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DOE OSTI2024

A multisensory approach to understanding bat responses to wind energy developments

Abstract Millions of bats are killed at wind energy facilities worldwide, yet the behavioural mechanisms underlying why bats are vulnerable to wind turbines remain unclear. Anthropogenic stimuli that alter perceptions of the environment, known as sensory pollution, could create ecological traps and cause bat mortality at wind farms. We review the sensory abilities of bats to evaluate potential stimuli associated with wind farms and examine the role of spatial scale on the perceptual mechanisms of sensory pollutants associated with wind energy facilities. Audition, vision, somatosensation and olfaction are sensory modalities that bats use to perceive their environment, including wind farms and turbine structures, but they will not all be useful at the same spatial scales. Bats most likely use vision to perceive wind farms on the landscape, and obstruction lighting may be the first sensory cue to attract bats to wind farms from kilometres away. Research that assesses the risks posed by specific sensory pollutants, when conducted at the appropriate scale, can help identify solutions to reduce bat mortality, such as determining the attractiveness of obstruction lighting to bats at a landscape scale.

Jonasson, Kristin A.↗

DOE OSTI2023

COVID-19 Lead Time: Evaluating the timeliness and reliability of reported COVID-19 cases and hospitalizations as leading indicators of hospitalizations and death in the US

The COVID-19 pandemic prompted a reliance on real-time data sources to understand the global spread and impact of the SARS-CoV-2 virus. Reported cases were presumed leading indicators for hospitalizations, while hospitalizations were considered predictive of deaths. However, studies have questioned the consistency of reported cases as leading indicators. This study systematically assesses the reliability of United States (US) reported cases and hospitalizations as leading indicators for hospitalizations and deaths respectively, examining the first 2.5 years of the pandemic (January 2020 - June 2022) across different phases of the pandemic and states. Using correlation analysis, population data, and forecasting accuracy measures, we investigate the temporal relationships and identify possible determinants of lead time variability. Notably, we found that the average lead time between reported cases and hospitalizations across US states is relatively short at 1.76 days, implying that reported cases might not be as effective a leading indicator for hospitalizations as previously believed. Populations with higher comorbidity burdens, such as proportion of smokers, are expected on average to have shorter lead times, possibly due to shorter time to hospitalization among these vulnerable populations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Reviving the carbon sink: The influence of moderate wind disturbance in a secondary temperate mixed forest

Global forests are increasingly exposed to climate-driven perturbations, which may in turn alter their climate mitigation potential. As tropical cyclones expand poleward due to climate warming, wind disturbances in temperate forests have become increasingly frequent. The consequences of moderate wind disturbances remain poorly understood, hindering efforts to quantify their role in the global carbon cycle. Here, we used 16 years of continuous eddy covariance and biometric measurements to investigate the impacts of moderate wind disturbances on the structure and carbon sink dynamics of a temperate forest in Northeast China. Following Typhoon Maysak in 2020, the mortality of large trees (particularly the aging pioneer species) increased ninefold, whereas that of small trees decreased by nearly half. Both stand basal area and leaf area index were reduced between 2019 and 2023, with aging pioneer tree species being more vulnerable than mid-to-late species to wind disturbances. Shifts in species composition altered the environmental sensitivity of forest carbon sink function. Unexpectedly, wind disturbances reversed the declining trends in net ecosystem production and ecosystem carbon use efficiency of this secondary forest. A novel composite structural indicator—the standardized leaf area index (the maximum leaf area supported by per basal area of the stand)—provided robust predictions (R 2 > 0.4) of carbon sink dynamics throughout the study period. The selective removal of less efficient pioneer trees accelerated succession and reversed the aging-related decline in forest carbon sink strength and carbon use efficiency. In conclusion, these findings highlight the potential role of moderate wind disturbances in enhancing forest carbon sink function and offer a framework for understanding, assessing, and predicting forest carbon dynamics under increasing disturbance frequencies driven by climate change.

Carbon sink↗

DOE OSTI2025

Microbially mediated nitrification improves modeled temperate forest responses to declining nitrogen deposition

As nitrogen deposition declines across the US, uncertainty remains in whether temperate forests will continue to sequester carbon. This uncertainty is amplified by ecosystem models that inaccurately capture the microbial mechanisms that drive soil carbon sequestration and nitrogen loss. Further, even soil process models that represent decomposer microbes and better capture soil carbon retention under nitrogen deposition broadly underrepresent microbial nitrogen transformations. To address this limitation, we leveraged three decades of biogeochemical cycling data from a whole-watershed nitrogen fertilization experiment to incorporate microbially-driven nitrification in the FUN-CORPSE (Fixation and Uptake of Nitrogen-Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment) model. Our objectives include: 1) Reproducing key ecosystem responses to fertilization, 2) Integrating microbially-explicit nitrification in FUN-CORPSE, and 3) Assessing modeled soil C and N under projected N deposition shifts. FUN-CORPSE accurately represented soil C and streamwater N losses under ambient N deposition and captured how fertilization induced a 25 % decline in plant C cost of N acquisition, reducing decomposition and increasing soil C. Furthermore, with microbially-explicit nitrification, FUN-CORPSE captured the 100 % increase in nitrification rates and the 50 % increase in streamwater nitrate loss under N fertilization. Specifically, incorporating microbial nitrification improved modeled streamwater N leaching from R 2 = 0.01 to R 2 = 0.57. Under declining N deposition, FUN-CORPSE simulates that N losses recover more quickly than soil C pools. However, the predicted return of soil C to pre-fertilized levels suggests that additional C sequestered due to N deposition may be vulnerable to loss over the next century.

Microbial nitrification model↗

NASA NTRS2017

Qualitative Future Safety Risk Identification an Update

The purpose of this report is to document the results of a high-level qualitative study that was conducted to identify future aviation safety risks and to assess the potential impacts to the National Airspace System (NAS) of NASA Aviation Safety research on these risks. Multiple external sources (for example, the National Transportation Safety Board, the Flight Safety Foundation, the National Research Council, and the Joint Planning and Development Office) were used to develop a compilation of future safety issues risks, also referred to as future tall poles. The primary criterion used to identify the most critical future safety risk issues was that the issue must be cited in several of these sources as a safety area of concern. The tall poles in future safety risk, in no particular order of importance, are as follows: Runway Safety, Loss of Control In Flight, Icing Ice Detection, Loss of Separation, Near Midair Collision Human Fatigue, Increasing Complexity and Reliance on Automation, Vulnerability Discovery, Data Sharing and Dissemination, and Enhanced Survivability in the Event of an Accident.

future aviation safety risk↗

NASA NTRSDate not supplied

Advancing Dust Tolerant Mechanisms for a Sustained Exploration of the Moon

Introduction: “I think dust is probably one of our greatest inhibitors to a nominal operation on the Moon. I think we can overcome other physio-logical or physical or mechanical problems except dust.”– Gene Cernan, Apollo 17 Technical Debrief The Apollo missions revealed the impact of lu-nar dust on mechanisms. Lunar dust particles are jagged and electrostatically charged, giving them the ability to bind or damage mechanisms and alter thermal properties. Reports documented clogged equipment and jammed mechanisms in every mission, regardless of surface duration, as well as clogged mechanisms in the Extravehicular Mobility Suit (EMS), including zippers, wrist and hose locks, faceplates, and sunshades [1-2]. Several astronauts remarked they could not have sustained surface activity much longer because clogged joints would have frozen up completely [2]. Effective dust mitigation strategies are need-ed to support longer duration stays on the lunar surface [3-4]. State of the Art: Technology for mechanisms able to operate in dusty enviroments is advancing rapidly due to the needs of both Mars rovers and the Artemis program. Vacuum-tight connectors are essential for spacesuits and habitats, and their performance can be dependent on cleaning technologies, which have proven difficult on the lunar surface. Several TRL 3-5 technologies are undergoing tests with the expectation to reach TRL 6 within 1-2 years. Some mechanisms will be infused and tested on the VIPER (Volatiles Inves-tigating Polar Exploration Rover) mission planned for mid-2020s. NASA Funded Efforts: NASA has recognized the need for dust tolerant mechanisms, and has partnered with industry to advance the state-of-the-art. At NASA GRC, KSC, and JSC, the Dust Tolerant Mechanisms Project is working to devel-op advanced actuator seals for rotary joints and rotary bearing technologies for long-term sus-tained operation in lunar dust environments. An-other NASA project at NASA GRC, partnered with GSFC, JPL, and KSC is Motors for Dusty & Ex-treme Cold Environments (MDECE). MDECE is developing an unheated magnetically-geared mo-tor that can operate continuously for a long dura-tion at an ambient temperature of -243 ºC (33 K). NASA GRC has the capability to characterize the effects of dust on seals, mechanisms, and other mating surfaces and components under lunar conditions [5]. Through the SBIR/STTR program, NASA has funded several companies to advance dust toler-ant mechanisms via the Dust Tolerant Mecha-nisms sub-topic with applications in surface mobil-ity, spacesuits, connectors, joints, and more. LSIC and Community Efforts: The Lunar Surface Innovation Consortium (LSIC) Dust Miti-gation focus group has fostered collaborations across NASA, industry, and academia to develop solutions that minimizes the impact of lunar dust on robotic and human systems. Community ef-forts have included topical meetings on dust tol-erant mechanisms, featured technology presenta-tions, and feedback to NASA on potential gaps and needs. Testing: In 2021, NASA released NASA-STD-1008 [6]. This NASA Technical Standard estab-lishes minimum requirements and provides guid-ance for testing systems and hardware to be ex-posed to dust in planetary environments. The standard has specific sections dedicated to Mechanisms Testing (e.g. bearings, gears) as well as Seals and Mating Surfaces Testing (e.g. hatches, docking systems). Gaps and Needs: NASA is tracking dust tol-erant mechanisms as a gap in a cross-directorate analysis of capability areas needed to enable fu-ture human space-flight architectures. Two high-priority gap areas include additional facilities for testing mechanisms in lunar-surface conditions, and a better understanding of vulnerabilities to the smallest, nanometer-scale dust particles. Conclusion: Understanding and mitigating lu-nar dust is critical to successful, sustained opera-tions on the lunar surface – whether autonomous or otherwise. This presentation will discuss both the state-of-the-art and open needs in lunar dust tolerant mechanisms, technology impacts, mitiga-tion approaches, testing, LSIC community efforts, and more. References: [1] Gaier, J. R. (2020). The Im-pact of Dust on Lunar Surface Equipment During Apollo. Lunar Dust 2020. [2] GRC, & Gaier, J. R. (2005). The Effects of Lunar Dust on EVA Sys-tems During the Apollo Missions. [3] Johansen, M. R. (2020). An Update on NASA’s Lunar Dust Mitigation Strategy. Lunar Dust 2020. [4] ASI, CSA, ESA, JAXA, & NASA. (2016). Dust Mitiga-tion Gap Assessment Report. [5] Jimenez, N. et al (2022), LPSC Abstract 2572. [6] NASA-STD-1008, 2021.

J I Nunez↗

DOE OSTI2025

Influence of extreme temperature conditions on CO 2 direct air capture using amino-acid solutions

Geological features play a pivotal role in determining the feasibility of deploying CO₂ direct air capture (DAC) technologies, primarily because they influence the availability of cost-effective energy sources, such as natural gas and geothermal energy, and also due to the potential for CO₂ sequestration. Many regions face challenges due to variable weather conditions including seasonal temperature fluctuations, high or low humidity, and sub-ambient temperatures. These extremes can reduce DAC performance or even lead to catastrophic events. Aqueous solvents considered for DAC systems are particularly vulnerable to seasonal variations in colder climates, where the solvent may underperform or freeze. It is therefore essential to investigate the CO₂ capture efficiency of aqueous solvents across a broad range of environmental temperatures, spanning sub-zero to hot conditions (>30 °C). In this study, DAC operation is examined using a high-flux solvent–air crossflow contactor under two major weather scenarios: (i) cold conditions below 0 °C and (ii) hot conditions above 30 °C. A parametric study is conducted to investigate the contactor performance regarding CO₂ removal efficiency, uptake capacity, and reaction kinetics versus temperature when the air velocity through the contactor exceeds 1 m/s. The efficacy of the contactor is systematically investigated using various anti-freeze amino-acid solvent formulations. A mass-transfer mechanistic model is developed to assess the process performance over a wide temperature range and propose scalable design guidelines. Machine learning is also employed to identify key parameters affecting the CO₂ capture efficiency. It is shown that air velocity and temperature are the primary factors influencing CO₂ uptake. Based on performance data obtained under subfreezing temperatures, a technoeconomic analysis is conducted to evaluate the feasibility of using aqueous solvents in seasonal cold regions. In conclusion, the findings of this study provide valuable insights into siting considerations for deploying solvent-based DAC, thereby contributing to the advancement of sustainable carbon removal solutions.

Air–liquid contactor↗

NASA NTRSDate not supplied

Spaceborne Passive-Microwave Hail Detection: Global Climatologies, Validation, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and vulnerable to nonmeteorological biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global passive-microwave climatologies of severe hail using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We find that this retrieval, which leverages a signature in the Minimum 19-GHz polarization corrected temperature (PCT) combined with the 37-GHz PCT depression normalized by tropopause height constrains the radar reflectivity most tightly, and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D. Bang↗

DOE OSTI2025

Impact of developmental methylmercury exposure on avian embryonic development, hatchling growth, and survival

Abstract Methylmercury (MeHg) is a globally ubiquitous and persistent environmental toxicant that negatively affects animal behavior, health, and reproduction. In birds, MeHg is transferred from female to egg, contaminating embryos during sensitive stages of early embryonic development and growth. This toxic exposure in the prenatal environment not only induces mortality but also possible lasting impacts on physiology, health, and survival, even once hatched. The purpose of our study was to further elucidate the negative effects of MeHg exposure during avian embryonic development and explore how such exposure can impact offspring development, growth, and survival, both in ovo and posthatch. To assess this, we experimentally dosed fertile mallard and wood duck eggs with MeHg II chloride and reared developing embryos and ducklings to various endpoints. We found that embryos not only readily accumulated MeHg throughout incubation, but they also displayed varying dose-dependent disparities in body mass and morphometrics, with control individuals being larger during early and late embryonic stages of development (p < 0.05). Furthermore, hatched offspring exposed to MeHg exhibited increasingly slower growth rates between 7 to 10 and 10 to 15 days posthatch (p < 0.05), and were found to have lower survival probabilities both under controlled laboratory conditions (p < 0.005), and in the natural environment (p < 0.05). Our findings on the detrimental effects of MeHg on avian embryos and hatchlings emphasize the need for more proactive means of environmental protection and remediation to protect vulnerable avian populations and the ecosystems they inhabit.

Leaphart, James C.↗

DOE OSTI2022

The Impact of Freeze‐Thaw History on Soil Carbon Response to Experimental Freeze‐Thaw Cycles

Abstract Freeze‐thaw is a disturbance process in cold regions where permafrost soils are becoming vulnerable to temperature fluctuations above 0°C. Freeze‐thaw alters soil physical and biogeochemical properties with implications for carbon persistence and emissions in Arctic landscapes. We examined whether different freeze‐thaw histories in two soil systems led to contrasting biogeochemical responses under a laboratory‐controlled freeze‐thaw incubation. We investigated controls on carbon composition through Fourier‐transform ion cyclotron resonance mass spectrometry (FT‐ICR‐MS) to identify nominal carbon oxidation states and relative abundances of aliphatic‐type carbon molecules in both surface and subsurface soils. Soil cores (∼60 cm‐depth) were sampled from two sites in Alaskan permafrost landscapes with different in situ freeze‐thaw characteristics: Healy (>40 freeze‐thaw cycles annually) and Toolik (<15 freeze‐thaw cycles annually). FT‐ICR‐MS was coupled with in situ temperature data and soil properties (i.e., soil texture, mineralogy) to assess (a) differences in soil organic matter composition associated with previous freeze‐thaw history and (b) sensitivity to experimental freeze‐thaw in the extracted cores. Control (freeze‐only) samples showed greater carbon oxidation in Healy soils compared with Toolik, even in lower mineral horizons where freeze‐thaw history was comparable across both sites. Healy showed the most loss of carbon compounds following experimental freeze‐thaw in the lower mineral depths, including a decrease in aliphatics. Toolik soils responded more slowly to freeze‐thaw as shown by intermediary carbon oxidation distributed across multiple carbon compound classes. Variations in the response of permafrost carbon chemistry to freeze‐thaw is an important factor for predicting changes in soil function as permafrost thaws in high northern latitudes.

Rooney, Erin C.↗

DOE OSTI2025

Quantum Key Distribution Applicability to Smart Grid Cybersecurity Systems

To meet the increasing demand for electricity and to have a more reliable and resilient electric grid against conventional and extreme events, grid modernization is more crucial now than ever before. This will require the development and deployment of devices that provide advanced communication capabilities. The overall efficiency, reliability, and resilience of the smart grid will be inextricably linked to the exchange of information between these devices. Unfortunately, the increased information flow will increase the potential attack surface and introduce new vulnerabilities. While a smarter grid will depend critically on information flow, these benefits will be accrued only if that information can be protected. Nowadays, information is secured in smart grids primarily through cryptography. However, with the increasing number of sophisticated attacks as well as the increasing computational power, the security of the “classical” cryptographic algorithms is threatened. Quantum information science offers solutions to this problem, specifically quantum key distribution (QKD), which provides a means for the generation and secure distribution of symmetric cryptographic keys. The security of QKD stems ultimately from the very nature of quantum physics. In this paper, we investigate the applicability of QKD to the various smart grid sectors and specific use cases. We have identified 18 smart grid use cases of interest for QKD suitability together with 7 QKD factors used for the assessment of the various use cases. For each use case, the impact to security of the loss of confidentiality, integrity, and/or availability is specified. In addition, the suitability of QKD is assessed for each use case with respect to multiple factors.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Mortality correlates with tree functional traits across a wood density gradient in the Central Amazon

Introduction: Understanding the mechanisms of tree mortality in tropical ecosystems remains challenging, in part due to the high diversity of tree species and the inherently stochastic nature of mortality. Plant functional traits offer a mechanistic link between plant physiology and performance, yet their ability to predict growth and mortality remains poorly understood. Given recent increases in tree mortality rates in the Amazon forest following extreme drought and wind events, we tested if lower wood density and acquisitive plant functional traits were associated with increased growth and mortality for common co-occurring trees in the Central Amazon. Methods: Seventeen trees of different species with similar sizes but a range in wood density (WD) and wood traits were felled, then assessed for 27 different individual functional parameters, including whole tree architecture, stem xylem anatomical and hydraulic traits and leaf traits. Traits of the individual trees were related to stand-level growth and mortality rates collected periodically over 30 years from nearby permanent inventory plots. Results: Higher wood density was associated with smaller leaf size, lower foliar base cations, lower stem water content and sapwood fraction, in agreement with the fast-slow plant economics spectrum. Lower wood density was associated with more acquisitive characteristics with greater hydraulic capacity and foliar nutrient concentrations, correlating with greater growth and mortality rates. Discussion: Our results show that lower wood density is part of a coordinated suite of traits linked to high resource acquisition, fast growth, and increased mortality risk, providing a functional framework for predicting species performance and forest vulnerability under future climate stress.

demographics↗

NASA NTRS2002

Speech motor control and acute mountain sickness

BACKGROUND: An objective method that accurately quantifies the severity of Acute Mountain Sickness (AMS) symptoms is needed to enable more reliable evaluation of altitude acclimatization and testing of potentially beneficial interventions. HYPOTHESIS: Changes in human articulation, as quantified by timed variations in acoustic waveforms of specific spoken words (voice onset time; VOT), are correlated with the severity of AMS. METHODS: Fifteen volunteers were exposed to a simulated altitude of 4300 m (446 mm Hg) in a hypobaric chamber for 48 h. Speech motor control was determined from digitally recorded and analyzed timing patterns of 30 different monosyllabic words characterized as voiced and unvoiced, and as labial, alveolar, or velar. The Environmental Symptoms Questionnaire (ESQ) was used to assess AMS. RESULTS: Significant AMS symptoms occurred after 4 h, peaked at 16 h, and returned toward baseline after 48 h. Labial VOTs were shorter after 4 and 39 h of exposure; velar VOTs were altered only after 4 h; and there were no changes in alveolar VOTs. The duration of vowel sounds was increased after 4 h of exposure and returned to normal thereafter. Only 1 of 15 subjects did not increase vowel time after 4 h of exposure. The 39-h labial (p = 0.009) and velar (p = 0.037) voiced-unvoiced timed separations consonants and the symptoms of AMS were significantly correlated. CONCLUSIONS: Two objective measures of speech production were affected by exposure to 4300 m altitude and correlated with AMS severity. Alterations in speech production may represent an objective measure of AMS and central vulnerability to hypoxia.

NASA Discipline Space Human Factors↗

DOE OSTI2021

Autonomous Tools for Attack Surface Reduction (Final Report)

The electric power grid is a complex critical infrastructure that forms the lifeline of modern society, and its secure and reliable operation is of paramount importance to national security and economic wellbeing. However, recent findings documented in authoritative sources indicate the threat of cyber-based attacks growing in numbers and sophistication. However, securing the grid against stealthy cyberattacks is a challenging task due to legacy nature of the infrastructure coupled with dynamic nature of threat landscape and ever-growing sophistication of the adversaries. Additionally, the grid’s attack surface continues to grow with the increased dependence on digital communications and control that now extends to each consumer through smart meters and distributed energy resources. Unfortunately, this expansive surface increases the grid’s vulnerability and further exposes critical control systems in both substations and control centers. To respond to this emerging need, we had successfully assembled an interdisciplinary team with academic- industry partnership to successfully conduct research, development, evaluation, demonstration, and commercialization of attack surface reduction tools, whose goal was to significantly reduce the cyber attack surface in the North American power grid. Our proposed project was a synergistic collaborative effort leveraging the synergistic expertise of the team members across power systems, cyber security and CPS security, testbeds, field deployments and demonstration, and successful commercialization. The following are the specific tasks that have been successfully completed two phases (2016-2020). Phase I: Task 1: Developed and implemented a robust Project Management and Data Management Plan, coupled with a well thought out Risk Mitigation Plan. Task 2.1: Developed a comprehensive framework that continually assesses and autonomously reduces the attack surface for the power grid control environment spanning across substations, control center and the SCADA network to significantly reduce the risks of cyber attacks. Task 2.2: Developed attack surface analysis techniques, metrics, and tools that assess the attack surface at multiple levels including the control center, substations, and the SCADA network. Task 2.3: Developed attack surface reduction techniques and tools that dynamically reduce attack surface and hence increase attacker’s cost without interfering in the critical functions of the system. Task 2.4: Prototyped, implemented, and quantitatively evaluated/validated the techniques and tools on a realistic industrial CPS security testbed environment by leveraging the unique resources of the team. Task 3: Developed Commercialization plan to transition the developed tools into power system industry stakeholders for a broader adoption by leveraging the expertise of our industrial members. Phase II: Task 4: Successfully completed field demonstration, verification, and evaluation of the effectiveness of the attack surface analysis and reduction techniques on a realistic utility testbed environment. This also involved the development of realistic scenarios, sound metrics, data sets, evaluation criteria, and documentation. Technology integration & Field demonstration: The project had significantly advanced the state-of-the-art research and practice in improving the cybersecurity of our nation’s power grid infrastructure against cyber threats. In particular, the proposed, designed, and deployed attack surface analysis and reduction algorithms and tools have contributed to significantly reducing the exposure and risk of the devices, substations, and the integrated SCADA/EMS/ DMS grid environment to cyber threat. Strong demonstration and evaluation techniques have verified the feasibility of the developed techniques on realistic cyber-physical testbeds and utility partner's real grid environment, and collaborative research and evaluation of attack surface reduction techniques (for wide-are monitoring and control) within a vendor (GE) EMS platform. The Attack Host Analyzer (AHA) tool that was developed through this project was made available through GitHub.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

LDRD23-0184: Resilience and Hazard Risk Assessment to Prioritize Security Operations for Decisions and Impacts (RHAPSODI)

Recent examples provide a significant concern for the resilience of the U.S. electric grid and represent a need for enhanced decision-making to address an increasingly wide range of complex system interactions and potential consequences. In response, this LDRD project produced a proof-of-concept evaluation called the Resilience and Hazard Assessment to Prioritize Security Operations for Decisions and Impacts (RHAPSODI) methodology as an agile and flexible analytic framework capable of addressing multiple, diverse threats to desired electric grid performance. After empirically grounding needs for the future of U.S. electric grid resilience, this project employed the systems-theoretic process analysis (STPA) to develop a systems engineering risk model. The results of a completed feasibility study of a notional high voltage transmission system demonstrate an improved ability to incorporate both spatial (e.g., geographically distributed) and temporal (e.g., dynamic and time-dependent) elements of security risk to the gird. The success of this LDRD project provides the foundation for further evolution of the systems engineering risk model for the grid; derivation of quantitative approaches to evaluate risk and resilience performance; facilitation of agile experimenting and grid sensitivity to a range of vulnerabilities; and development of tools to assist decision-makers in enhancing U.S. electrical grid resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2016

LS3MIP (v1.0) Contribution to CMIP6: The Land Surface, Snow and Soil Moisture Model Intercomparison Project Aims, Setup and Expected Outcome.

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow, and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth System Models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems).The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (LMIP, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (LFMIP, building upon the GLACE-CMIP blueprint).

atmospheric temperature↗

NASA NTRS2019

Snow Depth Variability in the Northern Hemisphere Mountains Observed from Space

Accurate snow depth observations are critical to assess water resources. More than a billion people rely on water from snow, most of which originates in the Northern Hemisphere mountain ranges. Yet, remote sensing observations of mountain snow depth are still lacking at the large scale. Here, we show the ability of Sentinel-1 to map the snow depth in the Northern Hemisphere mountains at 1 km² resolution using an empirical change detection approach. An evaluation with measurements from ~4,000 sites and reanalysis data demonstrates that the Sentinel-1 retrievals capture the spatial variability between and within mountain ranges, as well as their inter-annual differences. This is showcased with the contrasting snow depths between 2017 and 2018 in the US Sierra Nevada and European Alps. With Sentinel-1 continuity ensured until 2030 and likely beyond, these findings lay a foundation for quantifying the long-term vulnerability of mountain snow-water resources to climate change.

Hans Lievens↗

DOE OSTI2023

Hydropower Resilience Database for Assessing Microgrid Formation Capability and Enhancing Power Grid Resilience

In the face of increasing frequency of extreme events, enhancing resilience and reliability of energy infrastructure demands innovative solutions. Hydropower, with its inherent generation flexibility and grid-forming capability, offers significant potential for enhancing power grid resilience through the establishment of microgrids. To enable informed decision-making and strategic planning, we present the Hydropower Resilience Database (HRD) that integrates data from various sources such as Oakridge National Laboratory (ORNL) HydroSource, National Inventory of Dams, and US Western Grid database. By integrating relevant information on hydropower plant characteristics, including dams, reservoirs, and connected electrical grid, this resource enables hydropower plant owners, utilities, and community stakeholders to identify and evaluate the feasibility of using hydropower resources in microgrids to support nearby communities and critical infrastructure in various challenging scenarios. Using HRD, a set of metrics are evaluated to quantify the capability of hydropower plants to support essential microgrid functions. An interactive tool is developed using ArcGIS, enabling the visualization and analysis using HRD. Our research contributes to strategic planning efforts for fortifying energy infrastructure, ensuring reliable power supply during disruptions, and advancing the development of robust and resilient energy systems in regions susceptible to grid vulnerabilities.

13 HYDRO ENERGY↗