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Prediction of Intensity Change Subsequent to Concentric Eyewall Events

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Prediction of Intensity Change Subsequent to Concentric Eyewall Events Prediction of Intensity Change Subsequent to Concentric Eyewall Events DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Rachel Grant Mauk Graduate Program in Atmospheric Sciences The Ohio State University 2016 Dissertation Committee: Professor Jay S. Hobgood, Advisor Professor David H. Bromwich Professor Jialin Lin Professor Jeffery C. Rogers Copyrighted by Rachel Grant Mauk 2016 Abstract Concentric eyewall events have been documented numerous times in intense tropical cyclones over the last two decades. During a concentric eyewall event, an outer (secondary) eyewall forms around the inner (primary) eyewall. Improved instrumentation on aircraft and satellites greatly increases the likelihood of detecting an event. Despite the increased ability to detect such events, forecasts of intensity changes during and after these events remain poor. When concentric eyewall events occur near land, accurate intensity change predictions are especially critical to ensure proper emergency preparations and staging of recovery assets. A nineteen-year (1997-2015) database of concentric eyewall events is developed by analyzing microwave satellite imagery, aircraft- and land-based radar, and other published documents. Events are identified in both the North Atlantic and eastern North Pacific basins. TCs are categorized as single (1 event), serial (>= 2 events) and super- serial (>= 3 events). Key findings here include distinct spatial patterns for single and serial Atlantic TCs, a broad seasonal distribution for eastern North Pacific TCs, and apparent ENSO-related variability in both basins. The intensity change subsequent to the concentric eyewall event is calculated from the HURDAT2 database at time points relative to the start and to the end of the event. Intensity change is then categorized as Weaken (≤ -10 kt), Maintain (+/- 5 kt), and ii Strengthen ≥ 10 kt). Environmental conditions in which each event occurred are analyzed based on the SHIPS diagnostic files. Oceanic, dynamic, thermodynamic, and TC status predictors are selected for testing in a multiple discriminant analysis procedure to determine which variables successfully discriminate the intensity change category and the occurrence of additional concentric eyewall events. Intensity models are created for 12 h, 24 h, 36 h, and 48 h after the concentric eyewall event’s end. Leave-one-out cross validation is performed on each set of discriminators to generate classifications, which are then compared to observations. For each model, the top combinations achieve 80- 95% overall accuracy in classifying TCs based on the environmental characteristics, although Maintain systems are frequently misclassified. The third part of this dissertation employs the Weather Research and Forecasting model to further investigate concentric eyewall events. Two serial Atlantic concentric eyewall cases (Katrina 2005 and Wilma 2005) are selected from the original study set, and WRF simulations performed using several model designs. Despite strong evidence from multiple sources that serial concentric eyewalls formed in both hurricanes, the WRF simulations did not produce identifiable concentric eyewall structures for Katrina, and only transient structures for Wilma. Possible reasons for the lack of concentric eyewall formation are discussed, including model resolution, microphysics, and data sources. iii For Eric iv Acknowledgments Funding for this dissertation was provided by Graduate Assistantships in the Department of Geography and the Ohio Colleges of Medicine Government Resource Center, as well as a Graduate Fellowship from the Graduate School of The Ohio State University. I would like to acknowledge my committee: Jeff Rogers, David Bromwich, and Jialin Lin. Their patience and insight as this dissertation evolved over the last three years is much appreciated. Doug McCarty from Nationwide Children’s Hospital provided a much appreciated external perspective on this project at the defense. My advisor, Jay Hobgood, has been a major figure in my life for four OSU degrees. I had no idea when I picked your Basic Meteorology class in spring 2005 for an elective that it would set the path for the following 11 years, and likely the rest of my life. Thank you for the encouragement over the years, both big and small, professional and personal. Persistence, hope, and determination make a PhD. [And a good advisor.] Wes Haines, currently of the Byrd Polar and Climate Prediction Center, built the computer that was used to run WRF. Dr. Mark DeMaria of the National Hurricane Center’s Technology and Science Branch provided additional information about SHIPS. v Numerous family and friends have provided support throughout my graduate program. My mother, Jacqueline Kern (PhD, University of Arizona): thank you for encouraging me when I decided I wanted a doctorate in atmospheric sciences at age 10, and for making sure I kept at it. You knew the value of persistence. My office mates for the past year: Calvin, Chris, Sam, and Zoe. Thanks for the end-of-week donut runs and defense survival advice. My meteorology students this past year: we were thrown together rather suddenly, but you were awesome at rolling with problems, especially when technology (new or old) got in the way. Aaron Wilson (also of Byrd) provided WRF advice and surviving-the-dissertation moral support. Finally, my husband Eric: computer guru, cat-entertainer, and tireless champion. Thank you for sticking this out with me. vi Vita June 2004 .......................................................Mentor High School 2008................................................................B.S. Geography, The Ohio State University 2008................................................................B.S. Physics, The Ohio State University 2010................................................................M.S. Atmospheric Sciences, The Ohio State University 2010 to present ..............................................Graduate Researcher, Atmospheric Sciences Program, The Ohio State University Publications Mauk, R. G., and J. S. Hobgood, 2012: Tropical cyclone formation in environments of cool SST and high wind shear. Wea. Forecasting, 27, 1433-1448. Fields of Study Major Field: Atmospheric Sciences vii Table of Contents Abstract ............................................................................................................................... ii Acknowledgments............................................................................................................... v Vita .................................................................................................................................... vii List of Tables ................................................................................................................... xiv List of Figures .................................................................................................................. xix Chapter 1: Introduction ....................................................................................................... 1 Chapter 2: Literature Review .............................................................................................. 7 2.1 Tropical Cyclone Structure ....................................................................................... 7 2.2 Tropical Cyclone Intensity and Intensity Change ................................................... 11 2.3 ENSO and TC Activity ........................................................................................... 16 2.4 Concentric Eyewall Events ..................................................................................... 18 2.4.1 Identification and Structure of Concentric Eyewalls ........................................ 19 2.4.2 Climatology of Concentric Eyewalls ................................................................ 25 2.4.3 Theories of Concentric Eyewall Formation...................................................... 27 2.4.4 Eyewall Replacement Cycles ........................................................................... 29 viii 2.4.5 Prediction of Concentric Eyewall Events ......................................................... 32 Chapter 3: Data and Concentric Eyewall Identification ................................................... 36 3.1 Data Sources ............................................................................................................ 36 3.1.1 HURDAT2........................................................................................................ 36 3.1.2 Tropical Cyclone Reports and Monthly Weather Review Annual Summaries 37 3.1.3 In-Situ Observations: Aircraft Vortex Data Messages ..................................... 37 3.1.4 Aircraft-Based Radar, Including SFMR ........................................................... 38 3.1.5 Ground-Based Radar ........................................................................................ 39 3.1.6 Geostationary Satellite Imagery and the Dvorak Technique ............................ 40 3.1.7 Polar-Orbiting Satellites and Microwave Imagery ........................................... 43 3.2 Environmental Data: SHIPS.................................................................................... 44 3.3 Methodology ........................................................................................................... 46 3.3.1 Concentric Eyewall Identification Criteria ......................................................
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