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At least 91 records · Page 5

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DOE OSTI2024

A valuation framework for customers impacted by extreme temperature-related outages

Extreme temperature outages can lead to not just economic losses but also various non-energy impacts (NEI), such as increased mortality rates, property damage, and reduced productivity, due to significant degradation of indoor operating conditions caused by service disruptions. However, existing resilience assessment approaches lack specificity for extreme temperature conditions. They often overlook temperature-related mortality and neglect the customer characteristics and grid response in the calculation, despite the significant influence of these factors on NEI-related economic losses. This paper aims to address these gaps by introducing a comprehensive framework to estimate the impact of resilience enhancement not only on the direct economic losses incurred by customers but also on potential NEI, including mortality and the value of statistical life during extreme temperature-related outages. The proposed resilience valuation integrates customer characteristics and grid response variables based on a scalable grid simulation environment. This study adopts a holistic approach to quantify customer-oriented economic impacts, utilizing probabilistic loss scenarios that incorporate health-related factors and damage/loss models as a function of exposure for valuation. The proposed methodology is demonstrated through comparative resilient outage planning, using grid response models emulating a Texas weather zone during the 2021 winter storm Uri. The case study results show that enhanced outage planning with hardened infrastructure can improve the system resilience and thereby reduce the relative risk of mortality by 16% and save the total costs related to non-energy impacts by 74%. In conclusion, these findings underscore the efficacy of the framework by assessing the financial implications of each case, providing valuable insights for decision-makers and stakeholders involved in extreme-weather related resilience planning for risk management and mitigation strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1986

Selective factors in sun-weather research

Research on the correlations between solar wind/IMF disturbances and subsequent winter troposphere vorticity changes (denoted SV) are reviewed to investigate sun-weather relationships. Uncertainties in the research attempting to link short-term solar variations and associated changes in the lower atmosphere are discussed, and it is noted that such analyses have generally not addressed either the choice of parameters or the selective factors involved in the physical relationships existing between parameters. It is suggested that the identification of a viable mechanism scenario would require a detailed multiparameter selective factor analysis, extending to the investigation of the atmospheric data as well as the solar wind/IMF parameters.

Taylor, H. A., Jr.↗

DOE OSTI2020

Simulations of Winter Arctic Clouds and Associated Radiation Fluxes Using Different Cloud Microphysics Schemes in the Polar WRF: Comparisons With CloudSat, CALIPSO, and CERES

Clouds are important for the Arctic climate, but simulating such clouds with numerical models is still challenging. The accuracy of model clouds has not been sufficiently examined due to the harsh Arctic environment obstructing cloud observations, especially during Arctic winters experiencing polar nights. This study compares the Arctic winter clouds simulated by a weather forecast model to cloud observations from active (lidar and radar) satellite instruments. The model successfully produced cloud patterns similar to the satellite observations. However, the choice of the cloud physics module in the model can modify the amount of cloud water significantly enough to affect the simulated surface climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Feb. 2021 Electricity Blackouts and Natural Gas Shortages in Texas

An extreme winter storm and extended cold weather event hit Texas and the central United States February 8–19, 2021. This led to both exceptional energy demands and issues with electricity and natural gas supplies over several days. Residential space heating drove the increases in demand, with over 60% of Texas homes using electric heat pumps and 35% using natural gas furnaces. Supply issues were caused by freezing equipment and supply lines, impacting both natural gas supplies and most forms of electricity generation. [1] Natural gas supplies were especially important because natural gas also supplied about 50% of the electricity generating capacity in ERCOT, the primary grid operator in Texas. [2] Due to the supply shortages, wholesale electricity prices were forced to the ERCOT maximum of $\$9,000$ /MWh for over three days (recent range $\$20$–40/MWh), [3] and natural gas prices for physical delivery exceeded $\$400$ /MMBtu in some areas (recent range $\$3$–4/MMBtu). [4]

03 NATURAL GAS↗

NASA NTRS1988

Research at the earth's edge

The Space Shuttle Orbiter-deployed Tethered Satellite System (TSS) could allow an Orbiter at a 200 km orbital altitude to reach down to atmospheric altitudes of 90 km, in order to study weather phenomena, pollutant transport, 'nuclear winter' smoke transport, atmospheric physics and dynamics, sun-earth interactions, ecosystem interactions, and radio communications. The TSS satellite, a 1.5-m diameter sphere, would carry scientific instrumentation which could initially be dedicated to the investigation of energy and momentum transfer between a tethered system and the upper atmosphere.

Anderson, John L.↗

NASA NTRS2007

Preliminary Validation of the AFWA-NASA Blended Snowcover Product Over the Lower Great Lakes region

A new snow product created using the standard Moderate-Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) snow cover and snow-water equivalent products has been evaluated for the Lower Great Lakes region during the winter of 2002- 03. National Weather Service Co-Operative Observing Network stations and student-acquired snow data were used as ground truth. An interpolation scheme was used to map snow cover on the ground from the station measurements for each day of the study period. It is concluded that this technique does not represent the actual ground conditions adequately to permit evaluation of the new snow product in an absolute sense. However, use of the new product was found to improve the mapping of snow cover as compared to using either the MODIS or AMSR-E product, alone. Plans for further analysis are discussed.

Hall, D. K.↗

NASA NTRS2016

Vibrating-Wire, Supercooled Liquid Water Content Sensor Calibration and Characterization Progress

NASA conducted a winter 2015 field campaign using weather balloons at the NASA Glenn Research Center to generate a validation database for the NASA Icing Remote Sensing System. The weather balloons carried a specialized, disposable, vibrating-wire sensor to determine supercooled liquid water content aloft. Significant progress has been made to calibrate and characterize these sensors. Calibration testing of the vibrating-wire sensors was carried out in a specially developed, low-speed, icing wind tunnel, and the results were analyzed. The sensor ice accretion behavior was also documented and analyzed. Finally, post-campaign evaluation of the balloon soundings revealed a gradual drift in the sensor data with increasing altitude. This behavior was analyzed and a method to correct for the drift in the data was developed.

Icing↗

NASA NTRS2016

Vibrating-Wire, Supercooled Liquid Water Content Sensor Calibration and Characterization Progress

Icing↗

NASA NTRSDate not supplied

Post-Severe Thunderstorm Damage Assessment from March 2-3, 2020, Nashville, TN, Using Synthetic Aperture Radar Observations

Severe weather events (e.g., hurricanes, tornadoes) are responsible for most weather-related infrastructure and building damages. The destruction caused by these events can cross several states, making damage estimates difficult, especially in heavily vegetated or rural areas. Drone or optical imagery is often relied upon in these cases but is limited by solar and atmospheric conditions. Synthetic Aperture Radar (SAR) is an active sensor allowing for day and night collections in all weather conditions. This research highlights the benefits and limitations of using SAR to detect tornado tracks and associated damages while also assessing the strengths and weaknesses of two SAR sensors with varying wavelengths and spatial resolutions from the March 2020 Tornado Outbreak. The outbreak occurred overnight on March 2-3, when several supercell thunderstorms tracked across multiple states producing numerous tornadoes (EF-0 through EF-4) and large hail. Most of the damage occurred in central Tennessee, resulting in 25 fatalities, hundreds of injuries, and over a billion dollars worth of damage. Publicly available C-band (~6 cm) imagery from the European Space Agency’s Sentinel-1 satellite and commercial X-band (~3 cm) imagery from Airbus’s TerraSAR-X satellite were used to generate amplitude and coherence products. The closest post-event collections were used for the amplitude products, and the closest pre- and post-collections were used to create the coherence pairs. If damage tracks were identified in any of the SAR products, the length (miles) and max width (yards) were recorded and compared to the National Weather Service Storm Data official records. SAR successfully detected five rated EF-1 or higher out of ten recorded tornadoes. However, none of the four EF-0 tornadoes were identified. X- and C-band SAR sensors are heavily impacted by dense vegetation, underestimating the extent of damage. Despite these limitations, SAR products can be beneficial when looking at severe weather impacts, especially during the winter and early spring when the coherence products are less influenced by vegetation. The upcoming L-band (~24 cm) NISAR mission will provide more accurate estimates of damage, with the longer wavelength, expanding the applications of SAR to assist in damage assessment caused by severe thunderstorms.

Hannah G Pankratz↗

NASA NTRSDate not supplied

Ice Cloud Observations and Science using Submillimeter-Wave Radiometry

Submillimeter-wave radiometers provide vital information on ice clouds and precipitation. These data are key for improving weather forecasting, particularly for disruptive winter storms, and for better understanding climate. Our airborne radiometer will provide data that will allow us to better use data from upcoming space missions with these types of sensors.

Ian Adams↗

NASA NTRS1980

A search for correlation between geomagnetic activity and stratospheric ozone

The total ozone column content (TOZ) measured from the Nimbus 4 BUV experiment is analyzed in geomagnetic coordinates to study a possible link between the solar corpuscular radiation and the lower stratosphere. Using planetary magnetic index Ap as a measure of the solar corpuscular radiation, it is shown that the correlation between TOZ and Ap, if any, occurs predominantly at high latitudes during winter seasons. This is typical of most of the claimed correlations between sun and weather and may be the result of the winter increase of planetary wave activity which by coincidence have periods comparable to magnetic activity. The fact that even major magnetic storms have no detectable effect on the stratospheric ozone during summer does not support a direct cause and effect relation between solar and stratospheric perturbations.

Chandra, S.↗

DOE OSTI2025

A Near-Real-Time Model for Predicting Electricity Disruptions in Texas During Winter Storms

There has been an increase in extreme weather events, posing a threat to power grid systems, potentially influenced by factors such as population growth, changes in ecosystems, land cover, and land use in the service area, as well as the growth of certain vegetation types. This research seeks to develop a predictive model to mitigate potential damages caused by future winter storms. This research utilizes the Light Gradient Boosting Machine (LightGBM), incorporating the number of power outages experienced at the county level, geographic details, weather information, and lagged outage and lagged weather data. The developed models were broadly divided into two groups, with six models in each group - one group without optimization and another with optimization, totaling 12 trained models. For model optimization, Bayesian optimization was employed using Root Mean Squared Error (RMSE) as the objective function. In results, when comparing Group 2 (the optimized group) with Group 1 (the non-optimized group), it was found that optimization did not always lead to a reduction in RMSE and Mean Absolute Error (MAE). However, in terms of Mean Directional Accuracy (MDA), while all results in Group 1 were below the baseline accuracy of 0.33, all results in Group 2 exceeded 0.33, with some cases showing an increase of more than three times the baseline. The results indicated that, in the optimized model group, Population and Pressure were the most influential factors when using current weather data and geographical information. When using lagged data, lagged recorded outages and lagged Pressure emerged as the most significant factors. Among the 12 developed models, the L-1-2-O model showed the lowest RMSE and MAE, as well as the highest accuracy, with values of 390.62 households and 168.13 households, respectively. To normalize the RMSE and MAE values, each metric was divided by the average number of households among the counties in Texas. For the L-1-2-O model, the scaled RMSE was 0.88% and the scaled MAE was 0.38%. In terms of MDA, which indicates the accuracy of the prediction direction, the L-1-O model achieved the highest score of 0.41. Although this study focused on Texas, which suffered the greatest impact from the winter storms in 2021, with additional validation, the methodology used in this research could be applied to other regions.

Lee, Jangjae [Texas A & M Univ., College Station, ↗

NASA NTRS2000

The Child's Tantrum: El Nino. The Origin of the El Nino-Southern Oscillation

In 1997, a child's tantrums caught the world's attention. These tantrums took the form not of crying and foot stamping, but of droughts and floods. Obviously, this was no ordinary child. It was, in fact, The Child, or El Nino, as it was, named in the late 1800s by South American observers, who noted that its timing coincided with the Christmas holiday. El Nino is a reversal in sea surface temperature (SST) distributions that occurs once every few years in the tropical Pacific. When it coincides with a cyclical shift in air pressure, known as the Southern Oscillation, normal weather patterns are drastically altered. The combined phenomenon is known as El Nino-Southern Oscillation (ENSO). Although ENSO is a regular phenomenon, it was unusually strong in 1997. It produced heavy rainfall and floods in California and bestowed spring-like temperatures on the Midwest during the winter. These drastic changes in normal weather patterns captured the public imagination, from news reports to jokes on late-night talk shows. Naturally, people wanted to. know as much, about El Nino as possible. Fortunately, scientists had at their disposal new satellites and ocean sensors that provided an unprecedented level of information. Consequently, not only was the 1997 ENSO the strongest in recent memory, but it was also the most thoroughly studied. Prominent groups such as the NASA Seasonalto-Interannual Prediction Project (NSIPP) combined numerous aspects of climate modeling into a single, predictive endeavor.

Picault, Joel↗

NASA NTRS1994

Meteorological observations of synoptic disturbances: Sensitivity to latitude

The Mars pathfinder MET experiment will make pressure, temperature, and wind measurements on the surface of Mars. The Viking Lander Meteorology Experiment measurements were marked by the presence of variations associated with synoptic weather disturbances throughout the fall and winter season. Numerical simulations of the Mars atmospheric circulation show that the winter midlatitudes are the center of activity for traveling disturbances of planetary scale, disturbances that have their fundamental origin in the baroclinic instability of the wintertime Mars atmospheric circulation. The studies are consistent with Viking observations in that the disturbances decay in amplitude toward lower latitudes. The further north the Mars Pathfinder is located, the more clearly it will be able to detect the signatures of the midlatitude weather system. A landing site close to 15 deg N should allow measurement of the weather disturbances, along with observations of the thermal tides, slope winds, and the relatively steady winds associated with the general circulation - the 'trade winds' of Mars. A landing site near 15 deg N would be significantly further equatorward than the Viking Lander 1 site, and thus would provide more of a view of tropical circulation processes.

Barnes, Jeff R.↗

DOE OSTI2021

A Meta-Level Framework for Evaluating Resilience in Net-Zero Carbon Power Systems with Extreme Weather Events in the United States

Important changes are underway in the U.S. power industry in the way that electricity is sourced, transported, and utilized. Disruption from extreme weather events and cybersecurity events is bringing new scrutiny to power-system resilience. Recognizing the complex social and technical aspects that are involved, this article provides a meta-level framework for coherently evaluating and making decisions about power-system resilience. It does so by examining net-zero carbon strategies with quantitative, qualitative, and integrative dimensions across discrete location-specific systems and timescales. The generalizable framework is designed with a flexibility and logic that allows for refinement to accompany stakeholder review processes and highly localized decision-making. To highlight the framework’s applicability across multiple timescales, processes, and types of knowledge, power system outages are reviewed for extreme weather events, including 2021 and 2011 winter storms that impacted Texas, the 2017 Hurricane Maria that affected Puerto Rico, and a heatwave/wildfire event in California in August 2020. By design, the meta-level framework enables utility decision-makers, regulators, insurers, and communities to analyze and track levels of resilience safeguards for a given system. Future directions to advance an integrated science of resilience in net-zero power systems and the use of this framework are also discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Factors influencing mode choice of adults with travel-limiting disability

Introduction: Despite the plethora of research devoted to analyzing the impact of disability on travel behavior, not enough studies have investigated the varying impact of social and environmental factors on the mode choice of people with disabilities that restrict their ability to use transportation modes efficiently. This research gap can be addressed by investigating the factors influencing the mode choice behavior of people with travel-limiting disabilities, which can inform the development of accessible and sustainable transportation systems. Additionally, such studies can provide insights into the social and economic barriers faced by this population group, which can help policymakers to promote social inclusion and equity. Method: This study utilized a Random Parameters Logit model to identify the individual, trip, and environmental factors that influence mode selection among people with travel-limiting disabilities. Here, using the 2017 National Household Travel Survey data for New York State, which included information on respondents with travel-limiting disabilities, the analysis focused on a sample of 8,016 people. In addition, climate data from the National Oceanic and Atmospheric Administration were integrated as additional explanatory variables in the modeling process. Results: The results revealed that people with disabilities may be inclined to travel longer distances walking in the absence of suitable accommodation facilities for other transportation modes. Furthermore, people were less inclined to walk during summer and winter, indicating a need to consider weather conditions as a significant determinant of mode choice. Moreover, low-income people with disabilities were more likely to rely on public transport or walking. Conclusion: Based on this study’s findings, transportation agencies could design infrastructure and plan for future expansions that is more inclusive and accessible, thus catering to the mobility needs of people with travel-limiting disabilities.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1975

Coast Guard/NOAA/NASA Great Lakes Project Icewarn

The operational feasibility of using remote sensing to provide all weather ice formation for Great Lakes winter navigation is explored. A combination airborne pulsed radar system to measure actual ice thickness, a satellite data link system, and a hand drawn interpretive ice chart proved valuable for extending winter navigation through the icepack.

Brennan, T. D.↗

NASA NTRS2021

Retrieval of Snow Water Equivalent by the Precipitation Imaging Package (PIP) over Northern Great Lakes

Performance of the Precipitation Imaging Package (PIP) for estimating the snow water equivalent (SWE) is evaluated through a comparative study with the collocated National Oceanic and Atmospheric Administration National Weather Service snow stake field measurements. The PIP together with a vertically pointing radar, a weighing bucket gauge, and a laser-optical disdrometer was deployed at the NWS Marquette, Michigan office building for a long-term field study supported by the National Aeronautics and Space Administration’s Global Precipitation Measurement mission Ground Validation program. The site was also equipped with a weather station. During the 2017-18 winter, PIP functioned nearly uninterrupted at frigid temperatures accumulating 2345.8 mm of geometric snow depth over a total of 499 hours. This long record consists of 30 events, and the PIP-retrieved and snow stake field measured SWE differed less than 15% in every event. For the windy events, the wind corrected stake field record agreed better with the PIP-retrieved SWE. Two of the major events with the longest duration and the highest accumulation are examined in detail. The particle mass with a given diameter was much lower during a shallow, colder, uniform lake-effect event than in the deep, less cold, and variable synoptic event. This study demonstrated that PIP is a robust instrument for operational use, and is reliable for deriving the bulk properties of falling snow.

Ali Tokay↗