Bayesian Monte Carlo Algorithm Research Articles

Along‐Strike Variations of Alaska Subduction Zone Structure and Hydration Determined From Amphibious Seismic Data

AbstractWe develop a 3‐D isotropic shear velocity model for the Alaska subduction zone using data from seafloor and land‐based seismographs to investigate along‐strike variations in structure. By applying ambient noise and teleseismic Helmholtz tomography, we derive Rayleigh wave group and phase velocity dispersion maps, then invert them for shear velocity structure using a Bayesian Monte Carlo algorithm. For land‐based stations, we perform a joint inversion of receiver functions and dispersion curves. The forearc crust is relatively thick (35–42 km) and has reduced lower crustal velocities beneath the Kodiak and Semidi segments, which may promote higher seismic coupling. Bristol Bay Basin crust is relatively thin and has a high‐velocity lower layer, suggesting a dense mafic lower crust emplaced by the rifting processes. The incoming plate shows low uppermost mantle velocities, indicating serpentinization. This hydration is more pronounced in the Shumagin segment, with greater velocity reduction extending to 18 ± 3 km depth, compared to the Semidi segment, showing smaller reductions extending to 14 ± 3 km depth. Our estimates of percent serpentinization from VS reduction and VP/VS are larger than those determined using VP reduction in prior studies, likely due to water in cracks affecting VS more than VP. Revised estimates of serpentinization show that more water subducts than previous studies, and that twice as much mantle water is subducted in the Shumagin segment compared to the Semidi segment. Together with estimates from other subduction zones, the results indicate a wide variation in subducted mantle water between different subduction segments.

Upper Mantle Hydration Indicated by Decreased Shear Velocity Near the Southern Mariana Trench From Rayleigh Wave Tomography

AbstractReduction of seismic velocities has been employed to study the hydration of incoming plates and forearc mantle in recent years. However, few constraints have been obtained in the Southern Mariana Trench. We use an ocean bottom seismograph (OBS) deployment to conduct Rayleigh wave tomographic studies to derive the SV‐wave velocity structure near the Southern Mariana Trench. Measured group and phase velocities as a function of period are inverted to determine the SV‐wave velocity using a Bayesian Monte Carlo algorithm. The incoming Pacific Plate is characterized by low velocities (3.6–4.1 km/s) within the upper ∼25 km of the mantle near the trench, indicating extensive mantle hydration of the incoming plate in southern Mariana. The velocity reduction in the forearc mantle is not as large as in central Mariana, most likely indicating a lower forearc serpentinization in this region, which is consistent with the absence of serpentinite mud volcanoes.

Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method

This paper develops a new prediction method for the aging trajectory of lithium-ion batteries with significantly reduced experimental tests. This method is driven by data collected from two types of battery operation modes. The first type is accelerated aging tests that are performed under stress factors, such as overcharging, over-discharging and large current rates, and cover most of the battery lifespan. In the second operation mode, the same kinds of cells are aged at normal speeds to generate a partial aging profile. An accelerated aging model is developed based on the first type of data and is then migrated as a new model to describe the normal-speed aging behavior. Under the framework of Bayesian Monte Carlo algorithms, the new model is parameterized based on the second type of data and is used for prediction of the remaining battery aging trajectory. The proposed prediction method is validated on three types of commercial batteries and also compared with two benchmark algorithms. The sensitivity of results to the number of cycles is investigated for both modes. Illustrative results demonstrate that based on the normal-speed aging data collected in the first 30 cycles, the proposed method can predict the entire aging trajectories (up to 500 cycles) at a root-mean-square error of less than 2.5% for all considered scenarios. When only using the first five-cycle data for model training, such a prediction error is bounded by 5% for aging trajectories of all the tested batteries.

The Crust and Upper Mantle Structure of Central and West Antarctica From Bayesian Inversion of Rayleigh Wave and Receiver Functions

AbstractWe construct a new seismic model for central and West Antarctica by jointly inverting Rayleigh wave phase and group velocities along with P wave receiver functions. Ambient noise tomography exploiting data from more than 200 seismic stations deployed over the past 18 years is used to construct Rayleigh wave phase and group velocity dispersion maps. Comparison between the ambient noise phase velocity maps with those constructed using teleseismic earthquakes confirms the accuracy of both results. These maps, together with P receiver function waveforms, are used to construct a new 3‐D shear velocity (Vs) model for the crust and uppermost mantle using a Bayesian Monte Carlo algorithm. The new 3‐D seismic model shows the dichotomy of the tectonically active West Antarctica (WANT) and the stable and ancient East Antarctica (EANT). In WANT, the model exhibits a slow uppermost mantle along the Transantarctic Mountains (TAMs) front, interpreted as the thermal effect from Cenozoic rifting. Beneath the southern TAMs, the slow uppermost mantle extends horizontally beneath the traditionally recognized EANT, hypothesized to be associated with lithospheric delamination. Thin crust and lithosphere observed along the Amundsen Sea coast and extending into the interior suggest involvement of these areas in Cenozoic rifting. EANT, with its relatively thick and cold crust and lithosphere marked by high Vs, displays a slower Vs anomaly beneath the Gamburtsev Subglacial Mountains in the uppermost mantle, which we hypothesize may be the signature of a compositionally anomalous body, perhaps remnant from a continental collision.

Approximate Bayesian Inference in Semiparametric Copula Models

We describe a simple method for making inference on a functional of a multivariate distribution, based on its copula representation. We make use of an approximate Bayesian Monte Carlo algorithm, where the proposed values of the functional of interest are weighted in terms of their Bayesian exponentially tilted empirical likelihood. This method is particularly useful when the “true” likelihood function associated with the working model is too costly to evaluate or when the working model is only partially specified.

Toward an Algorithm for Estimating Latent Heat Release in Warm Rain Systems

AbstractThis paper outlines an approach for estimating latent heating, surface rainfall rate, and liquid water path in warm rain from downward-viewing W-band radar observations using a Bayesian Monte Carlo algorithm. The algorithm utilizes observed vertical and path-integrated characteristics of precipitating liquid clouds to identify the most appropriate hydrometeor and latent heating structures in a large database of profiles generated using a cloud-resolving model. These characteristics are selected by applying multiple performance metrics to synthetic retrievals. Analysis of the retrievals suggests that a combination of cloud-top, rain-top, and maximum reflectivity heights; vertically integrated reflectivity and attenuation; and a measure of near-surface intensity is sufficient to constrain bulk properties and the vertical structure of warm rain systems. When applied to observations at CloudSat resolution, biases in retrieved liquid water path and surface rainfall rate are small (less than 10%). The algorithm also captures the vertical structure of latent heating, although the magnitudes of integrated heating and cooling exhibit nearly compensating low biases. Random errors are larger owing to the limitations of single-frequency radar observations in constraining drop size distributions. Uncertainties in the altitudes of peak heating and cooling at the pixel scale are typically less than one vertical level, while uncertainties in vertically resolved estimates of heating and cooling rates are on the order of a factor of 2. The utility of the technique is illustrated through application to case studies from airborne radar data from the VAMOS Ocean–Cloud–Atmosphere–Land Study field campaign and satellite observations from CloudSat.

Application of a Bayesian Method to Absorption Spectral-Line Finding in Simulated ASKAP Data

AbstractThe large spectral bandwidth and wide field of view of the Australian SKA Pathfinder radio telescope will open up a completely new parameter space for large extragalactic HI surveys. Here we focus on identifying and parametrising HI absorption lines which occur in the line of sight towards strong radio continuum sources. We have developed a method for simultaneously finding and fitting HI absorption lines in radio data by using multi-nested sampling, a Bayesian Monte Carlo algorithm. The method is tested on a simulated ASKAP data cube, and is shown to be reliable at detecting absorption lines in low signal-to-noise data without the need to smooth or alter the data. Estimation of the local Bayesian evidence statistic provides a quantitative criterion for assigning significance to a detection and selecting between competing analytical line-profile models.