We develop a Hamiltonian Monte Carlo (HMC) sampler which solves a multi-parameter elastic full-waveform inversion (FWI) in a probabilistic setting for the first time. This gives novel access to the full posterior distribution for this type of highly non-linear inverse problem. Typically, FWI has focused on using gradient descent methods with proper regularization to iteratively update models to a minimum misfit value. Non-uniqueness and uncertainties are mostly in this approach. Bayesian inversions offer an alternative by assigning a probability to each model in model space given some data and prior constraints. The drawback is the need to evaluate a very large number of models. Random walks from Markov chains counter this effect by only exploring regions of model space where probability is significant. HMC method additionally incorporates gradient information, i.e. local structure, typically available for numerical waveform tomography experiments. So far, HMC has only been implented for acoustic FWI. We implement HMC for multiple 2D elastic FWI set-ups. Using parallelized wave propagation code, wavefields and kernels are computed on an regular numerical grid and projected onto basis functions. These gradients are subsequently used to explore the posterior space of different target models using HMC. The free parameters in these experiments are P and S velocity, and density. Although simulating Hamiltonian dynamics in the resulting phase space is approximated numerically, the results of the Markov chain are nevertheless very insightful. No prior tuning of kernels, data or model space is required, under the constraint that the sampler is properly tuned. After a burn in phase during which the mass matrix is iteratively optimized, the Markov chain is run on multiple nodes. After approximately 100,000 samples (combined from all nodes) the Markov chain mixes well. The resulting samples give access to the full posterior distribution, including the mean and maximum-likelihood models, conditional probabilities, inter-parameter correlations and marginal distributions.

Course Based Undergraduate Research Experiences (CUREs) are an effective method of teaching students not only content, but also critical thinking, scientific practice, and other skills beneficial to their education and success. They lower the barrier to participation in undergraduate research, thereby increasing access to entry. Thus, CUREs are especially valuable to under-performing students as they are an effective means of bridging the achievement gap. Due to the value and effectiveness of CUREs in student development, Lynn University has implemented a means by which students are exposed to CUREs and skills necessary to complete a CURE throughout the Environmental Studies major curriculum. This presentation will give a description of the curriculum and how CUREs and CURE-required skills are taught throughout the curriculum culminating in a fully independent capstone research project.

Mineral hazards are a common, yet often less-recognized group of features compared to other types of natural and man-made hazards. We define “mineral hazards” in part as minerals and elements that occur naturally in elevated, potentially harmful, concentrations in rocks, soils, and certain fluids. Also included are features from human activities related to extraction of mineral and energy resources. Along with its large human population, extensive development, and diverse natural environment, California is very complex geologically, thus it contains many areas of mineral hazards that make it appropriate for such a study. Although mineral hazards have been investigated over several decades by the California Geological Survey (CGS), no systematic statewide assessment had been accomplished until recently when, at the request of the California Department of Transportation (Caltrans), the CGS completed a preliminary assessment of potential mineral hazards over the entire state. This work focused on natural and man-made minerals-related features that might adversely affect construction, use, and maintenance of state and federal highways under Caltrans jurisdiction. The features evaluated include: 1) geologic units that may contain naturally-occurring asbestos (NOA), fibrous erionite, or elevated concentrations of regulated metals (Ag, Ba, Be, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Tl, V, Zn) and metalloids (As, Sb, Se); 2) faults, which can be sites of increased potential for certain types of mineralization; 3) mines and prospects, which can be sources of anomalous concentrations of metals and ore-processing chemicals; 4) oil and natural-gas seeps; 5) thermal springs and fumaroles; and 6) oil, natural-gas, and geothermal wells. The methods and products developed during the Caltrans study can be applied worldwide to many other uses besides highways where there are obligations to protect public health and safety and the environment. The products include maps that highlight types and locations of potential mineral hazards, digital data in GIS format, and accompanying reports that provide details and additional information. Although they do not indicate risk or probability, these products can be applied by users from many backgrounds as screening tools to assess potential for the presence of mineral hazards.

The strength of the biological soft tissue pump in the ocean critically depends on how much organic carbon is produced via photosynthesis and how efficiently the carbon is transferred to the ocean interior. For a given amount of limiting nutrient, phosphate, soft tissue pump would be strengthened if the carbon (C) to phosphorus (P) ratio of sinking organic matter increases as the remineralization length scale of C increases. Here, we present a new data compilation of particle flux stoichiometry and show that C:P of sinking particulate organic matter (POM) in the ocean twilight zone on average is likely to be higher than the C:P ratio of surface suspended POM. We further demonstrate using a physics-biology coupled global ocean model combined with a theory from first principles that an increase in C:P export flux ratio in the ocean’s twilight zone can lead to a considerable drawdown of atmospheric pCO2.

This paper describes and evaluates novel parameterizations for accounting for the effect of rooftop mitigation strategies on the urban environment, in the context of the mesoscale model Weather Research and Forecasting (WRF), coupled with a urban canopy parameterization and a building energy model (BEP+BEM). Through the new implementation, the sensitivity of near-surface air temperature and building energy consumption to different rooftop mitigation strategies is evaluated by means of numerical simulations in idealized urban areas, for typical summer and winter conditions. Rooftop mitigation strategies considered include cool roofs, green roofs and rooftop photovoltaic panels. Results indicate that near-surface air temperature is reduced by all the RMSs during the summer period: cool roofs are the most efficient in decreasing air temperature (up to 1 °C on average), followed by green roofs and photovoltaic panels. Green roofs reveal to be the most efficient strategy in reducing the energy consumption by air conditioning systems, up to 45%, while electricity produced by photovoltaic panels overcomes energy demand by air conditioning systems. During wintertime, green roofs maintain a higher near-surface air temperature than standard roofs. On the other hand, photovoltaic panels and cool roofs reduce near-surface air temperature, resulting in a reduced thermal comfort. The results presented here show that the novel parameterization schemes implemented in the WRF model can be a valuable tool to evaluate the effects of mitigation strategies in the urban environment. The new model is available as part of the public release of WRF in version 4.3.

Hot spring localities on continents may represent the most probable locales for the formation of early life constituents on Earth. Apart from liquid water and carbohydrates, these components also include elements like boron that are crucial for stabilization of the complex organic molecules that constitute life. Many of these life sustaining ingredients are commonly found in the vicinity of terrestrial hot springs. Analogously, similar existing or extinct hot spring localities on other planets may constitute prospective astrobiological sites. In the present study, we have characterized the complete mineralogical assemblage of the Puga hot spring deposit, Ladakh, India, using detailed spectroscopic and X-ray diffraction studies. The spectroscopic characterization was done using field based visible/near-infrared (VNIR; 400-2500 nm) and lab measured mid-infrared (MIR, 4000-400 cm-1) hyperspectral data. The identified mineral phases include Na-borates, such as, borax and tincalconite, and hydrous sulfates such as jarosite, alunite, copiapite, tamarugite and gypsum, in conjunction with native sulfur, halite and opaline silica. Borate minerals have been identified from the valley-fill material along with halite and opaline silica, whereas sulfates occur alongside crystalline sulfur deposits. We have compared mineral assemblages found in Puga with other hot spring/hydrothermal deposits on Earth identified as martian analog sites, and also with mineral assemblages identified in situ on Mars. We argue that the spectral characterization of hydrated borates in natural association with hydrous sulfates can be used for identification of fossilized martian hydrothermal settings that are prospective in the search for extinct/extant extra-terrestrial life.

Extraction of critical hydrologic features from high-resolution topographic data is challenging using existing grid coarsening approaches, such as surface flow path, river network, and slope, which limits the application of hydrological models. In this research, the influence of various grid coarsening techniques on the prediction outcomes was measured by a numerical experiment based on the integrated hydrological model ParFlow-Common Land Model (ParFlow.CLM). Three grid coarsening methods (Nearest Neighbor Coarsening, Majority Coarsening, Hydrography-Driven Coarsening) were applied to simulate evapotranspiration(E), soil temperature(ST), streamflow, soil moisture(SM) and latent(LE) heat fluxes in central China’s Sixi Valley, a classic example of a karstic basin. As a result, the three grid coarsening methods perform uniform in simulating latent heat fluxes and soil temperature. However, their ability to predict soil moisture surface flow and evapotranspiration are more diverging. The hydrography-driven coarsening extracts significantly more accurate valleys, rivers network, and slopes closer to the actual terrain than existing coarsening strategies. Slopes derived from hydrography-driven coarsening methods can be used to predict more accurately the top soil moisture, evapotranspiration, and streamflow dynamics processes. This study stresses that a hydrography-driven coarsening strategy is advocated for all those cases in which topographic slope extracted using a coarse-grid digital elevation model is an important influence on the ParFlow.CLM simulation of essential hydrographic features.

To improve surface mass balance (SMB) estimates for the Greenland Ice Sheet (GrIS), we develop a spatially and temporally high resolution polar regional climate model combining the Japan Meteorological Agency Non-Hydrostatic atmospheric Model and the Snow Metamorphism and Albedo Process model (NHM–SMAP). At present, the horizontal resolution of the model is set to be 5 km with the temporal interval of 1-hour. The model forced by the Japanese 55year Reanalysis (JRA-55) has been evaluated in the GrIS during the 2011–2014 mass balance years using in-situ surface meteorological and stake measurement data [1]. Results show that the model reproduced the measured features of the GrIS climate, diurnal variations, and even a meso-scale strong wind event. In particular, it reproduces the GrIS surface melt area extent well. Recently, near real-time calculations with the model are conducted operationally. Here we introduce the concept and framework of the model, then present performance of the model from various aspects. In addition, some new results from the operational near-real time calculations will be shown and discussed. Reference [1] Niwano et al. (2018) NHM-SMAP: Spatially and temporally high resolution non-hydrostatic atmospheric model coupled with detailed snow process model for Greenland Ice Sheet. The Cryosphere, 12, 635-655, doi:10.5194/tc-12-635-2018.

The full length of Parker Ice Tongue on the Victoria Land Coast, Antarctica, calved in March 2020. Calving of this magnitude (18 km) is not previously seen for this location. The mean growth rate (189 m yr-1) indicates that it is now at a historic minimum for at least the last 165 years. The 2020 calving occurred during a complete breakout of the land-fast sea ice. Here we link seasonal changes in ice velocity to the land-fast sea ice extent. With Summer/winter increase/decrease in velocity correlates with decrease/increase in land-fast sea ice extent (-0.62 with R-squared of -0.39). Although Parker Ice Tongue was relatively small compared to other ice tongues in the region, its sensitive behaviour highlights the vulnerability of ice tongues to a changing ocean environment, and poses questions about the future stability of larger floating ice masses if land-fast sea ice extent decreases more broadly in the future.

Accessibility of scientific research to underrepresented voices is a forefront issue. Intentionally-designed citizen science programs, such as the University of Alaska Fairbanks’ (UAF) citizen science and learning research project “Arctic Harvest-Public Participation in Scientific Research,” are poised to improve the participation and effectiveness of citizen science across diverse audiences while gathering rigorous data. We selected our research question after first listening to stories of how Alaska’s rural grocery store - the land and its bounty of berries - has become more variable. We investigate how shifts in climate affect the fate of subsistence berries and timing of berry loss from plants in fall and winter across Alaska. In our presentation, we outline the design elements and accommodations we made to enable a diverse group of 1,099 participants in 28 communities to collect phenology, berry abundance and condition, temperature, cloud cover, and snowpack data across ages, cultures, and learning environments. Over half of our volunteers were pre-K to 6th grade, while just under 10% were adults. Approximately 44% of our participants (479 of 1099 participants) were from groups historically underrepresented in STEM fields. We present learning outcomes evaluation, data collection approaches, and data quality per age group. To improve the success of a citizen science program, find the overlap between a topic of personal and cultural relevance to diverse participants and your university’s ongoing research programs.

Geoscience employers have increasingly called for the future workforce (students) to demonstrate competence in non-technical skills, including teamwork. This descriptive qualitative study contributes to ongoing efforts to identify the specific practices, skills, habits, and knowledge that make up these desired teamwork competencies in the geosciences. We collected data from three online focus group discussions centered around teamwork. Focus group participants were hydrogeology and environmental geology employers and team managers from government, private industry, and non-profit organizations in the United States. Using the Marks et al. (2001) teamwork taxonomy model as our conceptual framework, we generated three categories of teamwork skills specific to environmental geoscience teams. First, our data indicate that these employers value team transition skills related to specifying goals, interpreting team tasks, identifying resources, and planning. The second category of desired teamwork competencies included action skills such as metacognition, coordination and mentoring. These skills directly impact successful task completion. The third category captured interpersonal skills such as emotional intelligence, proactive communication, and organization. A fourth category of desired teamwork competencies emerged from data analysis and include ethical skills related to trust, integrity and humility. This study provides a detailed description of teamwork competencies desired by environmental geoscience employers and suggests implications for how to prepare students for this workforce.

The viscosity of the mantle affects every aspect of the thermal and compositional evolution of Earth's interior. Radial variations in viscosity can affect the sinking of slabs, the morphology of plumes, and the rate of convective heat transport and thermal evolution. Below the mantle transition zone, we detect changes in the long-wavelength pattern of lateral heterogeneity in global tomographic models, a peak in the the depth-distribution of seismic scatterers, and changes in the dynamics plumes and slabs, which may be associated with a change in viscosity. We analyze the long-wavelength structures, radial correlation functions, and spectra of four recent global tomographic models and a suite of geodynamic models. We find that the depth-variations of the spectral slope in tomographic models are most consistent with a geodynamic model that contains both a dynamically significant phase transition and a reduced-viscosity region at the top of the lower mantle. We present new inferences of the mantle radial viscosity profile that are consistent with the presence of such a feature.

To study the contributions of cusp outflow coming through the lobes and nightside auroral outflow to the O+ in the plasma sheet, we performed a statistical study of tailward streaming O+ in the lobes, the plasma sheet boundary layer (PSBL) and the plasma sheet (PS), using MMS/HPCA data. Similar spatial distributions demonstrate the entry of cusp-origin O+ from the lobes to the plasma sheet through the PSBL. There is an energy dependence in the lobe O+ spatial distribution, with low-energy O+ streaming near the center in YGSM while high energy (1-3 keV) O+ streams near the flanks. Low energy (< 100 eV) O+ from the nightside auroral oval can be identified in the near-Earth PSBL/PS with high-density (> 0.03 cm-3), and energetic (> 3 keV) streaming O+ with similar density (~0.02 cm-3) is seen further out on the duskside of the PSBL/PS. The rest of the nightside auroral O+ in the PSBL is mixed with O+ coming in from the lobe, and difficult to distinguish. We estimated the inflow and outflow of ions in the plasma sheet between 7-17 RE, using data extracted from previous studies and this work. Comparisons between the estimated fluence suggest that the majority of near-Earth plasma sheet H+ are from cusps and Earthward convection from the distant tail. The O+ in the same region, on the other hand, has a mixed source, with auroral outflow giving the highest contribution.

Hydrological distributed modeling is a key point for a comprehensive assessment of the feedback between the dynamics of the hydrological cycle, climate conditions, and land use. Such modeling results are markedly relevant in the fields of water resources management. Here TopModel (TOPography based hydrological MODEL) is employed for the hydrological modeling of an area in the Middle Magdalena Valley (MMV), a tropical basin located in Colombia. This study is located in the intertropical convergence zone and is characterized by special meteorological conditions, with fast water fluxes over the year. It has been subject to significant land use changes, as a result of intense economic activities, i.e., agriculture, energy and oil & gas production. The model employees a record of 12 years of: • Daily precipitation database from observed gauges • Daily evapotranspiration database from temperature data • Streamflow database as observed data from calibration Calibration is performed using data from 2000 to 2008, and validation is performed with data from 2009 to 2012. The Nash-Sutcliffe coefficient is used to assess the robustness of our calibration process.(values of this metric being 0.62 and 0.53, respectively for model calibration and validation). The results reveal high water storage capacity in the soil, and a marked subsurface runoff, consistent with the characteristics of the soil types in the regions. The calibrated model provides relevant indications about recharge in the region, which is important to quantify the interaction between surface water and groundwater, especially during the dry season, which is more relevant in climate-change and climate-variability scenarios.

This study develops a physics-informed neural network (PINN) model to efficiently generate high-fidelity local circulation patterns in Taiwan while preserving an accurate representation of the physical relationship between generated local turbulence and upstream synoptic flow regimes. Large ensemble semi-realistic simulations were conducted using a high-resolution (2 km) TaiwanVVM model, in which the critical characteristics of the various synoptic flow regimes are carefully selected to concentrate on the effects of local circulation variations. A variational autoencoder (VAE) was constructed to capture essential representations of local circulation scenarios associated with the lee vortices by training on the ensemble dataset. The VAE’s latent space effectively encapsulated synoptic flow regimes as controlling factors, aligning with the physical understanding of Taiwan’s local circulation. The critical transition of flow regimes under the southeasterly synoptic flow regimes is also well represented in the VAE’s latent space, indicating that the VAE can learn the nonlinear characteristics of the multiscale interaction of the lee vortex. We further construct a reduced-order model for local circulation predictions under diverse synoptic conditions. This physics-informed VAE ensures the accurate prediction of the nonlinear characteristics of multiscale interactions between synoptic flows and the turbulence induced by topography, thereby accelerating the assessment of the local circulation responses under various climate change scenarios.

Parameterizations of gas transfer velocities are needed for climate predictions. Single parameter models typically only include wind dependence and may readily be used in climate studies. Their application is however gas specific and limited to select environments. Mechanistic parameterizations incorporating multiple forcing factors allow modelling the transfer of gases with differing solubilities for a wide range of conditions. A novel framework is put forward to model gas transfer in the open ocean in the presence of breaking waves. It incorporates both the turbulence- and bubble-mediated transfers based on statistics determined from the breaking crest length distribution ($\Lambda(c)$). Testing the mechanistic model with measurements from the HiWinGS field campaign shows promising results for both CO\textsubscript{2} and DMS. Uncertainties remain in the quantification of bubble clouds which are at the core of the formulation of the bubble-mediated transfer.

A document by Terence John O'Kane. Click on the document to view its contents.

In this study, we examine the nonlinear interdependence between the parameters of the solar wind influencing geomagnetic activity (proton density and solar wind dynamic pressure, IMF Bz and solar wind dynamic pressure) and geomagnetic activity (AE and SYM-H) during pre-storm, storm and post-storm of intense, major, moderate and minor geomagnetic storms. Nonlinear analytical tools comprising cross recurrence plot (CRP) and Recurrence Rate (RR) was used to capture the features of nonlinear interdependence in the time series data of the solar wind parameter (solar wind dynamic pressure, IMF Bz and proton density) and geomagnetic indices (AE and SYM-H). The pearson correlation coefficient was also used to reveal the features of linear dependence between the parameters of the solar wind during the different categories of geomagnetic storms. Our result shows that during the storm, the CRPs of the solar wind parameters investigated pictured a strong deterministic structure of CRP which is an indication of strong interdependence. In particular, the results of our analysis showed that the solar wind dynamic pressure and proton density depicted very strong interdependence features. On the other hand, during pre-storm and post-storm, the CRP of solar wind dynamic pressure in relation to IMF Bz and proton density pictured a rare deterministic structure signifying weak interdependence. Furthermore, the values of RR were very high (an indication of strong interdependence between the parameters of the solar wind) during the storm while at pre-storm and post-storm, the values of RR declined significantly in most of the periods which further strengthened the evidence of weak interdependence in the parameters of solar wind. The CRP and RR of the geomagnetic indices (AE and SYM-H) reveals no significant difference between pre-storm, storm and post-storm of the different categories of geomagnetic storms. However, strong interdependence between the geomagnetic indices were observed in most of the periods investigated. Finally, the pearson correlation coefficient reveals high values of linear dependence between the solar wind parameters without any significant difference between pre-storm, storm and post-storm periods during intense, major, moderate and minor geomagnetic storms.