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

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Social inequalities in climate change-attributed impacts of Hurricane Harvey

Climate change is already increasing the severity of extreme weather events such as with rainfall during hurricanes. But little research to date investigates if, and to what extent, there are social inequalities in climate change-attributed extreme weather event impacts. Here, we use climate change attribution science paired with hydrological flood models to estimate climate change-attributed flood depths and damages during Hurricane Harvey in Harris County, Texas. Using detailed land-parcel and census tract socio-economic data, we then describe the socio-spatial characteristics associated with these climate change-induced impacts. We show that 30 to 50% of the flooded properties would not have flooded without climate change. Climate change-attributed impacts were particularly felt in Latina/x/o neighborhoods, and especially so in Latina/x/o neighborhoods that were low-income and among those located outside of FEMA’s 100-year floodplain. Our focus is thus on climate justice challenges that not only concern future climate change-induced risks, but are already affecting vulnerable populations disproportionately now.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A storyline analysis of Hurricane Irma’s precipitation under various levels of climate warming

Abstract Understanding how extreme weather, such as tropical cyclones, will change with future climate warming is an interesting computational challenge. Here, the hindcast approach is used to create different storylines of a particular tropical cyclone, Hurricane Irma (2017). Using the community atmosphere model, we explore how Irma’s precipitation would change under various levels of climate warming. Analysis is focused on a 48 h period where the simulated hurricane tracks reasonably represent Irma’s observed track. Under future scenarios of 2 K, 3 K, and 4 K global average surface temperature increase above pre-industrial levels, the mean 3-hourly rainfall rates in the simulated storms increase by 3–7% K −1 compared to present. This change increases in magnitude for the 95th and 99th percentile 3-hourly rates, which intensify by 10–13% K −1 and 17–21% K −1 , respectively. Over Florida, the simulated mean rainfall accumulations increase by 16–26% K −1 , with local maxima increasing by 18–43% K −1 . All percent changes increase monotonically with warming level.

Environmental Sciences & Ecology↗
DOE OSTI2024

Future projections of storm surge in Hurricane Katrina and sensitivity to meteorological forcing resolution

In this study, we investigated whether and how the storm surge induced by Hurricane Katrina could change if it occurs in a future warmer climate, and the sensitivity of the changes to atmospheric forcing resolution. Climate model simulations of Hurricane Katrina at 27 km, 4.5 km, and 3 km resolutions were used to drive storm surge simulations in historical and future climates using the ADvanced CIRCulation (ADCIRC) model. We found that peak surge height increased significantly in the future with all forcing resolutions. However, the future projection is 22% greater in the 3 km forcing, typical of regional climate models, compared to the 27 km forcing, typical of state-of-the-art global climate models. Additionally, the spatial extent of the future change is highly sensitive to forcing resolution, extending most broadly under the 27 km forcing. Furthermore, we found that storm surge duration decreases in the future with all forcing resolutions due to increasing TC translation speed and decreasing ocean lifetime. However, the future change in the surge duration is sensitive to the forcing resolution, decreasing by 31% in the 27 km forcing and 6% in the 3 km forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Real-time attribution of the influence of climate change on extreme weather events: a storyline case study of Hurricane Ian rainfall

Abstract As the Earth continues to warm due to human greenhouse gas emissions, there is a growing need to efficiently communicate the effect that global warming has on individual extreme weather events. Using a storyline approach, we present a rapid attribution of the increase in rainfall over Florida during Hurricane Ian in 2022 due to climate change as a case study. We find that extreme accumulated rainfall amounts associated with Hurricane Ian increased by 18%, far in excess of what would be expected by Clausius–Clapeyron scaling. The study offers a blueprint for rapid operational climate change attribution statements about extreme storms and other very rare weather events.

Reed, Kevin A. (ORCID:0000000337417080)↗
DOE OSTI2024

Resilience Assessment for Distribution Systems during Hurricanes: A Learning-Based Framework

This paper presents a proactive strategy for hurricane-resilient distribution systems. It proposes a Bayesian Neural Network-based outage prediction model considering various parameters, including electrical components, and weather and environmental factors. Addressing challenges in imbalanced outage datasets, a Bias-Variance Tradeoff method is proposed. A resilience assessment model quantifies resilience indices, providing insights into system weaknesses. The approach identifies weak points and serves as a planning benchmark. Numerical results on the modified IEEE 123-node test system demonstrate effectiveness in realistic hurricane scenarios.

Vahedi, Soroush↗
DOE OSTI2025

Distribution System Resilience Assessment Considering PV Vulnerabilities for Hurricane Events

Distribution networks are increasingly vulnerable to damage and outages from extreme weather events. The integration of solar photovoltaics (PVs) further complicates resilience analysis due to its weather-dependent nature. However, limited research has examined the impacts of weather on PVs under severe events like hurricanes. This paper proposes a probabilistic framework to assess distribution system resilience considering PV vulnerabilities during hurricanes. The framework incorporates (i) a spatiotemporal fragility model to evaluate failure probabilities for distribution lines and PVs, and (ii) resilience indices at both system and component levels. The approach offers valuable insights into the resilience of modern distribution grids under extreme weather conditions. Numerical results on the unbalanced IEEE 123-bus test system validate the effectiveness of the framework.

Vahedi, Soroush [University of Connecticut, Storrs↗
DOE OSTI2021

Root responses to warming and hurricane disturbances in a wet tropical forest of Puerto Rico: R code and data

The purpose of this data was to generate a scientific article that describes the responses of tropical roots to a warming experiment and to the effect of two consecutive hurricanes in Puerto Rico (Yaffar et al. in review). This data is from 10 months of minirhizotron images taken every 2 weeks at the experimental warming Tropical Responses to Altered Climate Experiment (TRACE) plots in Puerto Rico before and after Hurricanes Irma and Maria. This project has 3 warmed plots (plot 2,4,6) and 3 control plots (plot 1,3,5) with 2 minirhizotron tubes at each plot. As part of the data, there is also root data taken from cores and in-growth cores. Additionally, there is soil nutrient concentration data, soil microclimate, total leaf area, and canopy openness taken by Reed et al. 2020, and the TRACE census. Data files are in CSV format and the R code included in this package can be used with R 3.4.4 (R Core Team and contributors worldwide).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Canopy damage and recovery following Hurricane Maria using multitemporal lidar data, Mar/2017 - Mar/2020, Puerto Rico

Hurricane Maria (Category 4) snapped and uprooted canopy trees, removed large branches, and defoliated vegetation across Puerto Rico. The magnitude of forest damages and the rates and mechanisms of forest recovery following Maria provide important benchmarks for understanding the ecology of extreme events. We used airborne lidar data acquired before (2017) and after Maria (2018, 2020) to quantify landscape-scale changes in forest structure along a 439-ha elevational gradient (100 to 800 m) in the Luquillo Experimental Forest. Damages from Maria were widespread, with 73% of the study area losing ≥1 m in canopy height (mean = -7.1 m). Taller forests at lower elevations suffered more damage than shorter forests above 600 m. Yet only 13% of the study area had canopy heights ≤2 m in 2018, a typical threshold for forest gaps, highlighting the importance of damaged trees and advanced regeneration on post-storm forest structure. Heterogeneous patterns of regrowth and recruitment yielded shorter and more open forests by 2020. Nearly 45% of forests experienced initial height loss (<-1 m, 2017-2018) followed by rapid height gain (>1 m, 2018-2020), whereas 21.6% of forests with initial height losses showed little or no height gain, and 17.8% of forests exhibited no structural changes >|1| m in either period. Canopy layers <10 m accounted for most increases in canopy height and fractional cover between 2018-2020, with gains split evenly between height growth and lateral crown expansion by surviving individuals. These findings benchmark rates of gap formation, crown expansion, and canopy closure following hurricane damage. Included in the attached zip file are four TIF and four KML files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Hurricane Sandy Economic Impacts Assessment: A Computable General Equilibrium Approach and Validation

Economists use computable general equilibrium (CGE) models to assess how economies react and self-organize after changes in policies, technology, and other exogenous shocks. CGE models are equation-based, empirically calibrated, and inspired by Neoclassical economic theory. The focus of this work was to validate the National Infrastructure Simulation and Analysis Center (NISAC) CGE model and apply it to the problem of assessing the economic impacts of severe events. We used the 2012 Hurricane Sandy event as our validation case. In particular, this work first introduces the model and then describes the validation approach and the empirical data available for studying the event of focus. Shocks to the model are then formalized and applied. Finally, model results and limitations are presented and discussed, pointing out both the model degree of accuracy and the assessed total damage caused by Hurricane Sandy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

National Hurricane Program Metrics Framework

The need for metrics for planning and response measures was identified as key gap to be addressed in the National Hurricane Program's (NHP) Technology Modernization effort. This document proposes a framework for defining a set of metrics for planning and response that will be implemented in the NHP products of hurricane evacuation studies (HES) and post-storm assessments (PSA). To determine the feasibility of this framework, a survey of current HES and PSAs was carried out followed by and then used to determine if the proposed metrics are currently captured. While there is a wide variety in data availability and detail, the implementation of these metrics is not only feasible but presents an opportunity to improve on current practices. The final implementation of this framework shall require the ongoing feedback from local, state, tribal, and federal stakeholders.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Hurricane Isabel's Impact on JLab

Hurricane Isabel, originally a Category 5 storm (with winds in excess of 155mph), gradually deteriorated as it approached the eastern seashore of the United States arriving at Jefferson Lab on September 18, 2003 with sustained winds of 75mph or a category 2 storm. The storm resulted in minimal direct damage to the infrastructure of Jefferson Lab however caused significant community damage and loss of electric power for four days. Due to the power outage, public travel was limited and JLab was closed for five days before staff was allowed back to work. Without accelerator site utilities beamline vacuum deteriorated and the superconducting cryomodules warmed up causing a total loss of the liquid helium (65,000 liters). This presentation will review the lessons learned and preventive measures that were put in place to mitigate the impact of future hurricanes.

Wang, Yan↗
DOE OSTI2023

Toward Solar Photovoltaic Storm Resilience: Learning from Hurricane Loss and Rebuilding Better

The General Service Administration (GSA) suffered extensive damage to its solar arrays located throughout the Caribbean from Hurricanes Irma and Maria in 2017. While the damage that occurred was unfortunate, there are excellent lessons learned that can be gained and utilized on new systems. A site on St. Croix provides a particularly high-value opportunity for lessons learned due to the innovative rebuilding process utilized by GSA managers and the in-depth analysis performed by the project engineers. This case study focuses on the rebuild of a 469-kW ground array located at the Almeric L. Christian Federal Building in Christiansted, St. Croix in the U.S. Virgin Islands. This array was destroyed by Hurricane Maria. The entire process of planning and subsequent rebuilding that the GSA managers undertook was highly successful. Notably, GSA managers conducting the rebuild effort obtained an independent assessment of failure modes from U.S. Department of Energy (DOE) national labs and then retained a consulting engineering firm to develop design and construction guidance for the rebuild effort. This design and construction guidance was then provided to the engineering, procurement, and constructing firm to implement while rebuilding the site.

14 SOLAR ENERGY↗
DOE OSTI2026

A North Carolina Retrospective: Major Outage Event Trends & Hurricane Helene using TASTI-GRID

The impacts of Hurricane Helene in September of 2024 showed magnifying effects on the number of major power outages reported both during and after the catastrophic weather event. The affected areas on the western edge of North Carolina, particularly Buncombe County (Asheville), endured a disproportionate number of outage impacts than surrounding counties atop the Piedmont Plateau. In 2024, each of the counties with the highest frequency of major outage events received at least one category of FEMA Disaster Declaration following Hurricane Helene. While the storm’s impacts certainly skewed 2024’s yearly major outage frequencies, we use TASTI-GRID to identify existence resilience challenges in the years prior to 2024 that may have given way to understanding how geography, topography, population density and other factors have compounding effects on existing resilience challenges in Buncombe and Mecklenburg counties, specifically.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Long-Duration High-Resolution Large-Eddy Simulations of Hurricane Laura (2020) for Infrastructure Design

This dataset provides long-duration large-eddy simulations (LES) of Hurricane Laura (2020), capturing the turbulent boundary-layer wind field during the storm's passage at horizontal grid spacings of 55.55 m and 10 m. Hurricane Laura made landfall as a Category 4 storm in southwestern Louisiana at 06:00 UTC on 27 August 2020, producing widespread damage to coastal infrastructure. The simulations characterize the spatial and temporal variability of the turbulent wind at heights spanning the lowest 300 m of the boundary layer, throughout the approach and passage of the storm's eyewall over a fixed location. To resolve the spatial heterogeneity of wind and turbulence conditions across the storm, seven independent refined LES runs are performed at radial locations spanning the storm relative to its direction of motion. The refinement positions are defined on a normalized radial coordinate r ̂=r/R, where R≈21 km is Laura's radius of maximum wind, and lie between r ̂=-1.5 and r ̂=+1.5 in ∆r ̂=0.5 increments along a line perpendicular to the storm's track at the midpoint of the simulation. Negative r ̂ corresponds to locations south-southwest of the storm center and positive r ̂ to locations north-northeast. The dataset is segmented into seven radial refinement groups.

17 WIND ENERGY↗
DOE OSTI2025

Advancements on Multi-Fidelity Random Fourier Neural Networks: Application to Hurricane Modeling for Wind Energy

Multi-fidelity approaches are emerging as effective strategies in computational science to handle otherwise intractable tasks like Uncertainty Quantification (UQ), training of Machine Learning (ML) models, and optimization, for expensive high-fidelity applications in which the amount of available simulations or data is limited. The main idea is simple: large datasets generated for low-fidelity approximations of the problem at hand are fused with a much sparser dataset for the target (high-fidelity) system. In this paper, we build on our recent success in designing random Fourier Neural Networks (rFNNs) [1] to target problems arising in wind energy applications and in particular problems of interest for hurricane modeling. In this context, data for the high-fidelity models are limited and lower fidelity alternatives are needed. In this work, we introduce a novel multi-fidelity training approach for our rFNNs and demonstrate its use on a simple verification problem and on a hurricane modeling problem in which high-fidelity data are generated via Large-Eddy Simulations (LES), while low-fidelity data are given by a mesoscale model. Initial results demonstrate how the multi-fidelity training approach can improve the quality of the resulting surrogate.

Fourier Neural Networks↗
DOE OSTI2024

Correlating Power Outage Spread with Infrastructure Interdependencies During Hurricanes

Power outages caused by extreme weather events, such as hurricanes, can significantly disrupt essential services and delay recovery efforts, underscoring the importance of enhancing our infrastructure's resilience. This study investigates the spread of power outages during hurricanes by analyzing the correlation between the network of critical infrastructure and outage propagation. We leveraged datasets from Hurricanemapping.com, the North American Energy Resilience Model Interdependency Analysis (NAERM-IA), and historical power outage data from the Oak Ridge National Laboratory (ORNL)'s EAGLE-I system. Our analysis reveals a consistent positive correlation between the extent of critical infrastructure components accessible within a certain number of steps (k-hop distance) from initial impact areas and the occurrence of power outages in broader regions. This insight suggests that understanding the interconnectedness among critical infrastructure elements is key to identifying areas indirectly affected by extreme weather events.

Bose, Avishek↗
DOE OSTI2018

Simulation and Analysis of Hurricane-Driven Extreme Wave Climate Under Two Ocean Warming Scenarios

Ocean wave climate is an important area of research, particularly in the context of extremes driven by tropical cyclones (TC). We can now simulate global climate at resolutions sufficient to resolve TCs and for durations long enough to explore climatological changes. Both the devastating 2017 North Atlantic hurricane season and growing evidence for the connection between TC activity and increasing ocean temperature motivate investigation of possible future changes. We present two simulated 50-year global wave climate data sets under possible future warming scenarios characterized by +1.5°C and +2.0°C stabilized global mean temperatures that capture the effects of TCs. Differences in extreme wave climate between these possible scenarios and present-day conditions appear to be significant in many areas, particularly those affected by TCs. However, for computational feasibility, simulations of this kind rely on fixed sea surface temperatures, so we also investigate and elucidate effects from the lack of a dynamic ocean by simulating waves from a number of recent hurricanes and comparing output to observations. We conclude that atmosphere-only forcing is likely to result in an overestimate of extreme wind speeds and wave heights in TC-affected regions. More ensemble studies are needed to help elucidate detailed processes relevant to extreme wave climate, and important community projects such as the Coordinated Wave Climate Intercomparison Project (COWCLIP) should be supported.

54 ENVIRONMENTAL SCIENCES↗