This work reports on the design and implementation of advanced geospatial simulations using an Agent-Based Model (ABM) integrated with an augmented reality solution for interactive and immersive modeling exploration. The multi-scenario modeling framework allows for emergent phenomena and provides flexible representation of biological and physical environmental factors associated with natural and man-made systems. Augmented reality is provided by a sandbox running Tangible Landscape, based on a customization of GRASS GIS. An integrated Microsoft Kinect sensor mounted over the sandbox captures real-time topography produced by physical interactions with sand and resulting digital elevation models are ingested into the Recursive Porous Agent Simulation Toolkit (Repast) as landscape definition input. We illustrate the implementation by presenting a model system that includes a classic predator-prey relationship over a grassland habitat where sheep and wolves coexist as agents. Food sources for sheep are scattered over the landscape and are consumed as agents forage. Wolves control sheep population by actively searching for sheep and chasing individuals when their presence is detected. We simulate natural conditions by defining that the presence and movement of agents over the landscape is controlled by elevation provided by the sandbox. For instance, the presence of agents and resources can be limited to specific elevation ranges and slope is used to incorporate movement cost (energy loss) while individual agents travel over the landscape. Ecological conditions are further simulated by the consumption and regrowth of food resources. Users interact with the sandbox and the modeling effort by manually moving sand and altering landforms. This effort brings together multiple technologies and data manipulation/visualization strategies and allows for feature-rich experimentation by supporting multiple co-located and georeferenced layers (e.g., land use/land cover, soil, hydrography).

Understanding rock mechanical behavior, especially the onset and nature of yield (i.e. permanent deformation), is critical to ensure safe and sustainable operations in many geological engineering applications, including ‘low-carbon’ subsurface technologies to aid decarbonization. In porous sandstones, yield corresponds to onset of either permanent dilatation or compaction accompanied by microcracking and is defined by a ‘capped’ yield surface in differential stress vs effective mean stress (Q/P) space. Previous studies showed that compactive yield in porous sandstones corresponds to the onset of grain fragmentation and pore collapse, manifested by the deviation of the porosity reduction curve from the hydrostat. However, determining the onset of yield can be ambiguous. Here, we investigate the micromechanical basis for the compactive yield behavior of porous (25%) Hollington sandstone, which is comparable to common aquifers, hydrocarbon and geothermal reservoir rocks and other sandstone formations with potentials for underground storage of fluids (e.g. carbon dioxide and hydrogen). A suite of conventional triaxial compression experiments with concomitant pore volumometry were performed to characterize the mechanical behavior of the rock. Effective mean stress vs porosity reduction data show a slow but near-linear initial deviation from the hydrostat followed by a sharp increase in the rate of compaction for most samples that underwent inelastic porosity reduction below 243 MPa effective mean stress (P*). Synthesis of mechanical with microstructural data suggests that the initial deviation from the hydrostat is related to the collapse of local large pores while the sharp increase in the rate of compaction corresponds to the onset of grain fragmentation leading to widespread pore collapse. Plotting yield stresses in Q/P space reveal a near linear cap of negative slope, albeit with considerable scatter, for stresses related to the collapse of local large pores, evolving into an elliptical cap for stresses approximately corresponding to the onset of widespread grain fragmentation. The results highlight the enhancing influence of non-hydrostatic stresses acting around large pores on the compactive yield in rocks with porosity heterogeneities.

Hydrochemical constituents in streams may originate from currently active sources at the surface and/or legacy sources retained in soil, slow-flowing groundwater and sediments from earlier surface inputs, waste deposits, and land contamination. These source contributions need to be distinguished for effective pollution mitigation and water quality improvement. This study outlines a methodology for such distinction based on some general mechanistic differences in stream concentration and load behavior versus discharge between the contributions from these different types of sources. The methodology is applied to and tested on stream concentration data for chloride, nitrogen, phosphorous, copper, lead, and zinc, and corresponding data for water discharge, measured over recent decades (time series of 1-3 decades) in multiple Swedish hydrological catchments of different scales (10-37 catchments depending on substance, chloride/nutrient/metal, and its monitoring). Mixed sources are indicated in most (18 of 19) catchments for chloride (with average 19% active-source contribution to total load), but only in 3-4 (of 37) catchments for total nitrogen and total phosphorus (32-59% active), and 1-3 (of 11) catchments for copper, lead, and zinc (1-3% active). Only 1 catchment (of 37) is indicated to have dominant active sources for total nitrogen, and most catchments thus have dominant legacy source contributions for all substances. The legacy contributions correlate well with human activity indicators in the catchments (urban areas for chloride, agricultural land share for nitrogen, population density for phosphorus, historic mining and mine waste areas for the metals), indicating that they are largely anthropogenic. The developed and tested methodology is relatively simple and can be used to screen commonly available stream monitoring data for distinction of active and legacy contributions of any hydrochemical constituent in and across various hydrological catchment settings.

Despite significant advances in monitoring of the development of active lava flow fields, many challenges remain. Timely field surveys of active lava flows could improve our understanding of the development of flow fields, but data of sufficient accuracy, spatial extent and repeat frequency have yet to be acquired. Satellite remote sensing of volcanoes is very useful because it can provide data for large areas with a variety of modalities ranging from visible to infra-red and radar. Satellite sensing can also access remote locations and hazardous regions without difficulty. Radar and multispectral satellite sensing data have been shown that can be combined to map heterogeneous lava flows using machine learning techniques, but a robust general model trained with several different lava compositions has to be developed. Here, we propose a robust, automatic approach based on machine learning techniques for analysing open-access satellite data in order to map lava flows in near-real time applicable to different kind of lava with different thermal components (i.e., incandescent, cooling and cooled lava component). We built a neural network model and trained it with a set of satellite images (e.g., Sentinel-1 SAR, Sentinel-2 MSI and Landsat 8 OLI/TIRS) of recent lava flows, and the relative labels of the lava and background regions. In this way, the trained model becomes capable to detect and map lava flows and to classify any new image, when available. The relative output is a segmented image with lava and background classes, obtained without an analysis made by a human operator. This approach allows to segment lava flows with both hot spot and cooling parts, and to recognize lava flows with different characteristics in near-real time. The results obtained during the long sequence of short-lived eruptive events occurred at Mt. Etna (Italy) between 2020 and 2021 are shown.

We expand on previous observations of magnetic reconnection in Jupiter’s magnetosphere by constructing a survey of ion-inertial scale plasmoids in the Jovian magnetotail. We developed an automated detection algorithm to identify reversals in the component and performed the minimum variance analysis for each identified plasmoid to characterize its helical structure. The magnetic field observations were complemented by data collected by the Juno Waves instrument, which is used to estimate the total electron density, and the JEDI energetic particle detectors. We identified 87 plasmoids with ‘peak-to-peak’ durations between 10 s and 300 s. 31 plasmoids possessed a core field and were classified as flux-ropes. The other 56 plasmoids had minimum field strength at their centers and were termed O-lines. Out of the 87 plasmoids, 58 had in situ signatures shorter than 60 s, despite the algorithm’s upper limit to be 300 s, suggesting that smaller plasmoids with shorter durations were more likely to be detected by Juno. We estimate the diameter of these plasmoids assuming a circular cross-section and a travel speed equal to the Alfven speed in the surrounding lobes. Using the electron density inferred by Waves, we contend that these plasmoid diameters were within an order of the local ion-inertial length. Our results demonstrate that magnetic reconnection in the Jovian magnetotail occurs at ion scales like in other space environments. We show that ion-scale plasmoids would need to be released every 0.1 s or less to match the canonical 1 ton/s rate of plasma production due to Io.

This study presents the application of broadband seismic recordings in improving the quality of tidal gravimetric recordings, especially during strong earthquakes. Four sites in Western and Central Europe, where broadband seismometer and tidal gravimeter are collocated, are selected. The data together with transfer functions of instruments from the Black Forest (Germany), Membach (Belgium), and Rochfort (Belgium) are downloaded from the IRIS database. The GWR iGrav-027 superconducting gravimeter is fully operational at the Borowa Gora Geodetic-Geophysical Observatory of the Institute of Geodesy and Cartography (Poland) since late April 2016. Later, the REF-TEK broadband seismometer was installed in the cooperation with the University of Warsaw. The Observatory, also temporally hosts a spring gravimeter, LCR ET-26 (owned by the Warsaw University of Technology). The seismometric and gravimetric signals of high coherence are selected for each site. The complex transfer functions in frequency domain are found by the least square minimization of the seismometric and seismic-corrected gravimetric signal. The transfer functions are calculated when the coherence is significant for two cases: with and without observed earthquake recordings. Next, the estimated transfer functions and the ongoing seismometric recordings are used to improve the quality of tidal gravimetric recordings. The presented method shows a significant reduction of the noise level of gravimetric recordings in a frequency range of seismometer’s operability. In order to obtain reliable models of the Earth’s structure based on analysis of surface waves recorded by tidal gravimeters, the careful estimation of gravimeters’ transfer functions in the seismic frequency range is necessary. The transfer functions of iGrav-027 and ET-26 were determined by the step response method during the experiments in 2018-2019. Now, thanks to the presented research, their quality can be verified. The limitation of this verification can be tested on recordings of Black Forest, Membach and Rochfort with very well-determined and documented transfer functions of tidal gravimeters. This work has been done in the research project No. 2017/27/B/ST10/01600 financed from the funds of the Polish National Science Centre.

In this presentation, we highlight undergraduate research approaches and projects at Smith College, the largest college for women in the United States. We share lessons learned along with current challenges to spark conversation and improvement. We comprise a hydrologist (Guswa), environmental engineer (Ismail), and aqueous geochemist (Rhodes), and we investigate the effects of landscape, land management, and natural infrastructure on water quality and water resources. Rhodes and her students carryout field work and laboratory analyses to determine the impacts of development on water chemistry, and a recent project investigates the fate and transport of road salt in a calcareous fen in western Massachusetts. Ismail and her students conduct laboratory experiments to assess the efficacy of filter-feeding organisms to improve water quality in natural systems. A recent project determined how environmental conditions affect the uptake of bacteria by zooplankton. Guswa and his students use models to understand the interactions among climate, landscape, and water resources, and a recent project explores the effects on peak flows of a set of plausible land-use futures for New England in 2060. As undergraduates, students join these projects with limited relevant coursework and research experience. We find that undergraduate engagement is best facilitated by activities that are skill- or technique-based (such as making careful measurements) rather than those based on a deep understanding of theory. Additionally, multiple scales of involvement (e.g., newer students attending group meetings and more senior students designing experiments and serving as peer mentors) allow students to explore potential interests and possibly persist to richer levels of involvement.

We investigated the American low-latitude ionosphere around 75°W during the two 2013 sudden stratospheric warming (SSW) events: one in quiet geomagnetic conditions, and the other overlapped by a minor geomagnetic storm using total electron content (TEC) data from 12 Global Positioning System (GPS) receivers. A pair of magnetometers revealing the varying inferred vertical E X B drift and the NASA Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite airglow instrument to understand the global changes in the neutral composition, O⁄N_2 ratio are also used. The late morning inferred downward-directed E X B drift during the first major SSW did not support the varying equatorial ionization anomaly (EIA) signature. However, during the second major SSW, the well-reported and enhanced late morning inferred upward-directed E X B drift relocated a northern EIA crest to higher latitudes. Interestingly, the effect of a minor geomagnetic storm on 17 January 2013 that modulated the ongoing second SSW reduced the maximum inferred upward-directed E X B drift. The second major SSW contribution to the northern crest is higher than photo-ionization and the first major SSW contribution, while each major contribution is higher than minor warming. The minor geomagnetic storm reduced the effect of the second major SSW on the TEC from 58% to 50% and 28% to 20% at the northern and southern crest, respectively. Also, the storm’s overall effect of - 1 % (22 %) leads to a slight reduction (enhancement) in TEC magnitude at the northern (southern) crest.

Flare suprathermal ions with enhanced 3He and heavy-ion abundances are an essential component of the seed population accelerated by CME-driven shocks in gradual solar energetic particle (GSEP) events. However, the mechanisms through which CME-driven shocks gain access to flare suprathermals and produce spectral and abundance variations in GSEP events remain largely unexplored. We report two recent GSEP events: one observed by Solar Orbiter on 2020 Nov 24 (the first GSEP event on Solar Orbiter) and the other by ACE on 2021 May 29 (the most intense GOES proton event in the present solar cycle). The events were preceded by impulsive SEP (ISEP) events. Abundances and energy spectra are markedly different in the examined events at < 1 MeV/nucleon. For example, in the May event, Fe/O is typical of ISEP events, a factor of 100 to 10 higher than Fe/O in the November event. 3He abundance in the November event is high, typical of ISEP events, while in the May event, it is much lower, though finite. The May event shows a hard 4He spectrum with a power-law index of −1.6, and the November event a soft spectrum with an index of −3.5. The events were associated with halo CMEs with speeds around 900 km/s. The November event was also measured by Parker Solar Probe and the May event by STEREO-A and Solar Orbiter. This paper discusses the origin of vastly different abundances and spectral shapes in terms of variable remnant population from preceding ISEP events. Furthermore, we discuss a possible direct contribution from parent flares.

Knowing the centimeter- to meter-scale distribution of sand in clayey deposits is important for determining the dominating water flow pathways. Borehole information has a high vertical resolution, on the millimeter- to centimeter-scale, but provides poor lateral coverage. For highly heterogeneous deposits, such as glacial diamicts, this detailed borehole information may not be sufficient for creating reliable geological models. Crosshole ground-penetrating radar (GPR) can provide information on the decimeter- to meter-scale variation between boreholes, as the GPR response depends on the dielectric permittivity, electric conductivity, and the magnetic permeability of the subsurface. In this study, we investigate whether crosshole GPR can provide information on the material properties of diamicts, such as water content, bulk density, and clay content, as well as their structural relationships. To achieve ground truth, we compare the crosshole GPR data with geological information from both boreholes and excavation at the field site. The GPR data were analyzed comprehensively using several radar wave attributes in both time- and frequency domain, describing the signal velocity, strength, and shape. We found small variations in signal velocity (between 0.06-0.07 m/ns) but large variations in both amplitude and shape (either order of magnitude variation or doubling/tripling of attribute values). We see that the GPR response from wetter and more clayey diamicts have both lower amplitudes and lower centroid frequencies than the response from their drier and sandier counterparts. Furthermore, we find that the variation in amplitude and shape attributes are better correlated to the diamicts’ material properties than the signal velocity is.

Mapping wetland types in northern-latitude regions with Earth Observation (EO) data is important for several practical and scientific applications, but at the same time challenging due to the variability and dynamic nature in wetland features introduced by differences in geophysical conditions. The objective of this study was to better understand the ability of Sentinel-1, Sentinel-2 and terrain derivatives derived from Copernicus DEM to distinguish three main peatland types, two upland classes, and surface water, in five contrasting landscapes located in the northern parts of Alaska, Canada and Scandinavia. The study also investigated the potential benefits for classification accuracy of using regionalized classification models constructed from region-specific training data compared to a global classification model based on pooled reference data from all five sites. Overall, the results show high promise for classifying peatland types and the three other land cover classes using the fusion approach that combined all three EO data sources (Sentinel-1, Sentinel-2 and terrain derivatives). Overall accuracy for the individual sites ranged between 84% to 92%. Class specific accuracies for the peatland types were also high overall, but differed between the five sites as well as between the three classes bog, fen and swamp. A key finding is that the regionalized classification models consistently outperformed the global classification by producing significantly higher classification accuracies for all five sites. This opens for promising progress in terms of identifying effective approaches for stratifying northern-latitude areas for continental scale peatland classification.

The analysis of Very Low Frequency (VLF, 3-30 kHz) radio back-scattering can be used to measure the impact of lightning on the D region of the ionosphere (60-90 km). Early/fast events are prompt and rapid changes to the D-region ionosphere associated with certain lightning flashes, causing heating, ionization, and attachment. Previous work has observed the behavior of early/fast events and their connection to specific types of lightning flashes through VLF remote sensing and lightning geolocation, but the unique nature of each event makes it difficult to broadly infer the interactions between lightning and the ionosphere using a small number of case studies. We assembled a massive database of VLF amplitude samples for cases when high intensity lightning occurs near a transmitter-receiver path. We constructed an artificial neural network to detect and label early/fast events. With a large volume of events compiled, we charted detailed statistics of event occurrences and behavior. We find a correlation between lightning current magnitude and event likelihood, as well as inverse correlation between event likelihood and distance to transmitter-receiver path. We further confirm the asymmetry of the peak current trends, with positive-current strokes being significantly more likely to produce an event. We find that increased distance of the lightning to the transmitter, and to a lesser extent to the receiver, decreases the probability of an ionospheric disturbance. We find that recovery time is largely not a function of the peak current. We do not find evidence that long-recovery events are a distinct class of Early/Fast events.

The structure of the lowermost mantle and the core-mantle boundary (CMB) has profound implications for Earth’s evolution and current-day dynamics. Whilst tomographic studies of Vs show good agreement in the lowermost mantle, consensus as to Vp and especially CMB radius has not yet been reached. We perform a hierarchical Bayesian inversion for Vp in the lowermost 300 km of the mantle and the radius of the core-mantle boundary using differential travel time data. Concurrent with finding Vp perturbations of 0.56% RMS amplitude that spatially agree with previous studies in areas of low posterior variance, we find 4.5 km RMS amplitude core-mantle boundary radius perturbations with a broadly north-south hemispherical character, with spherical harmonic power evenly distributed between degrees 1-3. These results suggest that CMB radial processes are set by a longer scale process than the Vp perturbations.

The Southern Annular Mode (SAM) is the leading mode of atmospheric variability in the extratropical Southern Hemisphere, and its variations affect westerly winds, regional storm tracks, midlatitude wildfire activity, Antarctic and Southern Ocean dynamics, and surface mass balance. The SAM is therefore of high importance to both ecosystems and societies across the Southern Hemisphere. The behavior of the SAM has been extensively studied during the instrumental era, but there is substantially less confidence and considerable disagreement in its decadal to centennial-scale variability over the Common Era. Studying these longer time scales requires millennial-length reconstructions, but the sparsity of multi-century proxy records in the Southern Hemisphere has hindered the production of such reconstructions. Consequently, variability and trends in the SAM remain uncertain through most of the Common Era. Here, we use paleoclimate data assimilation to reconstruct the austral summer (DJF) SAM index (SAMI) over the entire Common Era. Our method integrates the South American Drought Atlas, Australia-New Zealand Drought Atlas, and the PAGES2k temperature-sensitive proxy network with a multi-model ensemble of last millennium GCM simulations using an offline ensemble Kalman Filter with a stationary prior. We use a novel nested variance adjustment to correct for the effect of changing proxy availability through time. Our reconstruction is not calibrated to the observed SAMI, yet exhibits a correlation coefficient greater than 0.6 over the instrumental era. Using superposed-epoch and wavelet analyses, we find the reconstruction exhibits minimal response to volcanic and solar forcings and is instead dominated by internal climate variability until the late 20th century. Our data assimilation framework also facilitates the use of optimal-sensor analysis, which we use to identify key proxy sites at different time periods in the reconstruction. Prior to 1400 CE, the reconstruction is strongly influenced by two tree-ring records (Mt. Read, Tasmania and Oroko, New Zealand) and two ice-cores (WDC05A and Plateau Remote). Finally, we examine the coherence of our results against existing reconstructions and compare reconstructed 20th century trends with the instrumental record.

Cheniers are ridges consisting of coarse-grained sediments, resting on top of the fine sediment that forms the otherwise muddy coast. In this paper, we use Delft3D to explore how cheniers are formed through wave winnowing. We identify three phases of chenier development: (1) a winnowing phase, during which mud is washed out of the seabed initially consisting of a mixture of sand and mud, (2) a sand transport phase, when the sand in the upper layer is transported onshore, and (3) a crest formation phase, during which a chenier crest rapidly develops at the landward limit of onshore sediment transport. The main mechanism driving onshore sand transport is wave asymmetry. During calm conditions, sand transport takes place within a narrow band limiting the volume of sand delivered nearshore, and therefore no chenier develops. In contrast, average storm conditions mobilise sufficient sand for a crest to develop. Our results thus reveal that chenier formation through wave winnowing does not require extreme storm conditions. Furthermore, our study showed that chenier formation through wave winnowing is a relatively slow process, with the largest time scales associated with the winnowing and sand transport. Once sufficient sand is available nearshore, the crest develops rapidly.

Multiple organic proxies and lipid biomarkers in the sediment core samples collected from Luoma Lake and Hongze Lake in Jiangsu are used to expound the relationships of global warming with lacustrine productivity and depostion of polycyclic aromatic hydrocarbons. Total organic carbon, S2, and hydrogen index in sedimentary organic matter were obtained with the Rock-Eval analysis. Nutrient status such as total phosphorus and total nitrogen was measured in the sediment cores. The source apportionment modeling and statistical analyses demonstrated that algal organic matter and bacteria organic matter showed an increasing trend and an obvious enrichment effect on PAHs, which was also related to the increasing temperature and algal productivity in the lakes. Global warming enhanced the lacustrine productivity and the accumulation of polycyclic aromatic hydrocarbons. The rapidly increasing ecological risks of PAHs in LM and HZ indicated the impact of global warming and human activities in the last 60 years. Therefore, the internal cycling and the input of contaminants and nutrients in the lakes should be controlled to reduce the algal growth in LM and HZ.

We investigated historical changes in temperature and phytoplankton in Fuxian Lake (FX) and Dianchi Lake (DC), two plateau lakes in Southwest China. We detected sterols and alkyl diols as algal biomarkers (Dinoflagellates, Diatoms, Eustigmatophytes, Cyanobacteria, and Chlorophyta) in the sediment cores by using GC-MS. We characterized sedimentary organic matter (SOM) via C-13 isotope and C/N ratio, and Rock-Eval analysis to obtain total organic carbon (TOC), S2, the hydrogen index (HI), refractory carbon (RC), and nutrient status such as total phosphorus (TP) and total nitrogen (TN) in the sediment cores. The results showed that the sedimentation rates measured by 210Pb dating ranged from 0.02 to 0.30 g cm-2 yr-1 and 0.07 g cm-2 yr-1 in FX and DC, respectively. The Bayesian isotope mixing model indicated that organic matter from plankton was the main contributor of organic matter in FX and DC and, its contents was gradually increasing . Primary productivity derived from the S2 and HI parameters showed an increasing trend in FX and DC. Cyanobacteria and Chlorophyta were the two dominant phyla in the two lakes. Algal growth was controlled primarily by temperature and nutrient availability. Principal component analysis (PCA) and multiple linear regression analysis showed that the major factors controlling the historical change in phytoplankton growth were TN and temperature in FX and DC.

Climate scenario dataset are indispensable for assessing future climate impacts. In this study, we developed statistically downscaled climate scenarios in Japan using modified bias correction method based on five general circulation models selected from the Coupled Model Intercomparison Project (CMIP) Phase 6 to facilitate impact assessments and adaptation strategies. Modification of time window of the original correction method results in successful agreement with the observed seasonal change of variables in each grid. The original CMIP6 models have a relatively small bias compared to CMIP5 models. The CMIP6-based bias-corrected scenarios are available for use with the emissions scenario of representative concentration pathway (RCP) 4.5 in addition to RCP2.6 and RCP8.5. Several temperature-related indices derived from the CMIP6-based climate scenarios agreed well with observations. The number of extremely hot days and nights increased nonlinearly in the future with additional global warming. An increase in the global warming level from 1°C to 2°C above the early 1900s would increase the probability of the number of extremely hot days per year exceeding the 2018 case by 4.1 times. The development of bias-corrected climate scenarios facilitates the study of various climate impacts on a CMIP6 basis.