Lecture 29 Tornadoes IV (CH19)
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From Improving Tornado Warnings: from Observation to Forecast
Improving Tornado Warnings: from Observation to Forecast John T. Snow Regents’ Professor of Meteorology Dean Emeritus, College of Atmospheric and Geographic Sciences, The University of Oklahoma Major contributions from: Dr. Russel Schneider –NOAA Storm Prediction Center Dr. David Stensrud – NOAA National Severe Storms Laboratory Dr. Ming Xue –Center for Analysis and Prediction of Storms, University of Oklahoma Dr. Lou Wicker –NOAA National Severe Storms Laboratory Hazards Caucus Alliance Briefing Tornadoes: Understanding how they develop and providing early warning 10:30 am – 11:30 am, Wednesday, 21 July 2010 Senate Capitol Visitors Center 212 Each Year: ~1,500 tornadoes touch down in the United States, causing over 80 deaths, 100s of injuries, and an estimated $1.1 billion in damages Statistics from NOAA Storm Prediction Center Supercell –A long‐lived rotating thunderstorm the primary type of thunderstorm producing strong and violent tornadoes Present Warning System: Warn on Detection • A Warning is the culmination of information developed and distributed over the preceding days sequence of day‐by‐day forecasts identifies an area of high threat •On the day, storm spotters deployed; radars monitor formation, growth of thunderstorms • Appearance of distinct cloud or radar echo features tornado has formed or is about to do so Warning is generated, distributed Present Warning System: Warn on Detection Radar at 2100 CST Radar at 2130 CST with Warning Thunderstorms are monitored using radar A warning is issued based on the detected and -
Evaluating Operational and Newly Developed Mesocyclone and Tornado Detection Algorithms for Quasi-Linear Convective Systems Thomas James Turnage
Florida State University Libraries Electronic Theses, Treatises and Dissertations The Graduate School 2007 Evaluating Operational and Newly Developed Mesocyclone and Tornado Detection Algorithms for Quasi-Linear Convective Systems Thomas James Turnage Follow this and additional works at the FSU Digital Library. For more information, please contact [email protected] THE FLORIDA STATE UNIVERSITY COLLEGE OF ARTS AND SCIENCES EVALUATING OPERATIONAL AND NEWLY DEVELOPED MESOCYCLONE AND TORNADO DETECTION ALGORITHMS FOR QUASI-LINEAR CONVECTIVE SYSTEMS By THOMAS JAMES TURNAGE A thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science Degree Awarded: Summer Semester, 2007 The members of the Committee approve the thesis of Thomas J. Turnage defended on April 5th, 2007. ____________________________________ Henry E. Fuelberg Professor Directing Thesis ____________________________________ Jon E. Ahlquist Committee Member ____________________________________ Paul H. Ruscher Committee Member ____________________________________ Andrew I. Watson Committee Member The Office of Graduate Studies has verified and approved the above named committee members. ii ACKNOWLEDGEMENTS I first want to thank the Lord. Without His blessings, none of this would have been possible. Next, I want to express my deepest gratitude and appreciation to my major professor Dr. Henry Fuelberg for working with me to complete this thesis in spite of rotating shift work at the National Weather Service (NWS) in Tallahassee and a subsequent move to Michigan. His high standards of integrity and academic excellence have been an inspiration to me. I also wish to thank the members of my thesis committee, Mr. Irv Watson of the NWS in Tallahassee, and Drs. Jon Ahlquist and Paul Ruscher for their advice and support. -
Downloaded 09/30/21 06:43 PM UTC JUNE 1996 MONTEVERDI and JOHNSON 247
246 WEATHER AND FORECASTING VOLUME 11 A Supercell Thunderstorm with Hook Echo in the San Joaquin Valley, California JOHN P. MONTEVERDI Department of Geosciences, San Francisco State University, San Francisco, California STEVE JOHNSON Association of Central California Weather Observers, Fresno, California (Manuscript received 30 January 1995, in ®nal form 9 February 1996) ABSTRACT This study documents a damaging supercell thunderstorm that occurred in California's San Joaquin Valley on 5 March 1994. The storm formed in a ``cold sector'' environment similar to that documented for several other recent Sacramento Valley severe thunderstorm events. Analyses of hourly subsynoptic surface and radar data suggested that two thunderstorms with divergent paths developed from an initial echo that had formed just east of the San Francisco Bay region. The southern storm became severe as it ingested warmer, moister boundary layer air in the south-central San Joaquin Valley. A well-developed hook echo with a 63-dBZ core was observed by a privately owned 5-cm radar as the storm passed through the Fresno area. Buoyancy parameters and ho- dograph characteristics were obtained both for estimated conditions for Fresno [on the basis of a modi®ed morning Oakland (OAK) sounding] and for the actual storm environment (on the basis of a radiosonde launched from Lemoore Naval Air Station at about the time of the storm's passage through the Fresno area). Both the estimated and actual hodographs essentially were straight and suggested storm splitting. Although the actual CAPE was similar to that which was estimated, the observed magnitude of the low-level shear was considerably greater than the estimate. -
ESSENTIALS of METEOROLOGY (7Th Ed.) GLOSSARY
ESSENTIALS OF METEOROLOGY (7th ed.) GLOSSARY Chapter 1 Aerosols Tiny suspended solid particles (dust, smoke, etc.) or liquid droplets that enter the atmosphere from either natural or human (anthropogenic) sources, such as the burning of fossil fuels. Sulfur-containing fossil fuels, such as coal, produce sulfate aerosols. Air density The ratio of the mass of a substance to the volume occupied by it. Air density is usually expressed as g/cm3 or kg/m3. Also See Density. Air pressure The pressure exerted by the mass of air above a given point, usually expressed in millibars (mb), inches of (atmospheric mercury (Hg) or in hectopascals (hPa). pressure) Atmosphere The envelope of gases that surround a planet and are held to it by the planet's gravitational attraction. The earth's atmosphere is mainly nitrogen and oxygen. Carbon dioxide (CO2) A colorless, odorless gas whose concentration is about 0.039 percent (390 ppm) in a volume of air near sea level. It is a selective absorber of infrared radiation and, consequently, it is important in the earth's atmospheric greenhouse effect. Solid CO2 is called dry ice. Climate The accumulation of daily and seasonal weather events over a long period of time. Front The transition zone between two distinct air masses. Hurricane A tropical cyclone having winds in excess of 64 knots (74 mi/hr). Ionosphere An electrified region of the upper atmosphere where fairly large concentrations of ions and free electrons exist. Lapse rate The rate at which an atmospheric variable (usually temperature) decreases with height. (See Environmental lapse rate.) Mesosphere The atmospheric layer between the stratosphere and the thermosphere. -
Tornadogenesis in a Simulated Mesovortex Within a Mesoscale Convective System
3372 JOURNAL OF THE ATMOSPHERIC SCIENCES VOLUME 69 Tornadogenesis in a Simulated Mesovortex within a Mesoscale Convective System ALEXANDER D. SCHENKMAN,MING XUE, AND ALAN SHAPIRO Center for Analysis and Prediction of Storms, and School of Meteorology, University of Oklahoma, Norman, Oklahoma (Manuscript received 3 February 2012, in final form 23 April 2012) ABSTRACT The Advanced Regional Prediction System (ARPS) is used to simulate a tornadic mesovortex with the aim of understanding the associated tornadogenesis processes. The mesovortex was one of two tornadic meso- vortices spawned by a mesoscale convective system (MCS) that traversed southwestern and central Okla- homa on 8–9 May 2007. The simulation used 100-m horizontal grid spacing, and is nested within two outer grids with 400-m and 2-km grid spacing, respectively. Both outer grids assimilate radar, upper-air, and surface observations via 5-min three-dimensional variational data assimilation (3DVAR) cycles. The 100-m grid is initialized from a 40-min forecast on the 400-m grid. Results from the 100-m simulation provide a detailed picture of the development of a mesovortex that produces a submesovortex-scale tornado-like vortex (TLV). Closer examination of the genesis of the TLV suggests that a strong low-level updraft is critical in converging and amplifying vertical vorticity associated with the mesovortex. Vertical cross sections and backward trajectory analyses from this low-level updraft reveal that the updraft is the upward branch of a strong rotor that forms just northwest of the simulated TLV. The horizontal vorticity in this rotor originates in the near-surface inflow and is caused by surface friction. -
Near-Surface Vortex Structure in a Tornado and in a Sub-Tornado-Strength Convective-Storm Vortex Observed by a Mobile, W-Band Radar During VORTEX2
VOLUME 141 MONTHLY WEATHER REVIEW NOVEMBER 2013 Near-Surface Vortex Structure in a Tornado and in a Sub-Tornado-Strength Convective-Storm Vortex Observed by a Mobile, W-Band Radar during VORTEX2 ,1 # @ ROBIN L. TANAMACHI,* HOWARD B. BLUESTEIN, MING XUE,* WEN-CHAU LEE, & & @ KRZYSZTOF A. ORZEL, STEPHEN J. FRASIER, AND ROGER M. WAKIMOTO * Center for Analysis and Prediction of Storms, and School of Meteorology, University of Oklahoma, Norman, Oklahoma # School of Meteorology, University of Oklahoma, Norman, Oklahoma @ National Center for Atmospheric Research, Boulder, Colorado & Microwave Remote Sensing Laboratory, University of Massachusetts, Amherst, Amherst, Massachusetts (Manuscript received 14 November 2012, in final form 22 May 2013) ABSTRACT As part of the Second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) field campaign, a very high-resolution, mobile, W-band Doppler radar collected near-surface (#200 m AGL) observations in an EF-0 tornado near Tribune, Kansas, on 25 May 2010 and in sub-tornado-strength vortices near Prospect Valley, Colorado, on 26 May 2010. In the Tribune case, the tornado’s condensation funnel dissipated and then reformed after a 3-min gap. In the Prospect Valley case, no condensation funnel was observed, but evidence from the highest-resolution radars in the VORTEX2 fleet indicates multiple, sub-tornado-strength vortices near the surface, some with weak-echo holes accompanying Doppler velocity couplets. Using high-resolution Doppler radar data, the authors document the full life cycle of sub- tornado-strength vortex beneath a convective storm that previously produced tornadoes. The kinematic evolution of these vortices, from genesis to decay, is investigated via ground-based velocity track display (GBVTD) analysis of the W-band velocity data. -
Radar Artifacts and Associated Signatures, Along with Impacts of Terrain on Data Quality
Radar Artifacts and Associated Signatures, Along with Impacts of Terrain on Data Quality 1.) Introduction: The WSR-88D (Weather Surveillance Radar designed and built in the 80s) is the most useful tool used by National Weather Service (NWS) Meteorologists to detect precipitation, calculate its motion, estimate its type (rain, snow, hail, etc) and forecast its position. Radar stands for “Radio, Detection, and Ranging”, was developed in the 1940’s and used during World War II, has gone through numerous enhancements and technological upgrades to help forecasters investigate storms with greater detail and precision. However, as our ability to detect areas of precipitation, including rotation within thunderstorms has vastly improved over the years, so has the radar’s ability to detect other significant meteorological and non meteorological artifacts. In this article we will identify these signatures, explain why and how they occur and provide examples from KTYX and KCXX of both meteorological and non meteorological data which WSR-88D detects. KTYX radar is located on the Tug Hill Plateau near Watertown, NY while, KCXX is located in Colchester, VT with both operated by the NWS in Burlington. Radar signatures to be shown include: bright banding, tornadic hook echo, low level lake boundary, hail spikes, sunset spikes, migrating birds, Route 7 traffic, wind farms, and beam blockage caused by terrain and the associated poor data sampling that occurs. 2.) How Radar Works: The WSR-88D operates by sending out directional pulses at several different elevation angles, which are microseconds long, and when the pulse intersects water droplets or other artifacts, a return signal is sent back to the radar. -
A Revised Tornado Definition and Changes in Tornado Taxonomy
1256 WEATHER AND FORECASTING VOLUME 29 A Revised Tornado Definition and Changes in Tornado Taxonomy ERNEST M. AGEE Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, Indiana (Manuscript received 4 June 2014, in final form 30 July 2014) ABSTRACT The tornado taxonomy presented by Agee and Jones is revised to account for the new definition of a tor- nado provided by the American Meteorological Society (AMS) in October 2013, resulting in the elimination of shear-driven vortices from the taxonomy, such as gustnadoes and vortices in the eyewall of hurricanes. Other relevant research findings since the initial issuance of the taxonomy are also considered and in- corporated, where appropriate, to help improve the classification system. Multiple misoscale shear-driven vortices in a single tornado event, when resulting from an inertial instability, are also viewed to not meet the definition of a tornado. 1. Introduction and considerations from a cumuliform cloud, and often visible as a funnel cloud and/or circulating debris/dust at the ground.’’ In The first proposed tornado taxonomy was presented view of the latest definition, a few changes are warranted by Agee and Jones (2009, hereafter AJ) consisting of in the AJ taxonomy. Considering the roles played by three types and 15 species, ranging from the type I buoyancy and shear on a variety of spatial and temporal (potentially strong and violent) tornadoes produced by scales (from miso to meso to synoptic), coupled with the the classic supercell, to the more benign type III con- requirement in the latest definition that a tornado must vective and shear-driven vortices such as landspouts and be pendant from a cumuliform cloud, it is necessary to gustnadoes. -
Glossary of Severe Weather Terms
Glossary of Severe Weather Terms -A- Anvil The flat, spreading top of a cloud, often shaped like an anvil. Thunderstorm anvils may spread hundreds of miles downwind from the thunderstorm itself, and sometimes may spread upwind. Anvil Dome A large overshooting top or penetrating top. -B- Back-building Thunderstorm A thunderstorm in which new development takes place on the upwind side (usually the west or southwest side), such that the storm seems to remain stationary or propagate in a backward direction. Back-sheared Anvil [Slang], a thunderstorm anvil which spreads upwind, against the flow aloft. A back-sheared anvil often implies a very strong updraft and a high severe weather potential. Beaver ('s) Tail [Slang], a particular type of inflow band with a relatively broad, flat appearance suggestive of a beaver's tail. It is attached to a supercell's general updraft and is oriented roughly parallel to the pseudo-warm front, i.e., usually east to west or southeast to northwest. As with any inflow band, cloud elements move toward the updraft, i.e., toward the west or northwest. Its size and shape change as the strength of the inflow changes. Spotters should note the distinction between a beaver tail and a tail cloud. A "true" tail cloud typically is attached to the wall cloud and has a cloud base at about the same level as the wall cloud itself. A beaver tail, on the other hand, is not attached to the wall cloud and has a cloud base at about the same height as the updraft base (which by definition is higher than the wall cloud). -
Weather Radar Quiz Name
Weather radar quiz Name: 1. Base velocity displays (select all that apply) 8. Targets that are ____ or ___ have no radial velocity (select all that apply) Select 2 answers Select 2 answers A Speed of the wind toward or away from the radar A stationary B Intensity of the precipitation B away from the radar C Movement of precipitation over the time C towards the radar D moving perpendicular to the radar beam 2. What are the values of reflectivity for precipitation mode? A From -28 dbz to +28 dbz B From 0 to 75 dbz C Above 45 dbz 3. Positive values (warm yellow to red colors) of velocities indicates movements 9. The higher gradient in the reflectivity values between the edge of the cell and core indicates a stronger storm. A perpendicular to the radar beam C towards the radar A True B False B away from the radar D parallel to the radar beam 10. What radar features indicate tropical cyclone? (select all that apply) Select 4 answers A Low reflectivity in the eye D High reflectivity band spiraling outward 4. Which non-meteorological targets can be detected by weather radars? (select all that apply) A Birds C Buildings E Dust B Small and circled shape echoes E Rotation B Trees D Smoke F All from the above C High reflectivity in eyewall 5. What factros enhance the radar reflectivity around the melting level? (select all that apply) Select 2 answers 11. What radar signature indicates that strong, straight-line winds are possible? A The targets become warmer A Hook echo B Bow echo C Rotation couplet B The targets increase in size 12. -
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1136 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 25 Tornado Detection Using a Neuro–Fuzzy System to Integrate Shear and Spectral Signatures YADONG WANG,TIAN-YOU YU, AND MARK YEARY School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma ALAN SHAPIRO School of Meteorology, University of Oklahoma, Norman, Oklahoma SHAMIM NEMATI Department of Mathematics, University of Oklahoma, Norman, Oklahoma MICHAEL FOSTER AND DAVID L. ANDRA JR. National Weather Service, Norman, Oklahoma MICHAEL JAIN National Severe Storms Laboratory, Norman, Oklahoma (Manuscript received 25 April 2007, in final form 22 October 2007) ABSTRACT Tornado vortices observed from Doppler radars are often associated with strong azimuthal shear and Doppler spectra that are wide and flattened. The current operational tornado detection algorithm (TDA) primarily searches for shear signatures that are larger than the predefined thresholds. In this work, a tornado detection procedure based on a fuzzy logic system is developed to integrate tornadic signatures in both the velocity and spectral domains. A novel feature of the system is that it is further enhanced by a neural network to refine the membership functions through a feedback training process. The hybrid ap- proach herein, termed the neuro–fuzzy tornado detection algorithm (NFTDA), is initially verified using simulations and is subsequently tested on real data. The results demonstrate that NFTDA can detect tornadoes even when the shear signatures are degraded significantly so that they would create difficulties for typical vortex detection schemes. The performance of the NFTDA is assessed with level I time series data collected by the KOUN radar, a research Weather Surveillance Radar-1988 Doppler (WSR-88D) operated by the National Severe Storms Laboratory (NSSL), during two tornado outbreaks in central Oklahoma on 8 and 10 May 2003. -
Development of Operational Doppler Weather Radars
244 WEATHER AND FORECASTING VOLUME 13 History of Operational Use of Weather Radar by U.S. Weather Services. Part II: Development of Operational Doppler Weather Radars ROGER C. WHITON* AND PAUL L. SMITH1 Air Weather Service, Scott Air Force Base, Illinois STUART G. BIGLER National Weather Service, Washington, D.C. KENNETH E. WILK National Severe Storms Laboratory, Norman, Oklahoma ALBERT C. HARBUCK# Air Weather Service, Scott Air Force Base, Illinois (Manuscript received 14 March 1997, in ®nal form 19 February 1998) ABSTRACT The second part of a history of the use of storm surveillance radars by operational military and civil weather services in the United States is presented. This part describes the genesis and evolution of two operational Doppler weather radars, the Next-Generation Weather Radar and Terminal Doppler Weather Radar. 1. Advances made by Doppler radar operational application of this capability. Thus, opera- meteorological research tional use of Doppler weather radar had to await the development of pulse-Doppler technology (that provid- The wartime Rad Lab investigators recognized the ed the range capability) for the extraction of moments possibility that radar systems could employ the Doppler such as mean radial velocity and spectrum width from effect to measure target velocities. This offered a po- tential for remote measurement of wind speeds. The pulse Doppler spectra and techniques for interpreting Weather Bureau followed up on this potential beginning the velocity patterns observable with a single radar. in fall 1956 and continued through 1960. This early Rogers (1990) reviews the history of early efforts to effort involved conducting tests on an experimental, 3- apply Doppler techniques in radar meteorology.