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At least 271 records · Page 15

Science-integrated Artificial-intelligence for Flooding and precipitation Extremes (SAFE)

A grand challenge in hydrologic science is to understand why signals of climate change and variability, which are often visible in precipitation extremes at aggregate scales, are not consistently observed in the case of extreme flooding. However, a solution to this challenge may prove elusive unless the water cycle is viewed in an integrative manner. Thus, for riverine flooding, while Hortonian (infiltration excess) runoff may have stronger correlation with precipitation extremes and hence perhaps to warming trends or climate oscillators, Dunne (saturation excess) runoff may have a more complex relationships with time series of precipitation and with evaporation and transpiration, but rain-on-snow and snowmelt events may depend on land-surface and atmospheric temperatures. Atmospheric rivers and tropical cyclones lead to precipitation or flooding and are impacted by climate. Flooding assessments need to consider long-term baselines, evolving risk factors, coupled natural-human systems, and novel adaptation such as nature-inspired design.

54 ENVIRONMENTAL SCIENCES↗

Machine learning to generate gridded extreme precipitation data sets for global land areas with limited in situ measurements

There is a strong need for gridded observational data sets that describe the climatology of extreme precipitation across the globe; such data sets are critical for quantifying precipitation extremes and their corresponding influence on large perturbations on surface and groundwater systems and flooding. Machine learning (ML) methods can be used to generate pseudo in situ measurements of the climatology of extreme precipitation for land regions with poor sampling by matching relevant geographic (e.g., orography) and atmospheric (e.g., surface temperature, precipitation, and pressure) variables for densely sampled regions and those with limited geographic sampling.

54 ENVIRONMENTAL SCIENCES↗

Trustworthy AI for Extreme Event Prediction and Understanding

Our transformational science question is: can we revolutionize both the prediction and understanding of extreme events through trustworthy AI? Our use-cases include extreme weather such as tornadoes and hail as well as water-based events including extreme precipitation, compound flooding, harmful algal blooms, and sea turtle cold stunnings and nest inundations.

54 ENVIRONMENTAL SCIENCES↗

Matter in Extreme Conditions Upgrade (Conceptual Design Report)

The Linac Coherent Light Source (LCLS) X-ray Free Electron Laser (XFEL) is an open-access user facility that delivers ultrashort X-ray pulses that are nine orders of magnitude brighter than any prior source, able to probe the characteristics of matter with unprecedented spatial and temporal precision. The Matter in Extreme Conditions (MEC) instrument at LCLS combines the XFEL with high-power, short-pulse lasers to produce and study high energy density (HED) plasmas to develop the fundamental understanding of plasmas and matter in extreme environments. This has driven a remarkably rich array of high-profile scientific results with applications in fusion energy, isotope production, advanced materials, and medical and nuclear technology. The Matter in Extreme Conditions Upgrade (MEC-U) Project proposes a major upgrade to MEC that would significantly increase the power and repetition rate of the high intensity laser system to the petawatt level (PW, 10 15 Watts) at 10 Hz, increase the energy of the shock-driver laser to the kilojoule level (kJ), and expand the capabilities of the MEC instrument to support groundbreaking experiments enabled by the combination of high-power lasers with the world’s brightest X-ray source.

36 MATERIALS SCIENCE↗

Simulating Extreme Precipitation in the United States in the Energy Exascale Earth System Model: Investigating the Importance of Representing Convective Intensity versus Dynamic Structure (Final Report)

Weather events that produce extreme precipitation are associated with severe flooding and winds that result in thousands of deaths and billions of dollars in damages annually in the United States (U.S.). This project aims to improve understanding of the small- and large-scale processes that govern these events and improve our ability to project changes in these extreme events under the influences of natural variability and human activities. We focus on two promising directions in the development of the U.S. Department of Energy’s Energy Exascale Earth System Model (E3SM) to investigate the tradeoffs between resolving the convective-scale processes that control the intensity versus the intermediate-scale processes that control the dynamic structure of the most prominent extreme precipitation events that impact the U.S. throughout the year (i.e., mesoscale convective systems, tropical cyclones, and extratropical cyclone).

58 GEOSCIENCES↗

Systems Biology-Based Optimization of Extremely Thermophilic Lignocellulose Conversion to Bioproducts

This was a collaborative project involving researchers at the University of Georgia, North Carolina State University, Sanford‐Burnham‐Prebys Med. Discovery Institute and the University of Rhode Island. The over-arching goal was to demonstrate that non-model microorganisms, specifically extreme thermophiles, can be a strategic metabolic engineering platform for industrial biotechnology. We engineered the most thermophilic lignocellulose-degrading organism known, Caldicellulosiruptor bescii (Cbes) , which grows optimally near 80°C, and the most thermophilic fermentative organism known, Pyrococcus furiosus (Pfu) , which grows optimally at 100°C, to produce several key industrial chemicals. This work leveraged recent breakthrough advances in the development of molecular genetic tools for these organisms, complemented by a deep understanding of its metabolism and physiology gained over the past decade of study in the PIs’ laboratories. We applied the latest metabolic reconstruction and modeling approaches to optimize biomass to product conversion. Bio-processing above 70°C can have important advantages over near-ambient operations. Highly genetically-modified microorganisms usually have a fitness disadvantage and can be easily overtaken in culture when contaminating microbes are present. The high growth temperature of extreme thermophiles precludes growth or survival of virtually any contaminating organism or phage. This reduces operating costs associated with reactor sterilization and maintaining a sterile facility. In addition, at industrial scales, heat production from microbial metabolic activity vastly outweighs heat loss through bioreactor walls such that cooling is required. Extreme thermophiles have the advantage that non-refrigerated cooling water can be used if needed, and heating requirements can be met with low-grade steam typically in excess capacity on plant sites. We assembled a highly interdisciplinary team that brought together all of the expertise for the project to have successful outcomes. This project also built upon and utilized extensive information already available in the PIs’ labs for both Cbes and Pfu to develop models that provide a comprehensive description of these organisms’ physiology and metabolism that were utilized to inform metabolic engineering strategies. The models were validated with experimental data and the results demonstrated that unpretreated lignocellulose has the potential to be converted into value-added industrial chemicals at high loading at bioreactor scale. The data generated from this research were published in twenty-one peer-reviewed papers in international journals with online access.

60 APPLIED LIFE SCIENCES↗

Grid Resilience to Extreme Events (ResiliEX 2.0)

The Grid Resilience to Extreme Events (ResiliEX) 2.0 workshop, co-hosted by Pacific Northwest National Laboratory and Seattle City Light, was held at the Seattle City Hall April 23–25, 2024. This is the second workshop of its kind, with the first one having occurred in Seattle in November 2022. Participants from the second workshop hailed from research organizations, utilities, professional associations, consultants, government organizations, and communities. The purpose of the workshop was to Connect scientists, energy professionals, and policy experts to build knowledge and partnerships Advance the understanding of the science of extreme events and application to the energy system Promote grid planning and engineering that addresses the increasingly complex interdependencies as society combats the climate crisis Understand the role of different decision-makers and policymakers in increasing and accelerating grid resilience Identify new approaches, processes, and structures that should be pursued to increase grid resilience to extreme events.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Collaborative: in situ visual analytics technologies for extreme scale combustion simulations

This project aims to drastically enhance the usability of in situ analysis and visualization for extreme-scale scientific simulations. Current exascale computing capabilities promise to offer greater predictive ability of simulations and to further push the frontiers of science and technology. However, to validate the simulation output at extreme scale, examine the modeled phenomena, and discover previously unknowns from the output data, the output must be reduced or transformed in situ as it is being generated during the simulation such that the amount of data to examine and store is kept to a minimum. Such in situ approaches allow us to process and analyze the data and any embedded geometry to an extent that would be prohibitively expensive, if not impossible, to perform as a post hoc task. While in situ processing has been demonstrated to be a feasible and promising approach, its full potential has not yet been leveraged. In this project, we have developed comprehensive enhancements to in situ technology based on probability distributions in data. Our research focuses on jointly developing new ways of interacting with massive statistical samples while creatively utilizing new state-of-the-art computational resources to push the boundaries of in situ exploration. Moreover, we have developed new time-dependent techniques to enable previously unattainable capabilities in areas such as intelligent simulation steering and precise feature identification. We have experimentally studied our design and implementation at NERSC and OLCF, and are able to leverage existing in situ infrastructures whenever possible. While the exemplar in this project is combustion, many other fields for which turbulent transport is important, e.g., fusion, climate, astrophysics among others, encounter similar issues as simulations scale up to the exascale. This project shows its potential to generate high impact on DOE missions since the resulting technology promises to improve scientists’ ability to rapidly and correctly interpret and tune extreme-scale simulations, leading to new scientific understanding and advancements.

97 MATHEMATICS AND COMPUTING↗

On the uncertainty of long-period return values of extreme daily precipitation

Methods for calculating return values of extreme precipitation and their uncertainty are compared using daily precipitation rates over the Western U.S. and Southwestern Canada from a large ensemble of climate model simulations. The roles of return-value estimation procedures and sample size in uncertainty are evaluated for various return periods. We compare two different generalized extreme value (GEV) parameter estimation techniques, namely L-moments and maximum likelihood (MLE), as well as empirical techniques. Even for very large datasets, confidence intervals calculated using GEV techniques are narrower than those calculated using empirical methods. Furthermore, the more efficient L-moments parameter estimation techniques result in narrower confidence intervals than MLE parameter estimation techniques at small sample sizes, but similar best estimates. It should be noted that we do not claim that either parameter fitting technique is better calibrated than the other to estimate long period return values. While a non-stationary MLE methodology is readily available to estimate GEV parameters, it is not for the L-moments method. Comparison of uncertainty quantification methods are found to yield significantly different estimates for small sample sizes but converge to similar results as sample size increases. Finally, practical recommendations about the length and size of climate model ensemble simulations and the choice of statistical methods to robustly estimate long period return values of extreme daily precipitation statistics and quantify their uncertainty.

54 ENVIRONMENTAL SCIENCES↗

Connection between Emission and Absorption Outflows through the Study of Quasars with Extremely High Velocity Outflows

A recently discovered class of outflows, extremely high velocity outflows (EHVOs), may be key to understanding feedback processes, as it is likely the most powerful in terms of mass energy. These EHVOs have been observed at redshifts 1.052 < z em < 7.641, but the potential connection with outflows in emission has not been studied. We find that EHVOs, albeit their small numbers at the moment, appear to show distinct C IV and He II properties. In particular, EHVOs are more predominant in quasars with large blueshifts of the C IV emission line, suggesting a connection between emission and absorption outflowing signatures for these extreme outflows. We also find incipient trends with the maximum velocity of the outflows, which is similar to what has been previously found in BALQSOs but now extending previous studies to speeds up to ~0.2c. We find that the bolometric luminosities, Eddington ratios, and black hole masses of our sample are overall very similar to the general quasar population upon considering their C IV emission properties. This is close to the case for He II EW, as we observe a tentative upper limit to the He II strength for a quasar to host an EHVO. This study shows that extreme outflows such as EHVOs appear in quasars that are clearly a distinct class from the overall BALQSO population and solidify the relation between outflows observed in emission and absorption.

79 ASTRONOMY AND ASTROPHYSICS↗

Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50 ha plot

Abstract. A mechanistic understanding of how tropical-tree mortality responds to climate variation is urgently needed to predict how tropical-forest carbon pools will respond to anthropogenic global change, which is altering the frequency and intensity of storms, droughts, and other climate extremes in tropical forests. We used 5 years of approximately monthly drone-acquired RGB (red–green–blue) imagery for 50 ha of mature tropical forest on Barro Colorado Island, Panama, to quantify spatial structure; temporal variation; and climate correlates of canopy disturbances, i.e., sudden and major drops in canopy height due to treefalls, branchfalls, or the collapse of standing dead trees. Canopy disturbance rates varied strongly over time and were higher in the wet season, even though wind speeds were lower in the wet season. The strongest correlate of monthly variation in canopy disturbance rates was the frequency of extreme rainfall events. The size distribution of canopy disturbances was best fit by a Weibull function and was close to a power function for sizes above 25 m2. Treefalls accounted for 74 % of the total area and 52 % of the total number of canopy disturbances in treefalls and branchfalls combined. We hypothesize that extremely high rainfall is a good predictor because it is an indicator of storms having high wind speeds, as well as saturated soils that increase uprooting risk. These results demonstrate the utility of repeat drone-acquired data for quantifying forest canopy disturbance rates at fine temporal and spatial resolutions over large areas, thereby enabling robust tests of how temporal variation in disturbance relates to climate drivers. Further insights could be gained by integrating these canopy observations with high-frequency measurements of wind speed and soil moisture in mechanistic models to better evaluate proximate drivers and with focal tree observations to quantify the links to tree mortality and woody turnover.

54 ENVIRONMENTAL SCIENCES↗

Evaluation and projection of long period return values of extreme daily precipitation in the CMIP5 and CMIP6 models

Using a non-stationary Generalized Extreme Value statistical method, we calculate selected extreme daily precipitation indices and their 20 year return values from the CMIP5 and CMIP6 climate models over the historical and future periods. We evaluate model performance of these indices and their return values in replicating similar quantities calculated from multiple gridded observational products. Difficulties in interpreting model quality in the context of observational uncertainties are discussed. Projections are framed in terms of specified global warming target temperatures rather than at specific times and under specific emissions scenarios. The change in framing shifts projection uncertainty due to differences in model climate sensitivity from the values of the projections to the timing of the global warming target. At their standard resolutions, we find there are no meaningful differences between the two generations of models in their quality or projections of simulated extreme daily precipitation.

54 ENVIRONMENTAL SCIENCES↗

Observations of extreme wave runup events on the US Pacific Northwest coast

Extreme, tsunami-like wave runup events in the absence of earthquakes or landslides have been attributed to trapped waves over shallow bathymetry, long waves created by atmospheric disturbances, and long waves generated by abrupt breaking. These runup events are associated with inland excursions of hundreds of meters and periods of minutes. While the theory of radiation stress implies that nearshore energy transfer from the carrier waves to the infragravity waves can also lead to very large runup, there have not been observations of runup events induced by this process with magnitudes and periods comparable to the other three mechanisms. This work presents observations of several runup events in the US Pacific Northwest that are comparable to extreme runup events related to the other three mechanisms. It also discusses possible generation mechanisms and shows that energy transfer from carrier waves to bound infragravity waves is a plausible generation mechanism. In addition, a method to predict and forecast extreme runup events with similar characteristics is presented.

54 ENVIRONMENTAL SCIENCES↗

Modeling the U.S. Western Electric Interconnection to Understand the Consequences of Hydrometeorological Extremes and Options for Risk Mitigation

Electricity grid operators around the world face a dual challenge; withstanding increasingly severe weather and the longer term impacts of climate change, while simultaneously decarbonizing. Extreme weather events such as heat waves and droughts are rising in both severity and frequency, which is threatening the reliability of electricity grids through increased demand, generation capacity losses, and equipment failures. Consequently, incorporating hydrometeorological stressors into computational power systems analysis is becoming an even more critical tool in long term planning and short term operations. However, there is a general lack of open-source customizable grid simulation software capable of exhaustively stress testing the grid under hydrometeorological uncertainty, and/or examining potential risk mitigation pathways. A related, persistent challenge for power system modelers is striking an appropriate balance between model fidelity (e.g. spatial scale and time resolution) and computational tractability (wall clock run-time). In this study, we are proposing a solution to this problem with open-source software that allows users to seamlessly customize the scale and track the accuracy of grid operations models. Our approach allows users to search over numerous model parameters (network topology, mathematical formulation, economic hurdle rates, and transmission line scaling) to identify model instantiations that accommodate experimental design. Further, we use this approach to demonstrate the importance of including extreme weather events in model validation and model selection. Focusing on the occurrence of heatwaves and droughts in the U.S. Western Interconnection, we examine role of extreme events in balancing tradeoffs between model fidelity and run-time at the model design stage.

Economics↗

Developing Materials for Extreme Environments and Their Use in Nuclear Waste Canisters and Reactors - 20559

The paper focuses on the development of materials which can be utilized in extreme industrial environments. The paper discusses the advancement of materials and their application in components which are utilized in extreme industrial environments as such that of the nuclear field and especially in the nuclear waste field. Nuclear power plants have become an indispensable part of the electricity generation, medical, food processing and many other industries. Though burning small amount of fuel as compared to conventional power plants, they also create waste which is not easy to handle as other types of wastes. The nuclear waste sitting at the bottom of spent fuel tanks around the globe has raised public concerns on how it will be dealt with. Europe has started to give an answer by working on geological repositories. Though till yet, waste has been cooled in spent fuel tanks and after processing, is precisely placed in nuclear waste canisters and casks and transported to sites across the country for further cooling and storage. Though in all this process there had been a great deal of advancement on the type of casks and canisters used and the processes for transporting nuclear material and waste. Often reports about radioactive material leakage, moisture content inside barrels etc. has surfaced. Be it official or unofficial report, there seems a technical failure on how the nuclear waste has been stored and placed at facilities around the globe. The other aspect of this material development is to be beneficial for nuclear reactors. As the technology gets advanced, nuclear reactors change their titles from Gen II to Gen III and so on. The new fleet of upcoming reactors will be exceptionally safer, reliable and more efficient. But these benefits will also bring drawbacks with them. As these reactors will operate at high temperature (above 800 degree Celsius) they also ask for advancement in materials used in the reactor core, fuel used, reactor control etc. The paper tries to answer such concerning questions. The work shows the study done on different material that can be better candidates for extreme environments. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Multi-Scenario Extreme Weather Simulator

The Multi-scenario Extreme Weather Simulator (MEWS) takes existing historical weather data and inserts trends and extreme events such as heat waves, hurricanes, extreme precipitation, or winter storms. The code includes functionality for projecting increasing frequency and duration of such events over a large range of statistically sampled realizations of the future. These weather files can then be used in building energy simulations through the Energy Plus software created by DOE. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-8658 O

Villa, Daniel↗

Domestic Extremism (Executive Summary)

Domestic extremism (DE) has been a growing concern in the U.S. in recent months, as illustrated in multiple bulletins from the Department of Homeland Security (DHS) warning law enforcement partners of the heightened threat. As concerns about these actors grows, it is important that facilities in the U.S. and internationally that protect critical assets, such as sensitive information, hazardous materials, or critical infrastructure, have effective methods in place to secure those assets. DE has challenged security systems through the danger of insider attack and violence, creating a new threat to be countered. In this effort, therefore, we used a literature review and focus group discussions with experts in critical asset security and extremism to understand the nature of the domestic extremist threat, to identify best practices in securing assets, recognize potential gaps in security measures to be corrected, and recommend actions for the Office of Radiological Security (ORS) to address DE with its partners.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Vapor‐Phase Infiltrated Organic–Inorganic Positive‐Tone Hybrid Photoresist for Extreme UV Lithography

Abstract Continuing extreme downscaling of semiconductor devices, essential for high performance and energy efficiency of future microelectronics, hinges on extreme ultraviolet lithography (EUVL) and addressing associated challenges. One of such challenges is a need for improved EUV photoresists featuring simultaneously high sensitivity, resolution, and etch selectivity. Here, a new, positive‐tone, organic–inorganic hybrid EUV photoresist is demonstrated that delivers a high‐resolution EUVL and electron‐beam lithography (EBL) patterning capability combined with high sensitivity and etch resistance. The new resist, poly(methyl methacrylate) infiltrated with indium oxide (PMMA‐InO x ), is synthesized via vapor‐phase infiltration (VPI), a material hybridization technique derived from atomic layer deposition. The weak binding of the gaseous indium precursor, trimethylindium, to the carbonyl group in PMMA allows the synthesis of hybrids with inorganic content distributed uniformly in the resist, enabling high EUVL and EBL sensitivities (18 mJ cm −2 and 300 µC cm −2 , respectively) and high‐resolution positive‐tone EUVL patterning (e.g., 40 nm half‐pitch line‐space and 50 nm diameter contact hole patterns) with high Si etch selectivity (>30–40). The low exposure doses required to pattern the PMMA‐InO x hybrid resist, high etch resistance, and processing strategies, which are developed, can pave the way for using infiltration‐synthesized hybrid thin films as reliable positive‐tone EUV photoresists for future semiconductor patterning.

36 MATERIALS SCIENCE↗