Waves and water level setup during storms can create overwashing flows across barrier islands. Overwashing flows can cause erosion, barrier breaching, and inlet formation, but their sediments can also be deposited and form washover fans. These widely different outcomes remain difficult to predict. Here we suggest that a breach develops when the sediment volume transported by overwashing flows exceeds the barrier subaerial volume. We form a simple analytical theory that estimates overwashing flows from storm characteristics, barrier morphology, and dune vegetation, and which can be used to assess washover deposition and breaching likelihood. Our theory suggests that barrier width and storm surge height are two important controls on barrier breaching. We test our theory with the hydrodynamic and morphodynamic model Delft3D as well as with field observations of 21 washover fans and 6 breaches that formed during hurricane Sandy. There is reasonable correspondence for natural but not for developed barrier coasts, where traditional sediment transport equations do not readily apply. Our analytical formulations for breach formation and overwash deposition can be used to improve long-term barrier island models.

The different olivine fabrics in ultramafic rocks have been widely used to discuss past tectonic settings, given that the olivine fabrics vary with pressure, temperature and water content. However, there are no researches that whether and how the olivine fabrics transform at different metamorphic stages in a natural rock during the process of deep subduction and exhumation. Yinggelisayi garnet lherzolites from South Altyn have experienced deep continental subduction and exhumation. The garnet lherzolites contain well-preserved residual protolith minerals, and near-peak (M1), granulite-facies retrograde (M2), and amphibolite-facies retrograde (M3) metamorphic mineral assemblages. Olivine grains in M1 formed at P–T conditions of 2.52–3.08 GPa, 1095–1136°C and low water contents (183–213 ppm H/Si), and showed [010] axes sub-normal to the foliation and [001] axes subparallel to the lineation, which is characteristic of B-type fabric ((010)[001]). Olivine grains in M2 formed at P–T conditions of 1.31–1.80 GPa, 851–893°C and also low water contents (93–139 ppm H/Si), and exhibited [010] axes sub-normal to the foliation and [100] axes subparallel to the lineation, which is characteristic of A-type fabric ((010)[100]). These observations suggest that olivine fabrics in HP-UHP metamorphosed ultramafic rocks are different in the near-peak and retrograde metamorphic stages, and also that the olivine fabrics can be transformed during deep continental subduction and exhumation. Therefore, the dispersed or no clear olivine fabric probably caused by multi-stage deformation and metamorphism, and the distinct olivine fabrics can be used as a clue to identify geological processes and better understand metamorphism and deformation during subduction and exhumation.

Yamato and Brun (Nature Geoscience 10, 46-50, 2017) claimed that metamorphic data from global (ultra)high-pressure ((U)HP) rocks exhibit an unusual linear relation, between peak pressure and pressure drop, which challenges current interpretation of P-T-t paths but supports their model invoking excessive overpressures. If their model holds, most research on (U)HP rocks since their discovery would require serious reconsideration. Here, I demonstrate that their model requires critical assumptions that are neither justified by the principles of rock mechanics in the context of realistic geologic settings nor consistent with microstructures of (U)HP rocks. Furthermore, contrary to their claim, the global (U)HP data can be readily explained in the current framework but are inconsistent with their model prediction.

Direction and depths of hyporheic exchange fluxes at the groundwater - surface water interface are drivers of biogeochemical processes influencing nutrient cycling and water quality. Model concepts on the dynamic relationship between hyporheic exchange fluxes and exchange depth are typically based on the assumption of a linear relationship between both measures. Here, we quantify seasonal and episodic variations of hyporheic exchange fluxes and hyporheic exchange depths with methods of heat tracing. Numerically (FLUX-BOT) and analytically (VFLUX; method based on temperature amplitude dampening developed by Hatch et al., 2006) working program scripts were used to solve the one-dimensional conduction-advection-dispersion equation and compute hyporheic flux rates from three vertical sediment water temperature profiles recorded continuously in a small low mountain creek between 2011 and 2017. By comparing the behavior of two differing water temperature-based modelling approaches, dissimilarities in the sensitivity to sediment thermal properties were identified. These differences in parameter responsivity explain deviating behavior of the models regarding exchange flux and depth calculations. We show that the vertical extension of hyporheic exchange depth has a distinctive seasonal pattern over seven years, which differs between the chosen models. Surface water levels, groundwater levels and stream discharges show significant correlations with both flux direction and hyporheic zone extension. In contrast to the numerical modelling approach, analytically derived flux data allowed for establishing a significant relationship between the hydraulic gradient observed at a nearby groundwater well and simulated hyporheic exchange depths.

An upper-crustal intrusive network in the 201.5 Ma, rift-related Central Atlantic Magmatic Province is exposed in the western Newark basin (PA, USA). Alpha-MELTS modeling was used to track magma evolution starting with initial pyroxene crystallization at depth (1000-500 MPa); plagioclase crystallized during ascent in the upper crust. For magma emplaced at 5-6 km depth (170 MPa), six MELTS models were generated to bracket different composition, H2O (1-3 wt.%), and crystallinity (28-49 vol.%). Corresponding magma viscosities evolved from 3 to 1624 Pa-sec (predicted using Giordano et. al 2008; Moitra and Gonnermann 2014). Detailed crystal mush structures in a diabase sill are revealed in a dimension stone quarry. Ubiquitous asymmetric modal layers a few mm thick comprising plag-rich layers (PRL, 75% modal plag) overlying more pyx-rich layers outline the tops of hundreds of dm-m scale flow lobes in the quarry. Tabular plag in PRL show shape-preferred orientations, tiling, and pressure shadows around larger pyx that resemble analog experiments on particle slurries and indicate flow with limited mechanical compaction. During magma emplacement, recursive interactions of propagation, sorting, and crystallization self-organized as flow lobes with plag entrained and aligned along lobe tops. Our calculations show plag separation can reduce bimodal suspension viscosity; a positive feedback likely enhanced by shear thinning and crystal alignments. EDS analyses and X-ray maps show that plag has oscillatory-zoned cores (An82-67) with patchy-zoned mantles (An67) filled in by An66-63. In PRL, plag are cemented together by An62-55; Na-rich rims occur next to qtz-Kspar pockets. By the end of cementation, PRL liquid volume was significantly reduced to 11-18% compared with 28-45% in overall magma based on MELTS models for An62-55 plag. Diabase suspension viscosity increased to >6000 Pa-sec; PRL viscosity cannot be modeled by equations based on random packing. PRL with aligned interlocking crystals were more rigid and less permeable than surrounding diabase. Upward flow of magma after modal layer development was channelized into pipes truncated and deflected by PRL. Thus, lateral flow during emplacement developed sub-vertical heterogeneities that exemplify complex mush rheology over m-scale distances.

This paper presents for the first time results on winds, tides, gradients of horizontal winds, and momentum fluxes at mesosphere and lower thermosphere (MLT) altitudes over southern Patagonia, one of the most dynamically active regions in the world. For this purpose, measurements provided by SIMONe Argentina are investigated. SIMONe Argentina is a novel multistatic specular meteor radar system that implements a SIMONe (Spread Spectrum Interferometric Multistatic meteor radar Observing Network) approach, and that has been operating since the end of September 2019. Average counts of more than 30000 meteor detections per day result in tidal estimates with statistical uncertainties of less than 1 m/s. Thanks to the multistatic configuration, horizontal and vertical gradients of the horizontal winds are obtained, as well as vertical winds free from horizontal divergence contamination. The vertical gradients of both zonal and meridional winds exhibit strong tidal signatures. Mean momentum fluxes are estimated after removing the effects of mean winds using a four-hour, eight-kilometer window in time and altitude, respectively. Reasonable statistical uncertainties of the momentum fluxes are obtained after applying a 28-day averaging. Therefore, the momentum flux estimates presented in this paper represent monthly mean values of waves with periods of four hours or less, vertical wavelengths shorter than eight kilometers, and horizontal scales less than 400 km.

We present a new approach for the analysis of high-resolution digital camera photographs taken by photographers who have fortuitously been able to capture rare events such as the glowing sky phenomenon known as STEVE. This method is especially effective with a time lapse series of images of the night sky taken under constant camera settings with a steady pointing. Stars, planets and satellites seen in such images can be used to determine precise and accurate registration of camera pixels to coordinates of angular altitude and azimuth. The location of satellites in the image enables precise and accurate synchronization of the images. We apply these techniques to the series of photographs of STEVE taken on 25 July 2016. We confirm the altitude structure previously found for STEVE. We find it most likely that the green picket fence features often seen during STEVE events are produced by auroral electron precipitation. With the precipitation assumption, we are able to extract novel information about the energy spectrum of the particles responsible for the production of STEVE luminosity in this particular event. Similar analyses of archived digital photographs may constitute a treasure trove of important data for improved understanding of rare and transient events such as STEVE.

Himalaya glaciers are invariably covered by supra-glacial debris. Of the glaciers, the Chhota Shigri Glacier (CSG) in the western Himalaya is basically debris-free yet has the highest melt rate compared to other central and eastern Himalayan glaciers. Here, utilizing osmium isotopic composition and major and trace element geochemistry of cryoconite — a dark-colored aggregate of mineral and organic materials —and glacial surface materials on the ablation zone of the CSG, we show that the surface of CSG is essentially free of anthropogenically emitted particles, contrary to many previous findings. Given this and the lack of debris, we conclude that the high melting rate in CSG is primarily related to the increase of the Earth’s near-surface temperature in direct response to global warming. Thus, monitoring the ice mass loss is further critical given the water source to millions of people.

In western Canada, there has been an increase in seismic activity linked to anthropogenic energy-related operations including conventional hydrocarbon production, wastewater fluid injection, and, more recently, hydraulic fracturing (HF). Statistical modeling and characterization of the space, time, and magnitude distributions of the seismicity clusters is vital for a better understanding of induced earthquake processes and development of forecasting models. In this work, a statistical analysis of the seismicity in the Western Canada Sedimentary Basin was performed across past and present time periods by utilizing a compiled earthquake catalogue for Alberta and eastern British Columbia. Specifically, the inter-event space-time distance distributions of earthquakes were studied using the nearest-neighbour distance (NND) method. Additionally, the frequency-magnitude statistics and aftershock parameters of several clusters were analyzed using the Gutenberg-Richter relation and the epidemic type aftershock sequence model. The results suggest that recent regional changes in the NND distributions, namely, a disproportionate increase in loosely and tightly clustered seismic activity over time, are unnatural and likely due to the rise in HF operations for the development of unconventional resources. It is concluded that both these loosely and tightly clustered earthquake subpopulations differ measurably from what may be the region’s tectonic seismic activity. Additionally, HF treatments have a greater probability of triggering swarm-like sequences that sharply spike the seismicity rate and are characterized by larger Gutenberg-Richter b-values. In contrast, conventional production and wastewater disposal operations largely trigger loosely clustered activity with more typical magnitude-occurrence distributions.

The societal importance of geothermal energy is significantly increasing because of its low carbon-dioxide footprint. However, geothermal exploration is also subject to high risks. For a better assessment of these risks, extensive parameter studies are required that improve the understanding of the subsurface. This yields computationally demanding analyses. Often this is compensated by constructing models with a small vertical extent. This paper demonstrates that this leads to entirely boundary-dominated and hence uninformative models. It demonstrates the indispensable requirement to construct models with a large vertical extent to obtain informative models with respect to the model parameters. For this quantitative investigation, global sensitivity studies are essential since they also consider parameter correlations. To compensate for the computationally demanding nature of the analyses, a physics-based machine learning approach is employed, namely the reduced basis method, instead of reducing the physical dimensionality of the model. The reduced basis method yields a significant cost reduction while preserving the physics and a high accuracy, thus providing a more efficient alternative to considering, for instance, a small vertical extent. The reduction of the mathematical instead of physical space leads to less restrictive models and, hence, maintains the model prediction capabilities. The combination of methods is used for a detailed investigation of the influence of model boundary settings in typical regional-scale geothermal simulations and highlights potential problems.

The Flare Irradiance Spectral Model (FISM) is an important tool for estimating solar variability for a myriad of space weather research studies and applications, and FISM Version 2 (FISM2) has recently been been released. FISM2 is an empirical model of the solar ultraviolet irradiance created to fill spectral and temporal gaps in the measurements, where these measurements are infrequent as they need to be made from space due to their absorption in the planetary atmospheres. FISM2 estimates solar ultraviolet irradiance variations due to solar cycle, solar rotation, and solar flare variations. The major improvement provided by FISM2 is that it is based on multiple new, more accurate instruments that have now captured almost a full solar cycle and thousands of flares, drastically improving the accuracy of the modeled FISM2 solar irradiance spectra. FISM2 is also improved to 0.1 nm spectral bins across the same 0-190 nm spectral range, and is already being used in research to estimate space weather changes due to solar irradiance variability in planetary thermospheres and ionospheres.

The paleogeographic evolution of the western USA Great Basin from the Late Cretaceous to the Cenozoic is critical to understanding how the Cordillera at this latitude transitioned from Mesozoic shortening to Cenozoic extension. According to a widely applied model, Cenozoic extension was driven by collapse of elevated crust supported by crustal thicknesses that were potentially double the present ~30–35 km. This model is difficult to reconcile with more recent estimates of moderate regional extension (≤ 50%) and the discovery that most high-angle, basin–range faults slipped rapidly ca. 17 Ma, tens of millions of years after crustal thickening occurred. Here we integrate new and existing geochronology and geologic mapping in the Elko area of northeast Nevada, one of the few places in the Great Basin with substantial exposures of Paleogene strata. We improve age control for strata that have been targeted for studies of regional paleoelevation and paleoclimate across this critical time span. In addition, a regional compilation of the ages of material within a network of middle Cenozoic paleodrainages developed across the Great Basin shows that the age of basal paleovalley fill decreases southward roughly synchronous with voluminous ignimbrite flareup volcanism that swept south across the region ca. 45–20 Ma. Integrating these datasets with the regional record of faulting, sedimentation, erosion, and magmatism, we suggest that volcanism was accompanied by an elevation increase that disrupted drainage systems and shifted the continental divide east into central Nevada from its Late Cretaceous location along the Sierra Nevada arc. The north–south Eocene–Oligocene drainage divide defined by mapping of paleovalleys may thus have evolved as a dynamic feature that propagated southward with magmatism. Despite some local faulting, the northern Great Basin became a vast, elevated volcanic tableland that persisted until dissection by Basin and Range faulting that began ca. 21–17 Ma. Based on this more detailed geologic framework, it is unlikely that Basin and Range extension was driven by Cretaceous crustal overthickening; rather, pre-existing crustal structure was just one of several factors that that led to Basin and Range faulting after ca. 17 Ma—in addition to thermal weakening of the crust associated with Cenozoic magmatism, thermally supported elevation, and changing boundary conditions. Because these causal factors evolved long after crustal thickening ended, during final removal and fragmentation of the shallowly subducting Farallon slab, they are compatible with normal (~45–50 km) thickness crust beneath the Great Basin prior to extension and do not require development of a strongly elevated, Altiplano-like region during Mesozoic shortening.

We develop a new method to analyze the total electron content (TEC) depression in the ionosphere after a tsunami occurrence. We employ Gaussian process regression to accurately estimate the TEC disturbance every 30 s using satellite observations from the GNSS network, even over regions without measurements. We face multiple challenges. First, the impact of the acoustic wave generated by a tsunami onto TEC levels is non-linear and anisotropic. Second, observation points are moving. Nevertheless, our method always computes these volumes, along with estimated uncertainties, when applied to the 2011 Tohoku-Oki Earthquake, even with random selections of only 5% of the 1,000 GPS Earth Observation Network System receivers considered here over Japan. The method can warn of a tsunami event within 15 minutes of the earthquake, at high levels of confidence, even with a sparse receiver network. Hence, it is potentially applicable worldwide using the existing GNSS network.

Satellite-atmosphere interactions cause large uncertainties in low-Earth orbit determination and prediction. Thus, knowledge of and the ability to predict the space environment, most notably thermospheric mass density, are essential for operating satellites in this domain. Recent progress has been made toward supplanting the existing empirical, operational methods with physics-based data-assimilative models by accounting for the complex relationship between external drivers such as solar irradiance, Joule, and particle heating, and their response in the upper atmosphere. Simultaneously, a new era of CubeSat constellations is set to provide data with which to calibrate our upper-atmosphere models at higher spatial resolution and temporal cadence. With this in mind, we provide an initial method for converting precision orbit determination (POD) solutions from global navigation satellite system (GNSS) enabled CubeSats into timeseries of thermospheric mass density. This information is then fused with a physics-based, data-assimilative technique to provide calibrated model densities.

STEVE (Strong Thermal Emission Velocity Enhancement) is an optical phenomenon of the sub-auroral ionosphere arising from extreme ion drift speeds. STEVE consists of two distinct components in true-color imagery: a mauve or whitish arc extended in the magnetic east-west direction, and a region of green emission adjacent to the arc, often structured into quasi-periodic columns aligned with the geomagnetic field (the “picket fence”). This work employs high-resolution imagery by citizen scientists in a critical examination of fine scale features within the green emission region. Of particular interest are narrow “streaks” of emission forming underneath field-aligned picket fence elements in the 100–110-km altitude range. The streaks propagate in curved trajectories with dominant direction toward STEVE from the poleward side. The elongation is along the direction of motion, suggesting a drifting point-like excitation source, with the apparent elongation due to a combination of motion blur and radiative lifetime effects. The cross-sectional dimension is <1 km, and the cases observed have a duration of ~10–30 s. The uniform coloration of all STEVE green features in these events suggests a common optical spectrum dominated by the oxygen 557.7-nm emission line. The source is most likely direct excitation of ambient oxygen by superthermal electrons generated by ionospheric turbulence induced by the extreme electric fields driving STEVE. Some conjectures about causal connections with overlying field-aligned structures are presented, based on coupling of thermal and gradient-drift instabilities, with analogues to similar dynamics observed from chemical release and ionospheric heating experiments.

The paper presents a combined numerical - deep learning (DL) approach for improving wind and wave forecasting. First, a DL model is trained to improve wind velocity forecasts by using past reanalysis data. The improved wind forecasts are used as forcing in a numerical wave forecasting model. This novel approach, used to combine physics-based and data-driven models, was tested over the Mediterranean. It resulted in ∼10% RMSE improvement in both wind velocity and wave height forecasts over operational models. This significant improvement is even more substantial at the Aegean Sea from May to September, when Etesian winds are dominant, improving wave height forecasts by over 35%. The additional computational costs of the DL model are negligible compared to the costs of either numerical models. This work has the potential to greatly improve the wind and wave forecasting models used nowadays by tailoring models to localized seasonal conditions, at negligible additional computational costs.

The effects of instrument noise on estimating the spectral attenuation rates of ocean waves in sea ice are explored using synthetic observations in which the true attenuation rates are known explicitly. The spectral shape of the energy added by noise, relative to the spectral shape of the true wave energy, is the critical aspect of the investigation. A negative bias in attenuation that grows in frequency is found across a range of realistic parameters. This negative bias decreases the observed attenuation rates at high frequencies, such that it can explain the rollover effect commonly reported in field studies of wave attenuation in sea ice. The published results from four field experiments are evaluated in terms of the noise bias, and a spurious rollover (or flattening) of attenuation is found in all cases. Remarkably, the wave heights are unaffected by the noise bias, because the noise bias occurs at frequencies that contain only a small fraction of the total energy.

Convection parameterizations such as eddy-diffusivity mass-flux (EDMF) schemes require a consistent closure formulation for the perturbation pressure, which arises in the equations for vertical momentum and turbulence kinetic energy (TKE). Here we derive an expression for the perturbation pressure from approximate analytical solutions for 2D and 3D thermal bubbles. The new closure combines modified pressure drag and virtual mass effects with a new momentum advection damping term. This advection damping is an important source in the lower half of the thermal bubble and at cloud base levels in convective systems. It represents the effect of the perturbation pressure to ensure the non-divergent properties of the flow. The new formulation represents the pressure drag to be inversely proportional to updraft depth. This is found to significantly improve simulations of the diurnal cycle of deep convection, without compromising simulations of shallow convection. It is thus a key step toward a unified scheme for a range of convective motions. By assuming that the pressure only redistributes TKE between updrafts and the environment laterally, a closure for the velocity pressure-gradient correlation is obtained from the perturbation pressure closure. This novel pressure closure is implemented in an extended EDMF scheme and is shown to successfully simulate a rising bubble as well as shallow and deep convection in a single column model.