Previous laboratory experiments with KIS tracers have shown promising results with respect to the quantification of fluid-fluid interfacial area (IFA) for dynamic, two-phase flow conditions. However, pore-scale effects relevant for two-phase flow (e.g. the formation of hydrodynamically stagnant/ immobile zones) are not yet fully understood, and quantitative information in how far these effects influence the transport of the tracer reaction products is not yet available. Therefore, a pore-scale numerical model that includes two-phase, reactive flow and transport of the KIS tracer at the fluid-fluid interface is developed. We propose a new method to quantitatively analyze how the concentration of the KIS-tracer reaction product in the effluent is affected by the presence of immobile zones. The model employs the phase field method (PFM) and a new continuous mass transfer formulation, consistent with the PFM. We verify the model with the analytical solution of a reaction-diffusion process for two-phase flow conditions in a conceptual capillary tube. The applicability of the model is demonstrated in NAPL/water drainage scenarios in a conceptual porous domain, comparing the results in terms of the spatial distribution of the phases and the quantified macro-scale parameters (saturation, capillary pressure, IFA and solute concentration). Furthermore, we distinguish the mobile and immobile zones based on the local Péclet number, and the corresponding solute mass in these two zones is quantified. Finally, we show that the outflow concentration can be employed to selectively determine the mobile part of the IFA.

The rhyolite-producing Laguna del Maule volcanic field (LdMVF) records magma-induced surface inflation rates of ~ 25 cm/year since 2007. During the Holocene, ~60 meters of cumulative surface uplift is recorded by paleoshorelines of the Laguna del Maule, located on the southeast edge of the LdMVF (Chile-Argentina border) near the Barrancas volcanic complex. Rhyolites from the Barrancas complex erupted over ~14 ka including some of the youngest (1.4 ± 0.6 ka) lava flows in the field. New gravity data collected on the Barrancas complex reveals a Bouguer low (-6 mGal, Barrancas anomaly) that is distinct from the pronounced gravity low (-19 mGal; Lake anomaly) associated with present-day deformation and magma intrusion to the north. Three-dimensional inversion of the Barrancas anomaly indicates the presence of a magma body with a maximum density contrast of -250 kg/m3 centered at a depth of ~ 3 km below surface. Comparison of model densities with measured densities from nearby silicic plutons suggest that a magma body, containing < 30 % melt phase and a low volatile content, exists beneath the Barrancas complex. The Barrancas and Lake gravity lows represent magma in different physical states, associated with past and present-day storage beneath the LdMVF. The gravity model mirrors existing geochemical observations which independently indicate that at least two distinct rhyolites were generated and stored as discrete magma bodies within the broader LdMVF. Small temperature changes of these discrete bodies could reverse crystallization and viscous lock-up and propel magma toward a crystal-poor eruptible state.

In this paper, we explore the use of unsteady transit time distribution (TTD) theory to model pollutant removal in biofilters, a popular form of nature-based or “green” stormwater infrastructure (GSI). TTD theory elegantly addresses many unresolved challenges associated with predicting pollutant fate and transport in these systems, including unsteadiness in the water balance (time-varying inflows, outflows, and storage), unsteadiness in pollutant loading, time-dependent reactions and scale-up to GSI networks and urban catchments. From a solution to the unsteady age conservation equation under uniform sampling, we derive an explicit expression for solute breakthrough with or without first-order decay. The solution is calibrated and validated with breakthrough data from 17 simulated storm events (+/- bromide as a conservative tracer) at a field-scale biofilter test facility in Southern California. TTD theory closely reproduces bromide breakthrough concentrations, provided that lateral exchange with the surrounding soil is accounted for. At any given time, according to theory, more than half of water in storage is from the most recent storm, while the rest is a mixture of penultimate and earlier storms. Thus, key management endpoints, such as the treatment credit attributable to GSI, are inexorably linked to the age distribution of water stored and released by these systems.

Madagascar hosts several Paleoproterozoic sedimentary sequences that are key to unravelling the geodynamic evolution of past supercontinents on Earth. New detrital zircon U–Pb and Hf data, and a substantial new database of ~15,000 analyses are used here to compare and contrast sedimentary sequences in Madagascar, Africa and India. The Itremo Group in central Madagascar, the Sahantaha Group in northern Madagascar, the Maha Group in eastern Madagascar, and the Ambatolampy Group in central Madagascar have indistinguishable age and isotopic characteristics. These samples have maximum depositional ages > 1700 Ma, with major zircon age peaks at c. 2500 Ma, c. 2000 Ma and c. 1850 Ma. We name this the Greater Itremo Basin, which covered a vast area of Madagascar in the late Paleoproterozoic. These samples are also compared with those from the Tanzania and the Congo cratons of Africa, and the Dharwar Craton and Southern Granulite Terrane of India. We show that the Greater Itremo Basin and sedimentary sequences in the Tanzania Craton of Africa are correlatives. These also tentatively correlate with sedimentary protoliths in the Southern Granulite Terrane of India, which together formed a major intra-Nuna/Columbia sedimentary basin that we name the Itremo-Muva-Pandyan Basin. A new Paleoproterozoic plate tectonic configuration is proposed where central Madagascar is contiguous with the Tanzania Craton to the west and the Southern Granulite Terrane to the east. This model strongly supports an ancient Proterozoic origin for central Madagascar against the Tanzania Craton of East Africa.

We propose a mechanism for the formation of the horse-collar auroral configuration during periods of strongly northwards interplanetary magnetic field, invoking the action of dual-lobe reconnection (DLR). Auroral observations are provided by the Imager for Magnetopause-to-Auroras Global Exploration (IMAGE) satellite and spacecraft of the Defense Meteorological Satellite Program (DMSP). We also use ionospheric flow measurements from DMSP and polar maps of field-aligned currents (FACs) derived from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). Sunward convection is observed within the dark polar cap, with antisunwards flows within the horse-collar auroral region, together with the NBZ FAC distribution expected to be associated with DLR. We suggest that newly-closed flux is transported antisunwards and to dawn and dusk within the reverse lobe cell convection pattern associated with DLR, causing the polar cap to acquire a teardrop shape and weak auroras to form at high latitudes. Horse-collar auroras are a common feature of the quiet magnetosphere, and this model provides a first understanding of their formation, resolving several outstanding questions regarding the nature of DLR and the magnetospheric structure and dynamics during northwards IMF. The model can also provide insights into the trapping of solar wind plasma by the magnetosphere and the formation of a low-latitude boundary layer and cold, dense plasma sheet.

We developed a numerical thermodynamics laboratory called “Thermolab” to study the effects of the thermodynamic behavior of non-ideal solution models on reactive transport processes in open systems. The equations of state of internally consistent thermodynamic datasets are implemented in MATLAB functions and form the basis for calculating Gibbs energy. A linear algebraic approach is used in Thermolab to compute Gibbs energy of mixing for multi-component phases to study the impact of the non-ideality of solution models on transport processes. The Gibbs energies are benchmarked with experimental data, phase diagrams and other thermodynamic software. Constrained Gibbs minimization is exemplified with MATLAB codes and iterative refinement of composition of mixtures may be used to increase precision and accuracy. All needed transport variables such as densities, phase compositions, and chemical potentials are obtained from Gibbs energy of the stable phases after the minimization in Thermolab. We demonstrate the use of precomputed local equilibrium data obtained with Thermolab in reactive transport models. In reactive fluid flow the shape and the velocity of the reaction front vary depending on the non-linearity of the partitioning of a component in fluid and solid. We argue that non-ideality of solution models has to be taken into account and further explored in reactive transport models. Thermolab Gibbs energies can be used in Cahn-Hilliard models for non-linear diffusion and phase growth. This presents a transient process towards equilibrium and avoids computational problems arising during precomputing of equilibrium data.

Six conceptually different models of steady groundwater flow and conservative transport are applied to the heterogeneous MADE aquifer. Their predictive capability is assessed by comparing the modelled and observed longitudinal mass distributions at different times of the plume in the MADE-1 experiment, as well as at a later time. The models differ in their conceptualization of the heterogeneous aquifer structure, computational complexity, and use of permeability data obtained from various observation methods (DPIL, Grain Size Analysis, Pumping Tests and Flowmeter). Models depend solely on aquifer structural and flow data, without calibration by transport observations. Comparison of model results by various measures, i.e. peak location, bulk mass and leading tail, reveals that the predictions of the solute plume agree reasonably well with observations if the models are underlined by a few parameters of close values: mean velocity, a parameter reflecting log-conductivity variability and a horizontal length scale related to conductivity spatial correlation. From practitioners perspective the robustness of the models is an important and useful property. The model comparison provides insight into relevant features of transport in heterogeneous aquifers. After further validation by additional field experiments or by numerical simulations, the results can be used to provide guidelines for users in selecting conceptual aquifer models, characterization strategies, quantitative models and implementation for particular goals.

Synchronization behavior of large earthquakes (rupture of nearby faults close in time for many cycles) has been reported in many fault systems. The general idea is that the faults in the system have similar repeating interval and are positively coupled through stress interaction. However, many details of such synchronization remain unknown. Here, we built numerical models in the framework of rate/state friction to simulate earthquake cycles on the west Gofar fault, East Pacific Rise. Our model consists of two seismic patches, separated by a barrier patch, constrained by seismic observations. We varied the parameters in the barrier to understand its role on earthquake synchronization. First, we found that static stress transfer can lead to synchronization, opposite to the suggestion by Scholz (2010). Second, the width of the barrier is more important than its strength. When the barrier is narrow enough (no more than half width of the seismic patch in our models), the system can achieve synchronization even with a very strong barrier. Third, for certain simulations, the interaction between the two seismic patches promotes partial rupture in the seismic patches and leads to complex behavior: the system switches from synchronized to unsynchronized over 10-20 cycles. Moreover, the average seismic ratio of the entire fault can be quite low, ranging between 0.2-0.4 because of the barrier patch. We suggest that the existence of large barrier patches contributes significantly to the well-observed low seismic ratio on oceanic transform faults.

Image cross-correlation techniques, such as Particle Image Velocimetry (PIV), can estimate water surface velocity (vsurf) of streams. However, discharge estimation requires water depth and the depth-averaged vertical velocity (Um). The variability of the ratio Um/vsurf introduces large errors in discharge estimates. We demonstrate a method to estimate vsurf from Unmanned Aerial Systems (UASs) with PIV technique. This method does not require any Ground Control Point (GCP): the conversion of velocities from pixels per frame into meters per time is performed by informing a camera pinhole model; the range from the pinhole to the water surface is measured by the drone-board radar. For approximately uniform flow, Um is a function of the Gauckler-Manning-Strickler coefficient (Ks) and vsurf. We implement an approach that can be used to jointly estimate Ks and discharge by informing a system of 2 unknowns (Ks and discharge) and 2 non-linear equations: i) Manning’s equation ii) mean-section method for computing discharge from Um. This approach relies on bathymetry, acquired in-situ a-priori, and on UAS-borne vsurf and water surface slope measurements. Our joint (discharge and Ks) estimation approach is an alternative to the widely used approach than relies on estimating Um as 0.85vsurf. It was extensively investigated in 27 case studies, in different streams with different hydraulic conditions. Discharge estimated with the joint estimation approach showed a mean absolute error in discharge of 19.1% compared to in-situ discharge measurements. Ks estimates showed a mean absolute error of 3.2 m^{1/3} /s compared to in-situ measurements.

The Atmosphere-Space Interactions Monitor (ASIM) on the International Space Station (ISS) provides optical radiances and images of lightning flashes in several spectral bands. This work presents a lightning flash simultaneously observed from space by ASIM, the Geostationary Lightning Mapper (GLM) and the Lightning Imaging Sensor on the International Space Station (ISS-LIS); and from ground by the Colombia Lightning Mapping Array (Colombia-LMA). Volumetric weather radar provides reflectivity data to help to interpret the effects of the cloud particles on the observed optical features. We found that surges in radiance in the band at 777.4 nm, appear to be related mostly with lightning processes involving currents as well with branching of lightning leaders with new leader development. In cloud areas with reflectivity <18 dBZ above the lightning leader channels at altitudes >7 km, these have been imaged by ASIM and GLM. But in the region with reflectivity <23 dBZ, despite its lower cloud tops and similar altitudes of lightning channels, these have been almost undetectable. The estimated relative optical depth results consistent with the observed optical features at the different locations of the flash. Despite of the effects of the cloud particles and the altitude of the lightning channels on the attenuation of the luminosity, the luminosity of the lightning channels due to different processes is fundamental for the imaging of lightning from space.

Subsurface tile drainage (TD) is a dominant agriculture water management practice in the United States (US) to enhance crop production in poorly-drained soils. Assessments of field- or watershed-level (<50 km2) hydrologic impacts of tile drainage are becoming common; however, a major gap exists in our understanding of regional (>105 km2) impacts of tile drainage on hydrology. The National Water Model (NWM) is a distributed 1-km resolution hydrological model designed to provide accurate streamflow forecasts at 2.7 million reaches across the US. The current NWM lacks tile drainage representation which adds considerable uncertainty to streamflow forecasts in tile-drained areas. In this study, we quantify the performance of the NWM with a newly incorporated tile drainage scheme over the heavily tile-drained Midwestern US. Implementing a tile drainage scheme enhanced the uncalibrated model performance by about 20% to 50% of the calibrated NWM (Calib). The calibrated NWM with tile drainage (CalibTD) showed enhanced accuracy with higher event hit rates and lower false alarm rates than Calib. CalibTD showed better performance in high-flow estimations as tile drainage increased streamflow peaks (14%), volume (2.3%), and baseflow (11%). Regional water balance analysis indicated that tile drainage significantly reduced surface runoff (-7% to -29%), groundwater recharge (-43% to -50%), evapotranspiration (-7% to -13%), and soil moisture content (-2% to -3%). However, infiltration and soil water storage potential significantly increased with tile drainage. Overall, our findings highlight the importance of incorporating the tile drainage process into the operational configuration of the NWM.

The latitudinal position of the subtropical jet over the Himalayas (Himalayan jet latitude or HJL) controls the region’s climate during winter and spring by guiding moisture-delivering storms. Here we use the Community Earth System Model-Last Millennium Ensemble to diagnose forced trends in HJL during the past millennium. During 850-1849, there is a weak equatorward trend in winter HJL. In contrast, the spring HJL has a relatively larger poleward trend, and increases in both variance and frequency of poleward/equatorward excursions. We demonstrate changes in orbital precession reduced the thermal gradient between tropical and subtropical Asia, shifting the spring HJL poleward. During 1850-2005, the spring HJL exhibits no trend due to compensating influences from orbital and anthropogenic greenhouse gas forcings. These findings suggest it is essential climate models properly simulate the effects of and potential interactions between orbital forcing and anthropogenic factors to accurately project Himalayan jet variability and associated storm tracks.

Science is fueled by data. Throughout history, scientists have operated sensors-from astronomical observatories to particle accelerators-that accumulate observations for analysis or to evaluate a hypothesis. However, as available technologies have increased both the volume of data and the efficiency of data storage and transmission, a new model of data access has emerged. The concept of a data buy is where an entity purchases access to a set of data or a data stream, instead of operating the sensors themselves. But why might a data consumer, whether a researcher or an end-user, prefer this kind of data access over the more traditional methods of running a network themselves? The simple answer, in some cases, is efficiency and, possibly, cost. Space weather forecasting and analysis has a growing private sector, and the extension to data gathering can be considered as a natural next step in the maturation of the field and the growing public-private partnerships. Operational applications require consistent, clean, and (in some cases) real-time data access that can be hard to support through the existing model of sensor deployment. Even in scientific applications, where access to raw information can be critical to discovery, there are benefits to the data buy model. Consistent access to a trusted data set allows more time to be spent on the scientific analysis, instead of maintaining machines that require consistent development, maintenance, and monitoring. The outsourcing of data infrastructure and pipelines can be particularly beneficial when the sensors are in distributed networks, spread over wide areas, and when there is a need to provide local data in observational gaps in existing networks. In the ideal case, a data buy can supplement the traditional observational networks in a beneficial and symbiotic way. It is important to note that data buys should not replace traditional observational networks, nor compete for funding with future observatories and infrastructure that the scientific community has deemed necessary (for example, through decadal survey processes).

Knowledge of soil properties is essential for risk assessment of vapor intrusion (VI). Data assimilation (DA) provides a valuable means to characterize contaminated sites by fusing the information contained in the measurement data (such as concentrations of volatile organic chemicals). Nevertheless, the application of DA in risk assessment of VI is quite limited. Moreover, soil heterogeneity is often overlooked in VI-related research. To fill these knowledge gaps, we apply a state-of-the-art DA method based on deep learning (DL), that is, ES(DL), to better characterize the contaminated sites in VI risk assessment. The effectiveness of ES(DL) is well demonstrated by three representative scenarios with increasing soil heterogeneity. The results clearly show that ignoring soil heterogeneity will significantly undermine one’s ability to make reasonable decisions in VI risk assessment. As a preliminary attempt of applying an advanced DA method in VI research, this work provides implications for the potential of using DL and DA in complex problems that couple hydrological and environmental processes.

Global change is a change in the planetary energy balance. It is usually expressed as a change in near-surface (2 m) air temperature (Ta), but changes to Ta represent only part of the atmospheric energy balance, which includes specific humidity (q) and more. We analyzed MERRA-2 reanalysis data and 15 Atmospheric Model Intercomparison Project (AMIP) models over the 1980-2014 period. Some 41%, 37%, and 49% of the near-surface atmosphere showed significant increases in ET, ESH, and E, respectively. The average increase in ET (ESH) was 10.6 J kg−1 year−1 (11.5 J kg−1 year−1) but AMIP models estimated that ET (14.5 J kg−1 year−1) exceeded ESH (13.7 J kg−1 year−1). Global near-surface Ta would have increased at more than twice the observed rate if energy was not partitioned into latent heat. Results demonstrate the critical role that q plays in recent changes to near-surface atmospheric energy.

Quantitative knowledge about the burial of sedimentary components at the seafloor has wide-ranging implications in ocean science, from global climate to continental weathering. The use of 230 Th-normalized fluxes reduces uncertainties that many prior studies faced by accounting for the effects of sediment redistribution by bottom currents and minimizing the impact of age model uncertainty. Here we employ a recently compiled global dataset of 230 Th-normalized fluxes with an updated database of seafloor surface sediment composition to derive global maps of the burial flux of calcium carbonate, biogenic opal, total organic carbon (TOC), non-biogenic material, iron, mercury, and excess barium (Baxs). The spatial patterns of burial of the major components are mainly consistent with prior work, but the new quantitative estimates allow evaluations of global deep-sea burial. Our integrated deep-sea burial fluxes are 136 Tg C/yr CaCO3, 153 Tg Si/yr opal, 20Tg C/yr TOC, 220 Mg Hg/yr, and 2.6 Tg Baxs/yr. Sedimentary Fe fluxes reflect a mixture of sources including lithogenic material, hydrothermal inputs and authigenic phases. The fluxes of some commonly used paleo-productivity proxies (TOC, biogenic opal, and Baxs) are not well-correlated geographically with satellite-based productivity estimates. Our new compilation of sedimentary fluxes provides more detailed information on burial fluxes, which should lead to improvements in the understanding of how preservation affects these paleoproxies.

In the past two decades, surface wave imaging based on seismic ambient noise cross-correlation (CC) has been one of the most important technologies in the field of seismology. With the development of this technology, high-mode surface waves have received increasing attention, especially after the proposition of the frequency-Bessel transform (F-J) method, which can effectively extract multimode dispersion curves from ambient noise data. In the past few years, our research group has made many attempts to improve this method. We summarized these experiences and the corresponding algorithm for fast CC, and packaged them into a Python package called CC-FJpy. It is commonly understood that CC takes a good deal of time. However, we found that a simple reorganization of the CC logic can achieve computational acceleration by a multiple of tens or even hundreds in comparison with classical CC open-source programs for N stations. For the F-J method, we use Nvidia’s graphics processing unit (GPU) to speed up computation, and this approach achieves a hundreds-fold computational acceleration. We have encapsulated our experiences and technologies into CC-FJpy and submitted it to various types of data tests to ensure its speed and ease of use. We hope that providing the open source of CC-FJpy can benefit the development of surface wave studies and make it easier to start with high-mode surface waves. We look forward to your use and valuable suggestions.

Super-Earth and super-Venus exoplanets may have similar bulk compositions, but their surface conditions and mantle dynamics are vastly different. Vigorous convection within their metallic cores may produce dynamos and thus magnetospheres if the total heat flow out of the core exceeds a critical value. Earth has a core-hosted dynamo because plate tectonics cools the core relatively rapidly. In contrast, Venus has no dynamo and its deep interior probably cools slowly, potentially due to a lack of plate tectonics. It is not fully known how or if magnetic fields affect habitability, but the size of a magnetosphere might indirectly constrain the habitability of a surface. In this study, we developed scaling laws for how planetary mass affects the minimum heat flows required to sustain both thermal and chemical convection, which we compared to a simple model for the actual heat flow of both super-Earth and super-Venus exoplanets conveyed by solid-state mantle convection. We calculated three critical thresholds for heat flow based on varying the size of an inner core, the rate at which light elements precipitate at the core-mantle boundary, and the thermal conductivity of the core. We found that the required heat flows increase with planetary mass (to a power of ~0.8–0.9), but the actual heat flows of both super-Earths and super-Venuses could increase even faster (to a power of ~1.6) (Figure 1). Massive super-Earths are likely to host a dynamo in their metallic cores if their silicate mantles are entirely solid. Super-Venuses with relatively slow mantle convection could host a dynamo if their mass exceeds ~1.5 (with an inner core) or ~4 (without an inner core) Earth-masses. However, the mantles of massive rocky exoplanets might not be completely solid. Basal magma oceans may reduce the heat flow across the core-mantle boundary and smother any core-hosted dynamo. Detecting a magnetosphere at an Earth-mass planet probably signals Earth-like geodynamics. In contrast, magnetic fields may not reliably reveal if a massive exoplanet is a super-Earth or a super-Venus. We eagerly await direct observations in the next few decades. Published in JGR, doi:10.1029/2020JE006739