The Impact of Dry Air on the Location of Tornado Outbreaks Associated with Landfalling Tropical Cyclones in the Atlantic Basin THESIS Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By Christian David Feliciano-Camacho Graduate Program in Atmospheric Sciences The Ohio State University 2016 Master's Examination Committee: Jay S. Hobgood, “Advisor” Jialin Lin Copyrighted by Christian David Feliciano-Camacho 2016 Abstract Tropical cyclones that form in the Atlantic Basin are responsible for causing major disruptions across a wide range of industries from government policy to transportation and tourism. With the continuous growth of coastal cities continuing, there has been an increasing demand for the scientific community to accurately predict the tracks and intensities of tropical cyclones in order to mitigate disruptions and damages. Although the scientific community has made tremendous advances in forecasting the tracks of tropical cyclones, predicting intensity has proven to be incredibly challenging. What has proved to be equally as difficult is predicting tropical cyclones that are capable of producing tornado outbreaks. Tornadoes that form as a result of tropical cyclones represent a small percentage of total tornado reports and they are often weaker compared to their supercell counterparts from mid latitude systems. Even though these tornadoes are not as common or as severe as supercell tornadoes that occur over the Great Plains, they are a serious threat to life and property. Recently it has been shown that dry air may be used as an indicator to pinpoint the location of tornado outbreaks which could give forecasters more lead time in alerting the public. Dry air can increase convective available potential energy (CAPE) which can lead to stronger updrafts, or it can lead to skies remaining clear so that solar radiation can heat the surface, eroding away any convective inhibition. All tropical cyclones that have made landfall between 2000 and 2014, regardless of their intensity, that produced at least six tornadoes within a 24 hour ii period before or after landfall were analyzed to determine any distinguishable patterns between dry air intrusions and the location of the tornado outbreaks. Dry air intrusions were easily visible by locating steep gradients in relative humidity. Images of relative humidity were created in Matlab using the European Centre for Medium-Range Weather Forecasts ERA-Interim reanalysis data for 700, 500, 400, and 300 hPa. Atmospheric soundings were used to analyze and verify if the observed conditions match what is being displayed by the reanalysis data. Finally, simple calculations were performed as well as an analysis on the location of the relative humidity gradients in order to separate each tropical cyclone into various groupings and to discover any noteworthy patterns or trends. iii Vita June 2010 .......................................................Framingham High School 2014................................................................B.S. Atmospheric Science, State University of New York at Albany 2014 to present ..............................................Graduate Teaching Associate, Department of Geography, The Ohio State University Fields of Study Major Field: Atmospheric Sciences iv Table of Contents Abstract ............................................................................................................................... ii Vita .................................................................................................................................... iiv List of Tables ..................................................................................................................... vi List of Figures ................................................................................................................... vii Chapter 1: Introduction ....................................................................................................... 1 Chapter 2: Methodology ................................................................................................... 10 Chapter 3: Results ............................................................................................................. 13 Chapter 4: Tornado Statistics .......................................................................................... 246 Chapter 5: Results & Discussion .................................................................................... 257 References ....................................................................................................................... 266 v List of Tables Table 1. Comparison of average LCL height and dewpoint depression (8C) at various levels in storms with midlevel dry intrusions that produced outbreaks (qualifying), storms without midlevel dry intrusions that produced outbreaks (nonqualifying), and storms with midlevel dry intrusions that failed to produce outbreaks (null). ......................................... 9 Table 2. Tropical cyclones associated with each group based on total number of tornadoes located under a RH gradient. .......................................................................... 255 Table 3. Tornado statistics calculated for each grouping ............................................... 256 Table 4. Examined tropical cyclones with an “X” denoting which level an RH gradient was found over at least one tornado outbreak ………………………………………….264 Table 5. Characterized location of the RH gradients associated with each tropical cyclone………………………………………………………………………………….265 vi List of Figures Figure 1. Position and track of Tropical Storm Alberto 10-14 June, 2006 created by NOAA and NHC. Image taken from National Hurricane Center tropical cyclone report. ................................................................................................................................ 18 Figure 2. Relative humidity for 300, 400, 500, and 700 hPa for 1200 UTC on 12 June. Images created using the European Centre for Medium-Range Weather Forecasts ERA- Interim reanalysis data within Matlab. Warmer colors indicate dry air while cooler colors indicate moist air. Black star indicates the location of the tropical cyclone at the current time. Dots represent the location of the various tornadoes that spawned at that time. ..... 19 Figure 3. Relative humidity for 300, 400, 500, and 700 hPa for 0600 UTC on 13 June. Images created using the European Centre for Medium-Range Weather Forecasts ERA- Interim reanalysis data within Matlab. Warmer colors indicate dry air while cooler colors indicate moist air. Black star indicates the location of the tropical cyclone at the current time. Dots represent the location of the various tornadoes that spawned at that time. ..... 20 Figure 4. Relative humidity for 300, 400, 500, and 700 hPa for 1200 UTC on 13 June. Images created using the European Centre for Medium-Range Weather Forecasts ERA- Interim reanalysis data within Matlab. Warmer colors indicate dry air while cooler colors indicate moist air. Black star indicates the location of the tropical cyclone at the current time. Dots represent the location of the various tornadoes that spawned at that time. ..... 21 vii Figure 5. Atmospheric profile sounding for Jacksonville, Florida taken at 0000 UTC on June 13. Sounding taken from the University of Wyoming Department of Atmospheric Science sounding page ...................................................................................................... 22 Figure 6. Atmospheric profile sounding for Jacksonville, Florida taken at 1200 UTC on June 13. Sounding was taken from the University of Wyoming Department of Atmospheric Science sounding page. ............................................................................... 23 Figure 7. Relative humidity for 300, 400, 500, and 700 hPa for 1800 UTC on 13 June. Images created using the European Centre for Medium-Range Weather Forecasts ERA- Interim reanalysis data within Matlab. Warmer colors indicate dry air while cooler colors indicate moist air. Black star indicates the location of the tropical cyclone at the current time. Dots represent the location of the various tornadoes that spawned at that time ...... 24 Figure 8. Atmospheric profile sounding for Charleston, South Carolina taken at 1200 UTC on June 13. Sounding was taken from the University of Wyoming Department of Atmospheric Science sounding page ................................................................................ 25 Figure 9. Best track positions for Tropical Storm Allison, 5-17 June 2001. Image taken from NCH tropical cyclone report. ................................................................................... 29 Figure 10. Relative humidity for 300, 400, 500, and 700 hPa for 0600 UTC on 11 June. Images created using the European Centre for Medium-Range Weather Forecasts ERA- Interim reanalysis data within Matlab. Warmer colors indicate dry air while cooler colors indicate moist air. Black star indicates the location of the tropical cyclone at the current time. Dots represent the location of the various tornadoes that spawned at that time. ..... 30 viii Figure 11. Relative humidity for 300, 400, 500, and 700 hPa for 1200 UTC on 11 June. Images created using the European Centre for Medium-Range Weather Forecasts ERA- Interim reanalysis data within Matlab. Warmer colors indicate dry air while cooler colors indicate moist air. Black star indicates the location