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Abstract Numerical modeling of ice sheet motion and hence projections of global sea level rise require information about the evolving subglacial environment, which unfortunately remains largely unknown due to its difficulty of access. Here we advance such subglacial observations by reporting multi‐year observations of seismic tremor likely associated with glacier sliding at Helheim Glacier. This association is confirmed by correlation analysis between tremor power and multiple environmental forcings on different timescales. Variations of the observed tremor power indicate that different factors affect glacial sliding on different timescales. Effective pressure may control glacial sliding on long (seasonal/annual) timescales, while tidal forcing modulates the sliding rate and tremor power on short (hourly/daily) timescales. Polarization results suggest that the tremor source comes from an upstream subglacial ridge. This observation provides insights on how different factors should be included in ice sheet modeling and how their timescales of variability play an essential role. 

Abstract Imaging of Earth’s interior has led to a large number of successful discoveries of plausible structures and associated geophysical processes. However, due to the limitations of geophysical data, Earth imaging has many trade-offs between the underlying features, and most approaches apply smoothing to reduce the effect of such trade-offs. Unfortunately, this smoothing often results in blurry images that are not clear enough either to infer the geologic processes of interest or to make quantitative inferences about the various geologic properties. Here, we first summarize some of the basic issues that make Earth imaging so difficult and explain how Earth imagers must choose between more open-ended discovery-oriented goals and more specific, scientific-inference-oriented goals. We discuss how the choice of the optimal imaging framework depends crucially on the desired goal, and particularly on whether plausible discovery or inference is the desired outcome. We argue that as Earth imaging has become more mature, sufficiently many plausible structures have been imaged that it is becoming more crucial for Earth imaging to serve the inference goal and would benefit from an inference-oriented imaging framework, despite the additional challenges in posing imaging problems in this manner. Examples of inference-oriented imaging frameworks are provided and contrasted with discovery-oriented frameworks. We discuss how the success of the various frameworks depends critically on the data quality and suggest that a careful balance must be struck between the ambition of the imager and the reality of the data. If Earth imaging is to move beyond presenting qualitatively plausible structures, it should move toward making quantitative estimates of the underlying geologic processes inferred through a self-consistent framework. 

ABSTRACT Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early-career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. It remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade. 

SUMMARY Seismic tomography is a cornerstone of geophysics and has led to a number of important discoveries about the interior of the Earth. However, seismic tomography remains plagued by the large number of unknown parameters in most tomographic applications. This leads to the inverse problem being underdetermined and requiring significant non-geologically motivated smoothing in order to achieve unique answers. Although this solution is acceptable when using tomography as an explorative tool in discovery mode, it presents a significant problem to use of tomography in distinguishing between acceptable geological models or in estimating geologically relevant parameters since typically none of the geological models considered are fit by the tomographic results, even when uncertainties are accounted for. To address this challenge, when seismic tomography is to be used for geological model selection or parameter estimation purposes, we advocate that the tomography can be explicitly parametrized in terms of the geological models being tested instead of using more mathematically convenient formulations like voxels, splines or spherical harmonics. Our proposition has a number of technical difficulties associated with it, with some of the most important ones being the move from a linear to a non-linear inverse problem, the need to choose a geological parametrization that fits each specific problem and is commensurate with the expected data quality and structure, and the need to use a supporting framework to identify which model is preferred by the tomographic data. In this contribution, we introduce geological parametrization of tomography with a few simple synthetic examples applied to imaging sedimentary basins and subduction zones, and one real-world example of inferring basin and crustal properties across the continental United States. We explain the challenges in moving towards more realistic examples, and discuss the main technical difficulties and how they may be overcome. Although it may take a number of years for the scientific program suggested here to reach maturity, it is necessary to take steps in this direction if seismic tomography is to develop from a tool for discovering plausible structures to one in which distinct scientific inferences can be made regarding the presence or absence of structures and their physical characteristics. 

ABSTRACT Meltwater is important to understanding glacier health and dynamics. Since melt measurements are uncommon, ice ablation estimates are often based on models including the positive degree day (PDD) model. The PDD estimate is popular since it only requires air temperature as input, but suffers from the lack of physical motivation of an energy-balance model. We present a physics-based alternative to the PDD model that still only takes air/surface temperature as input. The model resembles the PDD model except accounting for time lags in ablation when cold ice needs to be warmed. The model is expressed as a differential equation with a single extra parameter related to the efficiency of heating a near-surface layer of ice. With zero thickness, the model reduces to the PDD model, providing a physical basis for the PDD model. Applying the model to data from Greenland, it improves modestly upon the PDD model, with the main improvement being better prediction of early season melting. This new model is a useful compromise, with some of the physics of more realistic models and the simplicity of a PDD model. The model should improve estimates of meltwater production and help constrain PDD parameters when empirical calibration is challenging. 

Abstract The proliferation of dense arrays promises to improve our ability to image geological structures at the scales necessary for accurate assessment of seismic hazard. However, combining the resulting local high‐resolution tomography with existing regional models presents an ongoing challenge. We developed a framework based on the level‐set method that infers where local data provide meaningful constraints beyond those found in regional models ‐ for example the Community Velocity Models (CVMs) of southern California. This technique defines a volume within which updates are made to a reference CVM, with the boundary of the volume being part of the inversion rather than explicitly defined. By penalizing the complexity of the boundary, a minimal update that sufficiently explains the data is achieved. To test this framework, we use data from the Community Seismic Network, a dense permanent urban deployment. We inverted Love wave dispersion and amplification data, from the Mw 6.4 and 7.1 2019 Ridgecrest earthquakes. We invert for an update to CVM‐S4.26 using the Tikhonov Ensemble Sampling scheme, a highly efficient derivative‐free approximate Bayesian method. We find the data are best explained by a deepening of the Los Angeles Basin with its deepest part south of downtown Los Angeles, along with a steeper northeastern basin wall. This result offers new progress toward the parsimonious incorporation of detailed local basin models within regional reference models utilizing an objective framework and highlights the importance of accurate basin models when accounting for the amplification of surface waves in the high‐rise building response band. 

Abstract Understanding the dynamic response of glaciers to climate change is vital for assessing water resources and hazards, and subglacial hydrology is a key player in glacier systems. Traditional observations of subglacial hydrology are spatially and temporally limited, but recent seismic deployments on and around glaciers show the potential for comprehensive observation of glacial hydrologic systems. We present results from a high‐density seismic deployment spanning the surface of Lemon Creek Glacier, Alaska. Our study coincided with a marginal lake drainage event, which served as a natural experiment for seismic detection of changes in subglacial hydrology. We observed glaciohydraulic tremor across the surface of the glacier that was generated by the subglacial hydrologic system. During the lake drainage, the relative changes in seismic tremor power and water flux are consistent with pressurization of the subglacial system of only the upper part of the glacier. This event was not accompanied by a significant increase in glacier velocity; either some threshold necessary for rapid basal motion was not attained, or, plausibly, the geometry of Lemon Creek Glacier inhibited speedup. This pressurization event would have likely gone undetected without seismic observations, demonstrating the power of cryoseismology in testing assumptions about and mapping the spatial extent of subglacial pressurization.