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Florida State University Libraries Florida State University Libraries Electronic Theses, Treatises and Dissertations The Graduate School 2019 A Climatology of U.S. Tropical Cyclone Rainfall, Its Use in a Statistical Forecasting Technique and an Analysis of Global Forecast System Tropical Cyclone Rainfall FTriostarne J. cHallst Environments Follow this and additional works at the DigiNole: FSU's Digital Repository. For more information, please contact [email protected] FLORIDA STATE UNIVERSITY COLLEGE OF ARTS & SCIENCES A CLIMATOLOGY OF U.S. TROPICAL CYCLONE RAINFALL, ITS USE IN A STATISTICAL FORECASTING TECHNIQUE AND AN ANALYSIS OF GLOBAL FORECAST SYSTEM TROPICAL CYCLONE RAINFALL FORECAST ENVIRONMENTS By TRISTAN HALL A Dissertation submitted to the Department of Earth, Ocean, and Atmospheric Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy 2019 Copyright c 2019 Tristan Hall. All Rights Reserved. Tristan Hall defended this dissertation on July 9, 2019. The members of the supervisory committee were: Henry E. Fuelberg Professor Directing Dissertation David Van Winkle University Representative Robert E. Hart Committee Member Vasubandhu Misra Committee Member Philip Sura Committee Member The Graduate School has verified and approved the above-named committee members, and certifies that the dissertation has been approved in accordance with university requirements. ii To Catherine and Ainsley. iii ACKNOWLEDGMENTS This dissertation could not have been completed without the help and guidance of Dr. Henry Fuelberg. He is a craftsman of words and logical thought. Additionally, this research could not have been completed without the help of Dr. Bob Hart. His knowledge of tropical cyclones is unmatched. I thank them both immensely for their acceptance of me to pursue my Ph.D. I thank my additional committee members, Drs. Vasu Misra and Philip Sura, for taking the time to review this work and ensure its standards match those of what is expected from a Florida State Meteorologist. Thank you to Dr. Van Winkle for agreeing to be a University Representative. This work originally began as a NOAA CSTAR Grant (NA13NWS4680005). I am grateful for the support NOAA provided to complete this work. Thank you to my friends and colleagues past and present at Florida State University, especially Matthew DelCiampo, Heather Paudler, Max Marchand, Antonio Riggi, Dan Halperin, and \Steve Holt!." These stand-up individuals were a joy to be around and provided invaluable feedback on any topic. I would also like to thank the various communities I interacted with while at Florida State: COGS members, Hart Lab members, Fuelberg Lab members, and Musicology students. Thank you for the good times and challenging discussions. A special thank you goes to Dr. Peter Soul´ewho gave daily weather briefings to his classes while I was a geography student at Appalachian State University. Without these briefings and discussions, I would not have pursued a graduate education in meteorology. I'd like to thank my parents, Pattie and David, for raising such a stand-up individual, and my parents-in-law, Geoff and Mary Ann for the support during this process. Thank you to my brothers, Nicholas and A.J., and my sisters-in-law, Rachel and Kaili, for the food, support, and childcare services they provided during the last days of this. Finally, I never knew I could have such love in my heart for an individual until my daughter, Ainsley Clare Hall, was born on 22 March 2018 while I was writing this dissertation. I'm sorry for the time I had to spend away from you while I finished this work. Additionally, to her mother and my partner, Catherine: you are an amazing mother and a wonderful support system. Thank you for picking me up when I needed it and supporting me through this. iv TABLE OF CONTENTS List of Tables . vii List of Figures . ix Abstract . xv 1 Introduction and Motivation 1 2 Background 5 2.1 Rainfall characteristics . .5 2.2 Quantitative precipitation forecast models . .8 2.2.1 Legacy models . .8 2.2.2 The Rainfall-Climatology and Persistence Model . 13 2.2.3 The Areal Tropical Rainfall Potential Technique . 14 2.2.4 The Parametric Hurricane Rainfall Model . 14 2.2.5 The Ensemble Tropical Rainfall Potential . 15 2.2.6 Numerical weather prediction models . 16 3 Data & Methodology 19 3.1 Data . 19 3.1.1 The Global Forecast System . 21 3.1.2 Stage IV data . 24 3.2 Methodology . 25 3.2.1 Development of the Stage IV rainfall statistical dataset . 25 3.2.2 Development of the statistical rainfall forecasts . 28 3.3 Verification metrics and determination of forecast skill . 31 3.3.1 GFS environmental conditions . 33 4 Results 35 4.1 Regional and U.S. Stage IV TC rainfall composite analysis . 35 4.1.1 U.S. rainfall composites . 35 4.1.2 Selected regional composites . 44 4.1.3 Stage IV rainfall summary . 50 4.2 Example forecasts . 52 4.2.1 Stage IV statistical model forecast: Skillful . 53 4.2.2 Stage IV statistical model forecast: Not skillful . 61 4.3 Model verification . 67 4.3.1 Storm-by-Storm approach . 68 4.3.2 Forecast-by-Forecast approach . 72 v 5 Analysis of Errors and Possible Improvements to the Statistical Model 77 5.1 Theoretical maximum skill of the statistical model . 77 5.2 Radial distributions . 80 5.3 Environmental analysis . 85 5.3.1 Mean sea level pressure and 500 hPa composites . 86 5.3.2 Baroclinic processes . 95 5.3.3 Eddy flux convergence . 98 5.3.4 Upper-level winds . 101 5.3.5 Environmental summary . 104 6 Summary and Conclusions 107 References . 118 Biographical Sketch . 128 vi LIST OF TABLES 1 Summary of the models presented in Section 2.2 and their individual strengths and weaknesses. 18 2 Total number of storms and 6-h locations from HURDAT2, i.e., Best Track locations (BTK) for earth-, motion-, and shear-relative coordinate systems. Numbers of six- hour locations are in brackets. 21 3 Global Forecast System (GFS) resolution updates and grid spacing of output/working files for years used in this study. The developmental dataset is 2004 { 2012. The test years are 2013 { 2016. The \Dates Covered" column indicates the period available for thatyear............................................ 22 4 The number of 6 h Best Track locations and landfalls for the regions shown in Fig. 2. The number of landfalls refers to the number landfalls within the continental United States landfalls, not any landfalls on islands beyond the coastline that are included in the Best Track dataset. 27 5 TC intensity categories. Counts of storms for each category are in Table 6. For the Strong Hurricane category (HU1), 53% were Cat 2, 16% Cat 3, 26% Cat 4, and 5% Cat5.............................................. 28 6 Intensity and shear categories for each region's rainfall composites after combination (e.g., from Table 5) to produce robust datasets. Each categories' number of 6-hourly time steps and unique storms (shown in parentheses) are given. 29 7 The nine methodologies for the Stage IV statistical rainfall model, plus R-CLIPER. Each method (except R-CLIPER) uses either the full composite or the regional com- posites (resulting in 18 forecasts). 31 8 Fractions Skill Score (FSS) categories, mean FSS for each category as well as the 95% confidence interval, number of 72-h forecasts, and counts of unique storms within each category. 34 9 Forecast and Best Track storm intensities [kt], regions (number identifier and name), shear [m s−1], and Saffir-Simpson categories for the skillful and not-skillful example forecasts discussed in Sections 4.2.1 and 4.2.2. Colors indicate Saffir-Simpson category (Blue: TS; violet: TD) for forecast intensity and correspond to colors shown in Figures. 54 10 Fractions Skill Score (FSS) for all thresholds of the regional, shear-relative method using the shear magnitude method (REG-SS; Table 7), R-CLIPER (RCP), and the Global Forecast System (GFS) for the skillful 72-h rainfall forecast of TS Ana (2015; Fig. 17) beginning at 1200 UTC 8 May 2015 and the less-skilled forecast of TS Andrea vii (2013; Fig. 22) beginning at 1200 UTC 6 June 2013. The 95% confidence interval for all thresholds is shown in the Average field. 55 viii LIST OF FIGURES 1 Statistics of storm-related fatalities. Recreated from Rappaport (2000, 2014). .2 2 The seven geographical regions. TC landfall locations are green dots for 2004 { 2012. Other 6-h locations within 300 km (grey dashed buffer) of the U.S. coast are shown for comparison (grey dots). 20 3 Example of masking technique used to limit Stage IV observations to 150 km from a coastal radar. Example shown is for TC Fay (2008). The full Stage IV dataset is shown in (a), a zoomed version is in (b), and the final masked data is in (c). 26 4 Full domain Stage IV rain rate composites [in. 6 h−1] for years 2004 { 2012 for earth- relative (a), storm motion-relative (b), and shear-relative (c) coordinates with range rings shown every 200 km starting at 100 km. The latitude/longitude density (counts per 1 × 1 deg grid box) is shown in the bottom right panel (d). 36 5 Fractional histogram (defined as the count within a bin divided by the total count of the distribution) of intensity by minimum MSLP [hPa] (line) and storm intensity [kt] (bars) for all 6-hourly Best Track storm locations within 300 km of the U.S. coastline between 2004 { 2012. 37 6 Fractional histogram (as defined in Fig. 5) of shear magnitude [m s−1] and heading [degrees from North]. The line shows shear magnitude while the bars show shear heading.
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