THE INFLUENCE OF ATMOSPHERIC RIVERS ON EXTREME PRECIPITATION IN THE CONTINENTAL UNITED STATES By Christian Landry B.S., Texas A&M University, 2018 A Thesis Submitted in Partial Fulfillment of the Requirements for the Master of Science Degree School of Earth Systems and Sustainability in the Graduate School Southern Illinois University Carbondale December 2020 THESIS APPROVAL THE INFLUENCE OF ATMOSPHERIC RIVERS ON EXTREME PRECIPITATION IN THE CONTINENTAL UNITED STATES By Christian Landry A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in the field of Geography and Environmental Resources Approved by: Dr. Justin Schoof, Chair Dr. Trent Ford Dr. Jonathan Remo Graduate School Southern Illinois University Carbondale October 20, 2020 AN ABSTRACT OF THE THESIS OF Christian Landry, for the Master of Science degree in Geography and Environmental Resources, presented on October 6, 2020, at Southern Illinois University Carbondale. TITLE: THE INFLUENCE OF ATMOSPHERIC RIVERS ON EXTREME PRECIPITATION IN THE CONTINENTAL UNITED STATES MAJOR PROFESSOR: Dr. Justin Schoof The purpose of this study was to evaluate the influence of horizontal moisture fluxes from Atmospheric Rivers (ARs) on extreme precipitation (EP) events in the continental United States (CONUS). Climatological results for both EP, objectively defined using a peaks-over- threshold and block maxima approach, and ARs were processed and analyzed for co-occurrence. EP analyses produced a positive linear trend in magnitude, determined through the block maxima approach, in the Central US and a positive linear trend in frequency, determined by the peaks- over-threshold approach, predominantly for the Northern half of the CONUS. AR results show over 70 AR days throughout the country, and a linear trend of 10 less days per decade in the Central US. Results of the co-occurrence analysis suggest an increasing trend of about one instance of co-occurrence per decade throughout much of the Eastern Coast, Midwest and Pacific Northwest, with a corresponding negative linear trend of about one instance of co-occurrence per decade for much of the Southwest US to Louisiana. Throughout the world, the study of EP, and the careful analysis of its behavior, and possible amplification sources such as ARs, at the national and regional scale is imperative to obtain a comprehensive understanding of hydrometeorological impacts. i TABLE OF CONTENTS CHAPTER PAGE ABSTRACT ..................................................................................................................................... i LIST OF FIGURES ....................................................................................................................... iii CHAPTERS CHAPTER 1 – Introduction.................................................................................................1 CHAPTER 2 – Literature Review .......................................................................................5 CHAPTER 3 – Data and Methodology .............................................................................13 CHAPTER 4 – Results.......................................................................................................20 CHAPTER 5 – Discussion .................................................................................................59 CHAPTER 6 – Conclusion ................................................................................................62 REFERENCES ..............................................................................................................................65 APPENDIX ....................................................................................................................................72 VITA ............................................................................................................................................81 ii LIST OF FIGURES FIGURE PAGE Figure 1 – Average Annual Precipitation ........................................................................................3 Figure 2 – Sample Instance of Atmospheric River ..........................................................................9 Figure 3 – Demonstration of Extreme Precipitation Identification Methods ................................16 Figure 4 – Average Annual Block Maxima Precipitation .............................................................22 Figure 5 – Coefficient of Variation of Annual Block Maxima Precipitation ................................22 Figure 6 – Linear Trend of Annual Block Maxima Precipitation ..................................................24 Figure 7 – Seasonal Average Block Maxima Precipitation ..........................................................26 Figure 8 – Seasonal Coefficient of Variation of Block Maxima Precipitation ..............................27 Figure 9 – Linear Trend of Seasonal Block Maxima Precipitation ...............................................28 Figure 10 – Average Annual Number of PoT Events for 15, 25, and 50 mm/day ........................29 Figure 11 – Coefficient of Variation of Annual PoT Events for 15, 25, and 50 mm/day ............30 Figure 12 – Linear Trend of Annual PoT Events for 15, 25, and 50 mm/day ...............................31 Figure 13 – Seasonal Average Number of Daily 15 mm/day Exceedances ..................................33 Figure 14 – Seasonal Average Number of Daily 25 mm/day Exceedances ..................................34 Figure 15 – Seasonal Average Number of Daily 50 mm/day Exceedances ..................................34 Figure 16 – Seasonal Coefficient of Variation of Daily 15 mm/day Exceedances .......................35 Figure 17 – Seasonal Coefficient of Variation of Daily 25 mm/day Exceedances .......................36 Figure 18 – Seasonal Coefficient of Variation of Daily 50 mm/day Exceedances .......................36 Figure 19 – Seasonal Linear Trend of Daily 15 mm/day Exceedances .........................................37 Figure 20 – Seasonal Linear Trend of Daily 25 mm/day Exceedances .........................................38 Figure 21 – Seasonal Linear Trend of Daily 50 mm/day Exceedances .........................................38 iii Figure 22 – Annual Average AR Frequency .................................................................................40 Figure 23 – Coefficient of Variation of Annual AR frequency .....................................................41 Figure 24 – Linear Trend in Annual AR Frequency .....................................................................41 Figure 25 – Seasonal Average AR Frequency ...............................................................................43 Figure 26 – Seasonal Coefficient of Variation of AR Frequency ..................................................43 Figure 27 – Seasonal Linear Trend of AR Frequency ...................................................................44 Figure 28 – Percentage of Annual Block Maxima Precipitation Co-occurring ARs .....................45 Figure 29 – 3-Panel of Co-occurrence Statistics Using 15 mm/day EP Classification .................46 Figure 30 – 3-Panel of Co-occurrence Statistics Using 25 mm/day EP Classification .................46 Figure 31 – 3-Panel of Co-occurrence Statistics Using 50 mm/day EP Classification .................48 Figure 32 – Average Percent of Co-occurrences of AR and Precipitation ....................................49 Figure 33 – 3-Panel of Average Percent of Co-occurrence ...........................................................49 Figure 34 – 4-Panel of Percentage of Co-occurrences...................................................................50 Figure 35 – 4-Panel of Seasonal Average Number of Co-occurrences (15 mm/day) ..................51 Figure 36 – 4-Panel of Seasonal Coefficient of Variation of Co-occurrences (15 mm/day) .........52 Figure 37 – 4-Panel of Seasonal Linear Trend of Co-occurrences (15 mm/day) ..........................52 Figure 38 – 4-Panel of Seasonal Average Number of Co-occurrences (25 mm/day) ..................53 Figure 39 – 4-Panel of Seasonal Coefficient of Variation of Co-occurrences (25 mm/day) .........54 Figure 40 – 4-Panel of Seasonal Linear Trend of Co-occurrences (25 mm/day) ..........................55 Figure 41 – 4-Panel of Seasonal Average Number of Co-occurrences (50 mm/day) ...................57 Figure 42 – 4-Panel of Seasonal Coefficient of Variation of Co-occurrences (50 mm/day) .........57 Figure 43 – 4-Panel of Seasonal Linear Trend of Co-occurrences (50 mm/day) ..........................58 iv CHAPTER 1 INTRODUCTION Observations, theory, and modeling all indicate increases in extreme precipitation (EP) in North America (Kirchmeier-Young and Zhang, 2020; Zobel, 2018). Understanding historic changes in EP events and their future evolution is paramount for prosperity (Ralph, 2011). EP events resulting in flooding alone were responsible for over $85 Billion in 2014 (Smith and Matthews, 2015). Records show an increasing trend thereafter with a record-breaking season in 2017 that included EP events such as Hurricane Harvey totaling approximately $125 Billion (NCEI, 2018) in damages alone. EP events can result in catastrophic loss of agricultural assets, cause damage to property and loss of life (Janssen, 2013). The definition of EP also introduces considerable complexity, as “extreme” is characterized by three distinct aspects: magnitude, timescale, and spatial scale (Barlow et al., 2019). Variations in these characteristics may result in different associated