FEMA Tornadoes Fact Sheet
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Moore, Oklahoma—Growth Cushions Tornado Impact
Cover Story Moore, Oklahoma—Growth COVER STORY Cushions Tornado Impact By Sandra Patterson photo courtesy City of Moore Economic Development Department oore, Oklahoma, is a city on the fast track of growth. Straddling I-35 and just 10 miles from Mdowntown Oklahoma City and 8 miles from Norman, home of the University of Oklahoma, Moore is a bedroom community experiencing an unprecedented surge in new home construction and an accompanying growth in retail development. According to Moore’s Economic Development Author- ity, more than 826 new home permits were issued in 2005 and commercial construction was valued at more than $16 million. The commission reports that the town’s assessed valuation has increased an average of 10 percent per year since 2001 to over $200 million in 2005. With a population of 18,781 in 1970, the city had grown to 41,138 by the 2000 census. It is expected to top 49,000 in 2006. Moore is also located in that part of the country known as Tornado Alley. And, of all the tornado-prone areas that comprise Tornado Alley, Moore is situated in one of Figure 1. Path of 1998 tornado (Map from National Weather Service the two that experiences the highest tornado count per Web site) square mile. Six Years, Three Tornadoes Since 1998, three tornadoes have torn through Moore. On October 4, 1998, a tornado struck the southwest side of the city (figure 1). With only F1 strength (see page 9 sidebar on the Fujita Scale), the damage was limited to ripped up vegetation, downed property fences, and torn roof shingles. -
A Study of Synoptic-Scale Tornado Regimes
Garner, J. M., 2013: A study of synoptic-scale tornado regimes. Electronic J. Severe Storms Meteor., 8 (3), 1–25. A Study of Synoptic-Scale Tornado Regimes JONATHAN M. GARNER NOAA/NWS/Storm Prediction Center, Norman, OK (Submitted 21 November 2012; in final form 06 August 2013) ABSTRACT The significant tornado parameter (STP) has been used by severe-thunderstorm forecasters since 2003 to identify environments favoring development of strong to violent tornadoes. The STP and its individual components of mixed-layer (ML) CAPE, 0–6-km bulk wind difference (BWD), 0–1-km storm-relative helicity (SRH), and ML lifted condensation level (LCL) have been calculated here using archived surface objective analysis data, and then examined during the period 2003−2010 over the central and eastern United States. These components then were compared and contrasted in order to distinguish between environmental characteristics analyzed for three different synoptic-cyclone regimes that produced significantly tornadic supercells: cold fronts, warm fronts, and drylines. Results show that MLCAPE contributes strongly to the dryline significant-tornado environment, while it was less pronounced in cold- frontal significant-tornado regimes. The 0–6-km BWD was found to contribute equally to all three significant tornado regimes, while 0–1-km SRH more strongly contributed to the cold-frontal significant- tornado environment than for the warm-frontal and dryline regimes. –––––––––––––––––––––––– 1. Background and motivation As detailed in Hobbs et al. (1996), synoptic- scale cyclones that foster tornado development Parameter-based and pattern-recognition evolve with time as they emerge over the central forecast techniques have been essential and eastern contiguous United States (hereafter, components of anticipating tornadoes in the CONUS). -
Tornado Safety Q & A
TORNADO SAFETY Q & A The Prosper Fire Department Office of Emergency Management’s highest priority is ensuring the safety of all Prosper residents during a state of emergency. A tornado is one of the most violent storms that can rip through an area, striking quickly with little to no warning at all. Because the aftermath of a tornado can be devastating, preparing ahead of time is the best way to ensure you and your family’s safety. Please read the following questions about tornado safety, answered by Prosper Emergency Management Coordinator Kent Bauer. Q: During s evere weather, what does the Prosper Fire Department do? A: We monitor the weather alerts sent out by the National Weather Service. Because we are not meteorologists, we do not interpret any sort of storms or any sort of warnings. Instead, we pass along the information we receive from the National Weather Service to our residents through social media, storm sirens and Smart911 Rave weather warnings. Q: What does a Tornado Watch mean? A: Tornadoes are possible. Remain alert for approaching storms. Watch the sky and stay tuned to NOAA Weather Radio, commercial radio or television for information. Q: What does a Tornado Warning mean? A: A tornado has been sighted or indicated by weather radar and you need to take shelter immediately. Q: What is the reason for setting off the Outdoor Storm Sirens? A: To alert those who are outdoors that there is a tornado or another major storm event headed Prosper’s way, so seek shelter immediately. I f you are outside and you hear the sirens go off, do not call 9-1-1 to ask questions about the warning. -
Mesoscale Convective Vortex That Causes Tornado-Like Vortices Over the Sea: a Potential Risk to Maritime Traffic
JUNE 2019 T O C H I M O T O E T A L . 1989 Mesoscale Convective Vortex that Causes Tornado-Like Vortices over the Sea: A Potential Risk to Maritime Traffic EIGO TOCHIMOTO Atmosphere and Ocean Research Institute, The University of Tokyo, Tokyo, Japan SHO YOKOTA Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, Japan HIROSHI NIINO Atmosphere and Ocean Research Institute, The University of Tokyo, Tokyo, Japan WATARU YANASE Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, Japan (Manuscript received 24 August 2018, in final form 28 January 2019) ABSTRACT Strong gusty winds in a weak maritime extratropical cyclone (EC) over the Tsushima Strait in the south- western Sea of Japan capsized several fishing boats on 1 September 2015. A C-band Doppler radar recorded a spiral-shaped reflectivity pattern associated with a convective system and a Doppler velocity pattern of a vortex with a diameter of 30 km [meso-b-scale vortex (MBV)] near the location of the wreck. A high- resolution numerical simulation with horizontal grid interval of 50 m successfully reproduced the spiral- shaped precipitation pattern associated with the MBV and tornado-like strong vortices that had a maximum 2 wind speed exceeding 50 m s 1 and repeatedly developed in the MBV. The simulated MBV had a strong cyclonic circulation comparable to a mesocyclone in a supercell storm. Unlike mesocyclones associated with a supercell storm, however, its vorticity was largest near the surface and decreased monotonically with in- creasing height. The strong vorticity of the MBV near the surface originated from a horizontal shear line in the EC. -
Morning Tornado / Waterspout Guide (1950-2020) (For North Central and Northeast Wisconsin)
MORNING TORNADO / WATERSPOUT GUIDE (1950-2020) (FOR NORTH CENTRAL AND NORTHEAST WISCONSIN) MORNING TORNADOES (MIDNIGHT TO NOON CST) UPDATED: 2/1/21 1 MORNING TORNADO / WATERSPOUT GUIDE (1950-2020) (FOR NORTH CENTRAL AND NORTHEAST WISCONSIN) MORNING TORNADOES (MIDNIGHT TO NOON CST) Event EF Date Time TOR in GRB Service Area # Rank Month Date Year (CST) Start / End Location County or Counties 1 2 6 20 1954 02:30-02:40 Rothschild - 6 NE Mosinee Marathon 2 2 6 20 1954 04:00 Brothertown Calumet 3 1 5 4 1959 10:30 Wausau Marathon 4 1 5 4 1959 11:45 Deerbrook Langlade 5 2 5 6 1959 03:20 Symco - 3 SE Clintonville Outagamie - Waupaca 6 2 9 3 1961 00:10 Fenwood Marathon 7 1 9 3 1961 01:00 Athens Marathon 8 1 7 1 1967 00:45 3 E Kiel Manitowoc 9 2 6 30 1968 04:00 3 NW Cavour Forest 10 1 6 30 1968 04:45 3 S Pembine Marinette 11 1 12 1 1970 07:00 Hull Portage 12 2 12 1 1970 09:00 12 SE Marshfield Wood 13 2 12 1 1970 09:45-10:30 4 NW Iola - Pella Shawano - Langlade - Oconto 14 3 12 1 1970 10:10-1045 near Medina - Rose Lawn Outagamie - Shawano 15 1 7 8 1971 02:00 Wisconsin Rapids Wood 16 0 7 30 1971 07:00 4 E Oshkosh (waterspout) Winnebago 17 1 3 11 1973 10:30 2 E Calumetville Calumet 18 1 6 18 1973 11:00 2 W Athens Marathon 19 1 7 12 1973 03:00 Boulder Junction - Sayner Vilas 20 1 7 12 1973 07:30 Jacksonport Door 21 1 7 12 1973 08:00 4 W Freedom Outagamie 22 2 6 16 1979 09:30 Oconto Falls - 2 NE Lena Oconto 23 1 8 4 1979 10:00 Manitowoc Manitowoc 24 2 6 7 1980 00:20 Valders Manitowoc 25 1 7 5 1980 00:30 Valders Manitowoc 26 2 4 4 1981 00:35 4 W Kiel -
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. -
A Background Investigation of Tornado Activity Across the Southern Cumberland Plateau Terrain System of Northeastern Alabama
DECEMBER 2018 L Y Z A A N D K N U P P 4261 A Background Investigation of Tornado Activity across the Southern Cumberland Plateau Terrain System of Northeastern Alabama ANTHONY W. LYZA AND KEVIN R. KNUPP Department of Atmospheric Science, Severe Weather Institute–Radar and Lightning Laboratories, Downloaded from http://journals.ametsoc.org/mwr/article-pdf/146/12/4261/4367919/mwr-d-18-0300_1.pdf by NOAA Central Library user on 29 July 2020 University of Alabama in Huntsville, Huntsville, Alabama (Manuscript received 23 August 2018, in final form 5 October 2018) ABSTRACT The effects of terrain on tornadoes are poorly understood. Efforts to understand terrain effects on tornadoes have been limited in scope, typically examining a small number of cases with limited observa- tions or idealized numerical simulations. This study evaluates an apparent tornado activity maximum across the Sand Mountain and Lookout Mountain plateaus of northeastern Alabama. These plateaus, separated by the narrow Wills Valley, span ;5000 km2 and were impacted by 79 tornadoes from 1992 to 2016. This area represents a relative regional statistical maximum in tornadogenesis, with a particular tendency for tornadogenesis on the northwestern side of Sand Mountain. This exploratory paper investigates storm behavior and possible physical explanations for this density of tornadogenesis events and tornadoes. Long-term surface observation datasets indicate that surface winds tend to be stronger and more backed atop Sand Mountain than over the adjacent Tennessee Valley, potentially indicative of changes in the low-level wind profile supportive to storm rotation. The surface data additionally indicate potentially lower lifting condensation levels over the plateaus versus the adjacent valleys, an attribute previously shown to be favorable for tornadogenesis. -
Quasi-Linear Convective System Mesovorticies and Tornadoes
Quasi-Linear Convective System Mesovorticies and Tornadoes RYAN ALLISS & MATT HOFFMAN Meteorology Program, Iowa State University, Ames ABSTRACT Quasi-linear convective system are a common occurance in the spring and summer months and with them come the risk of them producing mesovorticies. These mesovorticies are small and compact and can cause isolated and concentrated areas of damage from high winds and in some cases can produce weak tornadoes. This paper analyzes how and when QLCSs and mesovorticies develop, how to identify a mesovortex using various tools from radar, and finally a look at how common is it for a QLCS to put spawn a tornado across the United States. 1. Introduction Quasi-linear convective systems, or squall lines, are a line of thunderstorms that are Supercells have always been most feared oriented linearly. Sometimes, these lines of when it has come to tornadoes and as they intense thunderstorms can feature a bowed out should be. However, quasi-linear convective systems can also cause tornadoes. Squall lines and bow echoes are also known to cause tornadoes as well as other forms of severe weather such as high winds, hail, and microbursts. These are powerful systems that can travel for hours and hundreds of miles, but the worst part is tornadoes in QLCSs are hard to forecast and can be highly dangerous for the public. Often times the supercells within the QLCS cause tornadoes to become rain wrapped, which are tornadoes that are surrounded by rain making them hard to see with the naked eye. This is why understanding QLCSs and how they can produce mesovortices that are capable of producing tornadoes is essential to forecasting these tornadic events that can be highly dangerous. -
Storm Spotting – Solidifying the Basics PROFESSOR PAUL SIRVATKA COLLEGE of DUPAGE METEOROLOGY Focus on Anticipating and Spotting
Storm Spotting – Solidifying the Basics PROFESSOR PAUL SIRVATKA COLLEGE OF DUPAGE METEOROLOGY HTTP://WEATHER.COD.EDU Focus on Anticipating and Spotting • What do you look for? • What will you actually see? • Can you identify what is going on with the storm? Is Gilbert married? Hmmmmm….rumor has it….. Its all about the updraft! Not that easy! • Various types of storms and storm structures. • A tornado is a “big sucky • Obscuration of important thing” and underneath the features make spotting updraft is where it forms. difficult. • So find the updraft! • The closer you are to a storm the more difficult it becomes to make these identifications. Conceptual models Reality is much harder. Basic Conceptual Model Sometimes its easy! North Central Illinois, 2-28-17 (Courtesy of Matt Piechota) Other times, not so much. Reality usually is far more complicated than our perfect pictures Rain Free Base Dusty Outflow More like reality SCUD Scattered Cumulus Under Deck Sigh...wall clouds! • Wall clouds help spotters identify where the updraft of a storm is • Wall clouds may or may not be present with tornadic storms • Wall clouds may be seen with any storm with an updraft • Wall clouds may or may not be rotating • Wall clouds may or may not result in tornadoes • Wall clouds should not be reported unless there is strong and easily observable rotation noted • When a clear slot is observed, a well written or transmitted report should say as much Characteristics of a Tornadic Wall Cloud • Surface-based inflow • Rapid vertical motion (scud-sucking) • Persistent • Persistent rotation Clear Slot • The key, however, is the development of a clear slot Prof. -
Explaining the Trends and Variability in the United States Tornado Records
www.nature.com/scientificreports OPEN Explaining the trends and variability in the United States tornado records using climate teleconnections and shifts in observational practices Niloufar Nouri1*, Naresh Devineni1,2*, Valerie Were2 & Reza Khanbilvardi1,2 The annual frequency of tornadoes during 1950–2018 across the major tornado-impacted states were examined and modeled using anthropogenic and large-scale climate covariates in a hierarchical Bayesian inference framework. Anthropogenic factors include increases in population density and better detection systems since the mid-1990s. Large-scale climate variables include El Niño Southern Oscillation (ENSO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), Pacifc Decadal Oscillation (PDO), Arctic Oscillation (AO), and Atlantic Multi-decadal Oscillation (AMO). The model provides a robust way of estimating the response coefcients by considering pooling of information across groups of states that belong to Tornado Alley, Dixie Alley, and Other States, thereby reducing their uncertainty. The infuence of the anthropogenic factors and the large-scale climate variables are modeled in a nested framework to unravel secular trend from cyclical variability. Population density explains the long-term trend in Dixie Alley. The step-increase induced due to the installation of the Doppler Radar systems explains the long-term trend in Tornado Alley. NAO and the interplay between NAO and ENSO explained the interannual to multi-decadal variability in Tornado Alley. PDO and AMO are also contributing to this multi-time scale variability. SOI and AO explain the cyclical variability in Dixie Alley. This improved understanding of the variability and trends in tornadoes should be of immense value to public planners, businesses, and insurance-based risk management agencies. -
MHMP 2014 UPDATE PART 3 I Ab Natural Weather Hazards
Severe Winds Non-tornadic winds of 58 miles per hour or greater. Hazard Description Severe winds, or straight-line winds, sometimes occur during severe thunderstorms and other weather systems, and can be very damaging to communities. Often, when straight-line winds occur, the presence of the forceful winds, with velocities over 58 mph, may be confused with a tornado occurrence. Severe winds have the potential to cause loss of life from breaking and falling trees, property damage, and flying debris, but tend not to cause as many deaths as tornadoes do. However, the property damage from straight line winds can be more widespread than a tornado, usually affecting multiple counties at a time. In addition to property damage to buildings (especially less sturdy structures such as storage sheds, outbuildings, etc.), there is a risk for infrastructure damage from downed power lines due to falling limbs and trees. Large scale power failures, with hundreds of thousands of customers affected, are common during straight-line wind events. Hazard Analysis Another dangerous aspect of straight line winds is that they occur more frequently beyond the April to September time frame than is seen with the other thunderstorm hazards. It is not rare to see severe winds ravage parts of the state in October and November—some winter storm events in Michigan have produced wind-speeds of 60 and 70 miles per hour. Stark temperature contrasts seen in colliding air masses along swift-moving cold fronts can occur during practically any month. Figures from the National Weather Service indicate that severe winds occur more frequently in the southern-half of the Lower Peninsula than any other area of the state.