UCLA UCLA Electronic Theses and Dissertations Title Multi-Temporal Variability Within Antarctic Coastal Polynyas and Their Relationships To Large-Scale Atmospheric Phenomena Permalink https://escholarship.org/uc/item/0tj68195 Author Ward, Jason Michael Publication Date 2018 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA Los Angeles Multi-Temporal Variability Within Antarctic Coastal Polynyas and Their Relationships To Large-Scale Atmospheric Phenomena A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Geography by Jason Michael Ward 2018 ABSTRACT OF THE DISSERTATION Multi-Temporal Variability Within Antarctic Coastal Polynyas and Their Relationships To Large-Scale Atmospheric Phenomena by Jason Michael Ward Doctor of Philosophy in Geography University of California, Los Angeles, 2018 Professor Marilyn N Raphael, Chair Open water and thin ice areas, known as coastal polynyas, form along the Antarctic coastline and allow continued interaction between the ocean and atmosphere throughout the sea ice advance season. Coastal polynyas are the most productive locations of sea ice formation, Antarctic bottom water formation, and biological activity in the Southern Ocean. Changes in these elements are greatly controlled by polynya area variability. To carry out an in-depth study of polynya area variability, a 26-year 25-polynya daily area dataset was created and analyzed. The long term trend and the daily, monthly, seasonal, and annual variations are separated to analyze the multi- temporal variability of the polynyas and investigate their individual and regional responses to prominent large-scale atmospheric circulation patterns. Results indicate that most polynya variability occurs at the daily scale, followed by monthly and seasonal variations. Very little variability occurs interannually. Thus, studies done at the annual scale mask most of the polynya ii activity. Only five of the polynyas have long term trends, which are all non-linear and arise from abrupt changes in the icescape. Three of the significant trends occur within the top four most significant regions of sea ice and bottom water formation. Long term changes in polynya area cause long term changes in the overall productivity of the Southern Ocean. The Southern Annular Mode (SAM), El Nino-Southern Oscillation (ENSO), and the Amundsen Sea Low (ASL) significantly contribute to individual and regional coastal polynya variability. Influence from the SAM and the ASL is primarily driven at the monthly and seasonal scales. Influence from ENSO is driven at the annual scale. Using Pearson correlations, principal component analysis, gaussian mixture models, and hierarchical agglomerative clustering, six regional polynya groups are delineated based on the strength and direction of inter-polynya co-variability. The mean polynya variability within each region is significantly correlated, which is driven at the seasonal scale. While the SAM, ENSO, and ASL are not the primary drivers of regional polynya group delineations, they are significantly influential in the mean variability of each group. iii The dissertation of Jason Michael Ward is approved. Alexander Dean Hall Yongwei Sheng Yongkang Xue Marilyn N Raphael, Committee Chair University of California, Los Angeles 2018 iv Dedication The completion of this dissertation is dedicated to my three children – Monique, Jamari, and Jana. I am continually amazed and inspired by each of them. It is my hope that this accomplishment inspires them to find their passion and strive for excellence. Hard work, dedication, and family are key components of success. v Table of contents Title Page..........................................................................................................................................i Abstract............................................................................................................................................ii Committee Page..............................................................................................................................iv Dedication........................................................................................................................................v Table of Contents............................................................................................................................vi List of figures...................................................................................................................................vii Acknowledgements........................................................................................................................viii Vita..................................................................................................................................................ix Chapter 1: Introduction...................................................................................................................1 Chapter 2: A new look at variability and trends ...............................................................................7 Chapter 3: The multi-temporal influence of large-scale atmospheric patterns...............................30 Chapter 4: A regional analysis........................................................................................................60 Chapter 5: Conclusion.................................................................................................................103 References....................................................................................................................................107 vi List of Figures Chapter 2 Figure 1: circumpolar distribution..................................................................................................15 Figure 2: cumulative circumpolar scales of variability....................................................................18 Figure 3: individual size, standard deviation, and scales of variability............................................20 Figure 4: annual trends...................................................................................................................21 Figure 5: seasonality of trends.........................................................................................................25 Chapter 3 Figure 1: circumpolar distribution and sea ice motion....................................................................34 Figure 2: scales of variability within atmospheric circulation patterns ...........................................39 Figure 3: large-scale polynya-atmosphere relationships.................................................................46 Figure 4: lagged large-scale polynya-atmosphere relationships......................................................47 Figure 5: cross correlations between atmospheric circulation patterns...........................................55 Chapter 4 Figure 1: circumpolar distribution..................................................................................................61 Figure 2: Pearson correlation matrix and corresponding polynya groups.......................................71 Figure 3: primary principal components and scree plots.................................................................74 Figure 4: polynya groups derived from gaussian mixture models...................................................75 Figure 5: polynya groups derived from hierarchical agglomerative clustering................................79 Figure 6: generalized polynya groups derived from all four grouping methods..............................82 Figure 7: inter-regional correlations...............................................................................................84 Figure 8: influence of atmospheric circulations on original group delineations..............................87 Figure 9: influence of atmospheric circulations on annual group delineations................................89 Figure 10: influence of atmospheric circulations on seasonal group delineations............................92 Figure 11: influence of atmospheric circulations on monthly group delineations...........................94 Figure 12: influence of atmospheric circulations on mean group variability ..................................95 vii Acknowledgments I would like to acknowledge the following people who have supported me, not only during the completion of this project, but also throughout my graduate career. They all contributed to my growth as a student, teacher, researcher, and father. First, I want to acknowledge Kasi McMurray and the Geography Department staff. They worked very hard and contributed to my smooth progression through the program. I thank my Ph.D. committee – Alex Hall, Yongwei Sheng, Yongkang Xue, and Marilyn Raphael. I could not accomplish many of my educational goals and fulfill my potential without their advice on research and publication. I thank them for all the time and energy they put into my work and my growth as a researcher. I especially thank my faculty advisor and mentor, Marilyn Raphael, for her continued belief, encouragement, and wisdom. Her availability and generosity are greatly appreciated. I am also very grateful to my friends. Anthony Howell, Tom Narins, Anna Dvorak, and Diane Ward were extremely supportive, gave great advice, and created an enjoyable experience for me. Ashlea McLaughlin, Eric Ferrer-Vaughn, Melody Davis,