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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Changes in Annual Extremes of Daily Temperature and Precipitation in CMIP6 Models

This study presents an analysis of daily temperature and precipitation extremes with return periods ranging from 2 to 50 years in phase 6 of the Coupled Model Intercomparison Project (CMIP6) multimodel ensemble of simulations. Judged by similarity with reanalyses, the new-generation models simulate the present-day temperature and precipitation extremes reasonably well. In line with previous CMIP simulations, the new simulations continue to project a large-scale picture of more frequent and more intense hot temperature extremes and precipitation extremes and vanishing cold extremes under continued global warming. Changes in temperature extremes outpace changes in global annual mean surface air temperature (GSAT) over most landmasses, while changes in precipitation extremes follow changes in GSAT globally at roughly the Clausius–Clapeyron rate of ~7% °C –1 . Changes in temperature and precipitation extremes normalized with respect to GSAT do not depend strongly on the choice of forcing scenario or model climate sensitivity, and do not vary strongly over time, but with notable regional variations. Over the majority of land regions, the projected intensity increases and relative frequency increases tend to be larger for more extreme hot temperature and precipitation events than for weaker events. To obtain robust estimates of these changes at local scales, large initial-condition ensemble simulations are needed. Appropriate spatial pooling of data from neighboring grid cells within individual simulations can, to some extent, reduce the needed ensemble size.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Exploring the Effects of Emplacement Conditions on Explosion P/S Ratios across Local to Regional Distances

High-frequency (~> 2 Hz) seismic P/S amplitude ratios are well-established as a discriminant to distinguish between natural earthquakes and underground explosions at regional distances (~200–1500 km). As research shifts toward identifying lower-yield events, work has begun to investigate the potential of this discriminant for use at local distances (<200 km), in which initial results raise questions about its effectiveness. Here, we utilize data from several chemical explosion experiment series at the Nevada National Security Site in southern Nevada in the United States to study explosion Pg/Lg ratios across the range of local to regional distances. Additionall, the experiments are conducted over differing emplacement conditions, with contrasting geologies and a variety of yields and depths of burial, including surface explosions. We first establish the similarities of Pg/Lg ratios from chemical explosions to those from historic nuclear tests and conclude that, as previous data have suggested, chemical explosion ratios are good proxies for nuclear tests. We then examine Pg/Lg ratios from the new experiment series as functions of distance, yield, depth of burial, and scaled depth of burial (SDOB). At far-local and regional distances, we observe consistently higher ratios from hard-rock explosions compared to ones in a weaker dry alluvium medium, consistent with prior regional distance results. No other trends with yield, depth of burial, or SDOB are strongly evident. Scatter in the observed ratios is very high, particularly at the shortest event-to-station distances, suggesting that small-scale path effects play a significant role. On average, the local distance explosion Pg/Lg ratios show remarkable consistency across all the variations in emplacement. Explosion source models will need to reproduce these results.

58 GEOSCIENCES↗
DOE OSTI2022

Performance Analysis of Speculative Parallel Adaptive Local Timestepping for Conservation Laws

Stable simulation of conservation laws, such as those used to model fluid dynamics and plasma physics applications, requires the satisfaction of the so-called Courant-Friedrichs-Lewy condition. By allowing regions of the mesh to advance with different timesteps that locally satisfy this stability constraint, significant work reduction can be attained when compared to a time integration scheme using a single timestep size. However, parallelizing this algorithm presents considerable difficulty. Since the stability condition depends on the state of the system, dependencies become dynamic and potentially non-local. In this article, we present an adaptive local timestepping algorithm using an optimistic (Timewarp-based) parallel discrete event simulation. We introduce waiting heuristics to limit misspeculation and a semi-static load balancing scheme to eliminate load imbalance as parts of the mesh require finer or coarser timesteps. Last, we outline an interface for separating the physics of the specific conservation law from the temporal integration allowing for productive adoption of our proposed algorithm. We present a misspeculation study for three conservation laws, demonstrating both the productivity of the local timestepping API, for which 74% of the lines of code are reused across different conservation laws, and the robustness of the waiting heuristics—at most 1.5% of element updates are rolled back. Our performance studies demonstrate up to a 2.8× speedup versus a baseline unoptimized local timestepping approach, a 4x improvement in per-node throughput compared to an MPI parallelization of synchronous timestepping, and scalability up to 3,072 cores on NERSC’s Cori Haswell partition.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Hydroxymethanesulfonate (HMS) Formation during Summertime Fog in an Arctic Oil Field

Hydroxymethanesulfonate (HMS) is produced in the aqueous-phase reaction of formaldehyde (HCHO) and sulfur dioxide (SO 2 ) and has been proposed as a significant contributor to midlatitude wintertime pollution events. In this work, we report HMS detection within submicrometer atmospheric aerosols during frequent late summer, regional fog events in an Arctic oil field. The number fraction of individual particles containing HMS increased during fog periods, consistent with aqueous-phase formation. The single-particle mass spectra showed the primary particle signature (oil field emissions), plus secondary oxidized organics and sulfate, consistent with aqueous-phase processing. HMS mass concentrations ranged from below the ion chromatography limit of detection (0.3 ng/m 3 ) to 1.6 ng/m 3 , with sulfate concentrations of 37-222 ng/m 3 . HCHO and SO 2 measurements suggest that the fog HMS production rate is ~10 times higher in the oil fields than in the upwind Beaufort Sea. Aqueous-phase reactions of local oil field emissions during frequent summertime regional fog events likely have downwind impacts on Arctic aerosol composition. The potential for fog-based HMS production was estimated to be an order of magnitude higher in Fairbanks and Anchorage, AK, than in the oil fields and may explain the missing organosulfate source contributing to Fairbanks air quality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

SOLAr Critical Infrastructure Energization (SOLACE): Leveraging Distributed Energy Resources to Provide Local Power

This document is a technical report based on a large-scale DOE-funded project conducted between 2019 and 2022. The project, called SOLAr Critical infrastructure Energization (SOLACE), is aimed at leveraging distributed energy resources (DERs) to provide local power to communities, feeders, or other regions. The project included a particular focus on high-value critical loads such as municipal water supply, telecommunication hubs, and disaster shelters. The key developments of the project were: (1) A comprehensive pre-event power system analysis methodology that identifies and characterizes the viable local power options. (2) A DMS-based example control system for activating and operating the local power solution during a time of crisis. (3) Grid-forming inverter technology to enable isolated local power operation and black-starting. (4) Cyber-security considerations for isolated systems when wider-area communication may be offline. This report describes the overall process that identifies and assesses the viable DER-based local power solutions for a given facility, region, or community. The report documents the process, including the key analysis steps, tools required, data requirements, and recommended pass/fail criteria for each step. It also provides a sample implementation of this process through a test case. Finally, it provides details of how a viable pre-event plan can be selected and activated at go-time when an event has occurred.

14 SOLAR ENERGY↗
DOE OSTI2022

Geometric compatibility measure m' for twin transmission: A predictor or descriptor?

In this work, the geometric compatibility factor m' is critically analyzed to assess whether it can be used to interpret/predict twin transmission (TT) across grain boundaries (GBs). This geometric measure is widely used to relate the likelihood of TT to the misalignment of both the shear and plane-normal directions within a twin set (i.e., incoming and outgoing twin). Here, using a large set of electron back scattering diffraction (EBSD) data, a detailed statistical analysis of twin-GB interactions is performed for {${1\bar{01}}2$} tensile twins in hexagonal close-packed (HCP) metals Mg, Zr, and Ti at different strain levels. In addition, a full-field crystal plasticity model is employed to quantify the role of local stresses and the applicability of m' as a criterion for the TT process. This combined study addresses the following three main questions: (i) What is the fidelity of m' in describing experimentally observed TTs? (ii) Can m' be used as a metric to predict/anticipate TT? (iii) Does m' naturally capture local stress effects? As a descriptor, m' cannot rationalize ~25% of TT events observed in Mg or more than 50% of TT events in Zr and Ti. As a predictor, the m'-measure does not predict TT events in over ~50% of twin-GB interactions analyzed. Further, the applicability of m' to describe and predict TT events decreases with an increase in elastic anisotropy, plastic anisotropy, and macroscopic strain levels. Finally, the twinning simulations reveal that m' does not capture the key effects of local stresses on variant selection upon twin transmission. The local stress induced by the twinning shear transformation plays a dominant role in driving the TT process compared to the geometric alignment of the constituting twins, i.e., m'.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Protoplast fusion in Bacillus species produces frequent, unbiased, genome-wide homologous recombination

Abstract In eukaryotes, fine-scale maps of meiotic recombination events have greatly advanced our understanding of the factors that affect genomic variation patterns and evolution of traits. However, in bacteria that lack natural systems for sexual reproduction, unbiased characterization of recombination landscapes has remained challenging due to variable rates of genetic exchange and influence of natural selection. Here, to overcome these limitations and to gain a genome-wide view on recombination, we crossed Bacillus strains with different genetic distances using protoplast fusion. The offspring displayed complex inheritance patterns with one of the parents consistently contributing the major part of the chromosome backbone and multiple unselected fragments originating from the second parent. Our results demonstrate that this bias was in part due to the action of restriction–modification systems, whereas genome features like GC content and local nucleotide identity did not affect distribution of recombination events around the chromosome. Furthermore, we found that recombination occurred uniformly across the genome without concentration into hotspots. Notably, our results show that species-level genetic distance did not affect genome-wide recombination. This study provides a new insight into the dynamics of recombination in bacteria and a platform for studying recombination patterns in diverse bacterial species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Rolling Root Mean Square Based Multimodal Anomaly Detection for Real Time Monitoring of Smart Grid

Reliable real-time monitoring is valuable for maintaining the operational integrity of modern electrical smart grids. Deployment of heterogeneous sensing technologies in substations has enabled high-resolution, multichannel waveform monitoring, but also introduces challenges for anomaly detection due to noise, baseline drift, and modality-dependent signal characteristics. In this work, we present a computationally efficient unsupervised method for multimodal event detection based on Rolling Root Mean Square based Event Detection (RRMSED). The method is developed using in-house, field deployed sensors collecting data at a utility substation. The sensing system comprises voltage and current sensors, triaxial accelerometers, and magnetometers, collectively capturing electrical, vibrational, and magnetic waveform measurements at high temporal resolution. RRMSED operates by extracting rolling RMS energy features and their first-order temporal differences from consecutive waveform segments for each channel and then applying channel-specific statistical thresholds learned from historical data. A persistence-based exceedance logic is employed to robustly identify transient events while suppressing impulsive noise, and to provide precise temporal localization with high resolution. The framework is designed for continuous server-side operation and can be deployed in real time without requiring complex models. Experiments on simulated waveform data with known ground truth demonstrate low false positive (FP) and false negative (FN) rates. Application to real substation data shows RRMSED to identify events that are not captured by conventional monitoring indicators including fast transient detection algorithm currently deployed in the system. These results indicate that rolling RMS based features provide an effective and practical basis for real-time multimodal event detection in smart-grid substations.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2023

QUENCH DETECTION IN A SUPERCONDUCTING RADIO FREQUENCY CAVITY WITH COMBINED TEMPERATURE AND MAGNETIC FIELD MAPPING

Local dissipation of RF power in superconducting radio frequency cavities create so called "hot-spots", primary precursors of cavity quench driven by either thermal or magnetic instability. These hot-spots are detected by a temperature mapping system, and a large increase in temperature on the outer surface is detected during cavity quench events. Here, we have used combined magnetic and temperature mapping systems using anisotropic magneto-resistance (AMR) sensors and carbon resisters to locate the hot spots and areas with high trapped flux on a 3.0 GHz single-cell Nb cavity during the RF tests at 2.0 K. The quench location and hot spots were detected near the equator when the residual magnetic field in the Dewar is kept < 1 mG. The hot spots and quench locations moved when the magnetic field is trapped locally, as detected by T-mapping system. No significant dynamics of trapped flux is detected by AMR sensors, however change in magnetic flux during cavity quench is detected by a flux gate magnetometer, close to the quench location. The result provide the direct evidence of hot spots and quench events due to localized trapped vortices.

Ciovati, Gianluigi↗
DOE OSTI2026

AI-assisted object condensation clustering for calorimeter shower reconstruction at CLAS12

Several nuclear physics studies using the CLAS12 detector rely on the accurate reconstruction of neutrons and photons from its forward angle calorimeter system. These studies often place restrictive cuts when measuring neutral particles due to an overabundance of false clusters created by the existing calorimeter reconstruction software. In this work, we present a new AI approach to clustering CLAS12 calorimeter hits based on the object condensation framework. The model learns a latent representation of the full detector topology using GravNet layers, serving as the positional encoding for an event’s calorimeter hits which are processed by a Transformer encoder. This unique structure allows the model to contextualize local and long range information, improving its performance. Evaluated on one million simulated $e^-$ $+$ $p$ collision events, our method significantly improves cluster trustworthiness: the fraction of reliable neutron clusters, increasing from 8.88% to 30.73%, and photon clusters, increasing from 51.07% to 64.73%. In conclusion, our study also marks the first application of AI clustering techniques for hodoscopic detectors, showing potential for usage in many other experiments.

Calorimeters↗
DOE OSTI2026

Regional inertia dynamics of U.S. interconnections: An event-based measurement approach

Power grid inertia plays a vital role in frequency stability following large disturbances, yet its distribution across the U.S. grid is highly uneven. While interconnection-wide inertia benchmarks are useful, they can mask regional variability driven by resource mix, network coupling, and geographic separation. This paper extends event-driven inertia estimation to the regional scale using field measurements from the Frequency Monitoring Network (FNET/GridEye). Starting from balancing authority and independent system operator footprints, candidate regions are refined using a composite coherency score that combines frequency-trajectory shape similarity, timing spread, and lead/lag behavior to ensure dynamic consistency. A filtered sliding difference method (FSDM) is then used to construct regional frequency trajectories, detect disturbance onset, and compute robust regional rate-of-change of frequency (RoCoF). Regional, local, and interconnection inertia are estimated by combining RoCoF with event power imbalance, and additional indicators (regional-to-system inertia ratio and inertial-support arrival time) quantify regional-to-interconnection coupling and relative regional contributions. The method is demonstrated on eleven regions across the Eastern Interconnection (EI) and the Western Electricity Coordinating Council (WECC), with the Electric Reliability Council of Texas (ERCOT) used for validation. In ERCOT, estimates compared against energy management system (EMS) values achieve a mean absolute percentage error of 17.94%. WECC exhibits consistently shorter inertial-support arrival times (0.15–0.3 s) than EI (0.7–1.1 s), highlighting contrasting coupling and disturbance-propagation behavior. Overall, the results reveal pronounced spatial heterogeneity in inertia and coupling, underscoring the value of regional monitoring for both operational decision-making and long-term system planning.

Disturbance events↗
DOE OSTI2023

Two Large-Scale Meteorological Patterns are Associated with Short-Duration Dry Spells in the Northeastern United States

Large-scale meteorological pattern (LSMP)–based analysis is used in a novel way to understand meteorological conditions before and during short-duration dry spells over the northeastern United States. These LSMPs are useful to assess models and select better-performing models for future projections. Dry-spell events are identified from histograms of consecutive dry days below a daily precipitation threshold. Events lasting 12 days or longer, which correspond to ~10% of dry-spell events, are examined. The 500-hPa stream-function anomaly fields for the first 12 days of each event are time averaged, and k -means clustering is applied to isolate the dry-spell-related LSMPs. The first cluster has a strong low pressure anomaly over the Atlantic Ocean, southeast of the region, and is more common in winter and spring. The second cluster has strong high pressure over east-central North America and is most common during autumn. Over the region, both clusters have negative specific humidity anomalies, negative integrated vapor transport from the north, and subsidence associated with a midlatitude jet stream dipole structure that reinforces upper-level convergence. Subsidence is supported by cold-air advection in the first cluster and the location on the east side of the lower-level high pressure in the second cluster. Extratropical cyclone storm tracks are generally shifted southward of the region during the dry spells. Individual events lie on a continuum between two distinct clusters. These clusters have similar local, but different remote, properties. Although dry spells occur with greater frequency during drought months, most dry spells occur during nondrought months. Significance Statement: This study examines the large-scale weather patterns and meteorological conditions associated with dry-spell events lasting at least 2 weeks while affecting the northeastern United States. A statistical approach groups events together on the basis of similar atmospheric features. We find two distinct sets of patterns that we call large-scale meteorological patterns. These patterns reduce moisture, foster localized sinking, and shift the storm track southward along the Atlantic seaboard, all of which reduce precipitation. Besides greater understanding, knowing the meteorological patterns during short-term dryness in the region provides an important tool to assess how well atmospheric models reproduce these specific patterns. More dry spells occur in non-drought months than in drought months, which means that dry spells can occur without preexisting drought conditions.

58 GEOSCIENCES↗
DOE OSTI2023

Energetic Electron Precipitation Driven by Electromagnetic Ion Cyclotron Waves from ELFIN’s Low Altitude Perspective

We review comprehensive observations of electromagnetic ion cyclotron (EMIC) wave-driven energetic electron precipitation using data collected by the energetic electron detector on the Electron Losses and Fields InvestigatioN (ELFIN) mission, two polar-orbiting low-altitude spinning CubeSats, measuring 50-5000 keV electrons with good pitch-angle and energy resolution. EMIC wave-driven precipitation exhibits a distinct signature in energy-spectrograms of the precipitating-to-trapped flux ratio: peaks at >0.5 MeV which are abrupt (bursty) (lasting ~17 s, or ΔL ~ 0.56) with significant substructure (occasionally down to sub-second timescale). We attribute the bursty nature of the precipitation to the spatial extent and structuredness of the wave field at the equator. Multiple ELFIN passes over the same MLT sector allow us to study the spatial and temporal evolution of the EMIC wave - electron interaction region. Case studies employing conjugate ground-based or equatorial observations of the EMIC waves reveal that the energy of moderate and strong precipitation at ELFIN approximately agrees with theoretical expectations for cyclotron resonant interactions in a cold plasma. Using multiple years of ELFIN data uniformly distributed in local time, we assemble a statistical database of ~50 events of strong EMIC wave-driven precipitation. Most reside at L ~ 5 – 7 at dusk, while a smaller subset exists at L ~ 8 – 12 at post-midnight. The energies of the peak-precipitation ratio and of the half-peak precipitation ratio (our proxy for the minimum resonance energy) exhibit an L-shell dependence in good agreement with theoretical estimates based on prior statistical observations of EMIC wave power spectra. The precipitation ratio’s spectral shape for the most intense events has an exponential falloff away from the peak (i.e., on either side of ~ 1.45 MeV). It too agrees well with quasi-linear diffusion theory based on prior statistics of wave spectra. It should be noted though that this diffusive treatment likely includes effects from nonlinear resonant interactions (especially at high energies) and nonresonant effects from sharp wave packet edges (at low energies). Sub-MeV electron precipitation observed concurrently with strong EMIC wave-driven >1 MeV precipitation has a spectral shape that is consistent with efficient pitch-angle scattering down to ~ 200-300 keV by much less intense higher frequency EMIC waves at dusk (where such waves are most frequent). At ~100 keV, whistler-mode chorus may be implicated in concurrent precipitation. These results confirm the critical role of EMIC waves in driving relativistic electron losses. Nonlinear effects may abound and require further investigation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Listening for the Landing: Seismic Detections of Perseverance's Arrival at Mars With InSight

The entry, descent, and landing (EDL) sequence of NASA's Mars 2020 Perseverance Rover will act as a seismic source of known temporal and spatial localization. We evaluate whether the signals produced by this event will be detectable by the InSight lander (3,452 km away), comparing expected signal amplitudes to noise levels at the instrument. Modeling is undertaken to predict the propagation of the acoustic signal (purely in the atmosphere), the seismoacoustic signal (atmosphere-to-ground coupled), and the elastodynamic seismic signal (in the ground only). Our results suggest that the acoustic and seismoacoustic signals, produced by the atmospheric shock wave from the EDL, are unlikely to be detectable due to the pattern of winds in the martian atmosphere and the weak air-to-ground coupling, respectively. However, the elastodynamic seismic signal produced by the impact of the spacecraft's cruise balance masses on the surface may be detected by InSight. The upper and lower bounds on predicted ground velocity at InSight are 2.0 × 10 -14 and 1.3 × 10 -10 m s -1 . The upper value is above the noise floor at the time of landing 40% of the time on average. The large range of possible values reflects uncertainties in the current understanding of impact-generated seismic waves and their subsequent propagation and attenuation through Mars. Uncertainty in the detectability also stems from the indeterminate instrument noise level at the time of this future event. A positive detection would be of enormous value in constraining the seismic properties of Mars, and in improving our understanding of impact-generated seismic waves.

58 GEOSCIENCES↗
DOE OSTI2024

A Pn magnitude scale m b ( Pn ) for earthquakes along the equatorial Mid-Atlantic Ridge

We developed a short-period Pn magnitude scale m b (Pn) for earthquakes along the equatorial Mid-Atlantic Ridge. Due to low signal-to-noise ratios, teleseismic body wave magnitude and long-period surface wave magnitude cannot be confidently determined for small earthquakes of m b < 4. Local magnitude scales are also not useful for these events because the oceanic environment does not allow the propagation of crustal phases. However, regional high-frequency Pn waves from these small- to moderate-size (m b 3–6) earthquakes are well recorded in the equatorial Atlantic region and can be used to assign magnitudes. We measured over 2041 Pn peak amplitudes on vertical records from about 21 stations in northeastern Brazil and 11 stations in western Africa in the distance range of 700–3700 km. We analysed data from 189 events from the global centroid moment tensor catalogue to tie our m b (Pn) scale to M w so that seismic moments can be readily estimated. Pn arrivals show apparent group velocity between 7.9 km s –1 at short ranges (~1000 km) and up to 9.1 km s –1 at 3500 km. The measured peak amplitudes have a frequency between 0.8 and 3 Hz at 1000–1800 km, but at greater distances, 1800–3700 km, they show a remarkably consistent frequency of about 0.8 Hz. The peak amplitude attenuates at a higher rate at short distances (~0.65 magnitude units between 700 and 2000 km) but attenuates at a lower rate at long distances (~0.35 magnitude units between 2000 and 3700 km). The low rate of amplitude decay with distance and nearly constant frequency content of the peak amplitudes suggest that Pn waves propagate efficiently in the lower part of the upper mantle in the equatorial Atlantic Ocean basins. Furthermore, these are important attributes of oceanic Pn waves that can be used to assign magnitude for small- to moderate-size earthquakes in the equatorial mid-Atlantic region. The estimated station corrections correlate well with upper mantle low-velocity anomalies, especially in Brazil.

58 GEOSCIENCES↗
DOE OSTI2025

Approaches to attributing underwater noise to a wave energy converter

Radiated noise from marine energy harvesting is of environmental and engineering interest. Here, drifting hydrophones measure underwater noise in the vicinity of a relatively small wave energy converter. A statistical approach is demonstrated for attributing range-dependent, commonly occurring sounds in the frequency band from 90 to 600 Hz. Time-delay-of-arrival localization is then demonstrated for attribution of individual acoustic events likely associated with the power takeoff and wave-hull interactions. Because the radiated noise from the wave energy converter falls below ambient levels at a range of approximately 150 m, it is unlikely to substantially affect marine life at greater distance.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Shallow-to-Deep Convective Transition in the Amazon (Final Report)

The frequent and extensive deep cloud formations over the Amazon Basin provide a vast area of atmospheric heating in the Tropics, forcing large-scale global circulations on daily to secular time scales. Motivated by the importance of these systems to the global climate system and the well-documented seasonal cycle in rainfall over the Amazon Basin, this study focused on improving understanding of the processes governing these systems on seasonal time scales and their impact on the typical growth of convection from early afternoon through evening, termed the shallow-to-deep transition. This study is based on observations from the Department of Energy (DOE) ARM Mobile Facility (AMF) near Manacapuru, Brazil collected during the Observations and Modeling of the Green Ocean Amazon (GOAmazon) field campaign from 1 January 2014 to 30 November 2015, together with total column water vapor (CWV) and surface meteorological observations from a dense Global Navigation Satellite System (GNSS) network within 50 km of the AMF site provided by the CHUVA Program collected in coordination with the GOAmazon campaign. The specific objectives of this study were to address the following questions: 1) What environmental conditions support the shallow-to-deep convective transition over the Central Amazon? 2) How does the relative importance of these conditions compare during the wet and dry seasons? 3) How are these conditions modulated by basin-scale transient forcing? 4) How well are these processes captured by regional model simulations convective resolving scale? Our main hypothesis was that intra-seasonal atmospheric disturbances were a primary driver of rainfall during the wet season in the Central Amazon, while localized surface heating of the land was the primary driver of enhanced rainfall during the dry season. Overall, our findings supported our hypothesis, with the convectively active phase of atmospheric Kelvin waves strongly favoring the development of larger, more organized rain systems during the wet season, while localized isolated deep convection dominated the types of rain events seen during the dry season. These results have implications for the predictability of rainfall over the Central Amazon and for its representation in climate and weather models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Inclusive Search for Anomalous Single-Photon Production in MicroBooNE

The MicroBooNE experiment is an 85-ton active volume liquid argon time projection chamber (LArTPC) neutrino detector situated in the Fermilab Booster Neutrino Beam. One of the main goals for MicroBooNE is to investigate the “low energy excess” (LEE) of electromagnetic events observed by the MiniBooNE experiment by leveraging the unique capabilities of the LArTPC technology to distinguish photons from electron electromagnetic showers. In this poster, we present an inclusive search for anomalous production of single-photon events from neutrino interactions in the MicroBooNE experiment, motivated by the MiniBooNE LEE. The analysis uses the Wire-Cell reconstruction framework to select a sample of inclusive single-photon final-state interactions and leverages simultaneous measurements of sidebands to constrain signal and background predictions and reduce uncertainties. We perform a blind analysis using a dataset collected from February 2016 to July 2018 from the Booster Neutrino Beam (BNB) at Fermilab. In the full signal region, we observe agreement between the data and the prediction, with a goodness-of-fit p-value of 0.11. We then isolate a sub-sample of these events containing no visible protons, and observe 93 $/pm$ 22(stat.) $\pm$ 35(syst.) data events above prediction, corresponding to just above 2$\sigma$ local significance, concentrated at shower energies below 600 MeV.

Yandel, Erin [Los Alamos] (ORCID:0000000277123709)↗