Conditions Necessary for a Hurricane to Form
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An Informed System Development Approach to Tropical Cyclone Track and Intensity Forecasting
Linköping Studies in Science and Technology Dissertations. No. 1734 An Informed System Development Approach to Tropical Cyclone Track and Intensity Forecasting by Chandan Roy Department of Computer and Information Science Linköping University SE-581 83 Linköping, Sweden Linköping 2016 Cover image: Hurricane Isabel (2003), NASA, image in public domain. Copyright © 2016 Chandan Roy ISBN: 978-91-7685-854-7 ISSN 0345-7524 Printed by LiU Tryck, Linköping 2015 URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-123198 ii Abstract Introduction: Tropical Cyclones (TCs) inflict considerable damage to life and property every year. A major problem is that residents often hesitate to follow evacuation orders when the early warning messages are perceived as inaccurate or uninformative. The root problem is that providing accurate early forecasts can be difficult, especially in countries with less economic and technical means. Aim: The aim of the thesis is to investigate how cyclone early warning systems can be technically improved. This means, first, identifying problems associated with the current cyclone early warning systems, and second, investigating if biologically based Artificial Neural Networks (ANNs) are feasible to solve some of the identified problems. Method: First, for evaluating the efficiency of cyclone early warning systems, Bangladesh was selected as study area, where a questionnaire survey and an in-depth interview were administered. Second, a review of currently operational TC track forecasting techniques was conducted to gain a better understanding of various techniques’ prediction performance, data requirements, and computational resource requirements. Third, a technique using biologically based ANNs was developed to produce TC track and intensity forecasts. -
Variations Aperiodic Extreme Sea Level in Cuba Under the Influence
Extreme non-regular sea level variations in Cuba under the influence of intense tropical cyclones. Item Type Journal Contribution Authors Hernández González, M. Citation Serie Oceanológica, (8). p. 13-24 Publisher Instituto de Oceanología Download date 02/10/2021 16:50:34 Link to Item http://hdl.handle.net/1834/4053 Serie Oceanológica. No. 8, 2011 ISSN 2072-800x Extreme non-regular sea level variations in Cuba under the influence of intense tropical cyclones. Variaciones aperiódicas extremas del nivel del mar en Cuba bajo la influencia de intensos ciclones tropicales. Marcelino Hernández González* *Institute of Oceanology. Ave. 1ra. No.18406 entre 184 y 186. Flores, Playa, Havana, Cuba. [email protected] ACKNOWLEDGEMENTS This work was sponsored by the scientific – technical service "Real Time Measurement and Transmission of Information. Development of Operational Oceanographic Products", developed at the Institute of Oceanology. The author wishes to thank Mrs. Martha M. Rivero Fernandez, from the Marine Information Service of the Institute of Oceanology, for her support in the translation of this article. Abstract This paper aimed at analyzing non-regular sea level variations of meteorological origin under the influence of six major tropical cyclones that affected Cuba, from sea level hourly height series in twelve coastal localities. As a result, it was obtained a characterization of the magnitude and timing of extreme sea level variations under the influence of intense tropical cyclones. Resumen El presente trabajo tuvo como objetivo analizar las variaciones aperiódicas del nivel del mar de origen meteorológico bajo la influencia de seis de los principales ciclones tropicales que han afectado a Cuba, a partir de series de alturas horarias del nivel del mar de doce localidades costeras. -
Hurricane and Tropical Storm
State of New Jersey 2014 Hazard Mitigation Plan Section 5. Risk Assessment 5.8 Hurricane and Tropical Storm 2014 Plan Update Changes The 2014 Plan Update includes tropical storms, hurricanes and storm surge in this hazard profile. In the 2011 HMP, storm surge was included in the flood hazard. The hazard profile has been significantly enhanced to include a detailed hazard description, location, extent, previous occurrences, probability of future occurrence, severity, warning time and secondary impacts. New and updated data and figures from ONJSC are incorporated. New and updated figures from other federal and state agencies are incorporated. Potential change in climate and its impacts on the flood hazard are discussed. The vulnerability assessment now directly follows the hazard profile. An exposure analysis of the population, general building stock, State-owned and leased buildings, critical facilities and infrastructure was conducted using best available SLOSH and storm surge data. Environmental impacts is a new subsection. 5.8.1 Profile 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 (National Oceanic and Atmospheric Administration [NOAA] 2013a). 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. -
Aerial Rapid Assessment of Hurricane Damages to Northern Gulf Coastal Habitats
8786 ReportScience Title and the Storms: the USGS Response to the Hurricanes of 2005 Chapter Five: Landscape5 Changes The hurricanes of 2005 greatly changed the landscape of the Gulf Coast. The following articles document the initial damage assessment from coastal Alabama to Texas; the change of 217 mi2 of coastal Louisiana to water after Katrina and Rita; estuarine damage to barrier islands of the central Gulf Coast, especially Dauphin Island, Ala., and the Chandeleur Islands, La.; erosion of beaches of western Louisiana after Rita; and the damages and loss of floodplain forest of the Pearl River Basin. Aerial Rapid Assessment of Hurricane Damages to Northern Gulf Coastal Habitats By Thomas C. Michot, Christopher J. Wells, and Paul C. Chadwick Hurricane Katrina made landfall in southeast Louisiana on August 29, 2005, and Hurricane Rita made landfall in southwest Louisiana on September 24, 2005. Scientists from the U.S. Geological Survey (USGS) flew aerial surveys to assess damages to natural resources and to lands owned and managed by the U.S. Department of the Interior and other agencies. Flights were made on eight dates from August Introduction 27 through October 4, including one pre-Katrina, three post-Katrina, The USGS National Wetlands and four post-Rita surveys. The Research Center (NWRC) has a geographic area surveyed history of conducting aerial rapid- extended from Galveston, response surveys to assess Tex., to Gulf Shores, hurricane damages along the Ala., and from the Gulf coastal areas of the Gulf of of Mexico shoreline Mexico and Caribbean inland 5–75 mi Sea. Posthurricane (8–121 km). -
Ex-Hurricane Ophelia 16 October 2017
Ex-Hurricane Ophelia 16 October 2017 On 16 October 2017 ex-hurricane Ophelia brought very strong winds to western parts of the UK and Ireland. This date fell on the exact 30th anniversary of the Great Storm of 16 October 1987. Ex-hurricane Ophelia (named by the US National Hurricane Center) was the second storm of the 2017-2018 winter season, following Storm Aileen on 12 to 13 September. The strongest winds were around Irish Sea coasts, particularly west Wales, with gusts of 60 to 70 Kt or higher in exposed coastal locations. Impacts The most severe impacts were across the Republic of Ireland, where three people died from falling trees (still mostly in full leaf at this time of year). There was also significant disruption across western parts of the UK, with power cuts affecting thousands of homes and businesses in Wales and Northern Ireland, and damage reported to a stadium roof in Barrow, Cumbria. Flights from Manchester and Edinburgh to the Republic of Ireland and Northern Ireland were cancelled, and in Wales some roads and railway lines were closed. Ferry services between Wales and Ireland were also disrupted. Storm Ophelia brought heavy rain and very mild temperatures caused by a southerly airflow drawing air from the Iberian Peninsula. Weather data Ex-hurricane Ophelia moved on a northerly track to the west of Spain and then north along the west coast of Ireland, before sweeping north-eastwards across Scotland. The sequence of analysis charts from 12 UTC 15 to 12 UTC 17 October shows Ophelia approaching and tracking across Ireland and Scotland. -
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. -
Space-Time Assessment of Extreme Precipitation in Cuba Between 1980 and 2019 from Multi-Source Weighted-Ensemble Precipitation Dataset
atmosphere Article Space-Time Assessment of Extreme Precipitation in Cuba between 1980 and 2019 from Multi-Source Weighted-Ensemble Precipitation Dataset Gleisis Alvarez-Socorro 1, José Carlos Fernández-Alvarez 1,2 , Rogert Sorí 2,3 , Albenis Pérez-Alarcón 1,2 , Raquel Nieto 2 and Luis Gimeno 2,* 1 Departamento de Meteorología, Instituto Superior de Tecnologías y Ciencias Aplicadas, Universidad de la Habana, La Habana 10400, Cuba; [email protected] (G.A.-S.); [email protected] (J.C.F.-A.); [email protected] (A.P.-A.) 2 Centro de Investigación Mariña, Universidade de Vigo, Environmental Physics Laboratory (EPhysLab), Campus As Lagoas s/n, 32004 Ourense, Spain; [email protected] (R.S.); [email protected] (R.N.) 3 Instituto Dom Luiz, Faculdade de Ciências da Universidade de Lisboa, 1749-016 Campo Grande, Portugal * Correspondence: [email protected] Abstract: Precipitation extremes such as heavy rainfall and floods are of great interest for climate scientists, particularly for small islands vulnerable to weather phenomena such as hurricanes. In this study, we investigated the spatio-temporal evolution of extreme rainfall over Cuba from 1980 to 2019, separating the dry and rainy periods. In addition, a ranking of extreme precipitation events was performed, which provides the number of events, the area affected, and a ranking of their magnitude Citation: Alvarez-Socorro, G.; by considering the magnitude of anomalies. The analysis was conducted using daily data from the Fernández-Alvarez, J.C.; Sorí, R.; multi-source weighted-ensemble precipitation (MSWEPv2). In determining the extreme precipitation Pérez-Alarcón, A.; Nieto, R.; Gimeno, ranking, the daily extreme precipitation anomaly was calculated with respect to the 95th percentile L. -
PROJECT REPORT NOAA/OAR Joint Hurricane Testbed Federal Grant
PROJECT REPORT NOAA/OAR Joint Hurricane Testbed Federal Grant Number: NA15OAR4590205 Probabilistic Prediction of Tropical Cyclone Rapid Intensification Using Satellite Passive Microwave Imagery Principal Investigators Christopher S. Velden1, [email protected] Christopher M. Rozoff2, [email protected] Submission Date: 30 March 2017 1Cooperative Institute for Satellite Meteorological Studies (CIMSS) University of Wisconsin-Madison 1225 West Dayton Street Madison, WI 53706 2National Security Applications Program Research Applications Laboratory National Center for Atmospheric Research P.O. Box 3000 Boulder, CO 80307-3000 Project/Grant Period: 1 September 2016 – 1 March 2017 Report Term or Frequency: Semi-Annual Final Annual Report? No 1. ACCOMPLISHMENTS The primary goal of this project is to improve the probabilistic prediction of rapid intensification (RI) in tropical cyclones (TCs). The framework in which we work is probabilistic models. We specifically are innovating upon existing statistical models that use environmental and TC-centric predictors. The statistical models used in this work include the Statistical Hurricane Intensity Prediction System (SHIPS) RI Index (RII) (Kaplan et al. 2010, Kaplan et al. 2015; Wea. Forecasting) and the logistic regression and Bayesian models of Rozoff and Kossin (2011; Wea. Forecasting) and Rozoff et al. (2015; Wea. Forecasting). The objectives of this project are to update the three statistical models to include a new class of predictors derived from satellite passive microwave imagery (MI) evincing aspects of storm structure relevant to RI, using a comprehensive dataset of MI that includes all available relevant sensors, and using these to develop a more skillful consensus model that can be tested and deployed in real-time operations. -
Downloaded 10/03/21 04:03 AM UTC 1672 JOURNAL of APPLIED METEOROLOGY and CLIMATOLOGY VOLUME 59
OCTOBER 2020 M C N E E L Y E T A L . 1671 Unlocking GOES: A Statistical Framework for Quantifying the Evolution of Convective Structure in Tropical Cyclones TREY MCNEELY AND ANN B. LEE Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, Pennsylvania KIMBERLY M. WOOD Department of Geosciences, Mississippi State University, Mississippi State, Mississippi DORIT HAMMERLING Department of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado (Manuscript received 2 December 2019, in final form 31 July 2020) ABSTRACT: Tropical cyclones (TCs) rank among the most costly natural disasters in the United States, and accurate forecasts of track and intensity are critical for emergency response. Intensity guidance has improved steadily but slowly, as processes that drive intensity change are not fully understood. Because most TCs develop far from land-based observing networks, geostationary satellite imagery is critical to monitor these storms. However, these complex data can be chal- lenging to analyze in real time, and off-the-shelf machine-learning algorithms have limited applicability on this front be- cause of their ‘‘black box’’ structure. This study presents analytic tools that quantify convective structure patterns in infrared satellite imagery for overocean TCs, yielding lower-dimensional but rich representations that support analysis and visu- alization of how these patterns evolve during rapid intensity change. The proposed feature suite targets the global orga- nization, radial structure, and bulk morphology (ORB) of TCs. By combining ORB and empirical orthogonal functions, we arrive at an interpretable and rich representation of convective structure patterns that serve as inputs to machine-learning methods. -
Brandon Valley School District District Learning Plan April 27-May 1, 2020
Brandon Valley School District District Learning Plan April 27-May 1, 2020 Grade 6 Science Brandon Valley School District Distance Learning Plan LESSON/UNIT: Natural Disasters SUBJECT/GRADE: Science/6th DATES: April 27- May 1 What do students need Monday (4/27): to do? ● Read Newsela article, What is a Hurricane? and ANSWER DOCUMENT Tuesday (4/28): Link to BV instructional ● Write a response on the ANSWER DOCUMENT about the Newsela article, What is a video for week of April Hurricane? 27 - May 1, 2020 Wednesday (4/29): ● Read the HURRICANE MITIGATION ARTICLE Thursday (4/30) & Friday (5/1) ● Complete the HURRICANE SCENARIO on the ANSWER DOCUMENT What do students need 1. Submit your Answer Document to bring back to school? Choose one way to submit from the list below ● Complete answer document by paper and pencil and submit to BVIS ● Complete answer document electronically through GOOGLE CLASSROOM What standards do the MS-ESS2-4 Develop a model to describe the cycling of water through Earth’s systems driven lessons cover? by energy from the sun and the force of gravity. MS-ESS2-5 Collect data to provide evidence for how the motions and complex interactions of air masses results in changes in weather conditions MS-ESS2-6 Develop and use a model to describe how unequal heating and rotation of the Earth cause patterns of atmospheric and oceanic circulation that determine regional climates. MS-ESS3-2 Analyze and interpret data on natural hazards to forecast future catastrophic events and inform the development of technologies to mitigate their effects MS-ESS3-3 Apply scientific principles to design a method for monitoring and minimizing a human impact on the environment What materials do Need: students need? What 1. -
Hurricane Sea Surface Inflow Angle and an Observation-Based
NOVEMBER 2012 Z H A N G A N D U H L H O R N 3587 Hurricane Sea Surface Inflow Angle and an Observation-Based Parametric Model JUN A. ZHANG Rosenstiel School of Marine and Atmospheric Science, University of Miami, and NOAA/AOML/Hurricane Research Division, Miami, Florida ERIC W. UHLHORN NOAA/AOML/Hurricane Research Division, Miami, Florida (Manuscript received 22 November 2011, in final form 2 May 2012) ABSTRACT This study presents an analysis of near-surface (10 m) inflow angles using wind vector data from over 1600 quality-controlled global positioning system dropwindsondes deployed by aircraft on 187 flights into 18 hurricanes. The mean inflow angle in hurricanes is found to be 222.6862.28 (95% confidence). Composite analysis results indicate little dependence of storm-relative axisymmetric inflow angle on local surface wind speed, and a weak but statistically significant dependence on the radial distance from the storm center. A small, but statistically significant dependence of the axisymmetric inflow angle on storm intensity is also found, especially well outside the eyewall. By compositing observations according to radial and azimuthal location relative to storm motion direction, significant inflow angle asymmetries are found to depend on storm motion speed, although a large amount of unexplained variability remains. Generally, the largest storm- 2 relative inflow angles (,2508) are found in the fastest-moving storms (.8ms 1) at large radii (.8 times the radius of maximum wind) in the right-front storm quadrant, while the smallest inflow angles (.2108) are found in the fastest-moving storms in the left-rear quadrant. -
Hurricane Harvey Evacuation Behavior Survey Outcomes and Findings
Coastal Bend Hurricane Evacuation Study: Hurricane Harvey Evacuation Behavior Survey Outcomes and Findings Prepared by Texas A&M Hazard Reduction & Recovery Center University of Washington Institute for Hazard Mitigation Planning and Research and Texas A&M Transportation Institute May 2020 Coastal Bend Hurricane Evacuation Study: Hurricane Harvey Evacuation Behavior Survey Outcomes and Findings Prepared by: Texas A&M Hazard Reduction & Recovery Center (HRRC) University of Washington (UW) Institute for Hazard Mitigation Planning and Research and Texas A&M Transportation Institute (TTI) Dr. David H. Bierling, TTI & HRRC Dr. Michael K. Lindell, UW Dr. Walter Gillis Peacock, HRRC Alexander Abuabara, HRRC Ryke A. Moore, HRRC Dr. Douglas F. Wunneburger, HRRC James A. (Andy) Mullins III, TTI Darrell W. Borchardt, PE, TTI May 2020 CONTENTS LIST OF FIGURES ........................................................................................................................... iv LIST OF TABLES ............................................................................................................................. iv INTRODUCTION .............................................................................................................................. 1 BACKGROUND ................................................................................................................................ 1 SURVEY OVERVIEW ...................................................................................................................... 2 Survey Topics