The potential and practicality of offshore geologic carbon dioxide (CO2) subsea storage is being explored through a Department of Energy (DOE) supported project entitled “Southeast Regional Carbon Storage Partnership: Offshore Gulf of Mexico” (SECARB Offshore). SECARB Offshore supports the DOE’s long-term objective to ensure a comprehensive assessment of the potential to implement offshore CO2 subsea storage in all Bureau of Ocean Energy Management (BOEM) Outer Continental Shelf (OCS) Oil and Gas Leasing Program Planning areas in the GOM. As an estimated 40% of U.S. anthropogenic CO2 emissions are generated in the southeast, with a large portion of these emissions generated within 100 km of the coastline, the eastern Gulf of Mexico (GOM) is a prime target for this type of storage. The project team has been assembling the knowledge base required for secure, long-term, large-scale CO2 subsea storage in the GOM with or without CO2 enhanced hydrocarbon recovery (CO2-EOR). The project team has confirmed that the storage potential in Cretaceous and Tertiary reservoirs in the eastern GOM is vast (e.g., ~1,000 Mt potential storage in the DeSoto Canyon Salt Basin alone). With the significant infrastructure already in place, abundant stacked saline formations, and depleted oil and gas reservoirs, the eastern GOM is an attractive prospect. However, offshore subsea CO2 storage has different challenges with respect to project development; monitoring, verification, and accounting (MVA); and outreach as compared to onshore CO2 storage. Thus, a significant effort moving forward will be surrounding education and outreach to facilitate engagement with stakeholders in potential CO2 storage in the offshore GOM. Such materials will describe the potential for CO2 storage in the offshore GOM, highlight the environmental and economic benefits that could accrue to the Gulf Coast region in pursuing this potential, characterize the risks associated with this pursuit, and document how offshore CO2 storage is currently being pursued effectively globally. The efforts need to be tailored for specific stakeholders – for example, commercial and recreational fishing industries may have different concerns than government officials – to be effective.

The Flint, Michigan, water crisis began in 2014 after officials switched the water supply to the Flint River, which was highly corrosive to the city’s pipes. Years later, the situation on the ground is still dire. Pipes are being replaced, but your average Flint citizen has no idea where the replacement is done. Citizens have such a history of tap water problems (pre-2014 and COVID) that they just continue to go and get (or buy) bottled water… for everything. Regaining trust in the viability/potability of their tap water is at odds with a local administration that doesn’t want to spend any more money and can’t wait for the situation to resolve itself. The Flint water crisis highlights the need for accessible and (re)usable data by all stakeholders. For example, if the officials who had originally switched the water supply had access to data in a way that was usable to them that showed how switching the water source without changing treatment would impact the infrastructure and water quality, they may have taken steps to prevent the crisis in the first place. Flint citizens should have access to data that shows water quality information and the status of infrastructure updates, in a way that is useful to them. Access to usable data is not just a nice thing to have; it can be a matter of life and death. We will outline the basic rights and responsibilities of researchers, data professionals, institutions, and others with regards to improving data access and reusability. For example, stakeholders and community members should have access to data that impacts their communities, and resources (such as access to researchers) to understand that data in a way that is useful for their situation.

Orca seamount is located in the Bransfield Strait, between the South Shetland Islands and the Antarctic Peninsula. The volcano developed on an extensional rift produced by a combination of slab rollback at the South Shetland trench and transtensional motions between the Scotia and Antarctic plates. From January 2019 to February 2020, the BRAVOSEIS project deployed a dense amphibious seismic network in the Bransfield region, comprising both land and ocean bottom seismometers (OBS), as well as moored hydrophones. We perform an analysis of the seismicity recorded in the area of Orca volcano using a subnetwork composed of 15 OBS around Orca seamount and its SW rift, covering a region of about 20 km x 10 km, with inter-station distances of ~4 km. OBS data are organized, visualized and analyzed using the SEISAN software package. Earthquake detection was achieved through an STA/LTA algorithm. We use a visual procedure including spectral analysis and filtering to discriminate local earthquakes from other types of signals. For earthquake location, we use P and S phase arrivals and a layered model derived from previous geophysical studies in the region. In this way, we identify and locate around 3000 earthquakes with magnitudes in the range from -1 to 3. There is a continuous background level of microearthquake activity, although a large part of the earthquakes occurred during a swarm in June-July 2019. Source depths are mostly concentrated in the first 10 km (within the crust). The epicentral distribution covers the whole area around the volcano, but it is clearly densest in the NE flank, where an intense seismic series started in September 2020.

Seismic source locations provide fundamental information on earthquakes and lay the foundation for seismic monitoring at all scales. Subsurface engineering operations, such as hydraulic fracturing, usually generate abundant microseismic events with low signal-to-noise ratios, thus raising a higher demand on the reliability and computational efficiency of seismic location methods. Stacking-based method involves reconstructing and focusing the radiated seismic source energy with a certain stacking operator, for example, the diffraction stacking operator or the cross-correlation stacking operator. They are noise-resistant, automatic, and data-driven. The source locations are resolved as images instead of discrete dots, offering more insights into source processes and surrounding structures. In this work, we conduct the performance evaluation and influential factor analysis with synthetic examples, to further improve the understanding of the method. Three categories of factors are investigated, including the velocity model, array geometry, and waveform complexity. Each of the three factors consists of several detailed factors, such as different array types and noise levels. Multiple parameters are considered for the performance evaluation, including location error/bias, imaging resolution, signal alignment with time shifts, and the computational cost. The proposed scheme is also applied to field microseismic datasets to demonstrate its feasibility. This study will be conducive to the design and evaluation of surface monitoring projects.

By using datasets of HadISST monthly SST from 1895 to 2014 and 600-year simulations of two CESM model experiments with/without doubling of CO2 concentration, ENSO characteristics are compared pre- and post- global warming. The main results are as follows. Due to global warming, the maximum climatological SST warming occurs in the tropical western Pacific (La Niña-like background warming) and the tropical eastern Pacific (El Niño-like background warming) for observations and model, respectively, resulting in opposite zonal SST gradient anomalies in the tropical Pacific. The La Niña-like background warming induces intense surface divergence in the tropical central Pacific, which enhances the easterly trade winds in the tropical central-western Pacific and shifts the strongest ocean-atmosphere coupling westward, correspondingly. On the contrary, the El Niño-like background warming causes westerly winds in the whole tropical Pacific and moves the strongest ocean-atmosphere coupling eastward. Under the La Niña-like background warming, ENSO tends to develop and mature in the tropical central Pacific, because the background easterly wind anomaly weakens the ENSO-induced westerly wind anomaly in the tropical western Pacific, leading to the so-called "Central Pacific ENSO (CP ENSO)". However, the so-called "Eastern Pacific ENSO (EP ENSO)" is likely formed due to increased westerly wind anomaly by the El Niño-like background warming. ENSO lifetime is significantly extended under both the El Niño-like and the La Niña-like background warmings, and especially, it can be prolonged by up to 3 months in the situation of El Niño-like background warming. The prolonged El Nino lifetime mainly applies to extreme El Niño events, which is caused by earlier outbreak of the westerly wind bursts, shallower climatological thermocline depth and weaker "discharge" rate of the ENSO warm signal in response to global warming. Results from both observations and the model also show that the frequency of ENSO events greatly increases due to global warming, and many more extreme El Niño and La Niña events appear under the El Niño-like and the La Niña-like background warmings, respectively. This study reconciles the phenomena and mechanisms of different characteristics of ENSO changes in observations and models.

Recent observations of warming trends in the Red Sea raise more attention to the response of the basin under a warming climate. Using two remotely sensed datasets, the Hadley Centre Sea Ice and Sea Surface Temperature [HadISST] and Extended Reconstructed Sea Surface Temperature [ERSST.v3], we investigate the reported sudden increase in the Red Sea sea surface temperatures (SST) in terms of average and maximum and assess their relation to multi-decadal climate variability. Prior to the analysis, the two datasets are successfully validated with respect to their ability to reproduce the recent observed and reported trends and their spatial features. Analysis of long-term SST variability revealed a sequence of alternating and similar in amplitude positive and negative trends, characterized by a period of nearly 70 years. Similar oscillations have been reported in other basins and have been related to atmospheric disturbances associated with the Atlantic Multidecadal Oscillation (AMO). A point-by-point spectral analysis of SST evolution shows a significant correlation with the basic modes of the AMO that explains a large fraction of its temporal and spatial variability. Projections on the major modes of the spectral analysis suggest a possible decreasing effect on local SST in the near future. Under this assumption, recent projected trends in the Red Sea may be exaggerated, whilst trends that may be related to anthropogenic influence could be masked by the projected negative influence of the AMO in the near future.

Improving photosynthesis has been considered critical to increasing crop yield to meet food demands from a growing population. To achieve this goal, high-throughput phenotyping techniques are highly needed to explore both natural and genetic variation in photosynthetic performance among crop cultivars. Due to the non-invasive nature of hyperspectral imaging, there is an increasing use of hyperspectral imaging for phenotyping of photosynthesis or photosynthetic physiology. The use of hyperspectral sensors has resulted in the accumulation of large amounts of data, shifting the research efforts into efficiently mining spectral information for high-throughput phenotyping. In this presentation, we will introduce data pipelines developed to leverage proximal sensing platforms and data sources including both reflectance spectra and solar-induced fluorescence (SIF) for quantifying photosynthetic performance at the canopy level. Photosynthetic performance was represented by the maximum carboxylation rate (Vcmax) and the maximum electron transport rate (Jmax). The experiments were conducted using eleven tobacco cultivars grown in field conditions during 2017 and 2018 at Energy Farm at University of Illinois. Time-synchronized hyperspectral images from 400 to 900 nm and irradiance measurements of sunlight under clear-sky conditions were collected for capturing reflectance spectra and SIF (and SIF related parameters). Within 30 minutes of spectral measurements, ground-truth Vcmax and Jmax were obtained from portable leaf gas exchange system. Our results suggested both reflectance spectra and SIF can provide accurate estimations of Vcmax and Jmax. The presented data pipelines have potential to relieve bottleneck in phenotyping of photosynthesis for breeding cultivars of enhanced photosynthesis.

In this poster, we begin to explore how socio-geographical considerations can inform the development of data infrastructure, notably Persistent Identifiers. PIDs have become largely accepted within the Research Data Alliance, W3C, and elsewhere as core elements of data infrastructure. Science is comprised of many divergent formal and informal viewpoints at many different levels with a need for generalizable findings. PIDs act as “Boundary Objects” (Star & Griesemer, 1989) — objects that are part of multiple social worlds and facilitate communication between them. They allow meaning to be understood in different contexts and are “plastic enough to adapt to local needs, … yet robust enough to maintain a common identity across sites. They are weakly structured in common use and become strongly structured in individual site use.” Boundary objects work to reduce local uncertainty without damaging cooperation. It is a question of re-representations across intersecting worlds not consensus. PIDs work to allow machines and humans to understand which digital object is in question (identity), what it is (type), and where it is (location). Each of these questions is surprisingly fraught and complex.

Accurately constraining N emissions in space and time has been a challenge for atmospheric scientists. It has been suggested that 15N isotopes may be a way of tracking N emission sources across various spatial and temporal scales. However, the complexity of multiple N sources that can quickly change in intensity has made this a difficult problem. We have used a SMOKE emission model to parse NOx emission across the Midwestern United States for a one-year simulation. An isotope mass balance methods was used to assign 15N values to road, non-road, point, and area sources. The SMOKE emissions and isotope mass balance were then combined to predict the 15N of NOx emissions (Figure 1). This δ15N of NOx emissions model was then incorporated into CMAQ to assess the role of transport and chemistry would impact the 15N value of NOx due to mixing and removal processes. The predicted 15N value of NOx was compared to those in recent measurements of NOx and atmospheric nitrate.

It is not uncommon that students in introductory survey courses are reluctant to participate in verbal inquiry. In a survey submitted to students of CLIMATE 102, Extreme Weather, over the past four semesters about 45% of male students professed comfort in asking verbal questions in a large lecture hall but less than 25% of females and only 15% of students for whom English is not their first language. Hence, large lecture hall courses may be inadvertently dissuading the inclusion of many of the students we wish to encourage to participate in our discipline. To combat this a system was used in CLIMATE 102 wherein students could pose questions digitally and anonymously. These questions could be seen by all and answered by all. The instructor and/or teaching assistant can also participate and answer or offer corrections to others’ answers. The use of this system had three important outcomes: 1. The number of questions posed during class time rose dramatically from previous semesters when only verbal questions were entertained. The number of questions in CLIMATE 102 with this system generally exceeded 500 per semester where the number of students ~200. 2. The number of per-capita questions from female students exceeded the male students, thus differences in gender inquiry was eliminated. 3. The number of per-capita questions from students whose first language was not English equaled the native English-speaking students. While it is the goal of higher education to encourage students to participate verbally in class discussions it is important to provide a “safe” environment in the first year(s) as many students are initially uncomfortable participating verbally in class. We hypothesize, but have not researched, that through this process students have the opportunity to see that their questions are as valid as others’ in the class and will subsequently gain the confidence to participate verbally.

Coronal mass ejections (CMEs) are fast-moving magnetic field structures of enhanced plasma density that play an important role in space weather. The Solar Orbiter and Parker Solar Probe will usher in a new era of in situ measurements, probing CMEs within distances of 60 and 10 solar radii, respectively. At the present, only remote-sensing techniques such as Faraday rotation can probe the plasma structure of CMEs at these distances. Faraday rotation is the change in polarization position angle of linearly polarized radiation as it propagates through a magnetized plasma (e.g. a CME) and is proportional to the path integral of the electron density and line-of-sight magnetic field. In conjunction with white-light coronagraph measurements, Faraday rotation observations have been used in recent years to determine the magnetic field strength of CMEs. We report recent results from simultaneous white-light and radio observations made of a CME in July 2015. We made radio observations using the Karl G. Jansky Very Large Array (VLA) at 1 - 2 GHz frequencies of a set of radio sources through the solar corona at heliocentric distances that ranged between 8 - 23 solar radii. These Faraday rotation observations provide a priori estimates for comparison with future in situ measurements made by the Solar Orbiter and Parker Solar Probe. Similar Faraday rotation observations made simultaneously with observations by the Solar Orbiter and Parker Solar Probe in the future could provide information about the global structure of CMEs sampled by these probes and, therefore, aid in understanding the in situ measurements.

The structure(s), distribution and dynamics of CDOM have been investigated over the last several decades largely through optical spectroscopy (including both absorption and fluorescence) due to the fairly inexpensive instrumentation and the easy-to-gather data (over thousands published papers from 1990-2016). Yet, the chemical structure(s) of the light absorbing and emitting species or constituents within CDOM has only recently being proposed and tested through chemical manipulation of selected functional groups (such as carbonyl and carboxylic/phenolic containing molecules) naturally occurring within the organic matter pool. Similarly, fitting models (among which the PArallel FACtor analysis, PARAFAC) have been developed to better understand the nature of a subset of DOM, the CDOM fluorescent matter (FDOM). Fluorescence spectroscopy coupled with chemical tests and PARAFAC analyses could potentially provide valuable insights on CDOM sources and chemical nature of the FDOM pool. However, despite that applications (and publications) of PARAFAC model to FDOM have grown exponentially since its first application/publication (2003), a large fraction of such publications has misinterpreted the chemical meaning of the delivered PARAFAC ‘components’ leading to more confusion than clarification on the nature, distribution and dynamics of the FDOM pool. In this context, we employed chemical manipulation of selected functional groups to gain further insights on the chemical structure of the FDOM and we tested to what extent the PARAFAC ‘components’ represent true fluorophores through a controlled chemical approach with the ultimate goal to provide insights on the chemical nature of such ‘components’ (as well as on the chemical nature of the FDOM) along with the advantages and limitations of the PARAFAC application.

Discrete fracture network (DFN) models provide a natural analysis framework for rock conditions where flow is predominately through a series of connected discrete features. Mechanistic models to predict the structural patterns of networks are generally intractable due to inherent uncertainties (e.g. deformation history) and as such fracture characterisation typically involves empirical descriptions of fracture statistics for location, intensity, orientation, size, aperture etc. from analyses of field data. These DFN models are used to make probabilistic predictions of likely flow or solute transport conditions for a range of applications in underground resource and construction projects. However, there are many instances when the volumes in which predictions are most valuable are close to data sources. For example, in the disposal of hazardous materials such as radioactive waste, accurate predictions of flow-rates and network connectivity around disposal areas are required for long-term safety evaluation. The problem at hand is thus: how can probabilistic predictions be conditioned on local-scale measurements? This presentation demonstrates conditioning of a DFN model based on the current structural and hydraulic characterisation of the Demonstration Area at the ONKALO underground research facility. The conditioned realisations honour (to a required level of similarity) the locations, orientations and trace lengths of fractures mapped on the surfaces of the nearby ONKALO tunnels and pilot drillholes. Other data used as constraints include measurements from hydraulic injection tests performed in pilot drillholes and inflows to the subsequently reamed experimental deposition holes. Numerical simulations using this suite of conditioned DFN models provides a series of prediction-outcome exercises detailing the reliability of the DFN model to make local-scale predictions of measured geometric and hydraulic properties of the fracture system; and provides an understanding of the reduction in uncertainty in model predictions for conditioned DFN models honouring different aspects of this data.

Backprojection (BP) of teleseismic P waves is a widely-used method to study the evolution of earthquake radiation and is particularly effective for large earthquakes. We can harness key information on the spatiotemporal evolution during the rupture process from waveform similarity or coherency. Understanding the relation between earthquake physics and the spatiotemporal evolution from BP imaging, which are usually obtained from high frequency seismic waveforms, is of great importance. Theoretical studies indicate that the high-frequency bursts can be related to abrupt changes in rupture velocity (e.g. stopping of rupture or kinks on the fault). Moreover, the BP images are thought to be equivalent to either slip or slip rate on the fault, provided that the Green’s functions from the sources to the receivers are incoherent delta functions. Furthermore, recent studies propose that the frequency dependent features of BP results can reflect the stress status, frictional and/or geometrical heterogeneity on the fault surface. It is promising that we can obtain more observational constraints and information about the earthquake dynamic source from the backprojection results combined with other independent techniques. In this study, we attempt to figure out the relation between the BP results and earthquake source process by testing both kinematic and dynamic source models. With these source models, we can synthesise the seismic waveforms and trace them back to the fault surface using the BP method. Therefore, we can directly compare the BP results with the already-known earthquake sources and further explore the possible relation to the source properties by varying our source models such as the friction laws, fault geometries. To simplify our problem and exclude the potential effects from complex earth structure, our tests are carried out in a purely elastic medium, whole space, allowing us to solve analytically for the far-field body waves. From these systematical tests and comparisons, we aim at building a comprehensive relation between the BP images and various source properties. Moreover, our results can provide significant help to better understand the physics of earthquake source process from seismic observations.

Airborne lidar surveys were used to characterize subsurface layers of phytoplankton in the Arctic Ocean during the latter half of July 2014 and again during the latter half of July 2017. The survey region included US waters in the Beaufort and Chukchi Seas. In 2014, layers were detected in open water and also in openings in pack ice where up to 90% of the surface was covered by ice. The layers in the pack ice were less prevalent, weaker, and shallower than those in open water. Layers were more prevalent in the Chukchi Sea than in the Beaufort Sea. Three quarters of the layers observed were thinner than 5 m. In 2017, ice conditions were significantly different. The ice edge was farther north at the beginning of the measurement period in 2017 and retreated faster during that period. As a result, flights were conducted in the areas surveyed in 2014 in addition to areas near the ice edge. Data analysis of the 2017 flights will be done in the same way as the 2014 data. Low clouds and fog are common in the Arctic. The lidar can operate through optically thin clouds and fog, but at some point, the beam is completely attenuated. Data where the atmospheric attenuation is too great must be removed from consideration by visual inspection. Detection of ice in the lidar return is straightforward, since ice produces a saturated return in the lidar receiver. Subsurface layers will be identified by visual inspection of the data, and the characteristics will be calculated. Subsurface layers are clearly present in the data, and their characteristics will be presented, along with a comparison between 2014 and 2017 results.

Management of uncertainty in hydrologic modeling is related to our ability to (a) select appropriate values for model parameters and (b) assess the extent to which their variation affects a simulated response. We focus on the application of sensitivity and uncertainty analyses to assess the influence of main parameters associated with the widely used distributed watershed model TopModel in estimating surface runoff in the area of the Middle Magdalena Valley, Colombia. We ground our study on the GLUE methodology, as included in the MCAT Toolbox. This methodology is conducive to a Regional Sensitivity Analysis (RSA), rendering global information about the relative importance of given model parameters through an a-posteriori probability function. GLUE is viewed as a first step to undertake a comprehensive global sensitivity analysis based on the statistical moments characterizing the outputs of the simulations. We do so upon relying on (a) the Sobol’ indices, associated with a classical decomposition of variance and (b) recently developed indices quantifying the relative contribution of each uncertain model parameter to the (ensemble) mean, skewness and kurtosis of the model output. Our analyses are grounded on a collection of 150.000 model simulations, each spanning a 12-year temporal window. These are constructed by assuming those model parameters are random and associated with a uniform distribution within a support of width selected on the basis of literature studies and preliminary model calibration against available data. Results of the global sensitivity analysis enable identifying a reduced set of model parameter values, showing that the parameter driving the transmissivity recession curve (associated with an exponential decrease of saturated hydraulic conductivity with depth), the maximum root zone storage deficit, and the initial subsurface flow can be considered as the most sensitive ones. Observed and simulated high values of surface runoff due to the excess of infiltration suggest a high water storage capacity of the soil and dominance of subsurface runoff processes, consistent with the local characteristics of the soils in the region.

Harvey was formed around 17 August with maximum winds 40 miles/hour. At the moment, Irma formation started on 20 August faster becoming a hurricane category five. Some days before these two events, the Uruguay and Brazil coast suffered a recede in the oceans near Punta del Este and Rio Grande do Sul it happened in the week of 11 August. The energy accumulated in the recede of waters was not released by a tsunami and the water slowly was back to the shore. This event repeated at August 25, however at higher latitudes as in Parana and Sao Paulo. And consequent high tides in Chile again. The absence of a recurrent tsunami at the Brazilian coast indicates the energy accumulated from the receding ocean was released as a tsunami in the oceans, it became another huge hurricane formation as Jose and Katia. All those events pointed out for an atmospheric pressure disturbance on the Atlantic East Coast. In South America happened a suddenly increase at the atmospheric pressure which made the ocean waves receded for many days. Another similar disturbance happened in Caribe area resulting in several huge hurricanes.

The biodiversity of reef fish in the Florida Keys National Marine Sanctuary was evaluated in terms of abundance, biomass, evenness, species richness, Shannon diversity, Simpson diversity, and functional diversity, using observations collected from 1999 – 2016 by the Reef Visual Census program. To compare the different diversity indices, species richness, Shannon diversity, Simpson diversity, and functional diversity were converted into effective number of species. We examined the seven indices by level of protection and type of no-take marine zones and by three habitat strata. The study detected abundance, biomass, and diversity were significantly greater (except evenness) inside no-take marine zones compared to areas open to fishing. Smaller reserves had higher abundance, biomass, and richness values than larger reserves and areas open to fishing, but had moderately higher diversity values. This may be attributed to a few species with many individuals that are dominant inside and outside no-take marine zones. Surprisingly, none of the indices were significantly different (except for functional diversity) between the larger Ecological Reserve and areas open for consumption. This may be due to spillover effects. Furthermore, the no-take marine zones only explained a small proportion of total percent deviance in the indices. Habitat type had a greater influence on patterns in composition and diversity where high relief reef habitats had the greatest abundance, biomass, and diversity indices. Based on our results managers should prioritize preserving high relief reefs through a network of small reserves to enhance reef fish composition and biodiversity.