A document by Haibo Huang. Click on the document to view its contents.

Excessive salinity can harm ecosystems and compromise the various anthropogenic activities that take place in river deltas. The issue of salinization is expected to exacerbate due to natural and/or anthropogenic climate change. Water regulations are required to secure a sufficient water supply in conditions of limited water volume availability. Research is ongoing in seek of the optimum flow distribution establishing longer-lasting and fresher conditions in deltas. In this study a three–dimensional (3D) numerical model was used to unravel the influence of hydrographs shape on the deltas salinity. Our results show that it is possible to improve the freshwater conditions in deltas without seeking for additional water resources but by modifying the water distribution. The peak flow magnitude and timing and the tails of a hydrograph were found to be important parameters affecting stratification, freshwater residence and renewal times. Hydrographs having lighter tails and smaller range were the most successful in keeping the delta and its river inlet fresher for longer periods. Salinity distributions showed a slower response to decreasing rather than increasing river discharges. An increase in the flow rate can achieve a desired salinity standard in much shorter time. Hydrographs with heavier tails can push the salt intrusion limit further away and are more efficient in mixing the water column. However, they present low freshwater residence and high water renewal times. These results have implications for coastal scientists and stakeholders dealing with the management of freshwater resources in river deltas across the world.

Integration of multiple geophysical methods in combined data analysis is a key practice to reduce model uncertainties and enhance geological interpretations. Electrical resistivity models resulting from inversion of marine magnetotelluric (MT) data, often lack depth resolution of lithological boundaries, and distinct information for shallow model parts. This is due to the nature of the physics i.e. diffusive method, model regularization during inversion, and survey setup i.e. large station spacing and missing high frequency data. Thus, integrating data or models to constrain layer thicknesses or structural boundaries is an effective approach to derive better constrained, more detailed resistivity models. We investigate the different impacts of three cross-gradient coupled constraints on 3D MT inversion of data from the Namibian passive continental margin. The three constraints are a) coupling with a fixed structural density model; b) coupling with satellite gravity data; c) coupling with a fixed gradient velocity model. Here we show that coupling with a fixed model (a and c) improves the resistivity model most. Shallow conductors imaging sediment cover are confined to a thinner layer in the resulting resistivity models compared to the MT-only model. Additionally these constraints help to suppress vertical smearing of a conductive anomaly attributed to a fracture zone, and clearly show that the seismically imaged Moho is not accompanied by a change in electrical resistivity. All of these observations aid interpretation of an Earth model indicating involvement of a plume impact in continental break-up during the early Cretaceous.

Charge exchange between hot ions and cold neutral atoms is an important effect in ring current loss processes on magnetized planets. In this letter, we investigate the spatial distribution of charge exchange loss contributions to terrestrial ring current decay using data from the Van Allen Probes. These contributions were calculated by dividing local energetic neutral atom energy density escape rates by local ring current energy density decay rates. The results exhibit clear MLT and L dependence, with larger contributions observed nightside during the recovery phase of geomagnetic storms. The contribution of H+; peaked at L~4 during early recovery phases and was stronger at higher L shells during late recovery phases, while O+; decreased slightly with L shell. Possible explanations for this inhomogeneous distribution are also discussed. The asymmetric exospheric hydrogen density distribution may cause the inhomogeneous distribution in the MLT, while the L dependence may be related to the charge exchange cross-section and the ion energy flux. These results provide the first spatial distribution of charge exchange contributions, which is helpful for understanding local terrestrial ring current evolution.

Structural imaging using body-wave energy present in ambient seismic data remains a challenging task, largely because these wave modes are commonly much weaker than surface wave energy. In a number of situations body-wave energy has been extracted successfully; however, (nearly) all successful body-wave extraction and imaging approaches have focused on cross-correlation processing. While this is useful for interferometric purposes, it can also lead to the inclusion of unwanted noise events that dominate the resulting stack, leaving body-wave energy overpowered by the coherent noise. Conversely, wave-equation imaging can be applied directly on non-correlated ambient data that has been preprocessed to mitigate unwanted energy (i.e., surface waves, burst-like and electromechanical noise) to enhance body-wave arrivals. Following this approach, though, requires a significant preprocessing effort on often Terabytes of ambient seismic data, which is expensive and requires automation to be a feasible approach. In this work we outline an automated processing workflow designed to optimize body wave energy from an ambient seismic data set acquired on a large-N array at a mine site near Lalor Lake, Manitoba, Canada. We show that processing ambient seismic data in the recording domain, rather than the cross-correlation domain, allows us to mitigate energy that is inappropriate for body-wave imaging. We first develop a method for window selection that automatically identifies and removes data contaminated by coherent high-energy bursts. We then apply time- and frequency-domain debursting techniques to mitigate the effects of remaining strong amplitude and/or monochromatic energy without severely degrading the overall waveforms. After each processing step we implement a QC check to investigate improvements in the convergence rates - and the emergence of reflection events - in the cross-correlation plus stack waveforms over hour-long windows. Overall, the QC analyses suggest that automated preprocessing of ambient seismic recordings in the recording domain successfully mitigates unwanted coherent noise events in both the time and frequency domain. Accordingly, we assert that this method is beneficial for direct wave-equation imaging with ambient seismic recordings.

In this study, we evaluated the variations of air quality in Lanzhou, a typical city in Northwestern China impacted by the COVID-19 lockdown. The mass concentration and chemical composition of non-refractory submicron particulate matter (NR-PM) were determined by a high-resolution aerosol mass spectrometry from January to March 2020. The concentration of NR-PM dropped by 40% from pre- to during control period. The five aerosol components (sulfate, nitrate, ammonium, chloride, and organic aerosol (OA)) were all decreased during control period with the largest from secondary inorganic species (70% of the total reduction), whereas the OA sources did not vary synchronously. OA from coal and biomass burning remained stably from pre- to during control period, while traffic and cooking related emissions were reduced by 30% and 50%, respectively. The production rates for secondary inorganic and organic aerosols were also evaluated and represented a decreased trend from pre- to during control periods.

We present observations in Earth’s magnetotail by the Magnetospheric Multiscale spacecraft that are consistent with magnetic field annihilation, rather than magnetic topology change, causing fast magnetic-to-electron energy conversion in an elongated electron-scale current sheet. This energy conversion process is in contrast to that in the standard electron diffusion region (EDR) of a reconnecting current sheet where the energy of antiparallel magnetic fields is mostly converted to electron bulk-flow energy. Fully kinetic simulation also demonstrates that an elongated EDR is subject to the formation of electron-scale magnetic islands in which fast energy conversion is dominated by the annihilation. Consistent with the observations and simulation, theoretical analysis shows that fast magnetic diffusion can occur in an elongated EDR in the presence of nongyrotropic electron effects. The discovery of the annihilation-dominated EDR reveals a new form of energy conversion in the collisionless reconnection process.

A document by Yang Wang. Click on the document to view its contents.

This study investigates land loss and coastal inundation in Louisiana's Barataria Basin, a region highly susceptible to anthropogenic pressures and natural factors like land subsidence, sea-level rise, and tidal dynamics. Using high-resolution Digital Elevation Models (DEM) and water level data from the Coastal Reference Monitoring System (CRMS) stations, we analyzed changes in land area and water levels between 2007 and 2022. The attenuation coefficient magnitude of tidal intrusion, which quantifies tidal amplitude reduction as a function of landward distance from the coastline, exhibited a persistent decrease from 2007 to 2022 for O1 and K1 (the dominant tidal constituents), with an accumulated decrease of nearly 20%, signaling enhanced hydrological connectivity across the region. We also projected land area for historic years and predicted it for future years up to 2075, based on a range of displacement rates to account for uncertainties in vertical land motion. Our analyses predict that, in the absence of human intervention, the significance of tidal variations in influencing land loss will escalate; by 2045, the land area estimated based on Mean Higher High Water (MHHW) will constitute approximately 65% of the land area estimated using Mean Sea Level (MSL). Our findings underline the importance of considering the compound effects of subsidence, sea-level rise, and tidal dynamics in future land loss mapping and flood risk assessments. 

Identifying useful microseismic events is one of the key steps in monitoring tunnel rockbursts. Here, we propose a strong noise-tolerant deep learning (SNTDL) network for the automatic classification of noisy microseismic events. First, to comprehensively characterize the microseismic events, we extract nine weakly correlated features of the microseismic recordings as the input of training the SNTDL network. Then, a jump connection and concatenation structure are added to this network, which can further enhances its generalization ability. Additionally, the SNTDL, AlexNet, Inception, Visual Geometry Group, and ResNet are compared using the synthetic microseismic recordings with different signal-noise ratios. The results demonstrate that the SNTDL network has a higher accuracy and stronger noise-tolerant capability than the other approaches. Application to a dataset collected from a different construction environment confirms that the SNTDL network can still achieve an accurate classification result, which further verifies that the proposed network has a reliable generalization performance.

The Mansurov Effect is related to the interplanetary magnetic field (IMF) and its ability to modulate the global electric circuit, which is further hypothesized to impact the polar troposphere through cloud generation processes. In this paper we investigate the connection between IMF By-component and polar surface pressure by using daily ERA5 reanalysis for geopotential height since 1980. Previous studies have shown to produce a significant 27-day cyclic response during solar cycle 23. However, when appropriate statistical tests are applied, the correlation is not significant at the 95\% level. Our results also show that data from three other solar cycles, which have not been investigated before, produce similar cyclic responses as during solar cycle 23, but with seemingly random offset in the timing of the signal. We examine the origin of the cyclic pattern occurring in the super epoch/lead lag regression methods commonly used to support the Mansurov hypothesis in all recent papers, as well as other phenomena in this community. By generating random normally distributed noise with different levels of temporal autocorrelation, and using the real IMF By-index as forcing, we show that the methods applied to support the Mansurov hypothesis up to now, are highly susceptible, as cyclic patterns always occurs as artefacts of the methods. This, in addition to the lack of significance, suggests that there is no adequate evidence in support of the Mansurov Effect.

Using a recently developed 1/12th degree regional ocean model, we establish a link between U.S. East Coast sea level variability and offshore upper-ocean heat content change. This link manifests as a cross-shore mass redistribution driven by an offshore thermosteric sea level response to subsurface warming or cooling. Approximately 50\% of simulated monthly to inter-annual coastal sea level variance south of Cape Hatteras can be statistically accounted for by this mechanism, realized as a function of regional ocean hypsometry, gyre scale warming, and the depth-dependence of density change. This response to offshore warming explains the non-stationarity of U.S. East coast sea level covariance, specifically observed and modeled behavior after $\sim$ 2010. Since approximately 2010, elevated rates of sea level rise south of Cape Hatteras can be partly explained as the result of shore-ward mass redistribution due to offshore sub-surface warming within the North Atlantic subtropical gyre. These results reveal a mechanism that connects local coastal sea level to a broader region and identifies the influence of regional heat content changes on coastal sea level. This analysis presents a framework for identifying new regions that may be susceptible to enhanced sea level rise due to ocean warming and helps bridge the gap between quantifying large scale change and anticipating local coastal impacts like flooding and storm surge.

Key Points: 8 • Bed heights of bedload-dominated rivers modeled by Distinct Element Method (DEM) 9 simulations follow a Gaussian distribution. 10 • The standard deviation of bed height, s η , increases as the shear stress increases. 11 • Peak entrainment of bed particles occurs at a distance 2s η above the average bed 12 height. Abstract 14 We investigate the statistics of bed height variability and particle entrainment height un-15 der steady state bedload transport conditions using distinct element method (DEM) sim-16 ulations. We do so in the context of a theoretical probabilistic formulation derived to 17 better capture spatial variation in sediment exchange between bed material load and al-18 luvial deposits (Parker et al., 2000). Using DEM simulations, we set the foundation for 19 a physics-based closure of this probabilistic framework toward its practical implemen-20 tation. Towards this, we perform DEM simulations for bedload transport under simi-21 lar boundary conditions to those of Wong et al. (2007) laboratory experiments: a bed 22 of gravel particles of median grain size 7.1mm with lognormal grain size distribution trans-23 ported under bed shear stresses ranging from τ 0 = 8.70 to 13.7 Pa. We first validate 24 these simulations by demonstrating that they capture measurable transport and height 25 variations from experimental measurements. We then compute the statistics of both the 26 bed height and entrainment height as they vary with bed shear stress. We find that vari-27 abilites in both bed height and entrainment height variabilities follow Gaussian distri-28 butions, for which: (1) the standard deviation of bed height variability s η increases with 29 shear stress, and (2) the peak entrainment height occurs a distance of twice the stan-30 dard deviation of bed height variability (2s η) above the mean bed height. We discuss 31 implications of these results and next steps for understanding these transport statistics 32 under a broader range of conditions. 33

Anhydrous carbonate shortite compressed in the aqueous fluid at high P-T (up to 5 GPa, 350°C) was studied with in situ Raman spectroscopy. The DFT was used to calculate the lattice dynamics and interpret the vibrational spectra. The shortite Raman bands are broadening with pressure and temperature, and signal are decreasing that is caused by gradual structure amorphisation accompanied by an orientational disordering of CO$_3$ triangle units. Despite the aqueous medium presence at high temperature and pressure, shortite did not go hydrated. At 3.2 GPa and 250°C, shortite begins to dissolve followed by crystallisation of aragonite and aragonite’ . A remnant part of shortite crystals was presented in the ex-situ sample. The transition of shortite to aragonite’ was monitored by in situ Raman spectra in the C-O stretching range: strong doublet transforms into singlet at ~4 GPa, 250°C. Additionally, the phases X-phase is characterised by strongest narrow 1358 cm-1 band. X1- and X2-phases are expected to represent organic materials are the most believable Na-formate and some polymorphs of Ca-formate. The unusual behaviour of aqueous carbonate fluid was observed at 4.8 GPa and 300-350°C. This process is characterised by the active formation of micro-bubbles that are inserted one into another. The existence time of the micro-bubbles is varied within 2-60 seconds. Micro-bubbles are considered to be a result of the two immiscible fluids stratification. This unusual dynamical immiscibility of the fluid promotes the appearance of several crystalline carbonates and organic molecular crystals.

The complexity of induced seismicity mechanisms significantly hampers seismic hazard assessment around injection wells. The largest magnitude events are commonly thought to be controlled by the size of the injection-affected area, but what controls the size of this area and what is the role of the regional geologic setting? Here we explore observations of deep and distant induced earthquakes in Oklahoma and California. Despite wide-spread injection close to seismically active faults, fluid injection-induced seismicity is comparably rare in California hydrocarbon basins. We identified a potential case of injection-induced earthquakes associated with San Ardo oilfield operations, with the largest events occurring in 1955 (ML5.2) and 1985 (Mw4.5) within ∼6 km from the oilfield. We performed an interferometric analysis of SAR images acquired by Sentinel-1A/B satellites between 2016 and 2020, and find surface deformation of up to 1.5 cm/yr, indicating pressure-imbalance in parts of the oilfield. Temporal correlations are observed over more than 40 years, with correlation coefficients of up to 0.71 for seismicity within 24 km of the oilfield. Such large distances have not previously been observed in California but are similar to the large spatial footprint of injection in Oklahoma. The San Ardo seismicity shows anomalous clustering with earthquakes consistently occurring at close spatial proximity but long inter-event times, analogous to induced earthquakes in geothermal reservoirs. The complexity of seismic behavior at San Ardo indicates that multiple processes, such as elastic stress transfer and aseismic slip transients, contribute to the potentially induced earthquakes. The observed power-law distance decay of induced events from the reservoir is in line with observations of stress decay from poroelastic models in which basement faults may be hydraulically isolated from the injection zone. Our model’s resolved fluid/solid stress interactions suggest that shallow injection can 1) activate deep basement faults and 2) lead to spatially extensive induced earthquake sequences. Both of these observations may significantly elevate the seismic hazard associated with fluid injection operations.

We report observations of the ion dynamics inside an Alfven branch wave that propagates near the reconnecting dayside magnetopause. The measured frequency, wave normal angle and polarization are within 1% with the predictions of a dispersion solver, and indicate that the wave is an electromagnetic ion cyclotron wave with very oblique wave vector. The magnetospheric plasma contains hot protons (keV), cold protons (eV), plus some heavy ions. The cold protons follow the magnetic field fluctuations and remain frozen-in, while the hot protons are at the limit of magnetization. The cold proton velocity fluctuations contribute to balance the Hall term in Ohm’s law, allowing the wave polarization to be highly-elliptical and right-handed, a necessary condition for propagation at oblique wave normal angles. The dispersion solver indicates that increasing the cold proton density facilitates generation and propagation of these waves at oblique angles, as it occurs for the observed wave.

Injection of CO2 for geologic carbon sequestration (GCS) into deep sedimentary formations involves fluid pressure increases that engage hydromechanical processes that can cause seismicity by activation of existing faults. In this work, we use a coupled multiphase fluid flow and geomechanical simulator to model spatiotemporal fluid pressure and stress changes in order to study the poroelastic effect of CO2 injection on faults in crystalline basement rock below the injection zone. The seismicity rate along features interpreted to be basement faults is modeled using Dieterich’s rate-and-state earthquake nucleation model. The methodology is applied to microseismicity detected during CO2 injection into the Mount Simon formation during the Illinois Basin – Decatur Project. The modeling accurately captures an observed reduction in seismicity rate when the injection in the second well was into a slightly shallower zone above the base of the Mount Simon formation. Moreover, the modeling shows that it is important to consider poroelastic stress changes, in addition to fluid pressure changes for accurately modeling of the observed seismicity rate.

We show how changes in the global distribution of anthropogenic aerosols favour different spatial patterns in the North Atlantic sea-surface temperature (NASST). The NASSTs largely show the expected decrease associated with the anthropogenic aerosols in the 1970s, but also a surprising warming response in the eastern sub-polar gyre, the region of the North Atlantic warming hole. The NASST response reversed for the anthropogenic aerosols in the 2000s against 1970s. The regional reduction in anthropogenic aerosols favoured (1) a strengthening of the warming hole and (2) a NASST increase at high latitudes associated with changes in the atmosphere-ocean dynamics. The gyre component of the northward Atlantic heat transport in mid- to high latitudes is an important driving mechanism. At least two-thirds of the NASST response is associated with the magnitude of aerosol-cloud interactions. Constraining the NASST response therefore depends on a better understanding of the uncertain aerosol effects on clouds.