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A Statistical Model to Forecast Short-Term Atlantic Hurricane Intensity

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A Statistical Model to Forecast Short-Term Atlantic Hurricane Intensity A STATISTICAL MODEL TO FORECAST SHORT-TERM ATLANTIC HURRICANE INTENSITY DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Kevin T. Law, M.S. ***** The Ohio State University 2006 Dissertation Committee: Approved by Professor Jay S. Hobgood, Adviser Professor Jeffrey C. Rogers ___________________________________ Professor Lawrence Krissek Adviser Graduate Program in Atmospheric Science ABSTRACT The accuracy of hurricane intensity forecasts has lagged the accuracy of hurricane track forecasts thereby creating a need for improvement. Many models struggle capturing the rapid intensification period and identifying when it will occur which causes a large amount of error in the intensity forecasts. The method described in this paper uses a discriminant function analysis (DFA) to help identify how intense the tropical cyclone will become and also how close it is to the rapid intensification period. Identifying the proximity to the rapid intensification period is a key factor in improving the intensity forecasts. Based upon the intensity and its proximity to its rapid intensification period, as selected by the DFA, an appropriate regression model is applied to forecast the 24-hour and 6-hour pressure reduction and wind speed increase. Other statistical intensity models apply the same regression model throughout the entire lifecycle of the tropical cyclone. This model relies on the premise that factors which cause intensification affect the tropical cyclone differently throughout its life cycle. Therefore, by using the DFA, different stages in its life cycle are identified, which allows the regression model to use the most significant variables at the particular stage. They are shown to improve the intensity forecasts at the stages leading up to and during the rapid intensification, which ii happen to be the most difficult stages to predict. The forecasts were validated with 13 independent case studies and compared with the official National Hurricane Center (NHC) forecasts. iii ACKNOWLEDGMENTS I wish to thank my adviser, Jay Hobgood, for always having the time to answer questions and correct errors. In addition, I would like to thank Gustavo Goni for personally making the AOML Hurricane Heat Potential data readily available. Both of whom without their support, this dissertation would not have been possible. iv VITA July 9, 1976………………… ……... Born – Parkersburg, West Virginia 1998………………………………... B.A. Geography, West Virginia University 1999-present……………………… Graduate Teaching Associate, The Ohio State University 2001………………………………... M.S. Atmospheric Science, The Ohio State University FIELDS OF STUDY Major Field: Atmospheric Science v TABLE OF CONTENTS Page Abstract.............................................................................................................................. iii Acknowledgments................................................................................................................v Vita..................................................................................................................................... vi List of Tables .......................................................................................................................x List of Figures.................................................................................................................. xiii Chapters: 1. Introduction .............................................................................................................1 2. Literature Review ....................................................................................................6 2.1 Environmental Influences on Tropical Cyclone Intensity Change ...................6 2.2 Potential Rapid Intensification Predictors ........................................................7 2.3 Other Factors Affecting Rapid Intensification ..................................................8 2.4 Wind Shear Processes .....................................................................................10 2.5 Vertical Wind Shear Numerical Simulation Studies ......................................13 2.6 Vertical Wind Shear Observational Studies ...................................................15 2.7 Vertical Wind Shear Individual Case Studies .................................................16 2.8 Thermodynamic Processes ..............................................................................20 2.9 Statistical Modeling of Tropical Cyclone Intensification ...............................25 3. Scientific Objective and Methodology .................................................................28 3.1 Introduction .....................................................................................................28 3.2 Tropical Cyclone Selection and (HURDAT) Data .........................................29 3.3 NCEP/NCAR Reanalysis Data .......................................................................32 3.4 AOML Tropical Cyclone Heat Potential ........................................................34 3.5 Variables and Data Used in the Study ............................................................37 3.5.1 NHC HURDAT data ........................................................................37 3.5.2 Vertical Wind Shear and Relative Humidity ....................................39 3.5.3 Holland MPI......................................................................................41 3.5.4 Attained MPI.....................................................................................43 3.5.5. Tropical Cyclone Heat Potential......................................................44 3.6 Discriminant Function Analysis ......................................................................45 3.7 Multiple Regression.........................................................................................49 vi 3.8 Testing the Models with an Independent Dataset............................................51 4. Results and Discussion..........................................................................................55 4.1 Discriminant Function Analysis Classification ...............................................55 4.2 Multiple Regression Equations........................................................................59 4.3 Evaluation of the Models with an Independent Dataset ..................................67 4.3.1 Hurricane Alex..................................................................................68 4.3.2 Hurricane Charley.............................................................................76 4.3.3 Hurricane Danielle............................................................................84 4.3.4 Hurricane Frances .............................................................................92 4.3.5 Hurricane Gaston ............................................................................100 4.3.6 Hurricane Ivan ................................................................................109 4.3.7 Hurricane Jeanne.............................................................................118 4.3.8 Hurricane Karl ................................................................................126 4.3.9 Hurricane Lisa.................................................................................134 4.3.10 Hurricane Dennis ..........................................................................142 4.3.11 Hurricane Emily............................................................................150 4.3.12 Hurricane Irene .............................................................................158 4.3.13 Hurricane Katrina..........................................................................166 5. Conclusion ..........................................................................................................176 Bibliography ....................................................................................................................187 Appendix A: Tropical Cyclone Tracks............................................................................193 vii LIST OF TABLES Table Page 1.1 Saffir-Simpson Scale...............................................................................................3 3.1 Tropical cyclone selection list from 1988-2003. Storms that are in boldface are considered “major”............................................................................31 3.2 List of variables used in the study..........................................................................40 3.3 Number of cases in each category for the multiple regression analysis ................52 3.4 List of Hurricanes in the Independent Dataset.......................................................53 4.1 Classification results for step one of the discriminant analysis .............................56 4.2 Step 2 of the DFA for major hurricanes.................................................................58 4.3 Step 2 of the DFA for minor hurricanes ................................................................58 4.4 Future 24-hour pressure drop regression equations...............................................63 4.5 Future 24-hour wind speed increase regression equations ....................................64 4.6 Future 6-hour pressure drop regression equations.................................................65 4.7 Future 6-hour wind speed increase regression equations ......................................66
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