A Diagnostic Study of the Intensity of Three Tropical Cyclones in the Australian Region
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Wave Data Recording Program
Wave data recording program Weipa Region 1978–2004 Coastal Sciences data report No. W2004.5 ISSN 1449–7611 Abstract This report provides summaries of primary analysis of wave data recorded in water depths of approximately 5.2m relative to lowest astronomical tide, 10km west of Evans Landing in Albatross Bay, west of Weipa. Data was recorded using a Datawell Waverider buoy, and covers the periods from 22 December, 1978 to 31 January, 2004. The data was divided into seasonal groupings for analysis. No estimations of wave direction data have been provided. This report has been prepared by the EPA’s Coastal Sciences Unit, Environmental Sciences Division. The EPA acknowledges the following team members who contributed their time and effort to the preparation of this report: John Mohoupt; Vince Cunningham; Gary Hart; Jeff Shortell; Daniel Conwell; Colin Newport; Darren Hanis; Martin Hansen; Jim Waldron and Emily Christoffels. Wave data recording program Weipa Region 1978–2004 Disclaimer While reasonable care and attention have been exercised in the collection, processing and compilation of the wave data included in this report, the Coastal Sciences Unit does not guarantee the accuracy and reliability of this information in any way. The Environmental Protection Agency accepts no responsibility for the use of this information in any way. Environmental Protection Agency PO Box 15155 CITY EAST QLD 4002. Copyright Copyright © Queensland Government 2004. Copyright protects this publication. Apart from any fair dealing for the purpose of study, research, criticism or review as permitted under the Copyright Act, no part of this report can be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise without having prior written permission. -
Estimates of Tropical Cyclone Geometry Parameters Based on Best Track Data
https://doi.org/10.5194/nhess-2019-119 Preprint. Discussion started: 27 May 2019 c Author(s) 2019. CC BY 4.0 License. Estimates of tropical cyclone geometry parameters based on best track data Kees Nederhoff1, Alessio Giardino1, Maarten van Ormondt1, Deepak Vatvani1 1Deltares, Marine and Coastal Systems, Boussinesqweg 1, 2629 HV Delft, The Netherlands 5 Correspondence to: Kees Nederhoff ([email protected]) Abstract. Parametric wind profiles are commonly applied in a number of engineering applications for the generation of tropical cyclone (TC) wind and pressure fields. Nevertheless, existing formulations for computing wind fields often lack the required accuracy when the TC geometry is not known. This may affect the accuracy of the computed impacts generated by these winds. In this paper, empirical stochastic relationships are derived to describe two important parameters affecting the 10 TC geometry: radius of maximum winds (RMW) and the radius of gale force winds (∆AR35). These relationships are formulated using best track data (BTD) for all seven ocean basins (Atlantic, S/NW/NE Pacific, N/SW/SE Indian Oceans). This makes it possible to a) estimate RMW and ∆AR35 when these properties are not known and b) generate improved parametric wind fields for all oceanic basins. Validation results show how the proposed relationships allow the TC geometry to be represented with higher accuracy than when using relationships available from literature. Outer wind speeds can be 15 well reproduced by the commonly used Holland wind profile when calibrated using information either from best-track-data or from the proposed relationships. The scripts to compute the TC geometry and the outer wind speed are freely available via the following URL. -
Rapid Intensification of a Sheared Tropical Storm
OCTOBER 2010 M O L I N A R I A N D V O L L A R O 3869 Rapid Intensification of a Sheared Tropical Storm JOHN MOLINARI AND DAVID VOLLARO Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York (Manuscript received 10 February 2010, in final form 28 April 2010) ABSTRACT A weak tropical storm (Gabrielle in 2001) experienced a 22-hPa pressure fall in less than 3 h in the presence of 13 m s21 ambient vertical wind shear. A convective cell developed downshear left of the center and moved cyclonically and inward to the 17-km radius during the period of rapid intensification. This cell had one of the most intense 85-GHz scattering signatures ever observed by the Tropical Rainfall Measuring Mission (TRMM). The cell developed at the downwind end of a band in the storm core. Maximum vorticity in the cell exceeded 2.5 3 1022 s21. The cell structure broadly resembled that of a vortical hot tower rather than a supercell. At the time of minimum central pressure, the storm consisted of a strong vortex adjacent to the cell with a radius of maximum winds of about 10 km that exhibited almost no tilt in the vertical. This was surrounded by a broader vortex that tilted approximately left of the ambient shear vector, in a similar direction as the broad precipitation shield. This structure is consistent with the recent results of Riemer et al. The rapid deepening of the storm is attributed to the cell growth within a region of high efficiency of latent heating following the theories of Nolan and Vigh and Schubert. -
Rapid Intensification of DOI:10.1175/BAMS-D-16-0134.1 Hurricanes Is Particularly Problematic
WILL GLOBAL WARMING MAKE HURRICANE FORECASTING MORE DIFFICULT? KERRY EMANUEL As the climate continues to warm, hurricanes may intensify more rapidly just before striking land, making hurricane forecasting more difficult. ince 1971, tropical cyclones have claimed about cyclone damage, rising on average 6% yr–1 in inflation- 470,000 lives, or roughly 10,000 lives per year, and adjusted U.S. dollars between 1970 and 2015 (CRED S caused 700 billion U.S. dollars in damages globally 2016). Thus, appreciable increases in forecast skill and/ (CRED 2016). Mortality is strongly dominated by a or decreases of vulnerability, for example, through small number of extremely lethal events; for example, better preparedness, building codes, and evacuation just three storms caused more than 56% of the tropical procedures, will be required to avoid increases in cyclone–related deaths in the United States since 1900. cyclone-related casualties. Tropical cyclone mortality and injury have been Unfortunately, there has been little improvement reduced by improved forecasts and preparedness, espe- in tropical cyclone intensity forecasts over the period cially in developed countries (Arguez and Elsner 2001; from 1990 to the present (DeMaria et al. 2014). While Peduzzi et al. 2012), but through much of the world hurricane track forecasts using numerical prediction this has been offset by large changes in coastal popula- models have steadily improved, there has been only tions. For example, Peduzzi et al. (2012) estimate that slow improvement in forecasts of intensity by these the global population exposed to tropical cyclone same models. Reasons for this include stiff resolu- hazards increased by almost threefold between 1970 tion requirements for the numerical simulations of and 2010, and they project this trend to continue for tropical cyclone intensity (Rotunno et al. -
Improvement of Wind Field Hindcasts for Tropical Cyclones
Water Science and Engineering 2016, 9(1): 58e66 HOSTED BY Available online at www.sciencedirect.com Water Science and Engineering journal homepage: http://www.waterjournal.cn Improvement of wind field hindcasts for tropical cyclones Yi Pan a,b, Yong-ping Chen a,b,*, Jiang-xia Li a,b, Xue-lin Ding a,b a State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China b College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China Received 16 August 2015; accepted 10 December 2015 Available online 21 February 2016 Abstract This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the cross-calibrated multi-platform (CCMP) reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data. -
Investigation and Prediction of Hurricane Eyewall
INVESTIGATION AND PREDICTION OF HURRICANE EYEWALL REPLACEMENT CYCLES By Matthew Sitkowski A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Atmospheric and Oceanic Sciences) at the UNIVERSITY OF WISCONSIN-MADISON 2012 Date of final oral examination: 4/9/12 The dissertation is approved by the following members of the Final Oral Committee: James P. Kossin, Affiliate Professor, Atmospheric and Oceanic Sciences Daniel J. Vimont, Professor, Atmospheric and Oceanic Sciences Steven A. Ackerman, Professor, Atmospheric and Oceanic Sciences Jonathan E. Martin, Professor, Atmospheric and Oceanic Sciences Gregory J. Tripoli, Professor, Atmospheric and Oceanic Sciences i Abstract Flight-level aircraft data and microwave imagery are analyzed to investigate hurricane secondary eyewall formation and eyewall replacement cycles (ERCs). This work is motivated to provide forecasters with new guidance for predicting and better understanding the impacts of ERCs. A Bayesian probabilistic model that determines the likelihood of secondary eyewall formation and a subsequent ERC is developed. The model is based on environmental and geostationary satellite features. A climatology of secondary eyewall formation is developed; a 13% chance of secondary eyewall formation exists when a hurricane is located over water, and is also utilized by the model. The model has been installed at the National Hurricane Center and has skill in forecasting secondary eyewall formation out to 48 h. Aircraft reconnaissance data from 24 ERCs are examined to develop a climatology of flight-level structure and intensity changes associated with ERCs. Three phases are identified based on the behavior of the maximum intensity of the hurricane: intensification, weakening and reintensification. -
NWS Unified Surface Analysis Manual
Unified Surface Analysis Manual Weather Prediction Center Ocean Prediction Center National Hurricane Center Honolulu Forecast Office November 21, 2013 Table of Contents Chapter 1: Surface Analysis – Its History at the Analysis Centers…………….3 Chapter 2: Datasets available for creation of the Unified Analysis………...…..5 Chapter 3: The Unified Surface Analysis and related features.……….……….19 Chapter 4: Creation/Merging of the Unified Surface Analysis………….……..24 Chapter 5: Bibliography………………………………………………….…….30 Appendix A: Unified Graphics Legend showing Ocean Center symbols.….…33 2 Chapter 1: Surface Analysis – Its History at the Analysis Centers 1. INTRODUCTION Since 1942, surface analyses produced by several different offices within the U.S. Weather Bureau (USWB) and the National Oceanic and Atmospheric Administration’s (NOAA’s) National Weather Service (NWS) were generally based on the Norwegian Cyclone Model (Bjerknes 1919) over land, and in recent decades, the Shapiro-Keyser Model over the mid-latitudes of the ocean. The graphic below shows a typical evolution according to both models of cyclone development. Conceptual models of cyclone evolution showing lower-tropospheric (e.g., 850-hPa) geopotential height and fronts (top), and lower-tropospheric potential temperature (bottom). (a) Norwegian cyclone model: (I) incipient frontal cyclone, (II) and (III) narrowing warm sector, (IV) occlusion; (b) Shapiro–Keyser cyclone model: (I) incipient frontal cyclone, (II) frontal fracture, (III) frontal T-bone and bent-back front, (IV) frontal T-bone and warm seclusion. Panel (b) is adapted from Shapiro and Keyser (1990) , their FIG. 10.27 ) to enhance the zonal elongation of the cyclone and fronts and to reflect the continued existence of the frontal T-bone in stage IV. -
Climate Early Warning System Feasibility Report: Early Warning Systems and Hazard Prediction
United Nations Environment Programme Climate Early Warning System Feasibility Report: Early Warning Systems and Hazard Prediction March 2012 Dr. Zinta Zommers University of Oxford 1 Table of Contents 1 INTRODUCTION AND PURPOSE ....................................................................................................................... 3 2. METHODOLOGY................................................................................................................................................. 6 3. CURRENT EARLY WARNING SYSTEMS.......................................................................................................... 8 3.1. COMPONENTS OF EWS ...................................................................................................................... 8 3.2. KEY ACTORS IN EWS......................................................................................................................... 9 3.3. EWS BY NATION .............................................................................................................................. 10 3.4. EWS BY HAZARD............................................................................................................................. 15 3.4.1. Drought.......................................................................................................................................... 15 3.4.2. Famine........................................................................................................................................... 20 3.4.3. Fire................................................................................................................................................ -
Dependency of U.S. Hurricane Economic Loss on Maximum Wind Speed And
Dependency of U.S. Hurricane Economic Loss on Maximum Wind Speed and Storm Size Alice R. Zhai La Cañada High School, 4463 Oak Grove Drive, La Canada, CA 91011 Jonathan H. Jiang Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109 Corresponding Email: [email protected] Abstract: Many empirical hurricane economic loss models consider only wind speed and neglect storm size. These models may be inadequate in accurately predicting the losses of super-sized storms, such as Hurricane Sandy in 2012. In this study, we examined the dependencies of normalized U.S. hurricane loss on both wind speed and storm size for 73 tropical cyclones that made landfall in the U.S. from 1988 to 2012. A multi-variate least squares regression is used to construct a hurricane loss model using both wind speed and size as predictors. Using maximum wind speed and size together captures more variance of losses than using wind speed or size alone. It is found that normalized hurricane loss (L) approximately follows a power law relation c a b with maximum wind speed (Vmax) and size (R). Assuming L=10 Vmax R , c being a scaling factor, the coefficients, a and b, generally range between 4-12 and 2-4, respectively. Both a and b tend to increase with stronger wind speed. For large losses, a weighted regression model, with a being 4.28 and b being 2.52, produces a reasonable fitting to the actual losses. Hurricane Sandy’s size was about 3.4 times of the average size of the 73 storms analyzed. -
A Diagnostic Study of the Intensity of Three Tropical Cyclones in the Australian Region
22 MONTHLY WEATHER REVIEW VOLUME 138 A Diagnostic Study of the Intensity of Three Tropical Cyclones in the Australian Region. Part II: An Analytic Method for Determining the Time Variation of the Intensity of a Tropical Cyclone* FRANCE LAJOIE AND KEVIN WALSH School of Earth Sciences, University of Melbourne, Parkville, Australia (Manuscript received 20 November 2008, in final form 14 May 2009) ABSTRACT The observed features discussed in Part I of this paper, regarding the intensification and dissipation of Tropical Cyclone Kathy, have been integrated in a simple mathematical model that can produce a reliable 15– 30-h forecast of (i) the central surface pressure of a tropical cyclone, (ii) the sustained maximum surface wind and gust around the cyclone, (iii) the radial distribution of the sustained mean surface wind along different directions, and (iv) the time variation of the three intensity parameters previously mentioned. For three tropical cyclones in the Australian region that have some reliable ground truth data, the computed central surface pressure, the predicted maximum mean surface wind, and maximum gust were, respectively, within 63 hPa and 62ms21 of the observations. Since the model is only based on the circulation in the boundary layer and on the variation of the cloud structure in and around the cyclone, its accuracy strongly suggests that (i) the maximum wind is partly dependent on the large-scale environmental circulation within the boundary layer and partly on the size of the radius of maximum wind and (ii) that all factors that contribute one way or another to the intensity of a tropical cyclone act together to control the size of the eye radius and the central surface pressure. -
Tropical-Cyclone Forecasting: a Worldwide Summary of Techniques
John L. McBride and Tropical-Cyclone Forecasting: Greg J. Holland Bureau of Meteorology Research Centre, A Worldwide Summary Melbourne 3001, of Techniques and Australia Verification Statistics Abstract basis for discussion at particular sessions planned for the work- shop. Replies to this questionnaire were received from 16 of- Questionnaire replies from forecasters in 16 tropical-cyclone warning fices. These are listed in Table 1, grouped according to their centers are summarized to provide an overview of the current state of ocean basins. Encouraged by the high information content of the science in tropical-cyclone analysis and forecasting. Information is tabulated on the data sources and techniques used, on their role and these responses, the authors sent a second questionnaire on the perceived usefulness, and on the levels of verification and accuracy of analysis and forecasting of cyclone position and motion. Re- cyclone forecasting. plies to this were received from 13 of the listed offices. This paper tabulates and syntheses information provided on the following aspects of tropical-cyclone forecasting: 1) the techniques used; 2) the level of verification; and 3) the level 1. Introduction of accuracy of analyses and forecasts. Separate sections cover forecasting of cyclone formation; analyzing cyclone structure Tropical cyclones are the major severe weather hazard for a and intensity; forecasting structure and intensity; analyzing cy- large "slice" of mankind. The Bangladesh cyclones of 1970 and 1985, Hurricane Camille (USA, 1969) and Cyclone Tracy (Australia, 1974) to name just four, would figure prominently TABLE 1. Forecast offices from which unofficial replies were re- in any list of major natural disasters of this century. -
Learning from Hurricane Hugo: Implications for Public Policy
LEARNING FROM HURRICANE HUGO: IMPLICATIONS FOR PUBLIC POLICY prepared for the FEDERAL INSURANCE ADMINISTRATION FEDERAL EMERGENCY MANAGEMENT AGENCY 500 C Street, S.W. Washington, D.C. 20472 under contract no. EMW-90-G-3304,A001 June 1992 CONTENTS INTRODUCTION ............................... 1.............I PHYSICAL CHARACTERISTICS OF THE STORM . 3 Wind Speeds .3 IMPACTS ON NATURAL SYSTEMS 5 ................................ Biological Systems ....... .................................5 Dunes and Beaches ....... .5............................... Beach Nourishment . .................................7 IMPACTS ON HUMANS AND HUMAN SYSTEMS ............................ 9 Deaths and Injuries ............................ 9 Housing ............................ 9 Utilities ................... 10 Transportation Systems .1................... 10 The Economy ................... 11 Psychological Effects ................... 11 INSURANCE .......................... 13 COASTAL DEVELOPMENT .......................... 14 Setbacks ........................... 15 Coastal Protection Structures .......................... 16 PERFORMANCE OF STRUCTURES ..... .... 18 Effects of Wind and/or Water ...... .... 18 Effects of Water, Waves, or Erosion . .. .18 Effects of Wind .............. .... 19 Foundations .................. .... 21 Slabs ................ .... 22 Piers and Columns ....... .... 22 Pilings............... .... 22 Elevation .................. .... 23 Lower Area Enclosures .... .... 23 Connections ................. ....24 Manufactured Housing .......... .... 24