HOWARD UNIVERSITY Investigating an Automated Method to Explore
Total Page：16
File Type：pdf, Size：1020Kb
HOWARD UNIVERSITY Investigating an Automated Method to Explore Mesoscale Convective Complexes in West Africa A Dissertation Submitted to the Faculty of the Graduate School of HOWARD UNIVERSITY in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Program of Atmospheric Sciences by Kim Dionne Whitehall Washington, D.C. May 2014 HOWARD UNIVERSITY GRADUATE SCHOOL PROGRAM OF ATMOSPHERIC SCIENCES DISSERTATION COMMITTEE ___________________________________ Belay Demoz, Ph.D. Chairperson ___________________________________ Gregory Jenkins, Ph.D. ___________________________________ Chris Mattmann, Ph.D. ___________________________________ Mugizi Rwebangira, Ph.D. ___________________________________ Claire Monteleoni, Ph.D. Assistant Professor School of Engineering and Applied Science Department of Computer Science George Washington University Washington, D.C. ___________________________________ Gregory Jenkins, Ph.D. Dissertation Advisor Candidate: Kim Whitehall Date of Defense: April 14, 2014 ! ii ACKNOWLEDGEMENTS First and foremost, I wish to give thanks to the Almighty Father. I am so thankful for the village of supporters God has blessed me with throughout my life, and this process. I wish to sincerely thank my advisor, Dr. Gregory Jenkins, for taking me on as a doctoral student during my first semester at Howard University. Greg’s support and guidance throughout my graduate school career, and belief in the research and my abilities to complete it will never be forgotten. I would also like to thank the members of my dissertation committee – Dr. Belay Demoz, Dr. Robert Rwebangira, Dr. Chris Mattmann and Dr. Claire Monteleoni. I appreciate the time you took to understand my research and the eagerness with which you encouraged it. I especially would like to thank Chris who I am forever indebted to for his tutelage, encouragement, and mentorship even far beyond the academics. The scope of this research lead to interesting collaborations and discussions with the Regional Climate Modeling Evaluation System (RCMES) team at the NASA Jet Propulsion Laboratory. As such, I wish to thank the entire team, and make special mention of Cameron Goodale and Paul Zimdars, for their contributions along the way that improved the quality and content of this dissertation research. I would also like to acknowledge some of the sources of funding that supported the research for this degree, which include primary funding from the National Science Foundation (NSF) grant AGS-1013179, and secondary funding from NSF awards PLR-1348450, ICER-1343800, ACS-1125798, and GEO-1229036 and GEO-1343583. Efforts were also partially supported by the Jet Propulsion Laboratory, managed by the California Institute of Technology under a contract with the National Aeronautics and Space Administration. ! iii! I must also acknowledge and thank the administrative staffs of the International Student Services Office, the Graduate School, the Howard Program in Atmospheric Sciences, and the Physics Department for their guidance throughout the three years. Finally, I wish to sincerely thank my village of family and friends, and acknowledge them for their support, friendships, and encouragement through it all - my mother who everyday offered words of wisdom and encouragement; Marquez, my significant other, for his patience, support, and invaluable ability to lightening my mood and aid with refocusing; Alexander, my darling nephew, whose smile brightened the worse of days; and my friends for their tireless support. ! iv! DEDICATION To my loving, supportive mother, who never ceased believing this was possible. To my caring, encouraging and most patient love, Marquez, whose personal sacrifices will never be forgotten. To my dearest friend, Barbara, who started this journey with me, and watched it come to completion from Heaven. ! v! ABSTRACT Mesoscale convective complexes are convectively driven, high impact weather systems with durations of approximately 10-12 hours, and are large contributors to daily and monthly rainfall totals. In West Africa, approximately 40 mesoscale convective complexes contribute an estimated one-quarter of the total rainfall amounts between July and September annually. As such, an understanding of the lifecycle, characteristics, frequency, and seasonality of these weather features is critical for climate studies, agricultural and hydrological studies, and for disaster management. Identification criteria of mesoscale convective complexes exist for infrared satellite data, but the spatial extent and the spatio-temporal variability of the convective characteristics of these mesoscale convective complexes make rainfall characterization difficult, even in dense networks of radars and / or surface gauges. Hence, fully automated methods are required to explore mesoscale convective complexes in long-term infrared satellite data, and to determine their characteristics from other datasets, such as precipitation rate satellite datasets. Automated identification methods of mesoscale convective complexes are based on forward- and / or backward-in-time spatial-temporal analyses of infrared satellite data, and usually incorporate a manual component to verify the features and / or characterize the associated precipitation. These existing identification and precipitation characterization methods are not readily transferable to “big data” such as satellite-derived datasets, thus hindering comprehensive studies of these features, both at weather and climate timescales. In recognizing these limitations and the growing volume of satellite data, this study explores the applicability of graph theory to creating a fully automated method for identifying mesoscale convective systems in satellite datasets. The framework for such a method is provided in this work. The results indicate that applying graph theory innately handles the complexity of the ! vi! mesoscale convective complexes, thus eliminating a manual verification stage. Furthermore, implementing a graph theory based method identifies individual and embedded features in infrared satellite datasets and extracts the associated precipitation rate data from other datasets for comparison in a seamless fully automated manner. The results also establish that a graph theory based method allows for studies over periods and spatial domains longer and larger than individual events. ! vii! ! TABLE OF CONTENTS DISSERTATION COMMITTEE ........................................................................................ ii ACKNOWLEDGEMENTS .................................................................................................. iii DEDICATION ....................................................................................................................... v ABSTRACT ........................................................................................................................... vi LIST OF TABLES ................................................................................................................ xii LIST OF FIGURES .............................................................................................................. xiii LIST OF ABBREVIATIONS .............................................................................................. xviii 1. INTRODUCTION ........................................................................................................... 1 1.1. Research Problem and Broader Impacts ..................................................................... 1 1.2. Research Objectives .................................................................................................... 4 1.3. Roadmap to the Document .......................................................................................... 5 2. BACKGROUND OF RAINFALL VARIABILITY IN WEST AFRICA .................. 7 2.1. A Summary of the Rainfall Variability in West Africa .............................................. 7 2.1.1. Rainfall Distribution in West Africa ............................................................... 7 2.1.2. Drivers of Rainfall Variability in West Africa ................................................ 8 2.1.3. Large-scaled Circulations ................................................................................ 11 2.1.4. Regional Circulations ...................................................................................... 12 2.1.5. Sea-Surface Temperature Anomalies .............................................................. 14 2.1.6. Land Use Changes ........................................................................................... 16 2.1.7. Synoptic-scaled Circulations – African Easterly Waves ................................ 17 2.1.8. Mesoscale Convective Systems and Mesoscale Convective Complexes ....... 17 2.2. A Summary of Mesoscale Convective Complexes ..................................................... 21 ! viii ! 2.2.1. Global Mesoscale Convective Complexes ...................................................... 21 2.2.2. West African Mesoscale Convective Complexes ........................................... 25 2.2.3. Identifying Mesoscale Convective Complexes ............................................... 27 2.2.3.1. The Mesoscale Convective Complex Criterion ...................... 27 2.2.3.2. Methods to Identify Mesoscale Convective Complexes ......... 28 2.2.3.3. Determining the Rainfall Amounts Associated with Mesoscale Convective Systems .............................................. 34 2.3. Data mining, management and