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Examining CERES Downward Shortwave Surface Radiative Flux Measurements in the Context of Oklahoma Mesonet Measurements in 2019-2021
Get PDFThe surface radiation budget affects different components of Earth’s climate system. Accurate assessments of the surface radiation budget help improve climate forecasts, such as drought prediction. In addition, short-term diabatic heating and cooling influence convection, temperature, and wind. Surface observations are the most accurate way to measure surface radiative fluxes. However, many locations across the globe do not have access to precise surface radiation measurements. In addition, surface observations are point-based measurements and offer little spatial coverage. As a result, areas with little to no surface observations rely on top-of-the-atmosphere (TOA) satellite instruments to measure surface radiation. Accurate radiative flux measurements from space are much more complicated and prone to errors than surface observations as they are derived from TOA radiances. Thus, a thorough understanding of satellite-based surface flux data are needed.
The Clouds and the Earth’s Radiant Energy System (CERES) is an instrument currently deployed on four satellites. Surface radiative fluxes derived from CERES TOA measurements must account for atmospheric variables such as aerosol optical depth, zenith angle, aerosol and trace gas concentrations, cloud fraction, cloud optical thickness, and cloud albedo. The State of Oklahoma invested in a dense Mesonet network of 120 stations. A dense population of Mesonet stations with a high-resolution product makes it possible to effectively evaluate the CERES surface downward shortwave radiative fluxes based on a simple parameterized code.
This work compares the CERES-Aqua and CERES-Terra Single Scanner Footprint (SSF) Level 2 Edition 4A surface radiation product collocated with the Mesonet-derived observed downward shortwave radiative fluxes for the period 2019 to 2021. We explore clear-sky and all-sky environments by separating the dataset into three different bins using the Moderate Resolution Imaging Spectrometer (MODIS). We find a strong correlation (i.e., correlation coefficient greater than 0.9) between CERES-Aqua and CERES-Terra downward shortwave surface radiative fluxes with the collocated equivalent Mesonet irradiance observations for all three cloud fraction bins. The correlation coefficients of the all-sky bins slightly increased versus the clear-sky bins. During all three years, the CERES-Terra data had higher Mean Absolute Difference (MAD), Mean Bias Difference (MBD), and Root Mean Squared Difference (RMS) than the CERES-Aqua data. We also examine the seasonal dependence of the CERES-Mesonet differences, where the summer all-sky differences are larger than the other seasons
Fluctuation-induced frictional effects on atoms and nanoparticles
Get PDFFluctuations can cause extraordinary effects on atoms and nanoparticles. For example, a neutral but polarizable particle sitting close to a planar surface feels an attraction force towards the surface. This is the well-known Casimir-Polder (CP) force. Fluctuations could also induce a quantum frictional force on a moving particle.
This quantum frictional force is different from the classical frictional phenomenon, where a particle slides above a rough surface, because it originates from the quantum and thermal fluctuations of the electromagnetic fields and it is non-contact. In fact, we will see that the frictional force may not even require a surface. It can occur on a particle moving in vacuum, not in contact or close to any other object. But it is also similar to the classical friction, in that both are nonconservative and cause energy transfer between the particle and the background. At finite temperature, the energy transfer accompanying the quantum frictional force is called the radiative heat transfer. This dissertation is devoted to study the quantum frictional force and radiative heat transfer in some simple backgrounds
Transient Brain-Wide Neuronal Activations in Nonhuman Primate Under Resting and Anesthetized Conditions
No full textThe aim of this thesis was to determine the existence of and identify transient brain-wide patterns in nonhuman primates if these patterns did exist. Specifically, this thesis revolves around identification of coactivation patterns (CAPs). Through observation of these CAPs derived from timeframe-wise cluster analysis, other questions arose: do these patterns I identified in monkeys show some correspondence to those in a different species using different modalities of neuroimaging, focusing on humans in the present thesis, and how do these patterns present in varying levels of consciousness within the same species using the same imaging technique?
Using electrocorticography (ECoG) monkey data, I have identified the existence of CAPs in monkeys as well as observed spatiotemporal patterns these activations exhibited in the resting state, the characteristics of neural networks which are similar to humans. Using human electroencephalography (EEG) data, I have also compared the results of monkey ECoG resting data analysis against human CAPs and found significant similarities in spatial, transitional, and temporal patterns between the two species.
Finally, I compared the same results from the monkey ECoG resting data analysis to patterns found in anesthetized conditions of nonhuman primates and found differences in the spatial and temporal characteristics of brain-wide coactivations between these different states of consciousness within the same species
Patterns of Pollution: A Legal Geography of America's Toxic History and the Road to Remediation at the Tar Creek Superfund Site
Get PDFToxic sites across the United States have been sacrificed for progress and prosperity somewhere else. Far and wide, the communities that inhabit sacrifice zones and experience slow violence–or harm that happens over long periods–have little influence on regulatory structures that determine the remediation of their homes and homelands. This research answers two questions: how do the legal and regulatory structures of remediation perpetuate injustice and how effective is community activism at influencing these systems? Using legal geography and environmental justice frameworks, this research broadly analyzes the history and governance of toxicity in the United States, as well as coupling these findings with analysis of a community archive at the Tar Creek Superfund site in northeastern Oklahoma using reflexive thematic analysis. I argue that the lack of focus, as well as the lack of enforced procedures, on environmental justice within legal and regulatory frameworks reproduces injustice without acknowledging what community perspectives of justice are. Additionally, I assert that community activism is the primary driver of justice at polluted sites and that community involvement in the remediation process is necessary to move toward justice
Carbon-Based Pollutant Analysis and Remote Sensor Validation Using Column-Observing Fourier Transform Infrared (FTIR) Spectrometers During the TRACER Campaign
Get PDFGreenhouse gases methane (CH4), and carbon dioxide (CO2), along with carbon monoxide (CO), while produced by both anthropogenic and natural sources, all contribute to atmospheric warming. Additionally, CO poses health risks to individuals. If the atmospheric dynamics in a region are understood, it should be possible to use regional-scale sensors to evaluate emissions from upwind sources with respect to atmospheric variability.
The GeoCarb-TRACER Campaign was designed to observe these trace gases and their dynamics as a part of the TRacking Aerosol Convection interactions ExpeRiment (TRACER), organized by the U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility in Houston, TX. During this campaign, portable Bruker EM27/SUN Fourier transform spectrometers were deployed at various urban and background sites in the summer of 2022. Each EM27/SUN captures high-resolution (0.5 cm-1) spectra in the near- and shortwave-infrared wavelength range. Multiple EM27/SUN spectrometers were deployed simultaneously alongside instruments gathering boundary layer, aerosol, and near-surface meteorological information. Spectra were analyzed to retrieve column-averaged concentrations of CO2, CO, and CH4, in reference to water vapor in the atmosphere. Researchers used unsupervised machine learning techniques to identify relationships between heightened EM27/SUN concentration measurements and local meteorological and anthropogenic source information. Targeting certain conditions for in-depth case studies identified by the machine learning analysis of local emission sources and co-emitted pollutants will inform further study. This cluster analysis approach highlights potential relationships between heightened EM27/SUN concentrations, surface meteorological conditions, and local industrial sources that may have been overlooked with a daily case study analysis.
Each EM27/SUN instrument was validated by intra- and inter-device comparison using a higher-resolution spectrometer from the TCCON (Total Carbon Column Observing Network) corrected to World Meteorological Organization (WMO) standards to ensure data accuracy, demonstrating minimal bias between instruments using the GGG2020 retrieval algorithm to process raw data. Empirical modifications to the retrieval algorithm were implemented to further correct the EM27/SUN data for solar zenith angle dependence and bring the retrieved concentration data up to the WMO standard, ultimately providing the most accurate representation of the data when compared to TCCON. Additionally, a series of automated data quality filters were developed to remove erroneous data during loss of tracking episodes. EM27/SUN TRACER data also validated the Orbiting Carbon Observatories, OCO-2 and OCO-3, indicating the bias between the EM27/SUN instruments and satellites were small, supporting the assertion that the OCO instruments provide an accurate representation of CO2 concentrations in the atmosphere even in proximity to urban and industrial pollutant sources
Application of untargeted metabolomics techniques based on LC-MS/MS to parasitic diseases and drug development
No full textMetabolites are small chemical molecules less than 1500 Da such as carbohydrates, lipids, and amino acids that provide different functions in organisms. These metabolites are the products of host metabolism or received from the environment. Exploring metabolite perturbation provides valuable insights into metabolic functions and responses to internal and external factors, including diseases. This dissertation applied untargeted metabolomics based on mass spectrometry to investigate metabolic perturbation induced by infection in two parasitic diseases, leishmaniasis and toxoplasmosis. We applied LC-MS/MS, a powerful analytical technique with high resolution and well-suited for complex biological samples. In these studies, we focused on individual organs and investigated how the metabolome changed and which metabolic pathways were affected by infection. Our results will increase knowledge about disease mechanisms, which can lead us to identify biomarkers and new treatments. In addition, we evaluated the effects of different doses of carnitine, alone or in combination with benznidazole, on chronic stage of Chagas disease in mouse models. Carnitine was identified through an untargeted metabolomics study related to Chagas disease caused by Trypanosoma cruzi, and shown to improve heart health in chronic infection, without affecting parasite burden. Our goal was to assess the safety and efficacy of carnitine as a potential treatment option combined with the antiparasitic drug, benznidazole, for chronic stage. Our result showed no negative effect of carnitine on antiparasitic effect of benznidazole and no negative effect on mice health. Based on our results, it is important to determine the right dose of carnitine to prevent from increase of trimethylamine N-oxide (TMAO) level in plasma to prevent cardiovascular risk. This dissertation provided new insights into host-parasite interactions for leishmaniasis and toxoplasmosis, while evaluating safety and efficacy of Chagas disease
Using Machine Learning to Improve the NSSL's Warn-On-Forecast System's Prediction of Thunderstorm Location
Get PDFDeep learning (DL) models have become immensely popular in recent years, with many models creating accurate and high-skill predictions for a wide range of atmospheric phenomena. Using DL models for predicting convection and associated hazards has experienced some of the most substantial gains in skill. The National Severe Storms Laboratory (NSSL) has created the experimental Warn-On-Forecast System (WoFS) to increase warning lead times through probabilistic short-term forecasts of individual thunderstorms. Currently, the WoFS has a shortcoming of missing storms due largely to poorly initialized environments. To help mitigate this issue, we developed a U-Net deep learning model to predict locations of thunderstorms trained on WoFS model data consisting of environmental data, such as CAPE and CIN, and intra-storm variables, such as WoFS ensemble average, mean, and max composite reflectivity and updraft and downdraft velocities. To address the issue of poorly initialized environments and lagging data assimilation, the model also has access to Multi-Radar/Multi-Sensor System (MRMS) data valid at the WoFS initialization is also used as an input. To evaluate the skill of the DL-based guidance, different baseline methods were tested to ensure a substantial performance increase. Comparing the performances of the WoFS baseline and DL model on an independent testing dataset, we were able to increase the maximum critical success index from 0.17 to 0.27, along with increasing the reliability and discrimination of the predictions. Using MRMS composite reflectivity proved to be vital for the DL model's performance when predicting values >= 40 dBZ. Through this work, we demonstrate DL models are an effective and efficient solution to improving the skill of the WoFS forecast of convection with a 30-minute lead time
Surfacing Oil: The Oil Industry and Environmental Knowledge in the 20th Century United States
Get PDFIn the 20th century United States, the oil industry expanded internationally, extracting in new environments with new technologies. Throughout this period, contemporary environmental knowledge shaped the oil industry’s perspective on oil extraction and its consequences. In this thesis, I aim to show how the oil industry has used and informed environmental knowledge, such as ecology and marine biology, to argue for certain kinds of production and to defend their practices against critics. This thesis examines three different case studies of the oil industry grappling with the nature of oil: the conservation movement of the early 20th century, Cold War ecological research on the North Slope, and the naturalization of oil via natural oil seep research in California and Rigs-to-Reefs programs in the Gulf of Mexico in the 1960s and 1970s. In these places, the oil industry’s relationship with the environment reaffirmed settler colonial power and questioned the division of nature and technology
Sedimentological Study of an Early Pleistocene Upland Lake Core, Unaweep Canyon, Colorado
No full textThe recent recovery of a core in Unaweep Canyon, Colorado, penetrated ~140 m of lacustrine sediment of what is here termed paleo-Lake Unaweep. The lake is inferred to have formed as a result of mass wasting that blocked the ancestral Gunnison River during the early Pleistocene, causing partial filling of Unaweep Canyon before the ancestral Gunnison River abandoned the canyon. This core has been correlated to previous core that also penetrated paleo-Lake Unaweep, and captures a sediment record that dates from ~1.4-1.3 Ma, enabling a glimpse of the Early Pleistocene before the mid-Pleistocene transition— a time interval rarely captured in an upland (or any) setting of the greater Rocky Mountains. The lacustrine section begins atop an interval of ~21 m of inferred ancestral Gunnison River gravels, and comprises a series of mass flows that, overall, decrease in thickness (2 to 60 cm) from the bottom to the top of the core. The entire lacustrine section exhibits an alternation of two intervals: one exhibiting an olive-gray color and containing siderite, and intervals exhibiting red and ochre colors, possibly recording climatic variations. The basal ~20 m consists of reddish-brown, graded (granules to fine sand) mass flows. Above this is a ~15 m interval of thinner (2-10 cm) and finer-grained mass flows exhibiting ochre colors with pink/white clay caps. Next is an olive-gray interval (~48 m) with mass flows exhibiting basal loading, convolute bedding, sand injections, and mud clasts with thin (<1 cm) clay caps. Siderite layers also occur locally in the olive gray interval. Above this, there is ~18.5 m of the same ochre-colored interval. The upper interval (~38.5 m) is also olive-gray and comprises 2-5 cm beds of upwardly fining, sandy clay. Macroscopic charcoal occurs commonly at the bases of event beds and in transitional units of the olive-gray interval but is absent from the intervals that exhibit an oxidized color. Many of the mass flows exhibit normal grading capped by silt, interpreted as partial turbidite sequences. Preliminary palynological results exhibit changes in pollen and spore assemblages that track the large-scale color variation observed, supporting the inference of a climate driver for these alternations. Analyses are ongoing to determine whether mass flows reflect autogenic (e.g., deltaic failure) events, or allogenic (e.g., flooding) events. The primary goal of this study is to utilize this recently recovered UDR1 core to understand the drainage history and the origin and evolution of this paleo-lake. These Quaternary paleo-lake sediments provide a continuous record of sedimentological processes within this unique upland lake that dates from before the Mid Pleistocene Transition. This study also provides new data points to help reconstruct a possible basement profile that mandates a remarkable shallowing of the gradient of the ancestral Gunnison River in westernmost Unaweep Canyon
Beyond Exploitation: Metadata Justice and Prison Labor
Get PDFLarge-scale digitization projects require enormous amounts of resources and labor, both of which are frequently in short supply in libraries and archives. How, then, has Oklahoma’s Yearbook Project been able to scan and process high school yearbooks at no cost for schools, libraries, museums, and historical societies? As a service of Oklahoma Correctional Industries, a state-level prison industry program, the Yearbook Project relied on the penal labor exemption of the Thirteenth Amendment which allows for involuntary servitude to occur behind prison bars. Although the Yearbook Project is currently on hiatus due to an ongoing investigation, metadata specialists, cataloguers, and the wider memory work community must still grapple with the legacy of this and other exploitative and unethical programs that have contributed to the resources and services we offer patrons. This presentation sheds light on the issue of exploitative prison labor on behalf of libraries and archives, and offers a solution grounded in metadata justice: labeling items, collections, and databases that benefit from exploitative labo