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28 results for “tornado”
United States tornado reports in landfalling tropical cyclones used in Paredes et al. (2021)
<p>These data include all tropical cyclone tornado reports used in Paredes et al. (2021) plus an additional year (e.g., 2020). These data will not be updated regularly. For the latest version, users should refer to https://www.spc.noaa.gov/misc/edwards/TCTOR/ or contact roger.edwards@noaa.gov.<br> <br> Each specific tropical cyclone tornado record has been extracted from the broader Storm Prediction Center tornado database, for all Atlantic and Gulf of Mexico tropical cyclones to affect the continental United States from 1995–2020. The tornado records were analyzed individually to determine their presence within the circulation envelope of either a classified or remnant tropical cyclone, without regard to fixed radii from tropical cyclone center, inland extent, temporal cutoffs before or after landfall, or other such arbitrary thresholds that may either exclude tropical cyclone events or include non-tropical cyclone tornadoes unnecessarily. Unlike other climatologies previously published in the literature, the chosen time period for this examination essentially covers only the full national deployment of the WSR-88D radar network in the United States. This permits consistent comparisons of a very large sample size of tropical cyclone tornado events (>1600) during the era of modernized National Weather Service warning and verification practices.</p>
Understanding Near-Ground Tornado Flows - Pressure, Shear and Turbulence, and their Importance in Structural Loading
<h1>Dataset Description</h1> <p>The research focuses on the velocity and pressure field of the near-ground region within one of the Wind Engineering, Energy, and Environment (WindEEE) Dome's tornadic-like flow simulations. This research also aims to provide valuable insight in the behaviour between tornado-building interactions. Measurement regions of interest range from the apparent centre of the tornado-like flow structure extending beyond twice the radius of maximum tangential velocity.</p> <p>Two vortex cases were simulated and measured:</p> <p>(1) TV0 - a stationary vortex where the bell mouth (updraft centre) aligns with the centre of the test chamber, and</p> <p>(2) TV1 - a vortex translating for a distance of 4.5 m at a nominal translation speed of about 1-1.2 m/s.</p> <div> <h2>S0. Documentation</h2> <p>Contains information documents regarding the instrumentation specifications, test plan, and other important diagrams.</p> <div> <h2>S1. Near-Ground Flow Model</h2> </div> <div> <p>TV0 and TV1 simulations were tested at the WindEEE Dome testing facility. Velocity measurement devices were used to characterize simulated vortex's horizontal flow field at heights of 3.2, and 7.2. Pressure measurement devices were used to characterize the vortex's ground surface pressure. These measurements aim to provide data for more accurate tornado wind field models.</p> <h3>E1. Near-Ground Velocity Field</h3> <p>During this test, 3-D point measurements were taken to aid in characterizing TV0 and TV1 simulations. Measurements were taken at locations R = 0, 60 and 105 cm measured perpendicularly from the bell mouth's path of translation. Two heights and four point positions were captured at each location. These measurements aim to provide detailed characteristics of the wind field.</p> <h3>E2. Ground Surface Instantaneous Pressure Field</h3> <p>A ground surface pressure model covering an area of 120 cm by 300 cm was used to characterize the ground pressure distribution of simulations: TV0 and TV1. Instantaneous pressure measurement devices captured the flow distribution throughout a 2-D grid of pressure taps mounted flush with the ground surface panels.</p> <div> <h2>S2. Low-Rise Building Model</h2> </div> <div> <p>A 3:12 roof slope, 1:100 scale, low-rise building model was instrumented with external surface pressure taps and tested under TV0 and TV1 flow simulations at WindEEE. The low-rise building model was measured in locations R = 0, 60, and 105 cm measured perpendicularly from the bell mouth translation pat, and at azimuth angles 0, 45, and 90 degrees relative to the path of the bell mouth.</p> <h3>E1. Low-Rise Building Aerodynamics</h3> <p>The effects of stationary and translating vortices on a low-rise building model were investigated.</p> <h2>S3. Small-Portable Temporary Building Model</h2> <div> <p>A temporary low-rise building was instrumented with external surface pressure taps and tested under TV0 and TV1 flow simulations at WindEEE. The small-portable building model of size 1.2 cm by 1.2 cm by 3.2 cm (1:70 scale) and ground surface model covering 120 cm by 300 cm. The small-portable building was measured in locations R = 0, 60, and 105 cm measured perpendicularly from the bell mouth translation path.</p> <h3>E1. Small-Portable Temporary Building Aerodynamics</h3> <p>The effects of stationary and translating vortices on a small-portable building model were investigated.</p> <div> <h2>S4. Near-Ground Particle Image Velocimetry (PIV)</h2> </div> <div> <p>A Continuum laser was focused and split through a cylindrical lens into a thin laser sheet, fog machines were used to seed the entire test chamber with long lasting fog fluid, and finally synchronized high-resolution cameras (flares) were used to capture laser light refraction. Flares send image data to the DVR Express Cores during test measurements. This PIV system was used to measure the horizontal velocity field of simulations: TV0 with an approximate total coverage of 80 cm by 240 cm.</p> <h3>E1. Near-Ground Horizontal Velocity Field</h3> <p>The PIV system was used to measure the 2-D velocity field at a height of 7.2 cm from the chamber floor. The plane of measure covers regions from the tornado-like flow's apparent centre to beyond the region of maximum tangential velocity.</p> <h3>E2. Low-Rise Building Wake Aerodynamics</h3> <p>A low-rise building model was measured at the centre of the test chamber, subject to the tornado vortex TV0. The model was made black to absorb energy and light from the PIV laser. The PIV system was used to measure the 2-D velocity field at a height of 7.2 cm from the chamber floor.</p> <p> </p> <p><strong>Note: </strong>Due to storage limitations we cannot include the entire PIV raw dataset, however data can be made available apon request. Please email the project contact person or the hosting instution (<a href="https://windeee.ca/contact/">Contact – WindEEE Research Facility</a>) for information or access to the complete dataset. </p> </div> </div> </div> </div> </div>
Tornado Reports in Southeast South America
<p>This dataset corresponds to <strong>reports of tornadoes</strong> that happened in <strong>Southeast South America (SESA)</strong> between 1991 and 2020. It was constructed and used for studying tornadic environments in SESA, work that was recently published in the American Meteorological Society (AMS) journal <em>Monthly Weather Review</em> under the title: <strong>"Tornadoes in Southeast South America: Mesoscale to Planetary-scale Environments". </strong>A PDF containing this article was included with the last update of this publication (January 2024). Additionally, a datasheet explaining everything you need to know about the database of tornadoes in Southeast South America was included in this new version (January 2024).</p>
Tornado Detection From Full-Resolution Polarimetric Weather Radar Data (SAMPLE)
<p>This dataset contains a small sample of the tornado dataset described in the talk "A Tornado Detection Algorithm using Deep Neural Networks, Full-Resolution Polarimetric Weather Radar Data, and Explainable AI" presented at the 40th Conference on Radar Meteorology on Aug 31st 2023.</p> <p>The files contained in this data represent approximately 1% of the full dataset that will be released upon final publication.</p> <p>For questions please contact</p> <p>James.Kurdzo@ll.mit.edu and mark.veillette@ll.mit.edu</p>
Understory vegetation response to post-tornado salvage logging
Open the record for dataset details and reuse information.
CFD Modeling Results and Related Data and Codes for Plotting of "A Mesoscale-to-LES Modeling of Tornado-like Vortex and Associated Local Strong Winds in Urban Area"
<p>The CFD modeling outputs, derived maximum wind fields in the analysis area, the topography data, the Python codes used to produce the figures, as we as the namelist of WRF simulation are available. The CFD modeling outputs are in binary format. The ctl. files of corresponding binary data (or dataset if ordered chronologically) are available in each directory (named after each experiment in our study).</p>
Data used in the study titled "Significant Tornado Environments In Canada Using ERA5-Derived Convective Parameters"
<p>These data include: (1) Observation-derived convective parameters at four Canadian sounding stations based on 1990-2020 data, and ERA5-derived convective parameters at grid points nearest to the same four Canadian sounding stations on 1990-2020 data - file called "ERA5 and Observation convective parameters.zip". (2) ERA5 vertical profile data, derived convective parameters, and skew-t images for the 166 Canadian F/EF2+ tornado events - file called "ERA5 profiles-parameters-skewt 166 cases.zip"</p>
Data for Numerical Simulation of Tornado-like Vortices Induced by Small-Scale Cyclostrophic Wind Perturbations
Open the record for dataset details and reuse information.
Las Olas de Calor ya tienen nombre como huracanes y tornados
<p>Entrevista en el programa Vida Verde de Radio Exterior de España sobre las olas de calor.</p> <p>Emitida el 2 de septiembre del 2023.</p> <p> </p> <p><a href="https://www.rtve.es/play/audios/vida-verde/olas-calor-ya-tienen-nombre-como-huracanes-tornados/6958790/" target="_blank" rel="noopener">https://www.rtve.es/play/audios/vida-verde/olas-calor-ya-tienen-nombre-como-huracanes-tornados/6958790/</a></p>
tornado_forecast_kit_v1
<p>Testing GFDL SPEAR for seasonal tornado forecast</p>
Soil moisture observations from shortwave infrared channels reveal tornado tracks: A case in December 10-11, 2021 tornado outbreak
<p>MODIS dataset used for the publication titled 'Soil moisture observations from shortwave infrared channels reveal tornado tracks: A case in December 10-11, 2021 tornado outbreak' on Geophysical Research Letters.</p>
TORNADO-Omics Techniques and Neural Networks for the Development of Predictive Risk Models
ClinicalTrials.gov study NCT06372054. IPD Sharing: NO. Countries: 1. Publications: 2.
Supporting information, WRF output, and processed WRF files used for the generation of the manuscript "Observational and modelling analysis of Canada's only F5/EF5 tornado"
<p>WRF simulation output and processed files used to generate the figures and calculations in the manuscript "Observational and modelling analysis of Canada's only F5/EF5 tornado". Two zipped folders are attached, one is from the original control simulation with the microphysics scheme on (MP), and the other is from the experimental simulation with the microphysics scheme turned off (NOMP).</p><p>Each simulation zipped folder includes sub-directories containing the processed observed and simulated surface station data, surface wet-bulb potential temperature, cross sections (the MP simulation only), and convective parameter fields at 2100 UTC 22 June 2007.</p><p>A supplemental material in the form of a movie showing the radar observation between 2000 UTC 22 June 2007 and 0000 UTC 23 June 2007 is also attached. See the manuscript's Figure 5 caption for more information on the data shown in the animation.</p>
Storm Interactions in Cases of EF2+ Tornadoes and EF3+ Hail (2008-2022)
<p>This is a quality-controlled dataset of 3"+ hail reports and EF3+ tornadoes (their genesis locations) within 90 km of a WSR-88D between 2008-2021. EF2+ tornadoes are also included west of -98 degrees longitude. Tornadoes are also included from 2022-2023. An analysis of nearby features accompanying the parent storms (performed by Nixon) is included. The orientation of storms are included. The positions of neighboring cells at 4 different times preceding hazard production (T-30, T-20, T-10, and T-0) are also included in the format "direction_distance" from the mesocyclone of the storm in question. </p>
Data related to tornadoes
<p>Haikou dual polarization radar data and 3-D lightning location data on August 29, 2019</p>
Data from: IM-TORNADO: a tool for comparison of 16S reads from paired-end libraries
Motivation: 16S rDNA hypervariable tag sequencing has become the de facto method for accessing microbial diversity. Illumina paired-end sequencing, which produces two separate reads for each DNA fragment, has become the platform of choice for this application. However, when the two reads do not overlap, existing computational pipelines analyze data from read separately and underutilize the information contained in the paired-end reads. Results: We created a workflow known as Illinois Mayo Taxon Organization from RNA Dataset Operations (IM-TORNADO) for processing non-overlapping reads while retaining maximal information content. Using synthetic mock datasets, we show that the use of both reads produced answers with greater correlation to those from full length 16S rDNA when looking at taxonomy, phylogeny, and beta-diversity. Availability and Implementation: IM-TORNADO is freely available at http://sourceforge.net/projects/imtornado and produces BIOM format output for cross compatibility with other pipelines such as QIIME, mothur, and phyloseq.
Figure 4 from: Sklodowski J, Garbalinska P (2011) Ground beetle (Coleoptera, Carabidae) assemblages inhabiting Scots pine stands of Puszcza Piska Forest: six-year responses to a tornado impact. ZooKeys 100: 371-392. https://doi.org/10.3897/zookeys.100.1360
Figure 4 - Regression distances between carabid assemblages inhabiting post-tornado (disturbed) and control stands during 2003-2008.
Figure 2 from: Sklodowski J, Garbalinska P (2011) Ground beetle (Coleoptera, Carabidae) assemblages inhabiting Scots pine stands of Puszcza Piska Forest: six-year responses to a tornado impact. ZooKeys 100: 371-392. https://doi.org/10.3897/zookeys.100.1360
Figure 2 - Dendrograms of species similarity of carabid beetle assemblages inhabiting tornado-impacted (D) and control stands (C) in age classes I–V (see text) in the first (2003) and last (2008) years of observation. The analysis was performed with the Ward method and Euclidean distance as the measure of similarity.
Figure 1 from: Sklodowski J, Garbalinska P (2011) Ground beetle (Coleoptera, Carabidae) assemblages inhabiting Scots pine stands of Puszcza Piska Forest: six-year responses to a tornado impact. ZooKeys 100: 371-392. https://doi.org/10.3897/zookeys.100.1360
Figure 1 - The proportion of individuals of European carabid species living in tornado-impacted and in control stands during 2003-2008.
Figure 3 from: Sklodowski J, Garbalinska P (2011) Ground beetle (Coleoptera, Carabidae) assemblages inhabiting Scots pine stands of Puszcza Piska Forest: six-year responses to a tornado impact. ZooKeys 100: 371-392. https://doi.org/10.3897/zookeys.100.1360
Figure 3 - The MIB/SPC model of carabid assemblages living in tornado-impacted (D) and control stands (C) during 2003-2008.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.