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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Responses of Compound Daytime and Nighttime Warm-Dry and Warm-H Events to Individual Anthropogenic Forcings

Daytime heat is often associated with reduced soil moisture and cloud cover, while nighttime heat is connected to high humidity and increased cloud cover. Due to these differing mechanisms, compound daytime and nighttime heat events may respond differently to major anthropogenic forcings (greenhouse gases, anthropogenic aerosols, land-use and land-cover change). Here, we use GISS ModelE2.1-G historical single-forcing runs from 1955 to 2014 to examine how individual anthropogenic forcings affect compound heat events—specifically warm daytime and nighttime temperatures compounded with dry precipitation or high humidity conditions. We show that greenhouse gases alone amplify the natural frequency of warm-dry events by 1.5–5 times and warm-humid events by 2–9 times in tropical and extratropical latitudes. Conversely, aerosols and land-use/land-cover change reduce the frequency of these events, resulting in more modest increases and in some regions, declines, in the historical 'all-forcings' scenario. Individually, aerosol effects are stronger and more widespread compared to land-use, oftentimes reducing the natural frequency of these events by 60%–100%. The responses of these compound events are primarily driven by changes in daytime and nighttime temperatures through large-scale warming via greenhouse gases and cooling from aerosols and land-use/land-cover change. However, changes in warm-dry events are amplified in regions with concurrent precipitation declines (e.g. Central America, Mediterranean regions) and warm-humid events are amplified by global concurrent humidity increases. Additionally, we find differences between daytime and nighttime compound responses in the historical experiment that can be traced back to the individual forcings. In particular, aerosols produce a greater cooling effect on daytime relative to nighttime temperatures, which notably results in a historical reduction of Northern Hemisphere daytime warm-dry events relative to natural conditions. Our analysis provides a more comprehensive understanding of the significant impacts of different anthropogenic climate forcings on daytime and nighttime warm-dry and warm-humid events, informing future risk and impact assessments.

Anthropogenic forcings↗
DOE OSTI2021

LeptonInjector and LeptonWeighter: A neutrino event generator and weighter for neutrino observatories

In this work, we present a high-energy neutrino event generator, called LeptonInjector, alongside an event weighter, called LeptonWeighter. Both are designed for large-volume Cherenkov neutrino telescopes such as IceCube. The neutrino event generator allows for quick and flexible simulation of neutrino events within and around the detector volume, and implements the leading Standard Model neutrino interaction processes relevant for neutrino observatories: neutrino-nucleon deep-inelastic scattering and neutrino-electron annihilation. In this paper, we discuss the event generation algorithm, the weighting algorithm, and the main functions of the publicly available code, with examples. Program summary: Program Titles: LeptonInjector and LeptonWeighter CPC Library link to program files: https://doi.org/10.17632/662gkpjfd9.1 Developer's repository links: https://github.com/icecube/LeptonInjector and https://github.com/icecube/LeptonWeighter Licensing provisions: GNU Lesser General Public License, version 3. Programming Language: C++11 External Routines: • Boost • HDF5 • nuflux (https://github.com/icecube/nuflux) • nuSQuIDS (https://github.com/arguelles/nuSQuIDS) • Photospline (https://github.com/icecube/photospline) • SuiteSparse (https://github.com/DrTimothyAldenDavis/SuiteSparse) Nature of problem: LeptonInjector: Generate neutrino interaction events of all possible topologies and energies throughout and around a detector volume. LeptonWeighter: Reweight Monte Carlo events, generated by a set of LeptonInjector Generators, to any desired physical neutrino flux or cross section. Solution method: LeptonInjector: Projected ranges of generated leptons and the extent of the detector, in terms of column depth, are used to inject events in and around the detector volume. Event kinematics follow distributions provided in cross section files. LeptonWeighter: Event generation probabilities are calculated for each Generator, which are then combined into a generation weight and used to calculate an overall event weight.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Disruption event characterization and forecasting in tokamaks

Disruption prediction and avoidance is a critical need for next-step tokamaks, such as ITER. Disruption Event Characterization and Forecasting (DECAF) research fully automates analysis of tokamak data to determine chains of events that lead to disruptions and to forecast their evolution allowing sufficient time for mitigation or complete avoidance of the disruption. Disruption event chains related to local rotating or global magnetohydrodynamic (MHD) modes and vertical instability are examined with warnings issued for many off-normal physics events, including density limits, plasma dynamics, confinement transitions, and profile variations. Along with Greenwald density limit evaluation, a local radiative island power balance theory is evaluated and compared to the observation of island growth. Automated decomposition and analysis of rotating tearing modes produce physical event chains leading to disruptions. A total MHD state warning model comprised of 15 separate criteria produces a disruption forecast about 180 ms before a standard locked mode detector warning. Single DECAF event analyses have begun on KSTAR, MAST, and NSTX/-U databases with thousands of shot seconds of device operation using from 0.5 to 1 × 10 6 tested sample times per device. An initial multi-device database comparison illustrates a highly important result that plasma disruptivity does not need to increase as βN increases. Global MHD instabilities, such as resistive wall modes (RWMs), can give the briefest time period of warning before disruption compared to other physics events. In an NSTX database with unstable RWMs, the mode onset, loss of boundary and current control, and disruption event warnings are found in all cases and vertical displacement events are found in 91% of cases. An initial time-dependent reduced physics model of kinetic RWM stabilization created to forecast the disruption chain predicts instability 84% of the time for experimentally unstable cases with a relatively low false positive rate. Instances of the disruption event chain analysis illustrate dynamics including H–L back transitions for rotating MHD and global RWM triggering events. Furthermore, disruption warnings are issued with sufficient time before the disruption (on transport timescales) to potentially allow active profile control for disruption avoidance, active mode control, or mitigation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Grid Edge Waveform Analytics Framework for Event Detection and Classification

This paper provides a grid edge waveform analytics framework for power system event detection and classification in the local as well as in the wide area. This framework overviews data excellence for event detection and classification. The data excellence describes the data acquisition process and requirements, data processing, data quality, and data integrity. Power system event detection in the local area based on different features such as energy-based, cyclostationary approach, template matching, and wavelet transform are also discussed. Furthermore, local area event detection and classification using approaches such as statistical, signal processing, artificial intelligence, and hybrid are also discussed. Moreover, an overview of wide-area event detection and classification along with several other aspects such as wide-area events, wide-area event detection approaches, event location and system performance, event pattern recognition, inter-area oscillation, and wide-area frequency response under variable deployment of inverter-based resources are also provided. The proposed framework is the first step toward the goal of developing appropriate tools and methodologies to detect and classify local as well as wide-area events using waveform analytics. The appropriate event detection and classification framework development is especially important now as more and more grid edge devices with communication capabilities are being deployed in the modern power grid than ever before.

Bhusal, Narayan↗
DOE OSTI2021

Local-Distance Seismic Event Relocation and Relative Magnitude Estimation, Applications to Mining Related Seismicity in the Powder River Basin, Wyoming

Recent efforts to characterize small ( M w < 3 ) seismic events at local distances have become more important because of the increased observation of human-triggered and induced seismicity and the need to advance nuclear explosion monitoring capabilities. The signals generated by low-magnitude seismic sources necessitate the use of nearby short-period observations, which are sensitive to local geological heterogeneity. Local to near-regional distance ( < 300 km ) surface and shear waves can dominate short-period observations from small, shallow seismic sources. In this work, we utilize these observations to estimate precise, relative locations and magnitudes of ~ 700 industrial mining events in Wyoming, using nearly 360,000 observations. The precise, relative location estimates (with formal location uncertainty estimates of less than 1 km) collapse a diffuse collection of mining events into discrete clusters associated with individual blasting operations. We also invert the cross-correlation amplitudes to estimate precise, relative moment magnitude estimates, which help validate and identify disparities in the event sizes reported by regional network catalogs. Joint use of multiple phases allows for the inclusion of more seismic events due to the increase in the number of observations. In some cases, using a single phase allowed us to relocate only 50% of the original reported seismic events within a cluster. Combining shear- and surface-wave phases increased the number of events to above 90% of the original events, allowing us to characterize a broader range of event sizes, source to station distances, and event distributions. This analysis takes a step toward making a fuller characterization of small industrial seismic events observed at local distances.

58 GEOSCIENCES↗
NASA NTRS1978

Z-rich solar particle event characteristics 1972-1976

It is found in the reported investigation that Z-rich solar particle events usually have large and prolonged anisotropies in addition to an extremely variable charge composition that varies not only from event to event but also throughout the event. These observations suggest that one can no longer regard the event-averaged composition of solar particle events at low energies as providing an unbiased global sample of the solar atmospheric composition. The variability from event to event and among classes of events is just too great. However, the tendency for the Z-rich events to be associated with both the low-speed solar wind at or just before the onset of solar wind streams and with active regions located in the western hemisphere, indicates that charge composition studies of solar particle events can yield a better knowledge of the flare acceleration process as well as the inhomogeneous nature of magnetic field structure and particle composition in the solar atmosphere.

Zwickl, R. D.↗
NASA NTRS1992

Synchronous parallel system for emulation and discrete event simulation

A synchronous parallel system for emulation and discrete event simulation having parallel nodes responds to received messages at each node by generating event objects having individual time stamps, stores only the changes to state variables of the simulation object attributable to the event object, and produces corresponding messages. The system refrains from transmitting the messages and changing the state variables while it determines whether the changes are superseded, and then stores the unchanged state variables in the event object for later restoral to the simulation object if called for. This determination preferably includes sensing the time stamp of each new event object and determining which new event object has the earliest time stamp as the local event horizon, determining the earliest local event horizon of the nodes as the global event horizon, and ignoring the events whose time stamps are less than the global event horizon. Host processing between the system and external terminals enables such a terminal to query, monitor, command or participate with a simulation object during the simulation process.

Steinman, Jeffrey S.↗
NASA NTRS2001

Synchronous Parallel System for Emulation and Discrete Event Simulation

A synchronous parallel system for emulation and discrete event simulation having parallel nodes responds to received messages at each node by generating event objects having individual time stamps, stores only the changes to the state variables of the simulation object attributable to the event object and produces corresponding messages. The system refrains from transmitting the messages and changing the state variables while it determines whether the changes are superseded, and then stores the unchanged state variables in the event object for later restoral to the simulation object if called for. This determination preferably includes sensing the time stamp of each new event object and determining which new event object has the earliest time stamp as the local event horizon, determining the earliest local event horizon of the nodes as the global event horizon, and ignoring events whose time stamps are less than the global event horizon. Host processing between the system and external terminals enables such a terminal to query, monitor, command or participate with a simulation object during the simulation process.

Jeffrey S Steinman↗
NASA NTRS2008

Ion Anisotropy and High-Energy Variability of Large Solar Particle Events: A Comparative Study

We have made comparative studies of ion anisotropy and high-energy variability of solar energetic particle (SEP) events previously examined by the Solar, Heliospheric, and Interplanetary Environment (SHINE) Workshop campaign. We have found distinctly different characteristics of SEPs between two large "gradual" events having very similar solar progenitors (the 2002 April 21 and August 24 events). Since the scattering centers of SEPs are approximately frozen in the solar wind, we emphasize work in the solar-wind frame where SEPs tend to be isotropized, and small anisotropies are easier to detect. While in the August event no streaming reversal occurred, in the April event the field-aligned anisotropy of all heavy ions showed sign of streaming reversal. The difference in streaming reversal was consistent with the difference in the presence of the outer reflecting boundary. In the April event the magnetic mirror, which was located behind the interplanetary shock driven by the preceding coronal mass ejection (CME), could block the stream of SEPs, while in the August event SEPs escaped freely because of the absence of nearby boundary. The magnetic mirror was formed at the bottleneck of magnetic field lines draped around a flank of the preceding CME. In the previous SHINE event analysis the contrasting event durations and Fe/O ratios of the both events were explained as the interplay between shock geometry and seed population. Our new findings, however, indicate that event duration and time as well as spectral variation are also affected by the presence of a nearby reflecting boundary.

Tan, Lun C.↗
NASA NTRS2008

The Long-term Middle Atmospheric Influence of Very Large Solar Proton Events

Long-term variations in ozone have been caused by both natural and humankind related processes. The humankind or anthropogenic influence on ozone originates from the chlorofluorocarbons and halons (chlorine and bromine) and has led to international regulations greatly limiting the release of these substances. Certain natural ozone influences are also important in polar regions and are caused by the impact of solar charged particles on the atmosphere. Such natural variations have been studied in order to better quantify the human influence on polar ozone. Large-scale explosions on the Sun near solar maximum lead to emissions of charged particles (mainly protons and electrons), some of which enter the Earth's magnetosphere and rain down on the polar regions. "Solar proton events" have been used to describe these phenomena since the protons associated with these solar events sometimes create a significant atmospheric disturbance. We have used the National Center for Atmospheric Research (NCAR) Whole Atmosphere Community Climate Model (WACCM) to study the long-term (> few months) influences of solar proton events from 1963 through 2004 on stratospheric ozone and temperature. There were extremely large solar proton events in 1972, 1989,2000,2001, and 2003. These events caused very distinctive polar changes in layers of the Earth's atmosphere known as the stratosphere (12-50 km; -7-30 miles) and mesosphere (50-90 km; 30-55 miles). The solar protons connected with these events created hydrogen- and nitrogen-containing compounds, which led to the polar ozone destruction. The nitrogen-containing compounds, called odd nitrogen, lasted much longer than the hydrogen-containing compounds and led to long-lived stratospheric impacts. An extremely active period for these events occurred in the five-year period, 2000- 2004, and caused increases in odd nitrogen which lasted for several months after individual events. Associated stratospheric ozone decreases of >lo% were calculated to last for up to five months past the largest events. However, the computed total column ozone and stratospheric temperature changes connected with the solar events were not found to be statistically significant. Thus, solar proton events do not likely contribute significantly to measured total column ozone fluctuations and stratospheric temperature changes.

Jackman, Charles H.↗
NASA NTRS2010

Type III Radio Burst Duration and SEP Events

Long-duration (>15 min), low-frequency (<14 MHz) type III radio bursts have been reported to be indicative of solar energetic particle events. We measured the durations of type III bursts associated with large SEP events of solar cycle 23. The Type III durations are distributed symmetrically at 1 MHz yielding a mean value of approximately 33 min (median = 32 min) for the large SEP events. When the SEP events with ground level enhancement (GLE,) are considered, the distribution is essentially unchanged (mean = 32 min, median = 30 min). To test the importance of type III bursts in indicating SEP events, we considered a set of six type III bursts from the same active region (AR 10588) whose durations fit the "long duration" criterion. We analyzed the coronal mass ejections (CMEs), flares, and type II radio bursts associated with the type III bursts. The CMEs were of similar speeds and the flares are also of similar size and duration. All but one of the type III bursts was not associated with a type II burst in the metric or longer wavelength domains. The burst without type II burst also lacked a solar energetic particle (SEP) event at energies >25 MeV. The 1-MHz duration of the type III burst (28 rein) is near the median value of type III durations found for gradual SEP events and ground level enhancement (GLE) events. Yet, there was no sign of SEP events. On the other hand, two other type III bursts from the same active region had similar duration but accompanied by WAVES type 11 bursts; these bursts were also accompanied by SEP events detected by SOHO/ERNE. This study suggests that the type III burst duration may not be a good indicator of an SEP event, consistent with the statistical study of Cliver and Ling (2009, ApJ ).

Gopalswamy, N.↗
NASA NTRS2012

Energy Spectra, Composition, and Other Properties of Ground-Level Events During Solar Cycle 23

We report spacecraft measurements of the energy spectra of solar protons and other solar energetic particle properties during the 16 Ground Level Events (GLEs) of Solar Cycle 23. The measurements were made by eight instruments on the ACE, GOES, SAMPBX, and STEREO spacecraft and extend from approximately 0.1 to approximately 500-700 MeV. All of the proton spectra exhibit spectral breaks at energies ranging from approximately 2 to approximately 46 MeV and all are well fit by a double power-law shape. A comparison of GLE events with a larger sample of other solar energetic particle (SEP) events shows that the typical spectral indices are harder in GLE events, with a mean slope of -3.18 at greater than 40 MeV/nuc. In the energy range 45 to 80 MeV/nucleon about approximately 50% of GLE events have properties in common with impulsive He-3-rich SEP events, including enrichments in Ne/O, Fe/O, Ne-22/Ne-20, and elevated mean charge states of Fe. These He-3 rich events contribute to the seed population accelerated by CME-driven shocks. An analysis is presented of whether highly-ionized Fe ions observed in five events could be due to electron stripping during shock acceleration in the low corona. Making use of stripping calculations by others and a coronal density model, we can account for events with mean Fe charge states of (Q(sub Fe) is approximately equal to +20 if the acceleration starts at approximately 1.24-1.6 solar radii, consistent with recent comparisons of CME trajectories and type-II radio bursts. In addition, we suggest that gradual stripping of remnant ions from earlier large SEP events may also contribute a highly-ionized suprathermal seed population. We also discuss how observed SEP spectral slopes relate to the energetics of particle acceleration in GLE and other large SEP events.

Mewaldt, R. A.↗
DOE OSTI2024

A Data-Driven Framework for Power System Event Type Identification via Safe Semi-Supervised Techniques

Herein this paper investigates the use of phasor measurement unit (PMU) data with deep learning techniques to construct real-time event identification models for transmission networks. Increasing penetration of distributed energy resources represents a great opportunity to achieve decarbonization, as well as challenges in systematic situational awareness. When high-resolution PMU data and sufficient manually recorded event labels are available, the power event identification problem is defined as a statistical classification problem that can be solved by numerous cutting-edge classifiers. However, in real grids, collecting tremendous high-quality event labels is quite expensive. Utilities frequently have a large number of event records without in-depth details (i.e., unlabeled events). To bridge this gap, we propose a novel semi-supervised learning-based method to improve the performance of event classifiers trained with a limited number of labeled events by exploiting the information from massive unlabeled events. In other words, compared to existing data-driven methods, our method requires only a small portion of labeled data to achieve a similar level of accuracy. Meanwhile, this work discusses and addresses the performance degradation caused by class distribution mismatch between the training set and the real applications. Based on the proposed safe learning mechanism, our model does not directly use all unlabeled events during model training, but selectively uses them through a comprehensive evaluation procedure. Numerical studies on a sizable PMU dataset have been used to validate the performance of the proposed method.

42 ENGINEERING↗
NASA NTRS2014

Major Solar Eruptions and High-Energy Particle Events During Solar Cycle 24

We report on a study of all major solar eruptions that occurred on the frontside of the Sun during the rise to peak phase of cycle 24 (first 62 months) in order to understand the key factors affecting the occurrence of large solar energetic particle events (SEPs) and ground level enhancement (GLE) events. The eruptions involve major flares with soft X-ray peak flux greater than or equal to 5.0 x10(exp−5) Wm(exp−2) (i.e., flare size greater than or equal to M5.0) and accompanying coronal mass ejections (CMEs). The selection criterion was based on the fact that the only front-side GLE in cycle 24 (GLE 71) had a flare size of M5.1. Only approximately 37% of the major eruptions from the western hemisphere resulted in large SEP events. Almost the same number of large SEP events was produced in weaker eruptions (flare size less than M5.0), suggesting that the soft X-ray flare is not a good indicator of SEP or GLE events. On the other hand, the CME speed is a good indicator of SEP and GLE events because it is consistently high supporting the shock acceleration mechanism. We found the CME speed, magnetic connectivity to Earth (in longitude and latitude), and ambient conditions as the main factors that contribute to the lack of high-energy particle events during cycle 24. Several eruptions poorly connected to Earth (eastern-hemisphere or behind-the-west-limb events) resulted in very large SEP events detected by the Solar Terrestrial Relations Observatory (STEREO) spacecraft. Some very fast CMEs, likely to have accelerated particles to GeV energies, did not result in a GLE event because of poor latitudinal connectivity. The stringent latitudinal requirement suggests that the highest-energy particles are likely accelerated in the nose part of shocks, while the lower energy particles are accelerated at all parts. There were also well-connected fast CMEs, which did not seem to have accelerated high-energy particles due to possible unfavorable ambient conditions (high Alfven speed, overall reduction in acceleration efficiency in cycle 24).

Flares↗
NASA NTRS2019

Negative extreme events in gross primary productivity and their drivers in China during the past three decades

Climate extremes have remarkable impacts on ecosystems and are expected to increase with future global warming. However, only few studies have focused on the ecological extreme events and their drivers in China. In this study, we carried out an analysis of negative extreme events in gross primary productivity (GPP) in China and the sub-regions during 1982–2015, using monthly GPP simulated by 12 process-based models (TRENDYv6) and an observation-based model (Yao-GPP). Extremes were defined as the negative 5th percentile of GPP anomalies, which were further merged into individual extreme events using a three-dimensional contiguous algorithm. Spatio-temporal patterns of negative GPP anomalies were analyzed by taking the 1000 largest extreme events into consideration. Results showed that the effects of extreme events decreased annual GPP by 2.8% (i.e. 208 TgC/year) in TRENDY models and 2.3% (i.e. 151 TgC/year) in Yao-GPP. Hotspots of extreme GPP deficits were mainly observed in North China (−53 gC/sq.m year) in TRENDY models and Northeast China (−42 gC/sq.m year) in Yao-GPP. For China as a whole, attribution analyses suggested that extreme low precipitation was associated with 40%–50% of extreme negative GPP events. Most events in northern and western China could be explained by meteorological droughts (i.e. low precipitation) while GPP extreme events in southern China were more associated with temperature extremes, in particular with cold spells. GPP was revealed to be much more sensitive to heat/drought than to cold/wet extreme events. Combined with projected changes in climate extremes in China, GPP negative anomalies caused by drought events in northern China and by temperature extremes in southern China might be more prominent in the future.

Climate change↗
DOE OSTI2021

ThickBrick: optimal event selection and categorization in high energy physics. Part I. Signal discovery

We provide a prescription called ThickBrick to train optimal machine-learning-based event selectors and categorizers that maximize the statistical significance of a potential signal excess in high energy physics (HEP) experiments, as quantified by any of six different performance measures. For analyses where the signal search is performed in the distribution of some event variables, our prescription ensures that only the information complementary to those event variables is used in event selection and categorization. This eliminates a major misalignment with the physics goals of the analysis (maximizing the significance of an excess) that exists in the training of typical ML-based event selectors and categorizers. In addition, this decorrelation of event selectors from the relevant event variables prevents the background distribution from becoming peaked in the signal region as a result of event selection, thereby ameliorating the challenges imposed on signal searches by systematic uncertainties. Our event selectors (categorizers) use the output of machine-learning-based classifiers as input and apply optimal selection cutoffs (categorization thresholds) that are functions of the event variables being analyzed, as opposed to flat cutoffs (thresholds). These optimal cutoffs and thresholds are learned iteratively, using a novel approach with connections to Lloyd’s k-means clustering algorithm. We provide a public, Python implementation of our prescription, also called ThickBrick, along with usage examples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

A universal implementation of radiative effects in neutrino event generators

Due to the similarities between electron-nucleus (eA) and neutrino-nucleus scattering (νA), eA data can contribute key information to improve cross-section modeling in eA and hence in νA event generators. However, to compare data and generated events, either the data must be radiatively corrected or radiative effects need to be included in the event generators. We implemented a universal radiative corrections program that can be used with all reaction mechanisms and any eA event generator. Our program includes real photon radiation by the incident and scattered electrons, and virtual photon exchange and photon vacuum polarization diagrams. It uses the “extended peaking” approximation for electron radiation and neglects charged hadron radiation. This method, validated with GENIE, can also be extended to simulate νA radiative effects. This work facilitates data-event-generator comparisons used to improve νA event generators for the next-generation of neutrino experiments. Program Title: emMCRadCorr CPC Library link to program files:https://doi.org/10.17632/hmsxg82vnf.1 Developer's repository link:https://github.com/e4nu/emMCRadCorr Licensing provisions: AGPLv3 Programming language:C++ Nature of problem: Radiative effects can significantly modify the event kinematics and the resulting cross-sections. Such effects must be accounted for when comparing event generators to eA data. Existing radiative correction codes are tailored to specific processes and topologies, and are limited to a restricted phase space defined by the spectrometer acceptance. Therefore, a more general approach is required to apply radiative corrections to semi-inclusive and exclusive eA measurements. Solution method: Our program incorporates real photon radiation from both the incident and scattered electrons, as well as virtual photon exchange and photon vacuum polarization effects. It employs the “extended peaking” approximation for electron radiation while neglecting contributions from charged hadron radiation. The code is fully decoupled from event generator codes and can be used for all event generators in the market.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

What Technical Choices Matter to Characterize Heat Wave and Cold Snap Events in Support of Bulk Power Grid Reliability Studies?

Extreme weather events, such as Heat Waves (HW) and Cold Snaps (CS), pose significant risks to the power grid. The United States (U.S.) Federal Energy Regulatory Commission Order No. 896 mandates regional coordination standards that account for extreme thermal events. However, the lack of a universal definition for extreme thermal events may lead to inconsistent compliance efforts among neighboring entities, undermining the reliability of the transmission system. This study directly addresses this challenge by systematically evaluating how varying technical choices in defining HW and CS fundamentally impact the characterization and ranking of extreme events for power grid reliability studies. We used 12 event definitions and multiple temperature spatial aggregation approaches to construct historical (1980–2024) regional extreme thermal event libraries across North American Electric Reliability Corporation (NERC) subregions in the conterminous U.S. We examined the sensitivity of event characteristics (e.g., duration, frequency, intensity, and spatial coverage) to different definitions. While some definitions produced similar libraries and top event rankings, definitions based on moving-window-averaged temperatures yielded markedly different characteristics. Spatial aggregation methods had minimal impact on heat wave or cold snap intensity, frequency and duration but significantly influenced spatial coverage. The top events identified across different aggregation methods were consistent, but their ranking order varied. These findings offer critical insights for characterizing and selecting extreme thermal events and for supporting local and cross-regional coordination as required by reliability standards.

Wan, Heng [Pacific Northwest National Laboratory (↗