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Variations in Winter Surface High Pressure in the Northern Hemisphere and Climatological Impacts of Diminishing Arctic Sea Ice

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Variations in Winter Surface High Pressure in the Northern Hemisphere and Climatological Impacts of Diminishing Arctic Sea Ice University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Dissertations & Theses in Earth and Earth and Atmospheric Sciences, Department Atmospheric Sciences of 5-2010 Variations in Winter Surface High Pressure in the Northern Hemisphere and Climatological Impacts of Diminishing Arctic Sea Ice Kristen D. Fox University of Nebraska at Lincoln, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/geoscidiss Part of the Other Earth Sciences Commons Fox, Kristen D., "Variations in Winter Surface High Pressure in the Northern Hemisphere and Climatological Impacts of Diminishing Arctic Sea Ice" (2010). Dissertations & Theses in Earth and Atmospheric Sciences. 8. https://digitalcommons.unl.edu/geoscidiss/8 This Article is brought to you for free and open access by the Earth and Atmospheric Sciences, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Dissertations & Theses in Earth and Atmospheric Sciences by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. VARIATIONS IN WINTER SURFACE HIGH PRESSURE IN THE NORTHERN HEMISPHERE AND CLIMATOLOGICAL IMPACTS OF DIMINISHING ARCTIC SEA ICE by Kristen D. Fox A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science Major: Geosciences Under the Supervision of Professor Mark Anderson Lincoln, Nebraska May, 2010 VARIATIONS IN WINTER SURFACE HIGH PRESSURE IN THE NORTHERN HEMISPHERE AND CLIMATOLOGICAL IMPACTS OF DIMINISHING ARCTIC SEA ICE Kristen D. Fox, M.S. University of Nebraska, 2010 Advisor: Mark Anderson This study explores the role Arctic sea ice plays in determining mean sea level pressure and 1000 hPa temperatures during Northern Hemisphere winters while focusing on an extended period of October to March. This is accomplished by investigating two regions of the same size and comparable climatic zones and elevations in the Northern Hemisphere. A breakdown of 29 years of reanalysis data into average monthly values, anomalies, trends, and comparisons between regions serves as current data to compare with a computer model control run. Ensuring the control run accurately models current atmospheric patterns, altering the model inputs to have no permanent Arctic sea ice will then show what winters could look like in the Siberian and Canadian regions if Arctic sea ice continues to diminish. The results for the reanalysis show that the Siberian region has higher MSLP and lower 1000 hPa temperatures than the Canadian region. The control run accurately captures the seasonal cycle from the reanalysis, except the values were offset slightly. Expected conditions associated with no sea ice would be warmer temperatures and lower pressures, and this situation is reflected in the results from the no sea ice run for the Canadian region. However, the no sea ice run results indicate stronger pressures and colder temperatures in the Siberian region, particularly from January to March. iii DEDICATION I would like to dedicate my thesis to my fiancé Corey Boe. Thank you for being willing to put our future on hold so that I could continue my education. iv ACKNOWLEDGEMENTS First, I would like to acknowledge and thank my advisor, Dr. Mark Anderson for all of his assistance, patience, and for keeping me focused in the writing and revising stages. I would like to thank the University of Nebraska-Lincoln Department of Geosciences and the Larson Fellowship for providing funding. I would like to thank my committee, Dr. Robert Oglesby, Dr. Merlin Lawson, and Dr. Song Feng for their support and critique of my research. Extra thanks to Dr. Lawson for being my mentor and a great person to teach under for the last two years. Many thanks to my officemate, Angela Bliss, for talking through ideas with me while still working on her own research, and for making the long days in our office more enjoyable. I have also had much long-distance encouragement and support from my best friend and Maid of Honor, Toni Hatinger, whose fresh eyes and honest opinions have helped me throughout this whole process. Finally, a big thank you to my parents, Jack and Diane, for fostering my curiosity and supporting my educational goals throughout my entire life. v CONTENTS Contents v List of Figures vii List of Tables ix Chapter 1. Introduction 1 Chapter 2. Background 3 2.a. Study Regions 3 2.b. Previous Work 6 Chapter 3. Methodology 12 3.a. Study Regions 12 3.b. NCEP-NCAR Reanalysis II Data 14 3.c. Computer Model Data 15 Chapter 4. Results 17 4.a. NCEP-NCAR Reanalysis II Data 17 4.a.1. Extended Study Period 17 4.a.2. Winter (DJF) Data Analysis: Seasons of 1979-2007 24 4.a.3. October Data Analysis: 1979-2007 35 4.a.4. November Data Analysis: 1979-2007 41 4.a.5. December Data Analysis: 1979-2007 48 4.a.6. January Data Analysis: 1980-2008 (Seasons of 1979-2007) 54 4.a.7. February Data Analysis: 1980-2008 (Seasons of 1979-2007) 61 4.a.8. March Data Analysis: 1980-2008 (Seasons of 1979-2007) 67 vi 4.b. Control Comparison to Reanalysis 73 4.c. No Sea Ice Comparison to Control 84 Chapter 5. Conclusions 94 References 98 vii LIST OF FIGURES Figure 1. Köppen-Geiger Climate Classification 4 Figure 2. Study Region Elevations 5 Figure 3. January MSLP Patterns 8 Figure 4. Study Areas 13 Figure 5. Extended Study Period (October to March) 18 Figure 6. Pearson Correlations 21 Figure 7. Winter (DJF) 29 Year Average MSLP 25 Figure 8. Winter (DJF) MSLP 26 Figure 9. Winter (DJF) 29 Year Average 1000 hPa Temperature 29 Figure 10. Winter (DJF) 1000 hPa Temperature 30 Figure 11. Winter (DJF) MSLP and 1000 hPa Temperature Anomalies 34 Figure 12. October 29 Year Average MSLP 36 Figure 13. October Reanalysis Data 37 Figure 14. October 29 Year Average 1000 hPa Temperature 39 Figure 15. November 29 Year Average MSLP 42 Figure 16. November Reanalysis Data 43 Figure 17. November 29 Year Average 1000 hPa Temperature 46 Figure 18. December 29 Year Average MSLP 49 Figure 19. December Reanalysis Data 50 Figure 20. December 29 Year Average 1000 hPa Temperature 53 Figure 21. January 29 Year Average MSLP 55 viii Figure 22. January Reanalysis Data 57 Figure 23. January 29 Year Average 1000 hPa Temperature 59 Figure 24. February 29 Year Average MSLP 62 Figure 25. February Reanalysis Data 63 Figure 26. February 29 Year Average 1000 hPa Temperature 66 Figure 27. March 29 Year Average MSLP 68 Figure 28. March Reanalysis Data 71 Figure 29. March 29 Year Average 1000 hPa Temperature 72 Figure 30. Siberian Region Comparison 75 Figure 31. Reanalysis and Control Differences 77 Figure 32. Canadian Region Comparison 79 Figure 33. Control and No Sea Ice Differences 87 ix LIST OF TABLES Table 1. Siberian Region Monthly MSLP (hPa) 19 Table 2. Canadian Region Monthly MLSP (hPa) 19 Table 3. Reanalysis: Pearson Correlations 22 Table 4. Siberian Region Monthly 1000 hPa Temperature (°C) 22 Table 5. Canadian Region Monthly 1000 hPa Temperature (°C) 22 Table 6. Winter Mean Sea Level Pressure Data Summary (hPa) 27 Table 7. Trends in MSLP (hPa/year) and 1000 hPa Temperature (°C/year) 27 Table 8. Winter 1000 hPa Temperature Data Summary (°C) 31 Table 9. October Data Summary 38 Table 10. November Data Summary 44 Table 11. December Data Summary 51 Table 12. January Data Summary 58 Table 13. February Data Summary 64 Table 14. March Data Summary 70 Table 15. Control Run Siberian Region Monthly MSLP (hPa) 76 Table 16. Model Correlations 78 Table 17. Control Run Canadian Region Monthly MSLP (hPa) 80 Table 18. Control Run Siberian Region Monthly 1000 hPa Temperature (°C) 82 Table 19. Control Run Canadian Region Monthly 1000 hPa Temperature (°C) 82 Table 20. No Sea Ice Run Siberian Region Monthly MSLP (hPa) 85 Table 21. No Sea Ice Run Canadian Region Monthly MSLP (hPa) 88 x Table 22. No Sea Ice Run Siberian Region Monthly 1000 hPa Temperature (°C) 90 Table 23. No Sea Ice Run Canadian Region Monthly 1000 hPa Temperature (°C) 92 1 Chapter 1. Introduction Cohen and Entekhabi (1999) postulate that cooling caused by early season (October through December) snowcover is a dominant force in Northern Hemisphere climate variability. According to Lockwood (1979), wintertime high pressures in Siberia usually form over areas where snow thickness is more than 50 cm and the snowcover duration exceeds 200 days. If snowcover plays such an important role, one can assume that Arctic sea ice also is an important factor in Northern Hemisphere winter conditions. This study analyzes current Northern Hemisphere winters for two regions and, through a global climate model, attempts to forecast 1000 hPa temperature and mean sea level pressure changes that could occur from the continued decline of Arctic sea ice coverage. The motivation of this study is to investigate how winters in the Northern Hemisphere will change if permanent Arctic sea ice does not exist. This will be done by focusing on mean sea level pressure and 1000 hPa temperature patterns in a Siberian and Canadian study region. To accomplish the goal of this study, a global climate model is run under conditions of open water, focusing on an extended winter season from October to March in the Northern Hemisphere. In order to evaluate the magnitude of the results from the no sea ice model run, there must be something to which it can be compared. A control run is used to represent current winter conditions for both regions, except there needs to be a way to make sure the control run is accurately modeling current patterns. This accuracy check is done through comparing control run data to a climatology of reanalysis data.
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