Hurricane Outer Rainband Mesovortices
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Squall Lines: Meteorology, Skywarn Spotting, & a Brief Look at the 18
Squall Lines: Meteorology, Skywarn Spotting, & A Brief Look At The 18 June 2010 Derecho Gino Izzi National Weather Service, Chicago IL Outline • Meteorology 301: Squall lines – Brief review of thunderstorm basics – Squall lines – Squall line tornadoes – Mesovorticies • Storm spotting for squall lines • Brief Case Study of 18 June 2010 Event Thunderstorm Ingredients • Moisture – Gulf of Mexico most common source locally Thunderstorm Ingredients • Lifting Mechanism(s) – Fronts – Jet Streams – “other” boundaries – topography Thunderstorm Ingredients • Instability – Measure of potential for air to accelerate upward – CAPE: common variable used to quantify magnitude of instability < 1000: weak 1000-2000: moderate 2000-4000: strong 4000+: extreme Thunderstorms Thunderstorms • Moisture + Instability + Lift = Thunderstorms • What kind of thunderstorms? – Single Cell – Multicell/Squall Line – Supercells Thunderstorm Types • What determines T-storm Type? – Short/simplistic answer: CAPE vs Shear Thunderstorm Types • What determines T-storm Type? (Longer/more complex answer) – Lot we don’t know, other factors (besides CAPE/shear) include • Strength of forcing • Strength of CAP • Shear WRT to boundary • Other stuff Thunderstorm Types • Multi-cell squall lines most common type of severe thunderstorm type locally • Most common type of severe weather is damaging winds • Hail and brief tornadoes can occur with most the intense squall lines Squall Lines & Spotting Squall Line Terminology • Squall Line : a relatively narrow line of thunderstorms, often -
J5J.1 1. Introduction the Bow Echo and Mesoscale Convective Vortex
J5J.1 Keynote Talk: BAMEX Observations of Mesoscale Convective Vortices Christopher A. Davis and Stanley B. Trier National Center for Atmospheric Research Boulder, Colorado 80307 1. Introduction and a Lear jet leased from Weather Modification Inc. (WMI). Mobile Ground- The Bow Echo and Mesoscale based facilities included the Mobile Convective Vortex (MCV) Experiment Integrated Profiling System (MIPS) from (BAMEX) is a study of life cycles of the University of Alabama (Huntsville) mesoscale convective systems using three and three Mobile GPS-Loran Atmospheric aircraft and multiple, mobile ground-based Sounding Systems (MGLASS) from instruments. It represents a combination of NCAR. The MIPS and MGLASS were two related programs to investigate (a) referred to as the ground based observing bow echoes (Fujita, 1978), principally system (GBOS). The two P-3s were each those which produce damaging surface equipped with tail Doppler radars, the winds and last at least 4 hours and (b) Electra Doppler Radar (ELDORA) being larger convective systems which produce on the NRL P-3. The WMI Lear jet long lived mesoscale convective vortices deployed dropsondes from roughly 12 km (MCVs) (Bartels and Maddox, 1991). The AGL. project was conducted from 20 May to 6 For MCSs, the objective was to sample July, 2003, based at MidAmerica Airport mesoscale wind and temperature fields in Mascoutah, Illinois. A detailed while obtaining high-resolution snapshots overview of the project, including of convection structures, especially those preliminary results appears in Davis et al. (2004). The reader wishing to view processed BAMEX data should visit http://www.joss.ucar.edu/bamex/catalog/. In this keynote address, I will focus on the study of MCVs, based particularly observations from airborne Doppler radar and dropsondes and wind profilers. -
US Landfalling and North Atlantic Hurricanes
44 MONTHLY WEATHER REVIEW VOLUME 140 U.S. Landfalling and North Atlantic Hurricanes: Statistical Modeling of Their Frequencies and Ratios GABRIELE VILLARINI Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, and Willis Research Network, London, United Kingdom GABRIEL A. VECCHI NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey JAMES A. SMITH Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey (Manuscript received 10 March 2011, in final form 11 July 2011) ABSTRACT Time series of U.S. landfalling and North Atlantic hurricane counts and their ratios over the period 1878– 2008 are modeled using tropical Atlantic sea surface temperature (SST), tropical mean SST, the North At- lantic Oscillation (NAO), and the Southern Oscillation index (SOI). Two SST input datasets are employed to examine the uncertainties in the reconstructed SST data on the modeling results. Because of the likely un- dercount of recorded hurricanes in the earliest part of the record, both the uncorrected hurricane dataset (HURDAT) and a time series with a recently proposed undercount correction are considered. Modeling of the count data is performed using a conditional Poisson regression model, in which the rate of occurrence can depend linearly or nonlinearly on the climate indexes. Model selection is performed following a stepwise approach and using two penalty criteria. These results do not allow one to identify a single ‘‘best’’ model because of the different model configurations (different SST data, corrected versus uncorrected datasets, and penalty criteria). Despite the lack of an objectively identified unique final model, the authors recommend a set of models in which the parameter of the Poisson distribution depends linearly on tropical Atlantic and tropical mean SSTs. -
Template for Electronic Journal of Severe Storms Meteorology
Lyza, A. W., A. W. Clayton, K. R. Knupp, E. Lenning, M. T. Friedlein, R. Castro, and E. S. Bentley, 2017: Analysis of mesovortex characteristics, behavior, and interactions during the second 30 June‒1 July 2014 midwestern derecho event. Electronic J. Severe Storms Meteor., 12 (2), 1–33. Analysis of Mesovortex Characteristics, Behavior, and Interactions during the Second 30 June‒1 July 2014 Midwestern Derecho Event ANTHONY W. LYZA, ADAM W. CLAYTON, AND KEVIN R. KNUPP Department of Atmospheric Science, Severe Weather Institute—Radar and Lightning Laboratories University of Alabama in Huntsville, Huntsville, Alabama ERIC LENNING, MATTHEW T. FRIEDLEIN, AND RICHARD CASTRO NOAA/National Weather Service, Romeoville, Illinois EVAN S. BENTLEY NOAA/National Weather Service, Portland, Oregon (Submitted 19 February 2017; in final form 25 August 2017) ABSTRACT A pair of intense, derecho-producing quasi-linear convective systems (QLCSs) impacted northern Illinois and northern Indiana during the evening hours of 30 June through the predawn hours of 1 July 2014. The second QLCS trailed the first one by only 250 km and approximately 3 h, yet produced 29 confirmed tornadoes and numerous areas of nontornadic wind damage estimated to be caused by 30‒40 m s‒1 flow. Much of the damage from the second QLCS was associated with a series of 38 mesovortices, with up to 15 mesovortices ongoing simultaneously. Many complex behaviors were documented in the mesovortices, including: a binary (Fujiwhara) interaction, the splitting of a large mesovortex in two followed by prolific tornado production, cyclic mesovortexgenesis in the remains of a large mesovortex, and a satellite interaction of three small mesovortices around a larger parent mesovortex. -
Hurricane & Tropical Storm
5.8 HURRICANE & TROPICAL STORM SECTION 5.8 HURRICANE AND TROPICAL STORM 5.8.1 HAZARD DESCRIPTION A tropical cyclone is a rotating, organized system of clouds and thunderstorms that originates over tropical or sub-tropical waters and has a closed low-level circulation. Tropical depressions, tropical storms, and hurricanes are all considered tropical cyclones. These storms rotate counterclockwise in the northern hemisphere around the center and are accompanied by heavy rain and strong winds (NOAA, 2013). Almost all tropical storms and hurricanes in the Atlantic basin (which includes the Gulf of Mexico and Caribbean Sea) form between June 1 and November 30 (hurricane season). August and September are peak months for hurricane development. The average wind speeds for tropical storms and hurricanes are listed below: . A tropical depression has a maximum sustained wind speeds of 38 miles per hour (mph) or less . A tropical storm has maximum sustained wind speeds of 39 to 73 mph . A hurricane has maximum sustained wind speeds of 74 mph or higher. In the western North Pacific, hurricanes are called typhoons; similar storms in the Indian Ocean and South Pacific Ocean are called cyclones. A major hurricane has maximum sustained wind speeds of 111 mph or higher (NOAA, 2013). Over a two-year period, the United States coastline is struck by an average of three hurricanes, one of which is classified as a major hurricane. Hurricanes, tropical storms, and tropical depressions may pose a threat to life and property. These storms bring heavy rain, storm surge and flooding (NOAA, 2013). The cooler waters off the coast of New Jersey can serve to diminish the energy of storms that have traveled up the eastern seaboard. -
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. -
Hurricane Andrew in Florida: Dynamics of a Disaster ^
Hurricane Andrew in Florida: Dynamics of a Disaster ^ H. E. Willoughby and P. G. Black Hurricane Research Division, AOML/NOAA, Miami, Florida ABSTRACT Four meteorological factors aggravated the devastation when Hurricane Andrew struck South Florida: completed replacement of the original eyewall by an outer, concentric eyewall while Andrew was still at sea; storm translation so fast that the eye crossed the populated coastline before the influence of land could weaken it appreciably; extreme wind speed, 82 m s_1 winds measured by aircraft flying at 2.5 km; and formation of an intense, but nontornadic, convective vortex in the eyewall at the time of landfall. Although Andrew weakened for 12 h during the eyewall replacement, it contained vigorous convection and was reintensifying rapidly as it passed onshore. The Gulf Stream just offshore was warm enough to support a sea level pressure 20-30 hPa lower than the 922 hPa attained, but Andrew hit land before it could reach this potential. The difficult-to-predict mesoscale and vortex-scale phenomena determined the course of events on that windy morning, not a long-term trend toward worse hurricanes. 1. Introduction might have been a harbinger of more devastating hur- ricanes on a warmer globe (e.g., Fisher 1994). Here When Hurricane Andrew smashed into South we interpret Andrew's progress to show that the ori- Florida on 24 August 1992, it was the third most in- gins of the disaster were too complicated to be ex- tense hurricane to cross the United States coastline in plained by thermodynamics alone. the 125-year quantitative climatology. -
A Long-Lasting Vortex Rossby Wave–Induced Rainband of Typhoon Longwang (2005)
A Long-Lasting Vortex Rossby Wave–Induced Rainband of Typhoon Longwang (2005) YANLUAN LIN, YUANLONG LI, QINGSHAN LI, MINYAN CHEN, FANGHUA XU, YUQING WANG, AND BIN HUANG n 2 October 2005, a record-breaking rainfall event Tsai 2013). As Typhoon Longwang approached the with 152 mm of rainfall in an hour occurred as coast of Fujian Province at 0800 UTC, one type of this OTyphoon Longwang approached Fujian Province, transient rainband in the northeast sector started to China. The severe rainfall was unexpected and signifi- weaken and dissipate (Fig. 1b). At the same time, the cantly underpredicted by the local weather forecasters eyewall underwent an asymmetry transformation and caused a total of 96 deaths. Because of the severe accompanied by a bended convection pattern in the damage over Taiwan and mainland China, the name north (Fig. 1b). The bended convection transformed of Longwang, which means a dragon in charge of into a strong convective band along the eyewall to the rainfall in Chinese, was removed from the name list north and moved outward relative to the storm center for future typhoons. (Fig. 1c). The convective band continued to intensify with a sharp inner edge (Fig. 1d). An hour later, the EVOLUTION AND BASIC FEATURES OF convective band achieved its maximum intensity with THE RAINBAND. The formation and evolution a large area of stratiform precipitation outward and of the rainband associated with the rainfall event was downstream (Fig. 1e). At this time, cloud brightness captured by the radar mosaic produced by the Central temperatures as low as −80°C were measured by a Weather Bureau (CWB) of Taiwan (Fig. -
Service Assessment Hurricane Irene, August
Service Assessment Hurricane Irene, August 21–30, 2011 U.S. DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration National Weather Service Silver Spring, Maryland Cover Photographs: Top Left - NOAA GOES 13 visible image of Hurricane Irene taken at 12:32 UTC (8:32 a.m. EDT) on August 27, 2011, as it was moving northward along the east coast. Map of total storm rainfall for Hurricane Irene (NCEP/HPC) overlaid with photos of Hurricane Irene’s impacts. Clockwise from top right: • Damage to bridge over the Pemigewasset River/East Branch in Lincoln, NH (NH DOT) • Trees across road and utility lines in Guilford, CT (CT DEP) • Damage to homes from storm surge at Cosey Beach, East Haven, CT (CT DEP) • Flooding of Delaware River closes Rt. 29 in Trenton, NJ (State of New Jersey, Office of the Governor) • Damage from storm surge on North Carolina’s Outer Banks (USGS) • Damage to home from an EF1 tornado in Lewes, DE (Sussex County, DE EOC) • River flooding on Schoharie Creek near Lexington, NY (USGS) • Flood damage to historic covered bridge and road in Quechee, VT (FEMA) ii Service Assessment Hurricane Irene, August 21–30, 2011 September 2012 National Oceanic and Atmospheric Administration Dr. Jane Lubchenco, Administrator National Weather Service Laura Furgione, Acting Assistant Administrator for Weather Services iii Preface On August 21-29, 2011, Hurricane Irene left a devastating imprint on the Caribbean and U.S. East Coast. The storm took the lives of more than 40 people, caused an estimated $6.5 billion in damages, unleashed major flooding, downed trees and power lines, and forced road closures, evacuations, and major rescue efforts. -
1 Vertical Structure of Tropical Cyclone Rainbands As Seen by The
Vertical Structure of Tropical Cyclone Rainbands as seen by the TRMM Precipitation Radar Deanna A. Hence and Robert A. Houze, Jr. University of Washington, Seattle, Washington Submitted to Journal of Atmospheric Sciences November 2011 Corresponding author address: Deanna Hence, Department of Atmospheric Sciences, University of Washington, Box 351640, Seattle, WA 98195 E-mail: [email protected] 1 ABSTRACT 1 Ten years of data from the Tropical Rainfall Measurement Mission satellite’s Precipitation 2 Radar (TRMM PR) show the vertical structure of tropical cyclone rainbands. Radar-echo 3 statistics show that rainbands have a two-layered structure, with distinct modes separated by the 4 melting layer. The ice layer is a combination of particles imported from the eyewall and ice left 5 aloft as convective cells collapse. This layering is most pronounced in the inner region of the 6 storm, and the layering is enhanced by storm strength. The inner-region rainbands are vertically 7 confined by outflow from the eyewall but nevertheless are a combination of strong embedded 8 convective cells and robust stratiform precipitation, both of which become more pronounced in 9 stronger cyclones. 10 Changes in rainband coverage, vertical structure, and the amount of active convection 11 indicate a change in the nature of rainbands between the regions inward and outward of a radius 12 of ~200 km. Beyond this radius, rainbands consist of more sparsely distributed precipitation that 13 is more convective in nature than that of the inner-region rainbands, and the outer-region 14 rainband structures are relatively insensitive to changes in storm intensity. -
TROPICAL CYCLONE ANALYSIS USING AMSU DATA Stanley Q
P3.2 TROPICAL CYCLONE ANALYSIS USING AMSU DATA Stanley Q. Kidder* CIRA, Colorado State University, Fort Collins, Colorado Mitchell D. Goldberg NOAA/NESDIS/CRAD, Camp Springs, Maryland Raymond M. Zehr and Mark DeMaria NOAA/NESDIS/RAMM Team, Fort Collins, Colorado James F. W. Purdom NOAA/NESDIS/ORA, Washington, D.C. Christopher S. Velden CIMSS, University of Wisconsin, Madison, Wisconsin Norman C. Grody NOAA/NESDIS/Microwave Sensing Group, Camp Springs, Maryland Sheldon J. Kusselson NOAA/NESDIS/SAB, Camp Springs, Maryland 1. INTRODUCTION estimate temperature between the surface and 10 hPa from AMSU observations were generated from collo- Scientific progress often comes about as a result of cated AMSU-A limb adjusted brightness temperatures new instruments for making scientific observations. The and radiosonde temperature profiles. Above 10 hPa, the Advanced Microwave Sounding Unit (AMSU) is one regression coefficients were generated from brightness such new instrument. First flown on the NOAA 15 satel- temperatures simulated from a set of rocketsonde pro- lite launched 13 May 1998, AMSU will fly on the NOAA files. The root mean square (rms) differences between 16 and NOAA 17 satellites as well. AMSU-A temperature retrievals and collocated ra- AMSU is a 20-channel instrument designed to diosondes for the latitude range of 0º to 30º north are make temperature and moisture soundings through less than 2 K. Additional details on the temperature re- clouds. Geophysical parameters such as rain rate, col- trieval procedures and accuracies are given in Goldberg umn-integrated water vapor and column-integrated (1999). cloud liquid water can also be retrieved. The AMSU has Rain rate and column-integrated cloud liquid water significantly improved spatial resolution, radiometric and water vapor are retrieved semi-operationally by the accuracy, and number of channels over the Microwave NESDIS/Microwave Sensing Group using algorithms Sounding Unit, which flew on TIROS N and the NOAA 6 described in Grody et al. -
Quick Response Report #112 IMPACT of HURRICANE BONNIE
Quick Response Report #112 IMPACT OF HURRICANE BONNIE (AUGUST 1998): NORTH CAROLINA AND VIRGINIA WITH SPECIAL EMPHASIS ON ESTUARINE/MAINLAND SHORES AND A NOTE ABOUT HURRICANE GEORGES, ALABAMA David M. Bush Department of Geology State University of West Georgia Carrollton, GA 30118 Tel: 770-836-4597 Fax: 770-836-4373 E-mail: [email protected] Tracy Monegan Rice Program for the Study of Developed Shorelines (PSDS) Division of Earth & Ocean Sciences Nicholas School of the Environment Duke University Durham, NC 27708 Tel: 919-681-8228 Fax: 919-684- 5833 E-mail: [email protected] Matthew Stutz Program for the Study of Developed Shorelines (PSDS) Division of Earth & Ocean Sciences Nicholas School of the Environment Duke University Durham, NC 27708 Tel: 919-681-8228 Fax: 919-684- 5833 E-mail: [email protected] Andrew S. Coburn Coburn & Associates Coastal Planning Consultants PO Box 12582 Research Triangle Park, NC 27709- 2582 Tel: 919-598-8489 Fax: 919-598- 0516 E-mail: [email protected] Robert S. Young Department of Geoscience and Natural Resource Management Western Carolina University 253 Stillwell Hall Cullowhee, NC 28723 Tel: (704) 227-7503 E-mail: [email protected] 1999 Return to Hazards Center Home Page Return to Quick Response Paper Index This material is based upon work supported by the National Science Foundation under Grant No. CMS-9632458. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. IMPACT OF HURRICANE BONNIE (AUGUST 1998): NORTH CAROLINA AND VIRGINIA WITH SPECIAL EMPHASIS ON ESTUARINE/MAINLAND SHORES AND A NOTE ABOUT HURRICANE GEORGES, ALABAMA Hurricane Bonnie was a Category 3 storm that made landfall near Cape Fear/Wilmington, North Carolina on August 27, 1998.