In this work we propose and apply a straightforward methodology for the automatic characterization of the extended earthquake source, based on the progressive measurement of the P-wave displacement amplitude at the available stations deployed around the source. Specifically, we averaged the P-wave peak displacement measurements among all the available stations and corrected the observed amplitude for distance attenuation effect to build the logarithm of amplitude vs. time function, named LPDT curve. The curves have an exponential growth shape, with 31 an initial increase and a final plateau level. By analyzing and modelling the LPDT curves, the information about earthquake rupture process and earthquake magnitude can be obtained. We applied this method to the Chinese strong motion data from 2007-2015 with MS ranging between 4 and 8. We used a refined model to reproduce the shape of the curves and different source models based on magnitude to infer the source-related parameters for the study dataset. Our study shows that the plateau level of LPDT curves has a clear scaling with magnitude, with no saturation effect for large events. By assuming a rupture velocity of 0.9Vs, we found a consistent self-similar, constant stress drop scaling law for earthquakes in China with stress drop mainly distributed between a lower level (0.23Mpa) and a higher level (3.74Mpa). The derived relation between the magnitude and rupture length can be used for probabilistic hazard analyses and real-time applications of Earthquake Early Warning systems.

It has been four decades since Apollo 16 returned the first wide-field UV imagery of the Earth and revealed the vast extent of exospheric hydrogen (H) atoms around the planet. Since that time, appreciation has grown regarding the significance of this outermost atmospheric layer, whose charge exchange interaction with ambient ions dissipates magnetospheric energy, generates the energetic neutral atoms (ENAs) widely used for remote sensing of the ring current dynamics during geomagnetic storms, and accelerates gravitational escape and thus permanent atmospheric evolution. Despite the importance of Earth’s H exosphere to the solar-terrestrial system, however, current understanding of its global structure and dynamical evolution is insufficient, such that the origin of persistent discrepancies between measurements and models remains unresolved. Remote sensing of UV emission from geocoronal H atoms, generated through resonant scattering of solar radiation at 121.6 nm (Lyman-alpha) is the only empirical means available to investigate the terrestrial exosphere. In this work, we present robust tomographic-based techniques we have developed in recent years to estimate the 3-D, global and time-dependent H-density distributions during quiet and storm-time from observations of its optically thin emission at Lyman-α acquired from the Lyman-alpha detectors onboard the NASA TWINS satellites. Several examples of recent 2D and 3D data analyses will be used to demonstrate the current state-of-the-art, reveal surprising exospheric phenomenon, and motivate future work.

Changes in the Atlantic Meridional Overturning Circulation (AMOC) and associated Meridional Heat Transport (MHT) can affect climate and weather patterns, regional sea levels, and ecosystems. However, despite its importance, direct observations of the AMOC are still limited spatially and temporally, particularly in the South Atlantic. The main goal of this study is to implement a cost-effective trans-basin section to estimate for the first time the AMOC at 22.5°S, using only sustained ocean observations. For this, an optimal mapping method that minimizes the difference between surface in-situ dynamic height and satellite altimetry was developed to retrieve monthly temperature and salinity profiles from Argo and XBT data along the 22.5°S section. The mean AMOC and MHT for 22.5°S were estimated as 15.55±2.81 Sv and 0.68±0.18 PW, respectively, and are stronger during austral fall/winter and weaker in spring. The high-resolution XBT data available at the western boundary are vital for capturing the highly variable Brazil Current, and our section shows a significant improvement when compared to Argo database. The mean values, interannual and seasonal time series of AMOC and MHT were compared with other products. At 22.5S the North Atlantic Deep Water is divided into two cores that flow along both western and eastern boundaries near 2500 m depth. Our results suggest a greater influence of western boundary system on the AMOC variability at 22.5°S; highlight the importance of high resolution in situ data for AMOC estimations; and contribute for a better understanding of AMOC and MHT variability in the South Atlantic.

We investigate the evolution of outwardly propagating simple MHD waves in a model of the expanding solar wind using MHD simulations. In order to understand the different evolution of slow, Alfvén and fast modes, the question of wave-action conservation is re-examined theoretically. Using the fluctuation averaged Lagrangian, we discuss the conservation of total wave action and Equi-partition of wave energy for MHD waves. Results show that, even though the wave action for a simple monochromatic wave is subject to loss under resonance/degeneracy condition - conditions that can occur in the expanding solar wind in the regions where plasma ß crosses one, the total wave action possessed by all modes remains conserved, representing a wave action exchange between different degrees of freedom. The Expanding Box simulations demonstrate the results of the theoretical modeling, and reveal further details about mode-mixing, Alfvén resonance and wave steepening. All of these may help to understand the evolution of fluctuations from the inner heliosphere out to Earth orbit and beyond.

Science Centers and Museums are indeed becoming communication hubs for many research areas, including, of course, Earth and Environmental Sciences. Over the last decades numerous new channels have opened for two-way communication and museums have embraced them enthusiastically, promoting dialogue and participation. The incorporation of citizen science, for example, into exhibitions and programming is one of the most recent trends in this direction. Often the question arises, however, of what such activities have to do with the objects and exhibits in the museum, and this perceived disconnect is used as an objection against such activities, which end up being considered as simple contingent add-ons that could just as well be done elsewhere, instead of necessary elements of museum communication. I will present a vision of museum communication that integrates such activities as part of its narrative, as long as they are incorporated using the unique and specific power of the language of exhibitions, a.k.a. the museographic language. To do so I ask the question: what is the museographic language good at communicating? In other words – what do museums communicate? If we center the answer around the concept of “phenomena” or “processes” we will be able to see how museum objects as well as interactive exhibits and a whole range of participatory activities can be successfully combined into a unique mode of communication through exhibitions that complements other channels in the ecosystem of science communication. While there are many scientific disciplines that can be communicated well using primarily collections of objects, other research areas, like Earth and Environmental Sciences need to extend their communication in Science Centers and Museums to include phenomena or processes (as well as objects) in order to actively engage audiences and harness their participation to shape the future of research and of science in society. I will share practical examples and recommendations for these disciplines.

A document by Poulomi Ganguli. Click on the document to view its contents.

An attempt has been made to quantitatively analyze different degrees of environmental drought events, given the limited scientific understanding of environmental droughts, which hinders practical assessment efforts. This study thus aims to rigorously develop and assess the applicability of a novel heuristic method in conjunction with creating an Environmental Drought Index \cite{Srivastava_2023}. The heuristic method evaluates the combined influences of drought duration and water shortage levels, providing crucial insights into the environmental flow requirements amidst climate change. The Minimum in-stream Flow Requirements (MFR) is first defined as the threshold value essential for sustaining the river basin's ecological functions, aligning with Tennant’s environmental flow concept. Establishing MFR enables a balance between water resource utilization and ecological preservation, fostering sustainable water management. To comprehensively assess the eco-status, the study defined the High Flow Season (HFS) and the Low Flow Season (LFS). Drought status is then determined by comparing MFR with observed streamflow rate, quantifying negative differences as environmental droughts. Drought Duration Length (DDL) and Water Shortage Level (WSL) are introduced as functions of environmental drought. DDL categorizes consecutive months into four classes: DDL 1 (1-3 months), DDL 2 (4-6 months), DDL 3 (7-12 months), and DDL 4 (>12 months). WSL is determined by the most significant water deficit observed during DDL, classified into four categories: WSL 1 (<40%), WSL 2 (40-60%), WSL 3 (60-80%), and WSL 4 (>80%). Integrating DDL and WSL yields an index classifying environmental drought events into slight, moderate, severe, and extreme levels. The index value is obtained by comparing DDL and WSL values and selecting the maximum. The study enhances the scientific rigor of environmental drought identification and analysis, contributing to understanding drought impacts and effective mitigation strategies.  

Insights from half a century investigating seafloor hydrothermal circulation on Earth can inform exploration on other Ocean Worlds. Early data/models for Earth provided useful predictions for flow at rift axes, but interpretations of the distribution of subseafloor circulation were revised significantly as data and simulations improved. Lessons learned for Earth systems elucidate how investigators might assess hydrothermal processes on other Ocean Worlds. Basin-scale morphology and heat flow indicate whether conduction explains the flux or cooling by seawater advection occurs. Detailed sonar mapping reveals areas where high flux is most likely. Seismicity patterns suggest different modes of circulation: East Pacific circulation is mapped via microseismicity within porous basaltic crust; Regional seismicity in the Atlantic highlights detachment-dominated rift segments, where faults channel circulation, sometimes within peridotite blocks that react with seawater. Exothermic serpentinization, also inferred for the lower ocean crust near subduction zones, should impart detectable temperature (T) signals. High-T/-flux circulation may be recognized with remote sensing (sonar, thermistors, chemical sensors, cameras) at the seafloor whereas low-T/-flux systems are difficult to identify. Modeling examines factors that influence hydrothermal circulation. Early models were simple single-pass cases; later data and more complex models show circulation includes multi-pass convection that can be 3D, unstable, and strongly guided by permeability patterns. Borehole observatories reveal heterogeneity in fluid chemistry and crustal microbiology. Interpreting Ocean World hydrothermal conditions will be challenging, but some fundamental inferences for Earth’s seafloor hydrothermal systems have proven robust. Early studies generated testable hypotheses, advanced instrumentation and simulations, and helped focus interdisciplinary discovery.

Rapid northward drift of the Indian plate after 130 Ma has also recorded significant plate rotations due to the torques resulting from multiple vector force components. Seismic tomography of the Indian Ocean and palaeomagnetic database of the Deccan Traps are used here to constrain drift velocities at different temporal snapshots, resulting into estimates of 263.2 to 255.7 mmyr-1 latitudinal drift, 234 to 227.3 mmyr-1 longitudinal drift and 352.2 to 342.1 mmyr-1 diagonal drift, for the period from ~66 to 64 Ma during the Chrons C30n.y–C29n.y. Alternative displacement models suggest active driving forces arising from i) slab pull, ii) ridge push from eastern-, western and southern plate margins, and iii) Reunion plume-push force; in addition to delamination of the lithospheric root during approximately 65+2 Ma. Delamination of the root amplified the buoyancy of the Indian plate in contrast to sudden loading from Deccan basaltic pile that resulted into complex drift dynamics expressed by hyper plate velocities with an anomalous westward drift component of >342 mmy-1.

Future coastal flood hazard at many locations will be impacted by both tropical cyclone (TC) change and relative sea-level rise (SLR). Despite sea level and TC activity being influenced by common thermodynamic and dynamic climate variables, their future changes are generally considered independently. Here, we investigate correlations between SLR and TC change derived from simulations of 26 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. We first explore correlations between SLR and TC activity by inference from two large‑scale factors known to modulate TC activity: potential intensity (PI) and vertical wind shear. Under the high emissions SSP5-8.5, SLR is strongly correlated with PI change (positively) and vertical wind shear change (negatively) over much of the western North Atlantic and North West Pacific. To explore the impact of the joint changes on flood hazard, we then conduct climatologyhydrodynamic modeling with New York City (NYC) as an example. Coastal flood hazard at NYC correlates strongly with global mean surface air temperature (GSAT), due to joint increases in both sea level and TC storm surges, the later driven by stronger and more slowly moving TCs. If positive correlations between SLR and TC changes are ignored in estimating flood hazard, the average projected change to the historical 100 year storm tide event is under-estimated by 0.09 m (7%) and the range across CMIP6 models is underestimated by 0.17 m (11 %). Our results suggest that flood hazard assessments that neglect the joint influence of these factors and that do not reflect the full distribution of GSAT changes will not accurately represent future flood hazard.

Fault-zones significantly influence the migration of fluids in the subsurface and can be important controls on the local as well as regional hydrogeology. Hence, understanding the evolution of fault porosity-permeability is critical for many engineering applications (like geologic carbon sequestration, enhanced geothermal systems, groundwater remediation, etc.) as well as geological studies (like sediment diagenesis, seismic activities, hydrothermal ore deposition, etc.). The highly heterogeneous pore structure of fault-zones along with the wide range of hydrogeochemical heterogeneity that a fault-zone can cut through make conduit fault-zones a dynamic reactive transport environment that can be highly complex to accurately model. In this paper, we present a critical review of the possible ways of modeling reactive fluid flow through fault-zones, particularly from the perspective of chemically driven “self-sealing” or “self-enhancing” of fault-zones. Along with an in-depth review of the literature, we consider key issues related to different conceptual models (e.g. fault-zone as a network of fractures or as a combination of damaged zone and fault core), modeling approaches (e.g. multiple continua, discrete fracture networks, pore-scale models) and kinetics of water-rock interactions. Inherent modeling aspects related to dimensionality (e.g. 1D vs 2D) and the dimensionless Damköhler number are explored. Moreover, we use a case-study of the Little Grand Wash Fault-zone from central Utah as an example in the review. Finally, critical aspects of reactive transport modeling 2 like multiscale approaches and chemo-mechanical coupling are also addressed in the context of fault-zones.

Critical Zone (CZ) scientists study the coupled chemical, biological, physical, and geological processes operating across scales to support life at the Earth's surface. In 2020, the U.S. National Science Foundation funded a network of Thematic Cluster projects called “CZ Net” to work collaboratively in answering scientific questions related to effects of urbanization on CZ processes; CZ function in semi-arid landscapes and the role of dust in sustaining these ecosystems; deep bedrock processes and their relationship to CZ evolution; CZ recovery from disturbances such as fire and flooding; and changes in the coastal CZ related to rising sea level. Data collected by these projects are diverse, ranging from time series from in situ sensors to laboratory analysis of physical samples, geophysical measurements, and others. Thus, coordinating data collection, archival, discovery, and access for the network presents significant challenges. Given the diversity in scientific domains represented, data produced, and collaborations, no single repository fully meets the needs of CZ scientists, posing questions of which repositories to use, how to enable discovery of and access to data across different repositories, and how to develop and promote best practices for sharing research products. This presentation describes cyberinfrastructure (CI) development by the CZ Net Coordinating Hub that leverages existing, domain-specific repositories for managing, curating, disseminating, and preserving data and research products from the CZ Net projects. We have developed CI that links existing data facilities and services, including HydroShare, EarthChem, Zenodo, and other repositories via a CZ Hub that provides tools for data submission, resource registry, metadata cataloging, resource discovery/access, and links to computational resources for analysis and visualization. The CZ Hub’s goal is to make data, samples, software, and other research products created by CZ Net projects Findable, Accessible, Interoperable, and Reusable (FAIR), using existing domain-specific repositories. The repository interoperability we have demonstrated for delivering data services for an interdisciplinary science program may provide a template for future development of integrated, interdisciplinary data services.

The East China Sea (ECS) seasonally receives a high organic input due to the terrestrial organic matter influx, which is controlled by the East Asian Summer Monsoon (EASM), and the increased productivity driven by upwelling of the subsurface Kuroshio Current (KC). Changes in benthic foraminiferal assemblage composition in combination with paleoceanographic proxy data (CaCO3 (%), TOC (%), δ13Cpf, and δ18Obf) are used to reconstruct bottom water oxygenation and organic export flux variability over the last 400 kyr in the ECS. Multivariate analyses of benthic foraminiferal census data identified six biofacies characteristic of varying environmental conditions. These results suggest that enhanced EASM precipitation and KC upwelling directly influenced organic export flux and bottom water oxygen content in the ECS. The ECS bottom water was suboxic during Marine Isotope Stage (MIS) 11 to 8; suboxic to dysoxic between MIS 7 and 6, strongly dysoxic between mid-MIS 5 and 4, and exhibited high variability between MIS 3 and 1. Spectral analysis of relative abundances of representative genera Quinqueloculina (oxic), Bulimina (suboxic), and Globobulimina (dysoxic) reveals a robust 23 kyr signal, which we attribute to precessionally-paced changes in surface productivity and bottom water oxygenation related to EASM and KC variability over the past 400 kyr.

In this study, based on the OI135.6 nm night airglow data of the FY-3D Ionospheric Photometer (IPM) during the 2018-2021 geomagnetically quiet period, the global wavenumber 4 longitudinal structure of the equatorial ionization anomaly (EIA) at 2:00 local time was discovered, and the component of the wavenumber 4 was extracted from these structures. Compared with the OI135.6 nm night airglow data of the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) F18 during 2011-2014, there were significant differences in the variation pattern of the relative amplitude of the two versus solar activity and the seasonal variation in the proportion of the component of the wavenumber 4. Based on the neutral wind speed observation results of Global High-Resolution Thermospheric Imaging (MIGHTI) on board the Ionospheric Connection Explorer (ICON) from 2020-2021, the longitudinal structures of the 4 ionospheric waves after midnight are related to the cross-equatorial meridional wind. We believe that the wavenumber 4 longitudinal structures after midnight originate from the eastward nonmigrating tidal semidiurnal wave (SE2) with a wavenumber of 2 in the cross-equatorial neutral wind rather than the eastward nonmigrating tidal semidiurnal wave (DE3) with a wavenumber of 3 in from the zonal wind, which modulates the daytime wavenumber 4 longitudinal structures.

Electrostatic solitary waves (ESWs) are a type of nonlinear time-domain plasma structure (TDS) generally defined by bipolar electric fields and propagation parallel to the local magnetic field. Formation mechanisms for TDSs in the magnetosphere have been studied extensively and are associated with plasma boundary layers and the braking of bursty bulk flows (BBFs). However, the rapid timescales over which these TDSs occur (< 2 ms) make them infeasible to count by eye over large time periods. Furthermore, high-cadence data are not always available. The Solitary Wave Detector (SWD) on NASA’s Magnetospheric Multiscale (MMS) mission quantifies the occurrence and amplitude of TDS throughout the constellation’s orbit; analysis of burst (65 kS/s) parallel electric field data indicates that the SWD captures appx. 60% of all bipolar TDS encountered in the tail region, enabling large-scale examination of their occurrence. Maps of TDS occurrence rates during several years of the MMS mission were generated from SWD data, showing enhanced TDS density in the tail region between 6-9 Re; enhance occurrence in or near shocks; and an unexpected enhancement in the dawn side of the tail and in the radiation belt.

While not specifically designed as a planetary mission, NASA’s Parker Solar Probe (PSP) mission uses a series of Venus gravity assists (VGAs) in order to reduce its perihelion distance. These orbital maneuvers provide the opportunity for direct measurements of the Venus plasma environment at high cadence. We present first observations of kinetic scale turbulence in the Venus magnetosheath from the first two VGAs. In VGA1, PSP observed a quasi-parallel shock, $\beta\sim1$ magnetosheath plasma, and a kinetic range scaling of $k^{-2.9}$. VGA2 was characterised by a quasi-perpendicular shock with $\beta\sim 10$, and a steep $k^{-3.4}$ spectral scaling. Temperature anisotropy measurements from VGA2 suggest an active mirror mode instability. Significant coherent waves are present in both encounters at sub-ion and electron scales. Using conditioning techniques to exclude these electromagnetic wave events suggests the presence of developed sub-ion kinetic turbulence in both magnetosheath encounters.

Private groundwater wells have the potential to be an unmonitored source of contaminants that can harm human health for millions of people throughout the United States. Developing models that predict potential exposure to contaminants, such as nitrate, could guide sampling efforts and allow the residents to take action to reduce their risk. Machine learning models have been successful in predicting nitrate contamination using geospatial information such as proximity to nitrate sources or soil type, but previous models have not considered meteorological factors that change temporally. In this study, we test random forest (regression and classification) and linear regression models to predict nitrate contamination of wells using rainfall and temperature records over the previous 180-days. We trained and tested models for (1) all of North Carolina, (2) each geographic region in North Carolina, (3) a three-county region with high density animal agriculture, and (4) a three-county region with a low density of animal agriculture. All regression models had poor predictive performance (R2 = 0.04) for all areas tested. The random forest classification model for the coastal plain region showed fair agreement (Cohen’s kappa = 0.23) when trying to predict whether contamination occurred. All other classification models had slight or poor predictive performance. Our results show that temporal changes in rainfall and temperature alone are not enough to predict nitrate contamination in most areas of North Carolina but show potential in the coastal plain region.

Multiphase fluid flow in porous media has been extensively studied for its applications in carbon capture and storage, hydrocarbon recovery, aquifer contamination, soil hydrology and subsurface energy resources. Fluid displacement in porous media can be investigated using highly time-resolved synchrotron X-ray microtomography. One consequence of extremely fast imaging can be compromised image quality, including noise and decreased contrast, which makes the images hard to be segmented. We trained an established convolutional neural network (CNN) architecture (U-Net) with 18,072 images from multiphase flow experiments generated by synchrotron μCT. The trained neural network can segment synchrotron μCT images of core-flooding experiments rapidly and accurately without any pre-processing of the raw image. Segmenting one μCT scan volume of size 1004x496x496 takes 5.6 minutes on an Nvidia Quadro K5200 GPU, while a conventional segmentation pipeline using CPU for the same size data takes 50.2 minutes. On the test dataset, the AUC-ROC score of individual class reached above 0.99 and the mean accuracy of the three segmentation classes reached 99%. The average IoU of the three classes is 0.98. The accuracy of the CNN segmentation is of the same order as conventional methods but it is significantly faster.