Supercritical CO2 (ScCO2) invades oilwell cement under geological CO2 sequestration conditions. With the penetration of ScCO2, cement structure prone to damage when the coupled effects of capillarity and carbonation were found. Microstructural evolution of oilwell cement samples was investigated by the CT scanning and the quantitative image-based analysis and show that ScCO2 with the high humid condition would penetrate much deeper than the dry ScCO2 because of the capillarity effects. Due to the deep saline condition in the sequestration formation, the penetration of ScCO2 was retarded by the salt deposition, comparing with the ultrapure water (UP water) conditions. For further assessment of this coupled mechanism, the permeability property and contact angle changes were proposed to analyse the interface region between ScCO2, saline/UP water and oilwell cement.

Roots are the interface between the plant and the soil and play a central role in multiple ecosystem processes. With intensification of agricultural practices, rhizosphere processes are being disrupted and are causing degradation of the physical, chemical, and biotic properties of soil. Improvement of ecosystem service performance is rarely considered as a breeding trait due to the complexities and challenges of belowground evaluation. Advancements in root phenotyping and genetic tools are critical in accelerating ecosystem service improvement in cover crops. Here I will present root phenotyping approaches for assessing ecosystem service in a prospective cash cover crop; pennycress (Thlaspi arvense L.). In development is a large format mesocosm system that will allow 3D root system architecture analysis of multiple plants. Using this system, we will be assessing how variation in pennycress root system architecture can affect ecosystem service and abiotic stress tolerance with the plant to scale from single plant to canopy level traits.

Jupiter possesses the strongest magnetic field of all planets in the solar system. Unique information about the dynamo process acting at Jupiter can be inferred by modelling and interpreting its field. Using the fluxgate magnetometer measurements acquired during the four years of the Juno mission, we derive an internal and secular magnetic field model in spherical harmonics. The static part is derived to degree 16 with a secular time variation to degree 8. We use properties of the power spectrum of the static field to infer the upper boundary of the dynamo convective region at 0.830±0.022 Jupiter radius. This confirms the role of the transition layer in the field generation inside Jupiter. The secular variation timescales indicate that advective effects dominate the dynamo and the secular variation structures estimated at the dynamo radius suggest that the complex flow involves non-zonal features.

We characterized the texture, composition, and seismic properties of the lithospheric mantle atop the Hawaiian plume by petrostructural analysis of 48 spinel-peridotite xenoliths from four localities in three Hawaiian islands. Coarse-porphyroclastic peridotites with variable degrees of recrystallization, recorded by growth of strain-free neoblasts onto the deformed microstructure, predominate. Full evolution of this process produced equigranular microstructures. Some peridotites have coarse-granular microstructures. Coarse-granular and coarse-porphyroclastic peridotites have strong orthorhombic or axial-[100] olivine crystal-preferred orientations (CPO). Recrystallization produced moderate dispersion and, locally, changed the olivine CPO towards axial-[010]. Enrichment in pyroxenes relative to model melting trends and pyroxenes with interstitial shapes and CPO uncorrelated with the olivine CPO suggest refertilization by reactive melt percolation. The unusual spatial distribution of the recrystallized fraction, Ti-enrichment, and REE-fractionation in recrystallized, equigranular, and coarse-granular peridotites support that these microstructures are produced by static recrystallization triggered by melt percolation. However, there is no simple relation between microstructure and chemical or modal composition. This, together with marked variations in mineral chemistry among samples, implies multiple spatially heterogeneous melt-rock reaction events. We interpret the coarse-porphyroclastic microstructures and CPO as representative of the original oceanic lithosphere fabric. Annealing changed the microstructure to coarse-granular, but did not modify significantly the olivine CPO. Recrystallization produced moderate dispersion of the CPO. “Normal” oceanic lithosphere seismic anisotropy patterns are therefore preserved. Yet Fe-enrichment, refertilization, and limited heating of the base of the lithosphere may reduce seismic velocities by up to 2%, partially explaining negative velocity anomalies imaged at lithospheric depths beneath Hawaii.

The goal of seismic inversion is to obtain subsurface properties from surface measurements. Seismic images have proven valuable, even crucial, for a variety of applications, including subsurface energy exploration, earthquake early warning, carbon capture and sequestration, estimating pathways of sub-surface contaminant transport, etc. These subsurface properties (such as wave speed, density, and elastic velocities) influence the transmission of seismic waves through the subsurface media, and well-understood physics models (so-called “forward models”) can be used to predict what surface measurements would be made, for any given subsurface configuration. Seismic inversion is the inverse problem: given actual surface measurements, infer what subsurface configuration would give rise to those measurements. Like most inverse problems, seismic imaging is ill-posed, meaning many different subsurface configurations can give rise to the same surface measurements. Iterative optimization algorithms for the inverse problem are typically very computationally expensive because they require many evaluations of the forward model, which is itself computationally expensive. A further challenge is the different sensitivity of subsurface properties to the seismic data; density for example is more difficult to accurately infer than is P-wave velocity. But recent advances in algorithms and computing provide an opportunity for remarkable progress in seismic inversion, and efficient solutions to previously infeasible problems have been obtained using data-driven approaches (such as the deep learning methods that were developed primarily for problems in computer vision). The excellent performance of learning-based methods arises from its ability to exploit large amounts of high-quality training data, without the need for hand-designed features. Unlike computer vision, however, seismic inversion is not a data-rich domain. There is a relatively small amount of field data in existence due to the high cost of acquisition, and as a result of its commercial value, a very limited amount is publicly available. To alleviate the data scarcity issue and improve model generalization, there has been growing interest in combining physics knowledge with machine learning for solving seismic inversion problems. This review will survey methods for incorporating physics knowledge with machine learning (primarily deep neural networks) to solve computational seismic inversion problems. We will provide a structured framework of the existing research in the seismic inversion community, and will identify technical challenges, insights, and trends.

On June 7th, 2021 the Juno spacecraft visited Ganymede and provided the first in situ observations since Galileo’s last flyby in 2000. The measurements obtained along a one-dimensional trajectory can be brought into global context with the help of three-dimensional magnetospheric models. Here we apply the magnetohydrodynamic model of Duling et al. (2014) to conditions during the Juno flyby. In addition to the global distribution of plasma variables we provide mapping of Juno’s position along magnetic field lines, Juno’s distance from closed field lines and detailed information about the magnetic field’s topology. We find that Juno did not enter the closed field line region and that the boundary between open and closed field lines on the surface matches the poleward edges of the observed auroral ovals. To estimate the sensitivity of the model results, we carry out a parameter study with different upstream plasma conditions and other model parameters.

The thickness-weighted average (TWA) framework, which treats the residual-mean flow as the prognostic variable, provides a clear theoretical formulation of the eddy feedback onto the residual-mean flow. The averaging operator involved in the TWA framework, although in theory being an ensemble mean, in practice has often been approximated by a temporal mean. Here, we analyze an ensemble of North Atlantic simulations at mesoscale-permitting resolution (1/12$^\circ$). We therefore recognize means and eddies in terms of ensemble means and fluctuations about those means. The ensemble dimension being orthogonal to the temporal and spatial dimensions negates the necessity for an arbitrary temporal or spatial scale in defining the eddies. Eddy-mean flow feedbacks are encapsulated in the Eliassen-Palm (E-P) flux tensor and its convergence indicates that eddy momentum fluxes dominate in the separated Gulf Stream. The eddies contribute to the zonal meandering of the Gulf Stream and a northward migration of it in the meridional direction. Downstream of the separated Gulf Stream in the North Atlantic Current region, the interfacial form stress convergence becomes leading order in the E-P flux convergence.

The cause of Heinrich events and their relationship with Dansgaard-Oeschger (DO) events are not fully understood. Previous modeling studies have argued that Heinrich events result from either internal oscillations generated within ice sheets or ocean warming occurring during DO events. In this study, we present a coupled model of ice stream and ocean dynamics to evaluate the behavior of the coupled system with few degrees of freedom and minimal parameterizations. Both components of the model may oscillate independently, with stagnant versus active phases for the ice stream model and strong versus weak Atlantic Meridional Overturning Circulation (AMOC) phases for the ocean model. The ice sheet and ocean interact through submarine melt at the ice stream grounding line and freshwater flux into the ocean from ice sheet discharge. We show that these two oscillators have a strong tendency to synchronize, even when their interaction is weak, due to the amplification of small perturbations typical in nonlinear oscillators. In syn- chronized regimes with ocean-induced melt at the ice stream grounding line, Heinrich events always follow DO events by a constant time lag. We also introduce noise into the ocean system and find that ice-ocean interactions not only maintain a narrow distribu- tion of timing between Heinrich and DO events, but also regulate DO event periodic- ity against noise in the climate system. This synchronization persists across a broad range of parameters, indicating that it is a robust explanation for Heinrich events and their timing despite the significant uncertainty associated with past ice sheet conditions.

Carbonate clumped isotopes (∆47) have become a widely applied method for paleothermometry, with applications spanning many environmental settings over hundreds of millions of years. However, ∆47-based paleothermometry can be complicated by closure temperature-like behavior whereby C–O bonds are reset at elevated diagenetic or metamorphic temperatures, sometimes without obvious mineral alteration. Laboratory studies have constrained this phenomenon by heating well-characterized materials at various temperatures, observing temporal ∆47 evolution, and fitting results to kinetic models with prescribed C–O bond reordering mechanisms. While informative, these models are inflexible regarding the nature of isotope exchange, leading to potential uncertainties when extrapolated to geologic timescales. Here, we instead propose that observed reordering rates arise naturally from random-walk 18O diffusion through the carbonate lattice, and we develop a “disordered” kinetic framework that treats C–O bond reordering as a continuum of first-order processes occurring in parallel at different rates. We show theoretically that all previous models are specific cases of disordered kinetics; thus, our approach reconciles the transient defect/equilibrium defect and paired reaction-diffusion models. We estimate the rate coefficient distributions from published heating experiment data by finding a regularized inverse solution that best fits each ∆47 timeseries without assuming a particular functional form a priori. Resulting distributions are well-approximated as lognormal for all experiments on calcite or dolomite; aragonite experiments require more complex distributions that are consistent with a change in oxygen bonding environment during the transition to calcite. Presuming lognormal rate coefficient distributions and Arrhenius-like temperature dependence yields an underlying activation energy, E, distribution that is Gaussian with a mean value of μE = 224.3 ± 27.6 kJ mol−1 and a standard deviation of σE = 17.4 ± 0.7 kJ mol−1 (±1σ uncertainty; n = 24) for calcite and μE = 230.3 ± 47.7 kJ mol−1 and σE = 14.8 ± 2.2 kJ mol−1 (n = 4) for dolomite. These model results are adaptable to other minerals and may provide a basis for future experiments whereby the nature of carbonate C–O bonds is altered (e.g., by inducing mechanical strain or cation substitution). Finally, we apply our results to geologically relevant heating/cooling histories and suggest that previous models underestimate low-temperature alteration but overestimate ∆47 blocking temperatures.

Phytoplankton blooms occur annually at the sea-ice edge throughout the Arctic during the spring melt period. Our study considers how these spring blooms may depend on sea-ice meltwater, focusing on the role of horizontal mixing and advection. We extend the classic Fisher reaction-diffusion equation to consider a time- and space-varying death rate that represents the role of meltwater in the system. Our results indicate that blooms peak at a characteristic distance from the ice edge where (i) meltwater is concentrated enough to stratify the upper ocean such that the phytoplankton are confined near the surface and (ii) phytoplankton have been exposed to sufficient sunlight to allow for optimized growth. The results reproduce key characteristics of a large bloom observed in Fram Strait in May 2019. Our findings support the idea that sea-ice meltwater is of central importance in setting the spatial patterns of Arctic phytoplankton blooms.

The future wide-swath satellite altimeters, such as the upcoming Surface Water Ocean Topography (SWOT) mission, will provide instantaneous 2D measurements of sea level down to the spatial scale of O(10 km) for the first time. However, the validity of the geostrophic assumption for estimating surface currents from these instantaneous maps is not known a priori. In this study, we quantify the accuracy of geostrophy for the estimation of surface currents from a knowledge of instantaneous sea level using the hourly snapshots from a tide- and eddy-resolving global numerical simulation. Geostrophic balance is found to be the leading-order balance in frontal regions characterized by large kinetic energy, such as the western boundary currents and the Antarctic Circumpolar Current. Everywhere else, geostrophic approximation ceases to be a useful predictor of ocean velocity, which may result in significant high-frequency contamination of geostrophically computed velocities by fast variability (e.g., inertial and higher). As expected, the validity of geostrophy is shown to improve at low frequencies (typically$<$0.5 cpd). Global estimates of the horizontal momentum budget reveal that the tropical and mid-latitude regions where geostrophic balance fails are dominated by fast variability and turbulent stress divergence terms rather than higher-order geostrophic terms. These findings indicate that the estimation of velocity from geostrophy applied on SWOT instantaneous sea level maps may be challenging away from energetic areas.

The North Anatolian Fault (NAF) has produced numerous major earthquakes. After decades of quiescence, the Mw 6.8 Elazig earthquake (January 24, 2020) has recently reminded us that the East Anatolian Fault (EAF) is also capable of producing significant earthquakes. To better estimate the seismic hazard associated with these two faults, we jointly invert Interferometric Synthetic Aperture Radar (InSAR) and GPS data to image the spatial distribution of interseismic coupling along the eastern part of both the North and East Anatolian Faults. We perform the inversion in a Bayesian framework, enabling to estimate uncertainties on both long-term relative plate motion and coupling. We find that coupling is high and deep (0-20 km) on the NAF and heterogeneous and superficial (0-5 km) on the EAF. Our model predicts that the Elazig earthquake released between 200 and 250 years of accumulated moment, suggesting a bi-centennial recurrence time.

The present paper examines the northern stratosphere during April 2020, when the polar vortex split into two cyclonic vortices after a winter with the strongest ozone depletion on record. We examine the dynamical evolution that led to the split at middle and lower stratospheric levels and the distribution of ozone between the main and off-spring vortices. Finally, we look at the vertical structure of the split down to the troposphere. The split event is analyzed with Lagrangian tools and an Eulerian diagnostic of planetary wave activity. The findings confirm the key role for the split played by a flow configuration with a polar hyperbolic trajectory and associated manifolds. A trajectory analysis illustrates how the ozone distribution between vortices was such that ozone poor air remained in the main vortex. The off-spring vortex became part of a deep structure from the troposphere, and connections with tropospheric disturbances over Eurasia are suggested.

Microseismicity, induced by the sliding of a glacier over its bed, can be used to characterize frictional properties of the ice-bed interface, which are a key parameter controlling ice stream flow. We use naturally occurring seismicity to monitor spatiotemporally varying bed properties at Rutford Ice Stream, West Antarctica. We locate 230000 micro-earthquakes with local magnitudes from –2.0 to –0.3 using 90 days of recordings from a 35-station seismic network located ~40 km upstream of the grounding line. Events exclusively occur near the ice-bed interface and indicate predominantly flow-parallel stick-slip. They mostly lie within a region of interpreted stiff till and along the likely stiffer part of mega-scale glacial landforms. Within these regions, micro-earthquakes occur in spatially (<100 m radius) and temporally (mostly 1-5 days activity) restricted event-clusters (up to 4000 events), which exhibit an increase, followed by a decrease, in event magnitude with time. This may indicate event triggering once activity is initiated. Although ocean tides modulate the surface ice flow velocity, we observe little periodic variation in overall event frequency over time and conclude that water content, bed topography and stiffness are the major factors controlling microseismicity. Based on variable rupture mechanisms and spatiotemporal characteristics, we suggest the event-clusters relate to three end-member types of bed deformation: (1) continuous creation and seismogenic destruction of small-scale bed-roughness, (2) ploughed clasts and (3) flow-oblique deformation during landform-formation or along bedrock outcrops. This indicates that multiple processes, simultaneously active during glacial sliding, can accommodate stick-slip behaviour and that the bed continuously reorganizes.

Experiment and observation have established the centrality of oxygen fugacity (fO2) to determining the course of igneous differentiation, and so the development and application of oxybarometers have proliferated for more than half a century. The compositions of mineral, melt, and vapor phases determine the fO2 that rocks record, and the activity models that underpin calculation of fO2 from phase compositions have evolved with time. Likewise, analytical method development has made new sample categories available to oxybarometric interrogation. Here we compile published analytical data from lithologies that constrain fO2 (n=860 volcanic rocks - lavas and tephras and n=326 mantle lithologies- the majority peridotites) from ridges, back-arc basins, forearcs, arcs, and plumes. Because calculated fO2 varies with choice of activity model, we re-calculate fO2 for each dataset from compositional data, applying the same set of activity models and methodologies for each data type. Additionally, we compile trace element concentrations (e.g. vanadium) which serve as an additional fO2-proxy. The compiled data show that, on average, volcanic rocks and mantle rocks from the same tectonic setting yield similar fO2s, but mantle lithologies span a much larger range in fO2 than volcanics. Multiple Fe-based oxybarometric methods and vanadium partitioning vary with statistical significance as a function of tectonic setting, with fO2 ridges < back arcs < arcs. Plume lithologies are more nuanced to interpret, but indicate fO2s  ridges. We discuss the processes that may shift fO2 after melts and mantle lithologies physically separate from one another. We show that the effects of crystal fractionation and degassing on the fO2 of volcanics are smaller than the differences in fO2 between tectonic settings and that effects of subsolidus metamorphism on the fO2 values recorded by mantle lithologies remain poorly understood. Finally, we lay out challenges and opportunities for future inquiry.

Short term aftershock incompleteness (STAI) can strongly bias any analysis built on the assumption that seismic catalogs have a complete record of events. Despite several attempts to tackle this issue, we are far from trusting any dataset in the immediate future of a large shock occurrence. Here we introduce RESTORE (REal catalogs STOchastic REplenishment), a Python toolbox implementing a stochastic gap-filling method, which automatically detects the STAI gaps and reconstructs the missing events in the space-time-magnitude domain. The algorithm is based on empirical earthquake properties and relies on a minimal number of assumptions about the data. Through a numerical test, we show that RESTORE returns an accurate estimation of the number of missed events and correctly reconstructs their magnitude, location and occurrence time. We also conduct a real-case test, by applying the algorithm to the Mw 6.2 Amatrice aftershocks sequence. The STAI-induced gaps are filled and missed earthquakes are restored in a way which is consistent with data. RESTORE, which is made freely available, is a powerful tool to tackle the STAI issue, and will hopefully help to implement more robust analyses for advancing operational earthquake forecasting and seismic hazard assessment.

Modelling the planetary heat transport of small bodies in the early Solar System allows us to understand the geological context of meteorite samples. Conductive cooling in planetesimals is controlled by thermal conductivity, heat capacity, and density, which are functions of temperature (T). We investigate if the incorporation of the T-dependence of thermal properties and the introduction of a non-linear term to the heat equation could result in different interpretations of the origin of different classes of meteorites. We have developed a finite difference code to perform numerical models of a conductively cooling planetesimal with T-dependent properties and find that including T-dependence produces considerable differences in thermal history, and in turn the estimated timing and depth of meteorite genesis. We interrogate the effects of varying the input parameters to this model and explore the non-linear T-dependence of conductivity with simple linear functions. Then we apply non-monotonic functions for conductivity, heat capacity and density fitted to published experimental data. For a representative calculation of a 250 km radius pallasite parent body, T-dependent properties delay the onset of core crystallisation and dynamo activity by ~40 Myr, approximately equivalent to increasing the planetary radius by 10 %, and extend core crystallisation by ~3 Myr. This affects the range of planetesimal radii and core sizes for the pallasite parent body that are compatible with paleomagnetic evidence. This approach can also be used to model the T-evolution of other differentiated minor planets and primitive meteorite parent bodies and constrain the formation of associated meteorite samples.

The November 2017 magnitude (MW) 5.5 Pohang, Korea, earthquake, induced by an Engineered 24 Geothermal Systems (EGS) project, caused one fatality and ~US$300M of economic 25 consequences. It has been proposed that a significant probability of such losses was predictable 26 beforehand, from the small earthquakes caused by well-stimulation, so the project should have 27 been suspended, implying that its developer was remiss for not doing so. This argument depends 28 on the low (~0.61) estimated b-value of this earthquake population. However, it is shown that 29 many of the magnitude determinations are inaccurate (underestimated) and the true b-value is 30 higher (1.12 for one subset). The probability of any earthquake as large as MW=5.5, predicted 31 beforehand by extrapolation, was thus much lower than has been claimed. This analysis 32 highlights the necessity of taking care over accuracy when reporting datasets like this, especially 33 in situations where such analyses might influence criminal trials of EGS developers.