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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Creating a High Energy Alert System for the HAWC Gamma Ray Observatory [Slides]

One of the greatest mysteries in astrophysics is exactly how Cosmic Rays (CRs) are accelerated up to extremely high energies within our galaxy. Hadronic models of possible CR accelerators, including supernova remnants and pulsars, require the production of both gamma rays and neutrinos at these sources. Searching for coincidences between neutrino and the highest energy gamma ray observations can help confirm these theories. The High Altitude Water Cherenkov (HAWC) observatory is a ground based gamma ray observatory located at 4100m in Puebla, Mexico. HAWC is able to detect gamma rays with energies greater than 100 TeV, has a wide field of view, and a 95% duty cycle, making it ideal for these types of coincidence searches. This work aims to create a high energy alert system for HAWC, sending out an alert to other experiments for gamma ray events it sees above 56 TeV.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Epidemiological Investigation of a Mortality Event in a Translocated Gopher Tortoise (Gopherus polyphemus) Population in Northwest Florida

Nokuse Plantation, a 22,055 ha private conservation preserve in northwest Florida, is a recipient site for gopher tortoises translocated from development sites in Florida. Since 2006, Nokuse has received over 5,000 tortoises from multiple development sites. During 2013–2015, 52 tortoises were found sick (n = 14) or dead (n = 38) in multiple soft-release enclosures in which tortoises consistently exhibited clinical signs, with additional sick (n = 5) and dead (n = 5) tortoises presenting similarly during 2016–2017. When found alive, tortoises behaved abnormally (e.g., frequently out of burrows during cold weather, pacing along enclosure fencing), appeared emaciated, were lethargic, and had developed redness under plastron scutes. Similar numbers of male (n = 28) and female (n = 32) tortoises were recovered along with two of unidentified sex, including mainly adults (n = 59) and three subadults. Physical examination, blood analysis, and other diagnostics were indicative of starvation and dehydration. Most sick tortoises provided with supportive care recovered. Necropsy findings generally confirmed starvation, with no evidence of infectious pathogens or contaminants. There were no apparent differences in quality of habitat, plant community, or soil or water among affected and unaffected enclosures. Botanical surveys indicated adequate forage quality and quantity, with no poisonous exotic or native plants detected. No land management practices changed prior to this event. Analysis of epidemiological data and demographic factors from before and during this mortality event identified initial density of tortoises in the enclosures as exerting the strongest influence on detection of tortoise morbidity and mortality. We believe that the stress associated with mixing tortoises from different populations and at higher densities during translocation impacted an individual tortoise’s ability to obtain or absorb adequate nutrients from foraging, ultimately leading to a wasting condition consistent with starvation. Based on our findings, we recommend a maximum of 3 gopher tortoises per ha in soft-release enclosures for translocation, but further research is warranted to investigate the complexity of stress and social pressures associated with translocation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Assessing residential activity in a home plumbing system simulator: monitoring the occurrence and relationship of major opportunistic pathogens and phagocytic amoebas

Opportunistic premise plumbing pathogens (OPPPs) have been detected in buildings’ plumbing systems causing waterborne disease outbreaks in the United States. In this study, we monitored the occurrence of OPPPs along with free-living amoeba (FLA) and investigated the effects of residential activities in a simulated home plumbing system (HPS). Water samples were collected from various locations in the HPS and analyzed for three major OPPPs: Legionella pneumophila, nontuberculous mycobacterial species (e.g., Mycobacterium avium, M. intracellulare, and M. abscessus), and Pseudomonas aeruginosa along with two groups of amoebas (Acanthamoeba and Vermamoeba vermiformis). A metagenomic approach was also used to further characterize the microbial communities. Results show that the microbial community is highly diverse with evidence of spatial and temporal structuring influenced by environmental conditions. L. pneumophila was the most prevalent pathogen (86% of samples), followed by M. intracellulare (66%) and P. aeruginosa (21%). Interestingly, M. avium and M. abscessus were not detected in any samples. The data revealed a relatively low prevalence of Acanthamoeba spp. (4%), while V. vermiformis was widely detected (81%) across all the sampling locations within the HPS. Locations with a high concentration of L. pneumophila and M. intracellulare coincided with the highest detection of V. vermiformis, suggesting the potential growth of both populations within FLA and additional protection in drinking water. After a period of stagnation lasting at least 2-weeks, the concentrations of OPPPs and amoeba immediately increased and then decreased gradually back to the baseline. Furthermore, monitoring the microbial population after drainage of the hot water tank and partial drainage of the entire HPS demonstrated no significant mitigation of the selected OPPPs. This study demonstrates that these organisms can adjust to their environment during such events and may survive in biofilms and/or grow within FLA, protecting them from stressors in the supplied water.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Accounting for Changes in Radiation Improves the Ability of SIF to Track Water Stress-Induced Losses in Summer GPP in a Temperate Deciduous Forest

Global observations of solar-induced chlorophyll fluorescence (SIF) are available from multiple satellite platforms, and SIF is increasingly used as a proxy for photosynthetic activity and ecosystem productivity. Because the relationship between SIF and gross primary productivity (GPP) depends on a variety of factors including ecosystem type and environmental conditions, it is necessary to study SIF observations across various spatiotemporal scales and ecosystems. To explore how SIF signals relate to productivity over a temperate deciduous forest, we deployed a PhotoSpec spectrometer system at the University of Michigan Biological Station AmeriFlux site (US-UMB) in the northern Lower Peninsula of Michigan during the 2018 and 2019 growing seasons. We found that SIF correlated with GPP across diurnal and seasonal cycles (R 2 = 0.61 and 0.64 for 90-min- and daily-averaged data), but that SIF signals were more strongly related to downwelling radiation than GPP (R 2 = 0.91 for daily-averaged data). The dependence of SIF on radiation obscured the impact of intraseasonal drought in the SIF timeseries, but drought stress was apparent as a decrease in relative SIF, which exhibited a stronger correlation with GPP (R 2 = 0.56) than other remotely sensed data over the drought period. These results highlight the potential of SIF for detecting stress-induced losses in forest productivity. Additionally, we found that the red:far-red SIF ratio did not exhibit a response to water stress-induced losses in productivity, but was largely driven by seasonal and interannual changes in canopy structure, as well as by synoptic changes in downwelling radiation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Measurement of neutron-proton capture in the $\mathrmSNO+ water phase

The SNO+ experiment collected data as a low-threshold water Cherenkov detector from September 2017 to July 2019. Measurements of the 2.2-MeV γ 's produced by neutron capture on hydrogen were made using an Am-Be calibration source, for which a large fraction of emitted neutrons are produced simultaneously with a 4.4-MeV γ. Analysis of the delayed coincidence between the 4.4-MeV γ and the 2.2-MeV capture γ revealed a neutron detection efficiency that is centered around 50% and varies at the level of 1% across the inner region of the detector, which to our knowledge is the highest efficiency achieved among pure water Cherenkov detectors. Finally, in addition, the neutron capture time constant was measured and converted to a thermal neutron-proton capture cross section of $336.3^{+1.2}_{-1.5}$ mb .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Fork Experiments in the Hot Cell Using Spent Fuel Rods for International Nuclear Safeguards

This work leveraged the rare availability of 25 full-length pressurized water reactor spent fuel rods and 1 irradiated mixed-oxide rod at an Oak Ridge National Laboratory hot cell. This was done to collect measurement data with two Fork detectors to assess the detectors’ capability of verifying operator declaration data and detecting partial defects in spent fuel, which are the two primary goals of international safeguards on spent nuclear fuel. The data can also be used to benchmark the ORIGEN module, which has been adopted in the International Atomic Energy Agency’s (IAEA’s)/European Atomic Energy Community’s (Euratom’s) Integrated Review and Analysis Program to predict the Fork detector count rates in real time. In this project, the authors first calibrated two Fork detectors—a standard one and a modified one—by using known strong neutron and gamma sources. Then, the authors measured all 26 fuel rods at multiple locations along the length. The fuel rods were then assembled into three arrays—2 × 2, 3 × 3, and 5 × 5—by using specially designed support grids to mimic fuel assemblies and measure the arrays with both detectors. For the 5 × 5 array, 4 and 8 fuel rods of the array were replaced in two separate cases with short stainless-steel rods to mimic two partial defect scenarios, and the arrays were measured before and after the replacements. Polyethylene blocks were used in this experiment to mimic water. The results show that the Fork detectors were able to verify operator declarations and detect partial defects in spent fuel, and the authors were the first to demonstrate this through experiments. A discovery was also made that determined the root cause of the nonlinear response to gamma dose in the ion chambers used in IAEA and Euratom’s Fork detectors. After the experiments, both detectors were retrieved from the hot cell for future use. The data collected in this project will be used in a parallel International Nuclear Safeguards Engagement Program (INSEP) project to enhance the safeguards in the Finnish spent fuel encapsulation plant, and the data will be useful to other projects in the future given the increased safeguards needs due to spent fuel transfer and disposal activities worldwide.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Seismic Ambient Noise Analyses Reveal Changing Temperature and Water Signals to 10s of Meters Depth in the Critical Zone

The critical zone sustains terrestrial life, but we have few tools to explore it efficiently beyond the first few meters of the subsurface. Using analyses of high-frequency ambient seismic noise from densely spaced seismometers deployed in the forested Shale Hills subcatchment of the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), we show that temporal changes in seismic velocities at depths from ~1 m to tens of m can be detected. Furthermore, these changes are driven by variations at the land surface. The Moving-Window Cross-Spectral (MWCS) method was employed to measure seismic-velocity changes in coda waves at hourly resolution in 10 different frequency bands. We observed a diurnal signal, a seasonal signal, and a meteorological-event-based signal. These signals were compared to time-series measurements of precipitation, well water levels, soil moisture, soil temperature, air temperature, latent heat flux, and air pressure in the heavily instrumented catchment. Most of the velocity changes can be explained by variations in temperature that result in thermoelastic strains that propagate to depth. But some double minima in seismic velocity time-series observed after large rain events were attributed in part to the effects of water infiltration. These results show that high-frequency ambient noise data may in some locations be used to detect changes in the critical zone from ~1 to ~100 m or greater depth with hourly resolution. But interpretation of such data requires multiple environmental data sets to deconvolve the complex interrelationships among thermoelastic and hydrological effects in the subsurface critical zone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Biogeochemical control points of connectivity between a tidal creek and its floodplain

As global climates shift, coastal systems experience changes that alter function within the tidal zone. However, it remains uncertain how changes in tidal extent and magnitude will alter coastal biogeochemical cycling. We present high-frequency data collected in-situ along two transects across a tidal creek and floodplain to capture how changes in vertical and lateral connectivity act as biogeochemical control points. Using wavelet analysis, we identified short periods of strong vertical connectivity during spring tides followed by extended periods of floodplain isolation from tides. During a drier period, neap tides were linked to lateral creek-floodplain connectivity, detected by discharge of saline, oxygen-depleted groundwater to the creek on ebb tides. We estimate up to half of creek water throughout the tidal cycle was associated with floodplain drainage. From point measurements of carbon, nitrogen, and greenhouse gases along the creek-floodplain transect, we infer that lateral connectivity functions as a biogeochemically significant control point.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Comparing the extraction performance of cyclodextrin-containing supramolecular deep eutectic solvents versus conventional deep eutectic solvents by headspace single drop microextraction

A headspace single drop microextraction (HS-SDME) method coupled with high performance liquid chromatography was developed to compare the extraction of eighteen aromatic organic pollutants from aqueous solutions using cyclodextrin-based supramolecular deep eutectic solvents (SUPRADESs) and alkylammonium halide-based conventional deep eutectic solvents (DESs). Different derivatives of beta-cyclodextrin (β-CD) were employed as hydrogen bond acceptors (HBA) in SUPRADESs and the extraction performance investigated. SUPRADES comprised of the 20 wt% native β-CD HBA provided the highest enrichment factors of analytes compared to SUPRADESs comprised of other derivatives of β-CD (random methylated β-cyclodextrin, heptakis(2,3,6-tri-O-methyl)-β-cyclodextrin, and 2-hydroxypropyl β-cyclodextrin). In addition, native β-CD and its derivatives were dissolved in the neat DESs and their effect on the extraction of analytes examined. Dissolution of 20 wt% native β-CD in the choline chloride ([Ch + ][Cl - ]):2Urea DES resulted in a significant increase in the extraction efficiencies of target analytes compared to the neat [Ch + ][Cl - ]:2Urea DES. Under optimum conditions, the extraction method required a solvent microdroplet of 6.5 μL, 1000 rpm stir rate, 30% (w/v) salt concentration, and a temperature of 40 °C. The tetrabutylammonium chloride: 2 lactic acid DES resulted in the highest enrichment factors while the [Ch + ][Cl - ]:2Urea DES had the lowest for most of the analytes among the evaluated solvents. The method provided limits of detection (LODs) down to 35 μg L -1 . Finally, the developed method was applied for the analysis of spiked tap and lake water, where relative recoveries ranging from 83.7% -119.7% and relative standard deviations lower than 19.2% were achieved.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Using Solid-State NMR to Understand the Structure of Plant Cellulose

The structure of plant cellulose microfibrils remains elusive, despite the abundance of cellulose and its utility in industry. Using 2D solid-state NMR of 13 C-labeled never-dried plants, six major glucose environments are resolved, which are common to the cellulose of softwood, hardwood, and grasses. These environments are maintained in isolated holocellulose nanofibrils, allowing more detailed microfibril characterization. We show that there are only two glucose environments that reside within the microfibril core. These have the same NMR 13 C chemical shifts as tunicate cellulose Iβ center and origin chains, with no cellulose Iα being detected. The third major glucose site within spectral domain 1, previously assigned to the crystalline microfibril interior, is in close proximity to water, which could indicate that it is a surface glucose environment. The NMR peak widths of all four surface glucose environments are similar to those of the core, indicating that their glucose local order is comparable; there is no significant “amorphous” cellulose in the microfibrils. Consequently, the ratio of the carbon 4 peaks at ∼89 and ∼84 ppm, which has often provided a sample cellulose crystallinity index, is not a meaningful measure of fibril crystallinity or the interior to surface ratio. The revised ratio for poplar wood microfibrils is estimated to be 1:2, which is consistent with an 18-chain microfibril having 6 core and 12 surface chains, although other microfibril sizes are possible. These advances substantially change both the interpretation of solid-state NMR studies of cellulose and the understanding of cellulose microfibril structure and crystallinity.

carbohydrates↗
DOE OSTI2024

Snow Distribution Patterns Revisited: A Physics-Based and Machine Learning Hybrid Approach to Snow Distribution Mapping in the Sub-Arctic

Snowpack distribution in Arctic and alpine landscapes often occurs in repeating, year-to-year patterns due to local topographic, weather, and vegetation characteristics. Previous studies have suggested that with years of observational data, these snow distribution patterns can be statistically integrated into a snow process modeling workflow. Recent advances in snow hydrology and machine learning (ML) have increased our ability to predict snowpack distribution using in-situ observations, remote sensing data sets, and simple landscape characteristics that can be easily obtained for most environments. Here, we propose a hybrid approach to couple a ML snow distribution pattern (MLSDP) map with a physics-based, snow process model. We trained a random forest ML algorithm on tens of thousands of snow survey observations from a subarctic study area on the Seward Peninsula, Alaska, collected during peak snow water equivalent (SWE). We validated hybrid model outputs using in-situ snow depth and SWE observations, as well as a light detection and ranging data set and a distributed temperature profiling sensor data set. When the hybrid results were compared with the physics-based method, the hybrid method more accurately depicted the spatial patterns of the snowpack, areas of drifting snow, and years when no in-situ observations were used in the random forest ML training data set. The hybrid method also showed improvements in root mean squared error at 61% of locations where time-series estimations of snow depth were observed. These results can be applied to any physics-based model to improve the snow distribution patterning to reflect observed conditions in high latitude and high elevation cold region environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Human-induced changes to the global ocean water masses and their time of emergence

The World Ocean is rapidly changing, with global and regional modification of temperature and salinity, resulting in widespread and irreversible impacts. While the most pronounced observed temperature and salinity changes are located in the upper ocean, changes in water masses at depth have been identified and will probably strengthen in the future. In this study, using 11 climate models, we define when anthropogenic temperature and salinity changes are expected to emerge from natural variability in the ocean interior along density surfaces. The models predict that in 2020, 20–55% of the Atlantic, Pacific and Indian basins have an emergent anthropogenic signal; reaching 40–65% in 2050 and 55–80% in 2080. The well-ventilated Southern Ocean water masses emerge very rapidly, as early as the 1980–1990s, while the Northern Hemisphere water masses emerge in the 2010–2030s. Our results highlight the importance of maintaining and augmenting an ocean observing system capable of detecting and monitoring persistent anthropogenic changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Templates for Risk Informed Assurance with Curvature Embeddings (TRACE)

We investigate recovery of geometric structure from networks embedded in manifolds with spatially varying curvature, extending the constant-curvature framework of Lubold et al. (2023). Our work supports cascade risk assessment in critical infrastructure through the Templates for Risk-informed Assurance with Curvature Embeddings (TRACE) framework. Simulations on a bi-modal Gaussian surface show that constant-curvature methods yield weighted averages shaped by clique patterns, while hierarchical clustering identifies distinct regimes. Localized estimation, however, reveals boundary contamination in transitional regions. To address heterogeneity, we develop distance metrics for graphs with edge and node features, proving their metric validity, and validate them via deterministic graph generation from canonical tilings. We further propose a diffusion-based anomaly detection approach that treats networks as glued manifolds, using curvature discontinuities to detect structural anomalies. Employing the carré-du-champ operator and scalar curvature, we achieve robust anomaly discrimination, demonstrated on the Singapore Water Treatment (SWaT) dataset with joint network-traffic and sensor features. Integration with TRACE reveals how curvature shapes cascade dynamics: positive curvature impedes, while negative curvature accelerates propagation. This geometric perspective provides interpretable risk metrics and visualization tools for critical infrastructure managers. While full validation remains ongoing, our contributions establish a rigorous foundation for geometric analysis of network resilience and cascade vulnerability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The Fuel Motion Monitoring System at TREAT - Current Status and Future Plans

An important component of the United States Nuclear Fuel Safety Transient Testing Program, the Fuel Motion Monitoring System (FMMS) at Idaho National Laboratory's Transient Reactor Test Facility (TREAT) is fast-neutron hodoscope capable of imaging the location, movement, and relocation of nuclear fuel experiments under simulated transient accident conditions. The FMMS was refurbished in parallel with the TREAT restart program starting in 2014, restoring 96-channels of fast-neutron detection. Since returning to operation in 2017 the FMMS has supported many fuel safety experiments supporting accident tolerant fuel development, light-water reactor safety, space thermal nuclear propulsion fuel development, and advanced reactor research and development. In Phase 2 of the FMMS restoration. work is now under way to expand the FMMS' field-of-view by adding an additional 96 channels of fast neutron detectors to the system's hodoscope, along with an expanded data acquisition system and associated transient timing electronics. An overview of the FMSS system and its fast-neutron detectors will be presented along with examples of current FMMS imaging performance and associated information.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

Laser-Induced Breakdown Spectroscopy (LIBS) Sensing for Environmental and Subsurface Monitoring

Groundwater monitoring is essential to timely and accurately reflect the current situations and the trends of water quality. However, the long-term stability and survival of any potential in-situ monitoring method is threatened by the harsh conditions and the groundwater monitoring in downhole environments poses numerous challenges to the sensor community. Laser induced breakdown spectroscopy (LIBS) has been demonstrated as a promising technology for chemical monitoring in high-temperature high-pressure (HTHP) environments and hard to reach places. The technique demonstrates several advantages, such as rapid, real-time, in-situ, and simultaneous detection of multiple elements with simple or no sample preparation. This chapter includes a brief review of the field-portable LIBS systems, and development of a compact, robust, and simple LIBS instrument for downhole HTHP water quality monitoring. The fieldable prototype sensor is tested in an onsite monitoring well where trace elements’ concentrations are tracked over an extended period. The testing has verified that the fiber coupled design performs as desired. The system shows good calibration linearity for tested elements and collection times, and Limits of Detection (LODs) that are comparable to those of tabletop LIBS instruments. In addition to groundwater quality monitoring, the fabricated LIBS-based sensor could have widespread sub-surface detection applications.

Jain, Jinesh [NETL Site Support Contractor, Nation↗
DOE OSTI2022

Modeling multiple scattering transient of an ultrashort laser pulse by spherical particles

The multiple scattering of an ultrashort laser pulse by a turbid dispersive medium (namely a cloud of bubbles in water) is investigated by means of Monte Carlo simulations. The theory of Gouesbet and Gréhan (2000) is used to derive an energetic model of the scattering transient. It is shown that the spreading and extinction of the pulse can be decoupled from the transient of scattering, which allows to describe each phenomenon individually. The transient of scattering is modeled with the Lorenz-Mie Theory and thus is also valid for a relative refractive index lower than one, contrary to the Debye series expansion which does not converge close to the critical angle. This is made possible after the introduction of a new physical object, the Scattering Impulse Response Function (SIRF) which allows to detect the different modes of scattering transient, in time and direction. Here the present approach is more generic, as it enables to simulate clouds of air bubbles in water, which was not possible previously. Two different approaches are proposed within the Monte Carlo framework. The first is a pure Monte Carlo approach where the delay due to the scattering is randomly drawn at each event, while the second is based on the transport of the whole scattering signal. They are both embedded in the Monte Carlo code Scatter3D. Both models produce equivalent trends and are validated against published numerical results. They are then applied to the multiple scattering of ultra short pulse by a cloud of bubble in water in the forward direction. The pulse spread due to the propagation in water is computed for a wide range of traveled distances and pulse durations, and the optimal pulse duration is given to minimize the pulse spread at a given distance. The main result is that the scattered photons exit the turbid medium earlier than the ballistic photons and produce a double peak related to the refraction in the bubble. This demonstrates the possibility to develop new diagnostics to characterize dynamic bubbly flows.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery

Thermal heterogeneity of rivers is essential to support freshwater biodiversity. Salmon behaviorally thermoregulate by moving from patches of warm water to cold water. When implementing river restoration projects, it is essential to monitor changes in temperature and thermal heterogeneity through time to assess the impacts to a river’s thermal regime. Lightweight sensors that record both thermal infrared (TIR) and multispectral data carried via unoccupied aircraft systems (UASs) present an opportunity to monitor temperature variations at high spatial (<0.5 m) and temporal resolution, facilitating the detection of the small patches of varying temperatures salmon require. Here, we present methods to classify and filter visible wetted area, including a novel procedure to measure canopy cover, and extract and correct radiant surface water temperature to evaluate changes in the variability of stream temperature pre- and post-restoration followed by a high-intensity fire in a section of the river corridor of the South Fork McKenzie River, Oregon. We used a simple linear model to correct the TIR data by imaging a water bath where the temperature increased from 9.5 to 33.4 °C. The resulting model reduced the mean absolute error from 1.62 to 0.35 °C. We applied this correction to TIR-measured temperatures of wetted cells classified using NDWI imagery acquired in the field. We found warmer conditions (+2.6 °C) after restoration (p < 0.001) and median absolute deviation for pre-restoration (0.30) to be less than both that of post-restoration (0.85) and post-fire (0.79) orthomosaics. In addition, there was statistically significant evidence to support the hypothesis of shifts in temperature distributions pre- and post-restoration (KS test 2009 vs. 2019, p < 0.001, D = 0.99; KS test 2019 vs. 2021, p < 0.001, D = 0.10). Moreover, we used a Generalized Additive Model (GAM) that included spatial and environmental predictors (i.e., canopy cover calculated from multispectral NDVI and photogrammetrically derived digital elevation model) to model TIR temperature from a transect along the main river channel. This model explained 89% of the deviance, and the predictor variables showed statistical significance. Collectively, our study underscored the potential of a multispectral/TIR sensor to assess thermal heterogeneity in large and complex river systems.

Barker, Matthew I. (ORCID:0000000252864930)↗
DOE OSTI2021

The Hubble PanCET Program: Transit and Eclipse Spectroscopy of the Strongly Irradiated Giant Exoplanet WASP-76b

Ultra-hot Jupiters with equilibrium temperatures greater than 2000 K are uniquely interesting targets as they provide us crucial insights into how atmospheres behave under extreme conditions. This class of giant planets receives intense radiation from their host star and usually has strongly irradiated and highly inflated atmospheres. At such a high temperature, cloud formation is expected to be suppressed and thermal dissociation of water vapor could occur. We observed the ultra-hot Jupiter WASP-76b with seven transits and five eclipses using the Hubble Space Telescope and the Spitzer Space Telescope (Spitzer) for a comprehensive study of its atmospheric chemical and physical processes. We detected TiO and H{sub 2}O absorption in the optical and near-infrared transit spectrum. Additional absorption by a number of neutral and ionized heavy metals like Fe, Ni, Ti, and SiO help explain the short-wavelength transit spectrum. The secondary eclipse spectrum shows muted water feature but a strong CO emission feature in Spitzer’s 4.5 μm band indicating an inverted temperature pressure profile. We analyzed both the transit and eclipse spectra with a combination of self-consistent PHOENIX models and atmospheric retrieval. Both spectra were well fitted by the self-consistent PHOENIX forward atmosphere model in chemical and radiative equilibrium at solar metallicity, adding to the growing evidence that both TiO/VO and NUV heavy metals opacity are prominent NUV-optical opacity sources in the stratospheres of ultra-hot Jupiters.

47 OTHER INSTRUMENTATION↗