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Results for “severe thunderstorms”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Ionospheric and satellite observations for studying the dynamic behavior of typhoons and the detection of severe storms and tsunamis

Atmospheric acoustic-gravity waves associated with severe thunderstorms, tornadoes, typhoons (hurricanes) and tsunamis can be studied through the coupling between the ionosphere and the troposphere. Reverse ray tracing computations of acoustic-gravity waves observed by an ionospheric Doppler sounder array show that wave sources are in the nearby storm systems and that the waves are excited prior to the storms. Results show that ionospheric observations, together with satellite observations, can contribute to the understanding of the dynamical behavior of typhoons, severe storms and tsunamis.

Hung, R. J.↗
NASA NTRS2014

Identifying Hail Signatures in Satellite Imagery from the 9-10 August 2011 Severe Weather Event

Severe thunderstorms can produce large hail that causes property damage, livestock fatalities, and crop failure. However, detailed storm surveys of hail damage conducted by the National Weather Service (NWS) are not required. Current gaps also exist between Storm Prediction Center (SPC) hail damage estimates and crop‐insurance payouts. NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra and Aqua satellites can be used to support NWS damage assessments, particularly to crops during the growing season. The two‐day severe weather event across western Nebraska and central Kansas during 9‐10 August 2011 offers a case study for investigating hail damage signatures by examining changes in Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery. By analyzing hail damage swaths in satellite imagery, potential economic losses due to crop damage can be quantified and further improve the estimation of weather impacts on agriculture without significantly increasing manpower requirements.

Dryden, Rachel L.↗
NASA NTRS1976

Conceptual design of an airborne laser Doppler velocimeter system for studying wind fields associated with severe local storms

An airborne laser Doppler velocimeter was evaluated for diagnostics of the wind field associated with an isolated severe thunderstorm. Two scanning configurations were identified, one a long-range (out to 10-20 km) roughly horizontal plane mode intended to allow probing of the velocity field around the storm at the higher altitudes (4-10 km). The other is a shorter range (out to 1-3 km) mode in which a vertical or horizontal plane is scanned for velocity (and possibly turbulence), and is intended for diagnostics of the lower altitude region below the storm and in the out-flow region. It was concluded that aircraft flight velocities are high enough and severe storm lifetimes are long enough that a single airborne Doppler system, operating at a range of less than about 20 km, can view the storm area from two or more different aspects before the storm characteristics change appreciably.

Thomson, J. A. L.↗
DOE OSTI2023

Urban land patterns can moderate population exposures to climate extremes over the 21st century

Abstract Climate change and global urbanization have often been anticipated to increase future population exposure (frequency and intensity) to extreme weather over the coming decades. Here we examine how changes in urban land extent, population, and climate will respectively and collectively affect spatial patterns of future population exposures to climate extremes (including hot days, cold days, heavy rainfalls, and severe thunderstorm environments) across the continental U.S. at the end of the 21st century. Different from common impressions, we find that urban land patterns can sometimes reduce rather than increase population exposures to climate extremes, even heat extremes, and that spatial patterns instead of total quantities of urban land are more influential to population exposures. Our findings lead to preliminary suggestions for embedding long-term climate resilience in urban and regional land-use system designs, and strongly motivate searches for optimal spatial urban land patterns that can robustly moderate population exposures to climate extremes throughout the 21st century.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Capturing Infrastructure Interdependencies for Power Outages Prediction During Extreme Events

As extreme weather events such as hurricanes, severe thunderstorms, and floods grow in frequency and intensity, the disruption of power grid systems poses significant challenges, including widespread electrical outages, economic losses, and threats to public safety. This paper presents a forward-looking approach that leverages geographical graph-based machine learning models to predict county-level maximum power outages during such events. By capturing the intricate interdependencies within power system networks, our approach aims to provide precise and actionable predictions that can optimize emergency response efforts and enhance grid resilience. Through the integration of real-world data, including hurricane advisories and power outage records, we have trained and benchmarked multiple machine learning models, demonstrating the feasibility and potential of this method. While our initial results are promising, this paper also charts a course for advancing these models, addressing the remaining challenges, and ultimately transforming how we anticipate and respond to the impacts of extreme weather on power systems.

Lee, Sangkeun (Matt) [ORNL] (ORCID:000000021317511↗
DOE OSTI2023

Predicting Power Outage During Extreme Weather with EAGLE-I and NWS Datasets

Extreme weather events, such as hurricanes, severe thunderstorms, and floods can significantly disrupt power grid systems, leading to electrical outages that result in inconvenience, economic losses, and life-threatening situations. There is a growing need for a robust and precise predictive model to forecast power outages, which will help prioritize emergency response before, during, and after extreme weather events. In this paper, we introduce machine-learning models that predict power outage risk at the state level during and after extreme weather events. We jointly utilized two publicly available datasets: the U.S. historical power outage data collected by the Environment for Analysis of Geo-Located Energy Information (EAGLE-I™) system, and the National Weather Service historical weather alert data sets. We highlight our initial result and discuss future work aimed at enhancing the model's robustness and accuracy for real-world applications.

Lee, Sangkeun (Matt)↗
DOE OSTI2024

A Comprehensive Model for Analyzing the Effects of Power Outages on Customers

Power outages can cause significant inconveniences to critical services and substantial economic losses. Therefore, it is crucial to systematically analyze the impact on customers during power outages caused by various factors, such as severe thunderstorms, floods, vegetation, or mechanical problems, and to plan for reliable operation and control under such events. Power outages in different locations may exhibit varying characteristics regarding customer impact. In this paper, we present a mathematical model that captures the essential characteristics of customer impact during power outages. The parameters of our model include impact duration, recovery duration, maximum impact level, increase curve parameter, and decrease curve parameter. We demonstrate how historical power outage data can be fitted to our model, enabling a systematic comparison of outages caused by different factors in various locations.

Lee, Sangkeun (Matt) [ORNL] (ORCID:000000021317511↗
DOE OSTI2020

Multiple Environmental Influences on the Lightning of Cold-Based Continental Cumulonimbus Clouds. Part I: Description and Validation of Model

In this two-part paper, influences from environmental factors on lightning in a convective storm are assessed with a model. In Part I, an electrical component is described and applied in the Aerosol–Cloud model (AC). AC treats many types of secondary (e.g., breakup in ice–ice collisions, raindrop-freezing fragmentation, rime splintering) and primary (heterogeneous, homogeneous freezing) ice initiation. AC represents lightning flashes with a statistical treatment of branching from a fractal law constrained by video imagery. The storm simulated is from the Severe Thunderstorm Electrification and Precipitation Study (STEPS; 19/20 June 2000). The simulation was validated microphysically [e.g., ice/droplet concentrations and mean sizes, liquid water content (LWC), reflectivity, surface precipitation] and dynamically (e.g., ascent) in our 2017 paper. Predicted ice concentrations (~10 L -1 ) agreed—to within a factor of about 2—with aircraft data at flight levels (-10° to -15°C). Here, electrical statistics of the same simulation are compared with observations. Flash rates (to within a factor of 2), triggering altitudes and polarity of flashes, and electric fields, all agree with the coincident STEPS observations. The “normal” tripole of charge structure observed during an electrical balloon sounding is reproduced by AC. It is related to reversal of polarity of noninductive charging in ice–ice collisions seen in laboratory experiments when temperature or LWC are varied. Positively charged graupel and negatively charged snow at most midlevels, charged away from the fastest updrafts, is predicted to cause the normal tripole. Total charge separated in the simulated storm is dominated by collisions involving secondary ice from fragmentation in graupel–snow collisions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Ice-nucleating particles in precipitation samples from the Texas Panhandle

Ice-nucleating particles (INPs) influence the formation of ice crystals in clouds and many types of precipitation. This study reports unique properties of INPs collected from 42 precipitation samples in the Texas Panhandle region from June 2018 to July 2019. We used a cold stage instrument called the West Texas Cryogenic Refrigerator Applied to Freezing Test system to estimate INP concentrations per unit volume of air (nINP) through immersion freezing in our precipitation samples with our detection capability of >0.006 INP L -1 . A disdrometer was used for two purposes: (1) to characterize the ground-level precipitation type and (2) to measure the precipitation intensity as well as size of precipitating particles at the ground level during each precipitation event. While no clear seasonal variations of n INP values were apparent, the analysis of yearlong ground-level precipitation observation as well as INPs in the precipitation samples showed some INP variations, e.g., the highest and lowest n INP values at -25°C both in the summer for hail-involved severe thunderstorm samples (3.0 to 1130 INP L -1 ), followed by the second lowest at the same temperature from one of our snow samples collected during the winter (3.2 INP L -1 ). Furthermore, we conducted bacteria community analyses using a subset of our precipitation samples to examine the presence of known biological INPs. In parallel, we also performed metagenomics characterization of the bacterial microbiome in suspended ambient dust samples collected at commercial open-lot livestock facilities (cattle feedyards hereafter) in the Texas Panhandle (i.e., the northernmost counties of Texas, also known as “West Texas”) to ascertain whether local cattle feedyards can act as a source of bioaerosol particles and/or INPs found in the precipitation samples. Some key bacterial phyla present in cattle feedyard samples appeared in precipitation samples. However, no known ice nucleation active species were detected in our samples. Overall, our results showed that cumulative n INP in our precipitation samples below -20°C could be high in the samples collected while observing > 10 mm h -1 precipitation with notably large hydrometeor sizes and an implication of cattle feedyard bacteria inclusion.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1969

Comments on Doppler radar applications

The application of Doppler methods to theoretical or meteorological problems is discussed. Research for using radar to study and monitor severe thunderstorms, turbulence, and tornadoes is recommended.

Kessler, E.↗
NASA NTRS1975

Solar modulation of atmospheric electrification through variation of the conductivity over thunderstorms

It is suggested that variations of the current in the global atmospheric electrical circuit can be produced through regulation of the resistance between the tops of thunderclouds and the ionosphere. Long- and short-term changes in the conductivity of this region occur due to changes in the ionization rate resulting from solar activity. Previous suggestions that the phenomena might be due to conductivity variations in the fair weather part of the world or an influx of space charge to the upper atmosphere are discussed and considered unlikely. It might be possible to test the proposed mechanism by measuring the temporal variation of the ionospheric potential during distributed solar periods. Another approach would be to measure simultaneously the variation in ionization rate and electric current over thunderstorms. Several ways in which changes in atmospheric electrification might influence other meteorological phenomena are mentioned.

Markson, R.↗
NASA NTRS1975

Sasaki's variational optimization analysis of temperature and moisture advection in a severe storm environment

Temperature and moisture advection patterns of dry air intrusion were analyzed by a variational optimization method to relate mesoscale advection to a severe thunderstorm environment. The analysis results presented here were obtained from a case study, May 26, 1973, when a tornado squall line developed in Oklahoma in conjunction with a clearly delineated dry air intrusion. Observations from the synoptic upper air network were used for inputs of horizontal wind components, potential temperature, and mixing ratio at each 50 mb increment from 950 to 100 mb. An objective analysis was performed to assign values of the variables to grid points of a 15 x 14 horizontal grid with approximate 125 km grid spacing at each pressure level. After the analysis the data fields were smoothed using a variational formalism.

Mcfarland, M. J.↗
NASA NTRS1977

National Severe Storms Forecast Center

The principal mission of the National Severe Storms Forecast Center (NSSFC) is to maintain a continuous watch of weather developments that are capable of producing severe local storms, including tornadoes, and to prepare and issue messages designated as either Weather Outlooks or Tornado or Severe Thunderstorm Watches for dissemination to the public and aviation services. In addition to its assigned responsibility at the national level, the NSSFC is involved in a number of programs at the regional and local levels. Subsequent subsections and paragraphs describe the NSSFC, its users, inputs, outputs, interfaces, capabilities, workload, problem areas, and future plans in more detail.

Source record↗
NASA NTRS1977

Analysis of satellite derived winds for April 24, 1975

Cumulus cloud tracking based on short-interval GOES satellite imagery provided a representation of the low-level wind fields existing prior to the outbreak of severe thunderstorms. Through use of the satellite-derived winds and surface mixing ratios, moisture convergence fields were estimated. The effect of the spatial distribution of trackable clouds on the computed dynamic fields was also investigated.

Maddox, R. A.↗
NASA NTRS1981

Artificial stereo presentation of meteorological data fields

The innate capability to perceive three-dimensional stereo imagery has been exploited to present multidimensional meteorological data fields. Variations on an artificial stereo technique first discussed by Pichel et al. (1973) are used to display single and multispectral images in a vivid and easily assimilated manner. Examples of visible/infrared artificial stereo are given for Hurricane Allen and for severe thunderstorms on 10 April 1979. Three-dimensional output from a mesoscale model also is presented. The images may be viewed through the glasses inserted in the February 1981 issue of the Bulletin of the American Meteorological Society, with the red lens over the right eye. The images have been produced on the interactive Atmospheric and Oceanographic Information Processing System (AOIPS) at Goddard Space Flight Center. Stereo presentation is an important aid in understanding meteorological phenomena for operational weather forecasting, research case studies, and model simulations.

Hasler, A. F.↗
NASA NTRS1982

Ageostrophic winds in the severe strom environment

The period from 1200 GMT 10 April to 0000 GMT 11 April 1979, during which time several major tornadoes and severe thunderstorms, including the Wichita Falls tornado occurred was studied. A time adjusted, isentropic data set was used to analyze key parameters. Fourth order centered finite differences were used to compute the isallobaric, inertial advective, tendency, inertial advective geostrophic and ageostrophic winds. Explicit isentropic trajectories were computed through the isentropic, inviscid equations of motion using a 15 minute time step. Ageostrophic, geostrophic and total vertical motion fields were computed to judge the relative importance of ageostrophy in enhancing the vertical motion field. It is found that ageostrophy is symptomatic of those mass adjustments which take place during upper level jet streak propagation and can, in a favorable environment, act to increase and release potential instability over meso alpha time periods.

Moore, J. T.↗
NASA NTRS1981

Summary of requirements and recommendations

Global climate, agricultural uses for precipitation information, hydrological uses for precipitation information, severe thunderstorms and local weather, and global weather are discussed.

Mcconnell, D. G.↗