The cycling of carbon within the earth system is intrinsically linked with major nutrients, notably nitrogen and phosphorus, due to the tendency of these elements to limit the productivity of terrestrial ecosystems. To understand the response of the carbon cycle to global change pressures, models must integrate Carbon-Nitrogen-Phosphorus cycles. Whilst such models exist, to-date these have focused on natural and semi-natural ecosystems. Agriculture results in significant modification to natural biogeochemical cycling, and currently represents approximately 37% of land-use. With the projected increase in global food demand over the 21st century, this area is expected to increase. It is therefore critical to understand and simulate biogeochemical cycling in both natural and agricultural systems, and the transition between these, to estimate ecosystem response to environmental change. In this study we present an integrated C-N-P model including both natural and agricultural temperate ecosystems. The N14CP model has been developed to include representation of both arable and grassland systems, with the inclusion of agricultural management practices such as fertilizer application, crop removal, grazing and yield estimation. The model has been tested both spatially and temporally using a range of long-term experimental sites across Northern-Europe, and applied at both local and national scales. We use the model to assess impacts of land-use change and management on long-term nutrient cycling, and discuss the implications of this for sustainable agriculture and ecosystem functioning.

Stochastic physics (SP) schemes provide a more realistic representation of the unresolved scales in global circulation models by improving both mean climate and climate variability. We study the impact of including an SP scheme in the atmospheric component of EC-Earth on the simulated climate. In particular, we analyze the evolution of the sea-ice extent in the Arctic during long-term simulations covering the historical and future periods. The experiments consist of coupled climate simulations in which three ensemble members constitute the control runs (base) and three ensemble members include stochastic physics (stoc). For the latter, the Stochastically Perturbed Parametrization Tendencies (SPPT) scheme is incorporated in the atmospheric component of EC-Earth. The original experiments, that are part of the SPHINX project, span from 1850 to 2100. We have additionally extended each simulation for 60 years; the future scenario corresponds to the CMIP5 RCP8.5 set up. We compare both sets of experiments to investigate the climate response to a perturbed atmosphere. The simulated Arctic sea-ice extent in September and March display an overall decrease. The sea-ice loss results faster in the base experiments than in the stoc ones. The model simulates an abrupt sea-ice loss in March that takes place about 10 years earlier in the base experiments than in the stoc ones. The evolution of the global annual mean surface air temperature differs if the SP is on or off. Curves start separating by the second half of the 20th century; reach the maximum difference in 2100 and become almost indistinguishable around 2110. Our results suggest that the transient climate sensitivity is lower when the SP is on than when it is off during the 21st century. However, the opposite occurs when the Arctic is free of sea ice along the whole year. This behavior might be the consequence of the asymmetric effect of stochastic perturbations on the process of condensation. We are now investigating the differences in the albedo and cloud feedbacks between both sets of experiments and the possible influence of the mean state on the model climate sensitivity.

This study provides a new, detailed, and fully three-dimensional structural interpretation of the active convergent plate boundary beneath the outer Nankai accretionary wedge offshore Kii Peninsula in SW Japan. Structural interpretation was done using the 12 by 56 km 2006 Kumano 3D seismic reflection volume, with the goal of providing new insights on the structural, temporal, and spatial evolution of the shallow plate boundary megathrust. Results of the structural analysis suggest three decollements with complex, three-dimensional geometries that have played a role in constructing the outer Nankai wedge in the study area, only one of which shows recent activity. Based on comparison to sandbox models and the presence of a modern, partially subducted seamount, their development and evolution are linked to past and present subduction of oceanic crust with signicant relief, including the Paleo-Zenisu Ridge east of the study area. Other characteristic features of the outer wedge likely developed from the effects of basement relief subduction as well, including the low velocity zone, along-strike variation of imbricate thrusts, prominent along-strike ridges across the margin, and several laterally discontinuous strike-slip faults. Evidence that the outer wedge evolved through several phases of basement relief subduction has strong implications for the mechanical properties of the deeper, seismogenic portions of the megathrust. Other studies suggest subduction of basement relief correlate with low slip-decit rates, VLFs, and slow slip, and may act as a barrier to coseismic rupture. Therefore, the results of this study can be applied to convergent margins with similar tectonic settings around the world to better understand the link between basement relief subduction, decollement and wedge evolution, and seismogenic behavior.

Each year the PRSN detects ~4,000 earthquakes within and around Puerto Rico, the Virgin Islands and the Eastern Dominican Republic. Given the seismic hazard presented by this earthquake activity it is critical to perform systematic and continuous studies aimed at understanding and mitigating the impacts of earthquakes. The major effects to a site are due to seismic wave amplification at specific frequencies caused by local unconsolidated sediments during strong ground motions. Therefore, it is important to recognize and mitigate these. The Puerto Rico Seismic Network (PRSN) at the University of Puerto Rico, Mayagüez (Recinto Universitario de Mayagüez [RUM]) and the Puerto Rico Strong Motion Program (PRSMP), in collaboration with the United States Geological Survey (USGS) are conducting a passive-source seismic experiment to investigate the potential for seismic amplification by soils in Mayagüez, Puerto Rico. The goal of this experiment is to quantify the potential soil amplification in Mayagüez, which is located in the western portion of the island. This region experienced significant damage from shaking in the 1918, 7.3 Mw earthquake offshore of western Puerto Rico, making it a prime target for a pilot study to examine soil amplification. Local soil and bedrock conditions in Mayagüez are similar to other areas of the Caribbean, so results will have implications throughout the region. For this study, eleven L-22 sensors with Reftek RT130 recorders were installed in April 2019 to collect data for a period of six months. Since this time, there have been sixty-one M3 or greater earthquakes in the region per month and six M6.5 or greater teleseisms that should provide data suitable for analysis. Data are currently being analyzed using simple spectral ratios of soil sites to bedrock sites. We will present information about the deployment, experiment goals, and preliminary results. The results of this experiment will provide data to refine future hazard mapping and ground motion models of the island.

The holy grail of ExoPlanet research is finding and characterizing terrestrial planets orbiting in the habitable zones of a neighboring stars. The first question to be answered is: does the planet have an atmosphere, and what is it’s composition. Theory and observation confirm that the one universal atmospheric component should be CO_2. Hence a successful mission must determine it’s presence. The most direct path to detection is through the enormously strong 15 micron vibration-rotation feature of CO_2, hence the technology we’re developing. Because of the CO_2 in the earth’s atmosphere, this requires a space observatory, such as the JWST. Our technology can also be used to detect water vapor and ozone in exoplanet atmospheres, the latter of which indicates abundant life, probably indicative of a ‘Cambrian Explosion’ event on the exoplanet.

Reconnection in the magnetotail transfers magnetic energy to thermal and kinetic energy in ions and electrons. These particles are injected both Earthward and tailward from the reconnection region. The Earthward particles are transported to the inner magnetosphere where they drive the ring current and radiation belts. The injections are observed in the plasma sheet in conjunction with dipolarizations of the magnetic field. The particles have been found to travel within narrow flow channels, rather than broadly across the magnetotail, in spatially and temporally localized events known as bursty bulk flows (BBF). Simulations of such events show these narrow flow channels moving from the reconnection region to the injection region. However, global observations are needed to understand how BBFs connect the reconnection region and the inner magnetosphere during storms and substorms. Ion heating has been observed with in situ measurements at the reconnection region and within the dipolarization fronts and BBFs. Using energetic neutral atom (ENA) imaging, ion temperature maps can be calculated to provide such global observations. Regions of ion heating have been observed in these maps and comparisons with in situ measurements demonstrate that they are associated with these phenomena. An automated identification algorithm has been developed and run on our database of storm-time ion temperatures. We will present the results of case and statistical studies of the characteristics of these features.

Generation Z (Gen-Z) is composed of those born in the late 1990’s or after. The first cohorts of Gen-Z students gradually started to enter colleges after 2013. Gen-Z students are very different than millennials in almost all aspects. They are more likely to reject the traditional and conventional teaching methods that lack active learning components. A shift towards modern and interactive student-centered methods is being implemented by a new generation of instructors to better serve Gen-Z needs. However, this transition from passive lecture-based instruction to active learning methods is hindered by a gap that we call “the missing step”. This missing step in the transition phase refers to training and preparing future faculty to adopt research-based instructional strategies. My fellow aspiring professors and I were mostly educated via old-school methods. Without proper training on STEM teaching, we were likely to approach our teaching by modeling what we saw. If granted the opportunity to teach engineering in a faculty role, we would have come into it lacking teaching theory and instructional strategies rooted in engineering education. If a new instructor is not familiar with subjects such as “active learning”, “backward design”, “evidence-based instructional strategies”, “flipped classroom”, and “Bloom’s revised taxonomy”, or is not acquainted with importance of modern classroom assessment techniques, rubrics, and motivation strategies, the result will be an unfillable gap between the instructor and the Gen-Z students. I was in the first cohort of Ph.D. students who completed the College of Engineering’s graduate teaching fellowship program at the University of Nebraska-Lincoln. This one-year, well-structured, peer-observation program gave me invaluable knowledge about teaching following the research, helped me in designing a course in Canvas system, taught me how to write my teaching philosophy properly, and prepared me to achieve the CIRTL associate status. Starting such a program in every school for interested graduate students can make a significant difference. I will present my perspectives on the program and its impact.

This study determines the rates of subsidence or uplift in coastal areas of SE Texas by comparing recent GNSS measurements to the original orthometric heights of 340 previously installed National Geodetic Survey (NGS) benchmarks. Understanding subsidence rates in coastal areas of SE Texas is critical when determining its vulnerability to local sea level rise and flooding, as well as for accurate elevation control for flood risk maps. The study area includes major metropolitan and industrial areas as well as more rural areas at risk for flooding and hurricane storm surge. The resurveying methods used in this RTK GNSS study allow a large area to be covered relatively quickly with enough detail to determine subsidence rates that are averaged over several decades, and identify at-risk regions that can be monitored more closely with permanent or campaign-style measurements. Overall, vertical rates vary from -6 to -15 mm/yr subsidence in Port Arthur, Nederland, and other areas of Jefferson County, as well as in areas northwest of Beaumont, Texas. Other areas with subsidence rates between -10 and -4 mm/yr include parts of the Bolivar Peninsula in Galveston County, northeastern Chambers County, and the Mont Belvieu area just east of Houston. Current benchmark elevations were as much as -0.86 m lower than the original, illustrating the need for height modernization surveys in the area. Surprisingly, areas of uplift, with rates as great as +5 mm/yr, were found in some parts of the study area. Several of the counties in the study area are experiencing inundation and erosion from global sea level rise, with local subsidence exacerbating the problem. Many of the counties in the study area were also affected by the storm surge from Hurricane Ike and flooding from Hurricane Harvey. Understanding the current elevation in these areas, as well as the rates of change in elevation, is critical for creating updated flood plain maps and surge inundation models, as well as planning how these maps and models will likely change in the future. Understanding how rapidly the elevations are changing is also critical for planning and maintaining flood and surge protection infrastructure projects such as levees, dune restoration, marsh restoration, and raising of structures to prevent flooding well into the future.

Archaeological evidence suggests that the interior of the Australian continent was first occupied during the Mid-Holocene. It is agreed that the general climate of Australia during this time was warmer and wetter, but the absence of reliable palaeoclimatic proxies in the arid interior makes precise localized reconstructions difficult. In addition, the main determinants of the patterns of human settlement of the interior is not well known. This study presents a thorough review of palaeoenvironmental proxy data and archaeological data of Mid-Holocene Australia coupled with hydrological and palaeoclimatological modeling approaches to determine what most strongly influenced the patterns of human occupation of the interior. This paper is the first to employ a reconstructive groundwater table depth model to determine if permanent and accessible subsurface water influenced the locations of human settlement. Results show that most of the Australian continent experienced wetter conditions during the Mid-Holocene which corresponds with an enhanced Northern Australian Monsoon. This study determines that groundwater table depth and elevation were the predominant determinants of human settlement patterns of the Australian interior.

We present our results on the second year of TOTO-Cheyenne (TGFs On Top Of Cheyenne), a continuing collaboration of the US Air Force Academy and the Naval Research Laboratory. The project’s goal is to study the ionizing radiation as lightning strikes near the antenna farm on the top of Cheyenne Mountain, near Colorado Springs CO. Thunderstorms and accompanying lightning produce ionizing radiation on time scales from milliseconds to minutes. This radiation includes terrestrial gamma-ray flashes, hard X-rays from stepped leaders, gamma-ray glows, and thunderstorm ground enhancements. Recent measurements indicate that getting up close and personal with the storms might produce more details about the complex processes inside. The US Rocky Mountains offer the opportunity to do just that by getting closer to the charge layers. This year’s experiment (starting in May 2019 and continuing to October 2019) involved the setup of a high speed camera at the Air Force Academy facing south to watch Cheyenne Mountain plus the reinstallation of a small gamma-ray and X-ray detection system (NaI and plastic scintillators) on the mountain. This year has proven to be a very active storm year. As of 20 July, there were already 25 strikes within 2 km of the detector (compared to 1 strike during the summer 2018).

We discuss an efficient implementation of the analog ensemble algorithm, the distilled analog ensemble, which is achieved by distilling the post-processing transformation generated by the analog ensemble into a deep neural network. While the analog ensemble has been shown to be able to improve deterministic forecasts and create calibrated probabilistic predictions in many contexts, a common issue with operationalizing a large, global analog ensemble-based system is the amount of data (a corpus of historical forecasts) and post-processing latency required to process that data in the time-critical path of producing a forecast. Deep neural networks are high capacity function approximators, and we demonstrate that we are able to train a network that memorizes the post-processing behavior of the analog ensemble on a particular corpus of forecasts. This technique breaks the scale factor between the size of the historical forecast corpus (larger is better for forecast skill improvements) and the calculation required to post-process the current forecast in real-time operations. We show that the distilled analog ensemble is able to improve European Centre for Medium-Range Weather Forecasts (ECMWF) high-resolution deterministic forecasts of winds in the lower stratosphere using as ground-truth either the ECMWF analysis or observations from Loon high altitude balloons. In this case, rather than requiring terabytes of historical forecast data to apply the conventional analog ensemble, we can perform the post-processing that improves forecast quality on the fly doing computationally efficient forward passes through a pre-trained network that has a data size of only 100’s of kilobytes.

A new diver-held magnetometer has been developed that directly senses the total magnetic gradient as a scalar quantity, independent of the orientation of the device. It therefore provides a direct signal if a magnetic (e.g. ferrous) object is in its vicinity, regardless of other ambient geomagnetic effects. The small (7cm diameter x75cm length), battery-powered device is neutrally buoyant, and provides a simple and intuitive audio interface to the diver. The device was field tested in July 2019 during the Lost Ships of Cortés Project offshore Villa Rica, Mexico, an area with strong underlying volcanic geology and large quantities of magnetic sediment that mask buried archaeological materials. Magnetic anomalies were recorded during boat-towed total-field magnetometer surveys, but divers could not identify their source using traditional underwater metal detectors. The new magnetometer decisively and precisely guided divers to an early 16th-century anchor at a range of several meters that was completely buried in magnetite-rich sand with its shallowest point at 50cm below the sea floor.

Tourmaline is a common mineral in Sn-W mineralizations. It is commonly strongly zoned, both optically and chemically, and may host a range of trace elements. High levels of Sn have been observed in tourmaline throughout the world, whereas W is typically very low, even in mineralized areas. Tourmaline from subeconomic cassiterite mineralizations and hydrothermally altered granite from the Land’s End granite, SW England, was analyzed by EPMA in order to identify Sn-rich zones. LA-ICP-MS is typically the go-to instrument for trace element analyses, but spatial resolution is strongly compromised compared to EPMA. The behavior of Sn in tourmaline varies from patchy to concentric zoning between different samples, and the highest recorded value was 2.48 wt% SnO2 in a patchily zoned rim. A high resolution WDS map of the area did not show any major Sn spikes, and TiO2, a common minor element in cassiterite, is low in the Sn-rich regions. Also, cassiterite in these samples are commonly light brown in plane polarized light, and the Sn-rich zones can be related to dark green zones. This indicates that the high Sn-values are not due to cassiterite inclusions, and may be structurally bound in tourmaline, most likely substituting into the Y-site. The highest Sn-values (>0.4 wt% SnO2) are coupled with a substantial substitution of Fe for Al in the Z-site, and the structural formula calculation indicate that some Fe is present as Fe3+ in the analyses with over ca. 20 wt% FeO. Trends between Sn and other elements are erratic, except for a weak positive correlation with Sr. The Sn-content in tourmaline combined with the inferred Fe3+ and the observed cassiterite in the samples may indicate that oxidation of the ore fluid caused cassiterite precipitation.

Recent fast developments of satellite magnetic observations facilitate global Lithospheric Magnetic Field (LMF) modelling and their applications to subsurface tectonics. Here, the vertical component (Bz) of LMF at an altitude of 200km in Mainland China and surroundings is calculated from two global LMF models NGDC-720 and EMM2017. Next, Bz is used to invert the Curie Point Depth (CPD) by Equivalent Source Dipole (ESD) forward and Nonlinear Conjugate Gradient Method (NCGM) inversion scheme. Then, the surficial Heat Flux (HF) is derived by a simple one-dimensional steady heat conduction equation from the CPD distribution. At last, the continental seismicity is compared statistically to Bz, CPD and HF. Our essential conclusions are as follow: 1) Histograms and boxplots show that most (81.8%) earthquakes (EQs, Ms≥5.0) occurred in negative Bz areas, and more than a half (53.2%) number of EQs (corresponding to an energy percent of 94.6%) occurred inside areas with Bz between -5 and -3nT, in a period between 2004 and 2007, which is the same with the satellite data collection. When the time span is extended (most to 110 years), these phenomena maintain while weaken; 2) Most (88%) EQs occurred in areas with CPD between 10 and 30km, while only a few (7% and 5%) occurred in shallow (<10km) and deep (>30km) CPD areas, in a period between 2000 and 2010; 3) EQs seldom occurred inside cold areas (HF<50mW/m2), and are prone to occur in warm areas (HF>120mW/m2). EQs are also prone to occur along the boundaries of warm or cold areas. The mechanism of the correlations between EQs and Bz, CPD and HF maybe the lithospheric strength jumps caused by the temperature variations at boundaries between blocks with different CPDs.

Tephra fallout hazard assessment relies on accurate reconstruction of eruption source parameters (ESPs) from tephra deposits. Models of tephra transport and sedimentation from a volcanic plume use ESPs (e.g. erupted mass, column height, mass eruption rate, total grain size distribution) that characterize the processes and the properties of the plume, particles and the atmosphere. We use Tephra2, an Eulerian model of tephra dispersion that simplifies atmospheric dynamics to reconstruct ESPs from mapped deposits. Tephra2 works well in reconstructing ESPs for some deposits, however it does not account for the geometry (i.e. shape) of umbrella clouds of large explosive eruptions. Since the accumulation of particles on the ground is calculated with respect to their release point in the atmosphere, we hypothesize that a modification of Tephra2 that accounts for umbrella clouds would better explain the deposit variations observed in the field associated with some large eruptions. We developed a Python version of Tephra2 that uses the advection – diffusion equation to calculate the mass accumulation of tephra released from an umbrella cloud. We tested three different geometries (i.e. point, vertical line and horizontal disk) against field data from the deposit of the 2450 BP Pululagua (Ecuador) eruption that occurred in absence of wind. Our preliminary results indicate three important aspects of tephra modeling: i) a disk geometry characterizing an umbrella cloud fits the data better than the line and point sources, the last two being highly sensitive to the atmospheric diffusion coefficient; ii) a disk geometry is sensitive to the volume of tephra and the radius of the disk and, iii) different discretization of disk geometries show little sensitivity in deposit geometry with change in the release height, suggesting that disk radius is a more sensitive parameter in modeling large umbrella clouds than the release point or release height. Since large explosive eruptions are characterized by large laterally spreading umbrella clouds even when advected by wind and the umbrella diameter is controlled by eruption rate, as is plume height in vertical plumes,, we suggest the modeling of large deposits with alternative models of the cloud geometries is an important step in analysis of ESPs associated with mapped deposits.

Coupled reservoir flow and geomechanics receives a growing research interests for applications in unconventional oil & gas recovery and geological CO2sequestration. For CO2 sequestration, accurate prediction of the behavior of the injected CO2 is important to the long-term success of the sequestration because even small leakage rates over long time periods can unravel the positive outcomes of net CO2 sequestered. Furthermore, the effect of high rates of injection of CO2 on natural fractures is crucial in determination of earthquake effects. High fidelity multiphysics models are needed to simulate these processes and their interactions accurately and efficiently to ensure the success and safety of the operations. Coupled flow-geomechanics simulations are computationally expensive and most of the computational time is usually spent on geomechanics updates. We present a three-way coupling algorithm for both single phase flow and compositional flow coupled with linear poroelasticity. An error indicator is calculated at each flow time step to determine when displacement must be updated and whether fixed-stress iterative coupling technique is required. Convergence of the three-way coupling is established by extending previous work on a priori analyses of fixed-stress iterative coupling. Numerical results for Mandel’s problem confirm these theoretical results for single phase flow. Numerical results for coupled compositional flow and geomechanics simulations for field-scale CO2sequestration and surfactant-alternating-gas (SAG)-assisted CO2 sequestration achieve a substantial reduction in mechanics update times for 99.4% and 97.5%, respectively.

Fast transients in the form of spiky radio bursts have been observed in solar flares events, emitting at different ranges in frequency. These dynamical phenomena show up as high brightness temperature increments with short durations of the order of milliseconds. In this work, we present results of the analysis of some properties of radio spike events observed at frequencies between 0.01 and 8.4 GHz, as reported in different studies. We analyze the relation of the duration, bandwidth, emitted flux, polarization and drift rate of the radio spikes with its observational frequency. Also, we analyze its correlation with other energetic solar events.

Research on modification to snowpacks as a result of forest disturbance has typically focused on spatiotemporal patterns of snow depth and snow water equivalent, snowpack energy fluxes, and melt/ablation characteristics. However, little work has been conducted on relationships between tree trunks and snowpack dynamics. Insight into drivers of internal snowpack thermodynamics around trees and their response to forest disturbance is crucial to understanding hydrological processes in forested regions of the cryosphere, especially as forest disturbance through climate change continues. This work investigates relationships between energy fluxes and thermodynamic patterns surrounding tree trunks and within the greater snowpacks of forest stands in the Snowy Mountains of the Australian Alps. Measurements of vertical and horizontal snowpack temperature profiles and sub-canopy energy fluxes were collected during the 2018 winter season in non-disturbed and fire-disturbed Eucalyptus pauciflora (Snow Gum) stands. Primary heat sources were identified for each measurement location in the snowpack through employing the Random Forest machine learning regression method. Preliminary results indicate that soil heat flux is the dominant control on snowpack temperature at all locations in the un-disturbed forest stand. However, outgoing longwave radiation is shown to be the prevalent driver at numerous locations within the fire-disturbed stand that are close to the snowpack surface and tree well. This work aims to develop the physical basis for a 3-dimensional thermodynamic model of snowpacks contained in forests that could be used in conjunction with existing 1-dimensional snowpack models to determine melt and variability.