El Nino and the Southern Oscillation - Surface Air Temperature Implications for Western Canada
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University of Calgary PRISM: University of Calgary's Digital Repository Graduate Studies Legacy Theses 2001 El Nino and the southern oscillation - surface air temperature implications for western Canada Budikova, Dagmar Budikova, D. (2001). El Nino and the southern oscillation - surface air temperature implications for western Canada (Unpublished doctoral thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/11622 http://hdl.handle.net/1880/40763 doctoral thesis University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. 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Please contact the University of Calgary Archives for further information, E-mail: [email protected] Telephone: (403) 220-7271 Website: http://www.ucalgary.ca/archives/ THE UNIVERSITY OF CALGARY El Nino and the Southern Oscillation - Surface Air Temperature Implications for Western Canada by Dagmar Budikova A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF GEOGRAPHY CALGARY, ALBERTA January, 2001 © Dagmar Budikova 2001 ABSTRACT The ENSO cycle made up of warm, cold and neutral phases is a primary contributor to global interannual climate variability. The release of excess energy from the Pacific Ocean to the atmosphere modifies air circulation patterns as far as Canada. Detailed understanding of El Nino's signatures on Canadian climates would help farmers, foresters, fishermen, and numerous government agencies design practices to minimize costs and maximize profit from El Nino. The objective of this study is to further the understanding of El Nino's influence on surface air temperatures across Western Canada in space and time. Twelve events between 1950 and 1996 were used. Statistical analyses and GIS technology helped fulfill the objective. Results indicate that there is a significant reduction in year-to-year and place-to-place surface air temperature signal variation throughout the area from neutral to El Nino periods, especially during winters. This suggests that the primary mechanism of air circulation across the study area is significantly moderated during El Nino periods, as weather becomes generally more stable. There are three sub-regions within the study area that show distinct El Nino signatures. These are Regions I, and II that are situated south of 51°N, and Region III, that represents the northwestern section of the area, above 51°N. Within each sub-region, two signal types exist and are distinguished by winter conditions. Warm winters, referred to as Type W, are most prominent to the southern sections of the area, whereas cold winters, or Type C signals are more common to the north. The presence of these signal types has been tied to El Nino. Findings converge to suggest that El Nino-related winter surface air temperatures over Western Canada may be predictable several seasons in advance, more so than during neutral periods. in ACKNOWLEDGEMENTS Several parties and individuals deserve to be acknowledged for their support of this work. The Meteorological Service of Canada, formerly known as Atmospheric Environment Canada provided generous funding for a period of three years through a series of post-graduate scholarships in Atmospheric Sciences. The Department of Geography provided financial support through teaching assistantships, graduate research scholarships and an honorary stipend. I am equally grateful to Lawrence Nkemdirim, my supervisor for monetary help and for devoting the necessary time to help bring this work to completion. During my stay at Calgary, I quickly learnt that our Department had invaluable support staff. The help of at least some of these people should also be recognized. Medina Hanson's superior knowledge of GIS and related technologies sped up the process of locating digital basemaps. Robin Poitras' knowledge of graphic arts and photography and his willingness to lend a hand at crucial moments always helped me look better when showing off my work to the outside world. Rick Smith, whose outstanding knowledge in data modeling, computer maintenance and what seemed an unlimited willingness to listen helped me get through the day-to-day challenges Thank you all. IV To my parents - Jiri & Vojteska Thank you v TABLE OF CONTENTS Approval Page " Abstract »i Acknowledgements iv Dedication v Table of Contents vi List of Tables x List of Figures xni List of Videos xxiii List of Symbols and Acronyms xxiv 1. EL NINO/SOUTHERN OSCILLATION (ENSO) 1 1.1. INTRODUCTION 1 1.2 EL NINO/SOUTHERN OSCILLATION - HISTORY 1 1.2.1. A "composite" El Nino 7 1.3. GLOBAL EL NINO CLIMATE-RELATED IMPACTS 10 1.4. THEORIES OF TELECONNECTIONS 12 1.5. EL NINO VARIABILITY 19 1.5.1. Observed changes in the character of ENSO 19 1.5.2. Recent theories on ENSO within global climate change 20 2. ENSO AND CLIMATE OF WESTERN CANADA 23 2.1 INTRODUCTION 23 2.2 STUDY AREA: WESTERN CANADA 23 2.2.1 Physiography 23 2.2.2 Vegetation 28 2.2.3 Climate 29 2.2.3.1 General Circulation 29 2.2.3.2 Surface Temperature and Precipitation Patterns 31 2.2.3.3 Climate Regions 33 2.2.3.3.1 Pacific Canada 33 vi 2.2.3.3.2 Cordilleran Canada 35 2.2.3.3.3 The Prairies 36 2.2.3.3.4 Arctic and Boreal climate 36 2.3 SOCIO-ECONOMIC IMPACTS OF EL NINO 37 2.4 EL NINO AND CANADIAN CLIMATE 38 2.5 THE PROBLEM 40 2.6 PROJECT OBJECTIVES AND METHODOLOGIES 41 3. DATA ISSUES 42 3.1 DATA ACQUISITION AND PREPARATION 42 3.2 QUALITY CONTROL 42 3.1.1 Data Homogenization 45 3.1.2 Data Estimation 51 3.3 TREND REMOVAL 55 3.4 SPATIAL INTERPOLATION 57 4. PRINCIPAL METHODS 65 4.1 INTRODUCTION 65 4.2 DATABASE ESTABLISHMENT 65 4.3 GEOGRAPHIC INFORMATION SYSTEMS (GIS) 71 4.3.1 Data exploration, visualization, and analysis using GIS 72 4.3.2 Dynamic mapping 73 4.4 EIGENVECTORREGIONALIZATION 75 4.5 MANN-WHITNEY U TEST 76 4.6 PAIRED DATA ANALYSIS 77 4.6.1 Pearson's correlation coefficient 77 4.6.2 Spearman's correlation coefficient 78 4.6.3 Cross-correlation 78 5. EL NINO DEFINITION AND SIGNAL CALCULATION 79 5.1 INTRODUCTION 79 5.2 DEFINITIONS OF ENSO 79 5.3 RESEARCH ENSO DEFINITION 82 5.3.1 Classification of S ST time series 82 5.3.2 El Nino in Canada 84 5.3.2.1 El Nino years 85 5.3.2.2 La Nina years 86 5.3.2.3 Neutral years 87 5.3.3 El Nino signal calculations 89 5.3.4 Calculation of El Nino signal in surface temperature records 89 vii 5.3.5 Signal analysis 94 5.3.5.1 General synthesis of El Nino-related signal 94 5.3.5.2 Differentiation of El Nino, La Nina and neutral signal time series 94 5.3.5.3 El Nino signal and SSTs in tropical Pacific ocean 96 5.4 SUMMARIES AND CONCLUSIONS 98 6. SIGNAL VARIATION ANALYSIS 100 6.1 INTRODUCTION 100 6.2 COMPOSITE MAPS 100 6.2.1 El Nino periods 102 6.2.2 Comparison to Neutral periods 106 6.3 SUMMARIES AND CONCLUSIONS 107 7. SIGNAL REGIONALIZATION AND CLUSTERING I 108 7.1 INTRODUCTION l°8 7.2 EIGENVECTORREGIONALIZATION 108 7.3 TEMPORAL CLUSTERING 113 7.3.1 Region I 115 7.3.2 Region 11 12° 7.3.3 Region III 123 7.4 SUMMARIES AND CONCLUSIONS 128 8 GRID-SCALE SURFACE AIR TEMPERATURE ANALYSIS 134 8.1 INTRODUCTION 134 8.2 METHODOLOGY 134 8.3 REGION 1 135 8.3.1 Type W signal 135 8.3.2 Type C signal 144 8.4 REGION II 144 8.4.1 Type W signal 144 8.4.2 Type C signal 153 8.5 REGION m 153 8.5.1 Type W signal 153 8.5.2 Type C signal 162 8.6 SUMMARY AND CONCLUSIONS 162 9. SPATIO-TEMPORAL SIGNAL ANALYSIS: REGION 1 166 9.1 INTRODUCTION 166 9.2 CONSTRUCTION OF ANIMATED SEQUENCE 166 viii 9.3 TYPE W SIGNAL 169 9.4 SUMMARY AND CONCLUSIONS 170 10. ASSOCIATION BETWEEN EL NINO AND SIGNALS IN SURFACE AIR TEMPERATURE 172 10.1 INTRODUCTION 172 10.2 DATA 172 10.2.1 Sea Surface Temperature Anomalies (SSTAs) 173 10.2.2 Southern Oscillation Index (SOI) 173 10.2.3 Sea Level Pressure over Indonesia (ZIND) 177 10.2.4 Sea Level Pressure over the Eastern Pacific Basin (ZEAS) 177 10.2.5 Equatorial Southern Oscillation Index (ESOI) 179 10.2.6 Multivariate ENSO Index (MEI) 182 10.3 METHODS 183 10.4 RESULTS AND DISCUSSION 188 10.4.1 Region I 188 10.4.1.1 Winter [DJF(+1)] 188 10.4.1.2 Fall [SON(0)] 189 10.4.1.2.1 Event Classification 191 10.4.1.3 Spring [MAM(+1)] 195 10.4.1.4 Summer [JJA( 11)| 195 10.4.2 Region II 195 10.4.2.1 Winter [DJF(+1)] 195 10.4.2.1.1 Event Classification 197 10.4.2.2 Fall [SON(0)] 197 10.4.2.3 Spring [MAM(+1)] 200 10.4.2.4 Summer [JJA(+1)] 209 10.4.3 Region III 210 10.4.3.1 Winter [DJF(+1)] 210 Event Classification 211 10.4.3.2 Fall [SON(0)] 213 10.4.3.3 Spring [MAM(+1)J 215 10.4.3.4 Summer [JJA(+1)] 215 10.5 SUMMARIES AND CONCLUSIONS 215 11.