 year of positions at 213 GNSS sites spanning a large geographic region from Southern California to Alaska. We characterize the behavior of noise and propose several references noise models which can be used as baselines to compare against as technological improvements allow for higher precision solutions. We also show how to use the reference noise models to generate realistic synthetic noise that can be used in simulations of HR‐GNSS waveforms. We discuss spatiotemporal variations in the noise and their potential sources and significance. We also detail how noise analysis can be used in a dynamic quality control to determine which sites should or should not contribute positions to an earthquake modeling algorithm at a particular moment in time. We posit that while there remain important improvements yet to be made, such as reducing the number of outliers in the time series, the present quality of real‐time HR‐GNSS waveforms is more than sufficient for monitoring large earthquakes

Validation of Peak Ground Velocities Recorded on Very-high rate GNSS Against NGA-West2 Ground Motion Models

Observations of strong ground motion during large earthquakes are generally made with strong-motion accelerometers. These observations have a critical role in early warning systems, seismic engineering, source physics studies, basin and site amplification, and macroseismic intensity estimation. In this manuscript, we present a new observation of strong ground motion made with very high rate (>= 5 Hz) Global Navigation Satellite System (GNSS) derived velocities. We demonstrate that velocity observations recorded on GNSS instruments are consistent with existing ground motion models and macroseismic intensity observations. We find that the ground motion predictions using existing NGA-West2 models match our observed peak ground velocities with a median log total residual of 0.03-0.33 and standard deviation of 0.72-0.79, and are statistically significant following normality testing. We finish by deriving a Ground Motion Model for peak ground velocity from GNSS and find a total residual standard deviation 0.58, which can be improved by ~2% when considering a simple correction for Vs30

Characterizing High Rate GNSS Velocity Noise for Synthesizing a GNSS Strong Motion Learning Catalog

Data-driven approaches to identify geophysical signals have proven beneficial in high dimensional environments where model-driven methods fall short. GNSS offers a source of unsaturated ground motion observations that are the data currency of ground motion forecasting and rapid seismic hazard assessment and alerting. However, these GNSS-sourced signals are superposed onto hardware-, location- and time-dependent noise signatures influenced by the Earth’s atmosphere, low-cost or spaceborne oscillators, and complex radio frequency environments. Eschewing heuristic or physics based models for a data-driven approach in this context is a step forward in autonomous signal discrimination. However, the performance of a data-driven approach depends upon substantial representative samples with accurate classifications, and more complex algorithm architectures for deeper scientific insights compound this need. The existing catalogs of high-rate (≥1Hz) GNSS ground motions are relatively limited. In this work, we model and evaluate the probabilistic noise of GNSS velocity measurements over a hemispheric network. We generate stochastic noise time series to augment transferred low-noise strong motion signals from within 70 kilometers of strong events (≥ MW 5.0) from an existing inertial catalog. We leverage known signal and noise information to assess feature extraction strategies and quantify augmentation benefits. We find a classifier model trained on this expanded pseudo-synthetic catalog improves generalization compared to a model trained solely on a real-GNSS velocity catalog, and offers a framework for future enhanced data driven approaches

National CO\u3csub\u3e2\u3c/sub\u3e budgets (2015-2020) inferred from atmospheric CO\u3csub\u3e2\u3c/sub\u3e observations in support of the global stocktake

Accurate accounting of emissions and removals of CO2 is critical for the planning and verification of emission reduction targets in support of the Paris Agreement. Here, we present a pilot dataset of country-specific net carbon exchange (NCE; fossil plus terrestrial ecosystem fluxes) and terrestrial carbon stock changes aimed at informing countries\u27 carbon budgets. These estimates are based on top-down NCE outputs from the v10 Orbiting Carbon Observatory (OCO-2) modeling intercomparison project (MIP), wherein an ensemble of inverse modeling groups conducted standardized experiments assimilating OCO-2 column-Averaged dry-Air mole fraction (XCO2) retrievals (ACOS v10), in situ CO2 measurements or combinations of these data. The v10 OCO-2 MIP NCE estimates are combined with bottom-up estimates of fossil fuel emissions and lateral carbon fluxes to estimate changes in terrestrial carbon stocks, which are impacted by anthropogenic and natural drivers. These flux and stock change estimates are reported annually (2015-2020) as both a global 1gg×g1g gridded dataset and a country-level dataset and are available for download from the Committee on Earth Observation Satellites\u27 (CEOS) website: 10.48588/npf6-sw92 . Across the v10 OCO-2 MIP experiments, we obtain increases in the ensemble median terrestrial carbon stocks of 3.29-4.58gPgCO2yr-1 (0.90-1.25gPgCyr-1). This is a result of broad increases in terrestrial carbon stocks across the northern extratropics, while the tropics generally have stock losses but with considerable regional variability and differences between v10 OCO-2 MIP experiments. We discuss the state of the science for tracking emissions and removals using top-down methods, including current limitations and future developments towards top-down monitoring and verification systems

Sub- and super-shear ruptures during the 2023 Mw 7.8 and Mw 7.6 earthquake doublet in SE Türkiye

An earthquake doublet (Mw 7.8 and Mw 7.6) occurred on the East Anatolian Fault Zone (EAFZ) on February 6th, 2023. The events produced significant ground motions and caused major impacts to life and infrastructure throughout SE Türkiye and NW Syria. Here we show the results of earthquake relocations of the first 11 days of aftershocks and rupture models for both events inferred from the kinematic inversion of HR-GNSS and strong motion data considering a multi-fault, 3D geometry. We find that the first event nucleated on a previously unmapped fault before transitioning to the East Anatolian Fault (EAF) rupturing for ~350 km and that the second event ruptured the Sürgü fault for ~160 km. Maximum rupture speeds were estimated to be 3.2 km/s for the Mw 7.8 event. For the Mw 7.6 earthquake, we find super-shear rupture at 4.8 km/s westward but sub-shear eastward rupture at 2.8 km/s. Peak slip for both events were as large as ~8m and ~6m, respectively

National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the Global Stocktake

Accurate accounting of emissions and removals of CO2 is critical for the planning and verification of emission reduction targets in support of the Paris Agreement. Here, we present a pilot dataset of country-specific net carbon exchange (NCE; fossil plus terrestrial ecosystem fluxes) and terrestrial carbon stock changes aimed at informing countries’ carbon budgets. These estimates are based on "top-down" NCE outputs from the v10 Orbiting Carbon Observatory (OCO-2) modeling intercomparison project (MIP), wherein an ensemble of inverse modeling groups conducted standardized experiments assimilating OCO-2 column-averaged dry-air mole fraction (XCO2) retrievals (ACOS v10), in situ CO2 measurements, or combinations of these data. The v10 OCO-2 MIP NCE estimates are combined with "bottom-up" estimates of fossil fuel emissions and lateral carbon fluxes to estimate changes in terrestrial carbon stocks, which are impacted by anthropogenic and natural drivers. These flux and stock change estimates are reported annually (2015–2020) as both a global 1° × 1° gridded dataset and as a country-level dataset. Across the v10 OCO-2 MIP experiments, we obtain increases in the ensemble median terrestrial carbon stocks of 3.29–4.58 PgCO2 yr-1 (0.90–1.25 PgC yr-1). This is a result of broad increases in terrestrial carbon stocks across the northern extratropics, while the tropics generally have stock losses but with considerable regional variability and differences between v10 OCO-2 MIP experiments. We discuss the state of the science for tracking emissions and removals using top-down methods, including current limitations and future developments towards top-down monitoring and verification systems

Biological sulfur reactions and the influence on fluid flow at mid-ocean ridge hydrothermal systems

This thesis is an investigation into biogenic sulfide oxidation and sulfate reduction associated with hydrothermal systems at oceanic spreading centers. First, the production of sulfur floc and 'snowblower' events due to sulfide oxidizing bacteria is investigated. The effects of sulfur floc on the pososity is shown to be negligible. 'Snowblower' events are shown to be sulfur floc that is stored over long periods of time mixed with a component of sulfur floc being created in a bloom event. Secondly, biogenic sulfate reduction in hydrothermal recharge zones is investigated and the effects on the concentration profiles is considered.M.S.Committee Chair: Lowell, Robert; Committee Member: Newman, Andrew; Committee Member: Peng, Zhigan

Using GPS to Rapidly Detect and Model Earthquakes and Transient Deformation Events /

The rapid modeling and detection of earthquakes and transient deformation is a problem of extreme societal importance for earthquake early warning and rapid hazard response. To date, GPS data is not used in earthquake early warning or rapid source modeling even in Japan or California where the most extensive geophysical networks exist. This dissertation focuses on creating algorithms for automated modeling of earthquakes and transient slip events using GPS data in the western United States and Japan. First, I focus on the creation and use of high-rate GPS and combined seismogeodetic data for applications in earthquake early warning and rapid slip inversions. Leveraging data from earthquakes in Japan and southern California, I demonstrate that an accurate magnitude estimate can be made within seconds using P wave displacement scaling, and that a heterogeneous static slip model can be generated within 2-3 minutes. The preliminary source characterization is sufficiently robust to independently confirm the extent of fault slip used for rapid assessment of strong ground motions and improved tsunami warning in subduction zone environments. Secondly, I investigate the automated detection of transient slow slip events in Cascadia using daily positional estimates from GPS. Proper geodetic characterization of transient deformation is necessary for studies of regional interseismic, coseismic and postseismic tectonics, and miscalculations can affect our understanding of the regional stress field. I utilize the relative strength index (RSI) from financial forecasting to create a complete record of slow slip from continuous GPS stations in the Cascadia subduction zone between 1996 and 2012. I create a complete history of slow slip across the Cascadia subduction zone, fully characterizing the timing, progression, and magnitude of events. Finally, using a combination of continuous and campaign GPS measurements, I characterize the amount of extension, shear and subsidence in the Salton Trough, one of the most complex zone of active faulting and seismicity in California. I show the implications that faulting in the Salton Trough has for the evolution of the Brawley Seismic Zone, and more importantly, the southern San Andreas faul