The Rock Valley fault zone (RVFZ), an intraplate strike-slip fault zone in the southern Nevada National Security Site (NNSS), hosted a series of very shallow (<3 km) earthquakes in 1993. The RVFZ may also have hydrological significance within the NNSS, potentially playing a role in regional groundwater flow, but there is a lack of local hydrological data. In the Spring of 2021, we collected active-source accelerated weight drop seismic data over part of the RVFZ to better characterize the shallow subsurface. We manually picked ∼17,000 P-wave travel times and over 14,000 S-wave travel times, which were inverted for P-wave velocity (VP), S-wave velocity (VS), and VP = VS ratio in a 3D joint tomographic inversion scheme. Seismic velocities are imaged as deep as ∼700 m in areas and generally align with geologic and structural expectations. VP and VS are relatively reduced near mapped and inferred faults, with the most prominent lower VP and VS zone around the densest collection of faults. We image VP = VS ratios ranging from ∼1.5 to ∼2.4, the extremes of which occur at a depth of ∼100 m and are juxtaposed across a fault. One possible interpretation of the imaged seismic velocities is enhanced fault damage near the densest collection of faults with relatively higher porosity and/or crack density at ∼100 m depth, with patches of semiperched groundwater present in the sedimentary rock in higher VP = VS areas and drier rock in lower VP = VS areas. A relatively higher VP = VS area beneath the densest faults persists at depth, which suggests percolation of groundwater via the fault damage zone to the regionally connected lower carbonate aquifer. Potentially, the presence and movement of groundwater may have played a role in the 1993 earthquake aftershocks.
Accurate event locations are important for many endeavors in seismology, and understanding the factors that contribute to uncertainties in those locations is complex. In this article, we present a case study that takes an in-depth look at the accuracy and precision possible for locating nine shallow earthquakes in the Rock Valley fault zone in southern Nevada. These events are targeted by the Rock Valley Direct Comparison phase of the Source Physics Experiment, as candidates for the colocation of a chemical explosion with an earthquake hypocenter to directly compare earthquake and explosion sources. For this comparison, it is necessary to determine earthquake hypocenters as accurately as possible so that different source types have nearly identical locations. Our investigations include uncertainty analysis from different sets of phase arrivals, stations, velocity models, and location algorithms. For a common set of phase arrivals and stations, we find that epicentral locations from different combinations of velocity models and algorithms are within 600 m of one another in most cases. Event depths exhibit greater uncertainties, but focusing on the S-P times at the nearest station allows for estimates within approximately 500 m.
In this brief report we document algorithmic choices and updates to our code related to the earthquake relocation portion of our tomographic imaging algorithm. We show results of these improvements by relocating over 40,000 events located within 20-30 km of the Rock Valley Direct Comparison (RV/DC) site using both absolute and differential arrival times within the context of two different 3-D Earth models. Accurate hypocentral locations and Earth models are important to the ultimate goals of the RV/DC program, which will co-locate a chemical explosion with a shallow earthquake within Rock Valley, southern Nevada, to investigate differences between the source types and improve our analysis algorithms for both types (Snelson et al., 2022). Our improvements to our relocation algorithms comprise just one step toward achieving these goals
In this report, we document the process related to developing a regional geologic model of a 605 x 1334 km area centered around Utah and encompassing surrounding states. This model is developed to test the effect that composition of a model has on the generation of synthetic data with the intent of using this information to improve upon full waveform moment tensor inversions. We compare observed data from three seismic events and five stations to the synthetic data generated by a preliminary model derived from a geologic framework model (GFM) developed by the USGS. The synthetic data and observed data comparisons indicate that our preliminary model performs well at smaller offset distances in the northern and central sections of the model. However, the southern stations consistently display synthetic data P- and S-wave arrival times that do not match the observed data arrival times, indicating that the velocity structure of the southern part of the model especially is inaccurate.
Work accomplished: Collected and compared historic data for the 1993 Rock Valley earthquake sequence; Compared preliminary and prior location work from different location algorithms, phase pick sets, station constellations, and velocity models; Selected a common set of stations that could be used across all location methods for consistency; Reviewed 8 different sets of phase picks and converged on a single, reviewed set of picks for all common stations; Evaluated four pre-existing regional velocity models and incorporated new and preliminary results for five new velocity models that provide information on the very shallow (< 2km) structure near station RTPP; Compared location results from different methods while using the common sets of picks, stations, and velocity models
The Source Physics Experiments (SPE) were designed to improve our physics-based understanding of explosion sources for the purposes of nuclear test monitoring. Phase I consisted of 6 chemical explosions in the Climax Stock Granite of the Nevada National Security Site (NNSS), while Phase II consisted of 4 explosions in a contrasting dry alluvium geology (DAG) in Yucca Flat, providing essential data in various media and emplacement conditions to further modeling efforts. For Phase III, the Rock Valley Direct Comparison (RVDC) seeks to directly compare earthquake and explosion source types. An unusually shallow series of events in 1993 along the Rock Valley Fault Zone in the southeastern portion of the NNSS has been targeted for this direct comparison. Depth ranges for the events, previously estimated to be less than 3 km, is achievable by modern drilling techniques and accessibility to the epicentral locations would require minimal improvements to the infrastructure. The events providing this unique opportunity for direct comparison are the focus of this report.
Marine hydrokinetic devices, such as wave energy converters (WECs), can unlock untapped energy from the ocean's currents and waves. Acoustic impact assessments are required to ensure that the noise these devices generate will not negatively impact marine life, and accurate modeling of noise provides an a priori means to viably perform this assessment. We present a case study of the PacWave South site, a WEC testing site off the coast of Newport, Oregon, demonstrating the use of ParAcousti, an open-source hydroacoustic propagator tool, to model noise from an array of 28 WECs in a 3-dimensional (3-D) realistic marine environment. Sound pressure levels are computed from the modeled 3-D grid of pressure over time, which we use to predict marine mammal acoustic impact metrics (AIMs). We combine two AIMs, signal to noise ratio and sensation level, into a new metric, the effective signal level (ESL), which is a function of propagated sound, background noise levels, and hearing thresholds for marine species and is evaluated across 1/3 octave frequency intervals. The ESL model can be used to predict and quantify the potential impact of an anthropogenic signal on the health and behavior of a marine mammal species throughout the 3-D simulation area.
Characterizing explosion sources and differentiating between earthquake and underground explosions using distributed seismic networks becomes non-trivial when explosions are detonated in cavities or heterogeneous ground material. Moreover, there is little understanding of how changes in subsurface physical properties affect the far-field waveforms we record and use to infer information about the source. Simulations of underground explosions and the resultant ground motions can be a powerful tool to systematically explore how different subsurface properties affect far-field waveform features, but there are added variables that arise from how we choose to model the explosions that can confound interpretation. To assess how both subsurface properties and algorithmic choices affect the seismic wavefield and the estimated source functions, we ran a series of 2-D axisymmetric non-linear numerical explosion experiments and wave propagation simulations that explore a wide array of parameters. We then inverted the synthetic far-field waveform data using a linear inversion scheme to estimate source–time functions (STFs) for each simulation case. We applied principal component analysis (PCA), an unsupervised machine learning method, to both the far-field waveforms and STFs to identify the most important factors that control variance in the waveform data and differences between cases. For the far-field waveforms, the largest variance occurs in the shallower radial receiver channels in the 0–50 Hz frequency band. For the STFs, both peak amplitude and rise times across different frequencies contribute to the variance. We find that the ground equation of state (i.e. lithology and rheology) and the explosion emplacement conditions (i.e. tamped versus cavity) have the greatest effect on the variance of the far-field waveforms and STFs, with the ground yield strength and fracture pressure being secondary factors. Differences in the PCA results between the far-field waveforms and STFs could possibly be due to near-field non-linearities of the source that are not accounted for in the estimation of STFs and could be associated with yield strength, fracture pressure, cavity radius and cavity shape parameters. Other algorithmic parameters are found to be less important and cause less variance in both the far-field waveforms and STFs, meaning algorithmic choices in how we model explosions are less important, which is encouraging for the further use of explosion simulations to study how physical Earth properties affect seismic waveform features and estimated STFs.
Gaining a proper understanding of how Earth structure and other near-source properties affect estimates of explosion yield is important to the nonproliferation mission. The yields of explosion sources are often based on seismic moment or waveform amplitudes. Quantifying how the seismic waveforms or estimates of the source characteristics derived from those waveforms are influenced by natural or man-made structures within the near-source region, where the wavefield behaves nonlinearly, is required to understand the full range of uncertainty in those yield estimates. We simulate tamped chemical explosions using a nonlinear, shock physics code and couple the ground motions beyond the elastic radius to a linear elastic, full waveform seismic simulation algorithm through 3D media. In order to isolate the effects of simple small-scale 3D structures on the seismic wavefield and linear seismic source estimates, we embed spheres and cylinders close to the fully- tamped source location within an otherwise homogenous half-space. The 3 m diameters spheres, given their small size compared to the predominate wavelengths investigated, not surprisingly are virtually invisible with only negligible perturbations to the far-field waveforms and resultant seismic source time functions. Similarly, the 11 m diameter basalt sphere has a larger, but still relatively minor impact on the wavefield. However, the 11 m diameter air-filled sphere has the largest impact on both waveforms and the estimated seismic moment of any of the investigated cases with a reduction of ~25% compared to the tamped moment. This significant reduction is likely due in large part to the cavity collapsing from the shock instead of being solely due to diffraction effects . Although the cylinders have the same diameters as the 3 m spheres, their length of interaction with the wavefield produces noticeable changes to the seismic waveforms and estimated source terms with reductions in the peak seismic moment on the order of 10%. Both the cylinders and 11 m diameter spheres generate strong shear waves that appear to emanate from body force sources.
We used the CTH shock physics code to simulate the explosion of an 18-t chemical explosive at a depth of 250 m. We used the CTH in the two-dimensional axisymmetric (cylindrical) geometry (2DC) and most simulations included fully tamped explosions in wet tuff. Our study focused on parametric studies of three of the traditional strength models available in CTH, namely, geologic-yield, elastic perfectly-plastic von Mises, and Johnson-Cook strength (flow stress) models. We processed CTH results through a code that generates Reduced Displacement Potential (RDP) histories for each simulation. Since RDP is the solution of the linear wave equation in spherical coordinates, it is mainly valid at far-enough distance from the explosion the elastic radius. Among various parameters examined, we found the yield strength to have the greatest effect on the resulting RDP, where the peak RDP reduces almost linearly in log-log space as the yield strength increases. Moreover, an underground chemical explosion results in a cavity whose final diameter is inversely proportional to the material yield strength, i.e., as the material's yield strength increases the resulting final cavity radius decreases. Additionally, we found the choice of explosive material (COMP-C4 versus COMP-B) has minor effects on the peak RDP, where denser COMP-C4 shows higher peak RDP than the less dense COMP-B by a factor of ~1.1. In addition to wet tuff, we studied explosions in dry tuff, salt, and basalt, for a single strength model and yield strength value. We found wet tuff has the highest peak RDP value, followed by dry tuff, salt, and basalt. 2DC simulations of explosions in 11 m radius spherical, hemispherical, and cylindrical cavities showed the RDP signals have much lower magnitude than tamped explosions, where the cavity explosions mimicked nearly decoupled explosions.
Seismic source modeling allows researchers both to simulate how a source that induces seismic waves interacts with the Earth to produce observed seismograms and, inversely, to infer what the time histories, sizes, and force distributions were for a seismic source given observed seismograms. In this report, we discuss improvements made in FY21 to our software as applies to both the forward and inverse seismic source modeling problems. For the forward portion of the problem, we have added the ability to use full 3-D nonlinear simulations by implementing 3-D time varying boundary conditions within Sandia’s linear seismic code Parelasti. Secondly, on the inverse source modeling side, we have developed software that allows us to invert seismic gradiometer-derived observations in conjunction with standard translational motion seismic data to infer properties of the source that may improve characterization in certain circumstances. First, we describe the basic theory behind each software enhancement and then demonstrate the software in action with some simple examples.
Most earth materials are anisotropic with regard to seismic wave-speeds, especially materials such as shales, or where oriented fractures are present. However, the base assumption for many numerical simulations is to treat earth materials as isotropic media. This is done for simplicity, the apparent weakness of anisotropy in the far field, and the lack of well-characterized anisotropic material properties for input into numerical simulations. One approach for addressing the higher complexity of actual geologic regions is to model the material as an orthorhombic medium. We have developed an explicit time-domain, finite-difference (FD) algorithm for simulating three-dimensional (3D) elastic wave propagation in a heterogeneous orthorhombic medium. The objective of this research is to investigate the errors and biases that result from modeling a non-isotropic medium as an isotropic medium. This is done by computing “observed data” by using synthetic, anisotropic simulations with the assumption of an orthorhombic, anisotropic earth model. Green’s functions for an assumed isotropic earth model are computed and then used an inversion designed to estimate moment tensors with the “observed” data. One specific area of interest is how shear waves, which are introduced in an anisotropic model even for an isotropic explosion, affect the characterization of seismic sources when isotropic earth assumptions are made. This work is done in support of the modeling component of the Source Physics Experiment (SPE), a series of underground chemical explosions at the Nevada National Security Site (NNSS).
An active source experiment using an accelerated weight drop was conducted in Rock Valley, Nevada National Security Site, during the spring of 2021 in order to characterize the shallow seismic structure of the region. P-wave first arrival travel times picked from this experiment were used to construct a preliminary 3-D compressional wave speed model over an area that is roughly 4 km wide east-west and 8 km north-south to a depth of about 500-600 m below the surface, but with primary data concentration along the transects of the experimental lines. The preliminary model shows good correlation with basic geology and surface features, but geological interpretation is not the focus of this report. We describe the methods used in the tomographic inversion of the data and show results from this preliminary P-wave model.
This report summarizes work completed under the Laboratory Directed Research and Development (LDRD) project "Uncertainty Quantification of Geophysical Inversion Using Stochastic Differential Equations." Geophysical inversions often require computationally expensive algorithms to find even one solution, let alone propagating uncertainties through to the solution domain. The primary purpose of this project was to find more computationally efficient means to approximate solution uncertainty in geophysical inversions. We found multiple computationally efficient methods of propagating Earth model uncertainty into uncertainties in solutions of full waveform seismic moment tensor inversions. However, the optimum method of approximating the uncertainty in these seismic source solutions was to use the Karhunen-Love theorem with data misfit residuals. This method was orders of magnitude more computationally efficient than traditional Monte Carlo methods and yielded estimates of uncertainty that closely approximated those of Monte Carlo. We will summarize the various methods we evaluated for estimating uncertainty in seismic source inversions as well as work toward this goal in the realm of 3-D seismic tomographic inversion uncertainty.
Rock Valley, in the southern end of the Nevada National Security Site, hosts a fault system that was responsible for a shallow (< 3 km below surface ) magnitude 3.7 earthquake in May 1993. In order to better understand this system, seismic properties of the shallow subsurface need to be better constrained. In April and May of 2021, accelerated weight drop (AWD) active-source seismic data were recorded in order to measure P- and S-wave travel-times for the area. This report describes the processing and phase picking of the recorded seismic waveforms. In total, we picked 7,982 P-wave arrivals at offsets up to ~2500 m, and 4,369 S-wave arrivals at offsets up to ~2200 m. These travel-time picks can be inverted for shallow P-wave and S-wave velocity structure in future studies.
We present preliminary work on propagating model uncertainty into the estimation of the time domain source time functions of the seismic source. Our method is based on an estimated model covariance function, which we estimate from the data. The model covariance function is then used to construct a suite of surrogate Greens functions which we use in a Monte Carlo type inversion scheme. The result is a probability density function of the six independent source time functions, each of which corresponds to an individual component of the seismic moment tensor. We compare the results of our method with those obtained using a computationally expensive finite difference Monte Carlo method and find that our new method produces results that are deficient in low frequencies. The advantage of our new method, which we term the Karhunen-Loeve Monte Carlo (KLMC) method, is that is several orders of magnitude faster than our current method, which uses a finite difference scheme to produce the suite of forward models.
Underground explosions nonlinearly deform the surrounding earth material and can interact with the free surface to produce spall. However, at typical seismological observation distances the seismic wavefield can be accurately modeled using linear approximations. Although nonlinear algorithms can accurately simulate very near field ground motions, they are computationally expensive and potentially unnecessary for far field wave simulations. Conversely, linearized seismic wave propagation codes are orders of magnitude faster computationally and can accurately simulate the wavefield out to typical observational distances. Thus, devising a means of approximating a nonlinear source in terms of a linear equivalent source would be advantageous both for scenario modeling and for interpretation of seismic source models that are based on linear, far-field approximations. This allows fast linear seismic modeling that still incorporates many features of the nonlinear source mechanics built into the simulation results so that one can have many of the advantages of both types of simulations without the computational cost of the nonlinear computation. In this report we first show the computational advantage of using linear equivalent models, and then discuss how the near-source (within the nonlinear wavefield regime) environment affects linear source equivalents and how well we can fit seismic wavefields derived from nonlinear sources.
We present a computationally efficient method to approximate the probability distribution of seismic Green's functions given the uncertainty of an Earth model. The method is based on the Karhunen-Loève (KL) theorem and an approximation of the Green's function (or seismogram) covariance. Using Monte Carlo (MC) simulations as a control case, we demonstrate that our KL-based method can accurately reproduce a probability distribution of seismograms that results from an uncertain Earth model for a MC-derived seismogram covariance. We then describe a method to estimate the covariance of the seismograms resulting from those Earth models that is not based on MC simulations. We use the estimated Green's function covariance in conjunction with our KL-based method to produce a Green's function probability distribution, and compare that distribution to a Green's function probability distribution produced using a MC finite difference method. We find that the Green's function probability distribution approximated using our KL-based method generally mimics that produced using the MC simulations, especially for direct-arriving body waves. However the accuracy of the KL-based method generally decreases for later times in the simulated Green's function distribution.
The complex postdetonation geologic structures that form after an underground nuclear explosion are hard to constrain because increased heterogeneity around the damage zone affects seismic waves that propagate through the explosion site. Generally, a vertical rub-ble-filled structure known as a chimney is formed after an underground nuclear explosion that is composed of debris that falls into the subsurface cavity generated by the explosion. Compared with chimneys that collapse fully, leaving a surface crater, partially collapsed chimneys can have remnant subsurface cavities left in place above collapsed rubble. The 1964 nuclear test HADDOCK, conducted at the Nevada test site (now the Nevada National Security Site), formed a partially collapsed chimney with no surface crater. Understanding the subsurface structure of these features has significant national security applications, such as aiding the study of suspected underground nuclear explosions under a treaty verification. In this study, we investigated the subsurface architecture of the HADDOCK legacy nuclear test using hybrid 2D–3D active source seismic reflection and refraction data. The seismic data were acquired using 275 survey shots from the Seismic Hammer (a 13,000 kg weight drop) and 65 survey shots from a smaller accelerated weight drop, both recorded by ∼ 1000 three-component 5 Hz geophones. First-arrival, P-wave tomographic modeling shows a low-velocity anomaly at ∼ 200 m depth, likely an air-filled cavity caused by partial collapse of the rock column into the temporary post-detonation cavity. A high-velocity anomaly between 20 and 60 m depth represents spall-related compaction of the shallow alluvium. Hints of low velocities are also present near the burial depth ( ∼ 364 m). The reflection seismic data show a prominent subhorizontal reflector at ∼ 300 m depth, a short-curved reflector at ∼ 200 m, and a high-amplitude reflector at ∼ 50 m depth. Comparisons of the reflection sections to synthetic data and borehole stratigraphy suggest that these features correspond to the alluvium–tuff contact, the partial collapse cavity, and the spalled layer, respectively.
We use Monte Carlo simulations to explore the effects of earth model uncertainty on the estimation of the seismic source time functions that correspond to the six independent components of the point source seismic moment tensor. Specifically, we invert synthetic data using Green's functions estimated from a suite of earth models that contain stochastic density and seismic wave-speed heterogeneities. We find that the primary effect of earth model uncertainty on the data is that the amplitude of the first-arriving seismic energy is reduced, and that this amplitude reduction is proportional to the magnitude of the stochastic heterogeneities. Also, we find that the amplitude of the estimated seismic source functions can be under-or overestimated, depending on the stochastic earth model used to create the data. This effect is totally unpredictable, meaning that uncertainty in the earth model can lead to unpredictable biases in the amplitude of the estimated seismic source functions.
This report presents the infrasound data recorded as part of the Source Physics Experiment - Phase 2, Dry Alluvium Geology. This experiment, also known colloquially as DAG, consisted of four underground chemical explosions at the Nevada National Security Site. We focus our analysis on only the fourth explosion (DAG-4) as we determined that this was the only event that produced clear source-generated infrasound energy as recorded by the DAG sensors. We analyze the data using two inversion methods. The first method is designed to estimate the point-source seismoacoustic source time functions, and the second inversion method is designed to estimate the first-order characteristics (e.g. horizontal dimensions and maximum amplitude) of the actual spall surface. For both analysis methods, we are able to fit the data reasonably well, with various assumptions of the source model. The estimated seismoacoustic source appears to be a combination of a buried, isotropic explosion with a maximum amplitude of ~2 x 109 Nm and a vertically oriented force, applied to the Earth's surface with a maximum amplitude of 4 x 107 N. We use the vertically oriented force to simulate surface spall. The estimated spall surface has an approximate radius of ~40 m with a maximum acceleration magnitude in the range of 0.8 to 1.5 m/s/s. These estimates are approximately similar to the measured surface acceleration at the site.
The interface between the Earth and the atmosphere forms a strong contrast in material properties. As such, numerical issues can arise when simulating an elastic wavefield across such a boundary when using a numerical simulation scheme. This is exacerbated when two different simulation codes are coupled straddling that interface. In this report we document how we implement the coupling of CTH, a nonlinear shock physics code, to a linearized elastic/acoustic wave propagation algorithm, axiElasti, across the air-earth interface. We first qualitatively verify that this stable coupling between the two algorithms produces expected results with no visible effects of the coupling interface. We then verify the coupling interface quantitatively by checking consistency with results from previous work and with coupled acoustic-elastic seismo-acoustic source inversions in three earth materials.
Explosions detonated in geologic media damage it in various ways via processes that include vaporization, fracturing, crushing of interstitial pores, etc. Seismic waves interact with the altered media in ways that could be important to the discrimination, characterization, and location of the explosions. As part of the Source Physics Experiment, we acquired multiple pre- and post-explosion near-field seismic datasets and analyzed changes to seismic P-wave velocity. Our results indicate that the first explosion detonated in an intact media can cause fracturing and, consequently, a decrease in P-wave velocity. After the first explosion, subsequent detonations in the pre-damaged media have limited discernible effects. We hypothesize this is due to the stress-relief provided by a now pre-existing network of fractures into which gasses produced by the explosion migrate. We also see an overall increase in velocity of the damaged region over time, either due to a slow healing process or closing of the fractures by subsequent explosions.
As a part of the series of Source Physics Experiments (SPE) conducted on the Nevada National Security Site in southern Nevada, we have developed a local-to-regional scale seismic velocity model of the site and surrounding area. Accurate earth models are critical for modeling sources like the SPE to investigate the role of earth structure on the propagation and scattering of seismic waves. We combine seismic body waves, surface waves, and gravity data in a joint inversion procedure to solve for the optimal 3D seismic compres-sional and shear-wave velocity structures and earthquake locations subject to model smoothness constraints. Earthquakes, which are relocated as part of the inversion, provide P-and S-body-wave absolute and differential travel times. Active source experiments in the region augment this dataset with P-body-wave absolute times and surface-wave dispersion data. Dense ground-based gravity observations and surface-wave dispersion derived from ambient noise in the region fill in many areas where body-wave data are sparse. In general, the top 1–2 km of the surface is relatively poorly sampled by the body waves alone. However, the addition of gravity and surface waves to the body-wave data-set greatly enhances structural resolvability in the near surface. We discuss the method-ology we developed for simultaneous inversion of these disparate data types and briefly describe results of the inversion in the context of previous work in the region.
We invert infrasound signals for an equivalent seismoacoustic source function using different atmospheric models to produce the necessary Green’s functions. The infrasound signals were produced by a series of underground chemical explosions as part of the Source Physics Experiment (SPE). In a previous study, we inverted the infrasound data using so-called predictive atmospheric models, which were based on historic, regional-scaled, publicly available weather observations interpolated onto a 3D grid. For the work presented here, we invert the same infrasound data, but using atmospheric models based on weather data collected in a time window that includes the approximate time of the explosion experiments, which we term postdictive models. We build two versions of the postdictive models for each SPE event: one that is based solely on the regional scaled observations, and one that is based on both regional scaled observations combined with on-site observations obtained by a weather sonde released at the time of the SPE. We then invert the observed data set three times, once for each atmospheric model type. We find that the estimated seismoacoustic source functions are relatively similar in waveform shape regardless of which atmospheric model that we used to construct the Green’s functions. However, we find that the amplitude of the estimated source functions is systematically dependent on the atmospheric model type: using the predictive atmospheric models to invert the data generally yields estimated source functions that are larger in amplitude than those estimated using the postdictive models.