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North Atlantic Winter Wild Storm Variability Across Different Time Scales

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North Atlantic Winter Wild Storm Variability Across Different Time Scales North Atlantic Winter Wind Storm Variability across different Time Scales Simon Wild A thesis submitted to the University of Birmingham for the degree of DOCTOR OF PHILOSOPHY. School of Geography, Earth and Environmental Sciences College of Life and Environmental Sciences University of Birmingham March 2018 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT ABSTRACT In this thesis atmospheric and oceanic conditions important for the development of wind storms on different time scales are analysed. The potential usefulness and limitations of seasonal prediction models and long-term reanalyses with respect to wind storm frequency is investigated and sources of potential seasonal predictability of wind storm frequency are discussed. On the synoptic scale tropospheric growth conditions such as baroclinicity, latent heat and upper level divergence show greater magnitudes of one standard deviation on average compared to all extra-tropical cyclones. Mid-latitude Rossby waves show generally greater amplitudes for different wave numbers during wind storm events. Greater amplitudes are also found in wave numbers not typically associated with storm track activity. The analysis of extra-tropical cyclones and wind storms on the seasonal scale reveal positive, significant skill for some European regions in state-of-the-art seasonal prediction models. North Atlantic sea surface temperatures (SST) are shown to be a source of seasonal predictability and a potential reason for the achieved skill for wind storm frequency predictions in reanalysis and AMIP-type sensitivity experiments. The role of tropical Pacific and Atlantic SST for the record number of wind storms over the UK in winter 2013/14 is discussed. i DECLARATION AUTHOR'S DECLARATION Individual contributions for each main chapter of this thesis are detailed below: Chapter 3 Concept: Simon Wild (SW) and Gregor C. Leckebusch (GCL) Method Development: SW, Daniel J. Befort (DJB), and GCL Analyses: SW Figures: SW Text: SW Chapter 4 Concept: SW and GCL Method Development: SW and Ian Simmonds Analyses: SW Figures: SW Text: SW Chapter 5 Concept: SW, DJB and GCL Method Development: SW, DJB and GCL Analyses: SW and DJB Figures: SW and DJB Text: SW (First Draft), DJB, and GCL Comments and Editing: Jeff R. Knight, Julia F. Lockwood, Hazel E. Thornton, Philip E. Bett, and Antje Weisheimer This chapter has been submitted to the Quarterly Journal of the Royal Meteorological Society and is currently under review ii DECLARATION Chapter 6 Concept: SW, DJB, Dominik Renggli (DR) and GCL Method Development: SW, DJB, DR, and GCL Analyses: SW and DJB Figures: SW Text: SW Chapter 7 Concept: SW and GCL Method Development: SW Analyses: SW Figures: SW Text: SW Comments and Editing: DJB and GCL This chapter is published in the Bulletin of the American Meteoro- logical Society. Appendix Concept: DJB Method Development: SW, DJB, Tim Kruschke (TK), and GCL Analyses: SW and DJB Figures: DJB Text: DJB Comments and Editing: SW, TK, and GCL This chapter is published in Atmospheric Science Letters. iii ACKNOWLEDGMENTS ACKNOWLEDGMENTS First and foremost I would like to thank Gregor Leckebusch for giving me this Philosophiae Doctor opportunity, for his supervision, support, general advice, trust, and the fact of bringing me to Birmingham. I thoroughly enjoyed very many lengthy discussions about obviously wind storms, but also about the UK, football, the French Revolution, and current politics. I would further like to thank Ian Simmonds who provided some very useful scientific guidance during my stay at the University of Melbourne. It was a great pleasure to be surrounded by his seemingly infinite knowledge. I am also very grateful to Len Shaffrey and Xiaoming Cai for agreeing to be my examiners and therefore be part of the lucky few to actually having to completely read this piece of work. I did the best I could to make it worth it! Further thanks goes to Daniel Befort for countless discussions, support, ideas, and critical reviews of scientific practices (not mine). I would also like to thank my office colleagues and team mates from B* Abrantas: Michael, Colin, Vasileios, Clemens, Jim, Tasos, Ian, Joss, and Sam, who made work and life certainly more enjoyable. The biggest thank you goes to Kaat for her endless patience and for simply being part of my life. iv CONTENTS CONTENTS Abstract i Author's Declaration ii Acknowledgements iv Contents v List of Figures vii List of Tables ix List of Acronyms x Preface xiii 1 General Introduction 1 1.1 Why Wind Storms? . 1 1.2 North Atlantic Winter Wind Storms in the Recent Climate . 2 1.3 Variability of Winter Wind Storms... 5 1.3.1 ...on the Synoptic Time Scale . 5 1.3.2 ...on Seasonal to Interannual Time Scales . 8 1.3.3 ...on Decadal to Centenary Time Scales . 10 1.4 Research Gaps . 12 1.5 Objectives of Thesis . 14 1.6 Structure of Thesis . 16 2 Data, Methods and Key Variables 18 2.1 Data . 18 2.1.1 ERA Interim . 18 2.1.2 Other Data Sets . 19 2.2 Methods . 20 2.2.1 Algorithm for the Identification and Tracking of Extra- tropical Cyclones and Wind Storms . 20 2.2.2 Matching Algorithm for the Association of a Wind Storm to an Extra-tropical Cyclone . 23 2.2.3 Storm Severity Index . 23 2.2.4 Normalisation of Analysed Variables . 25 2.2.5 Correlation Analyses . 26 2.2.6 Composite Analysis . 26 2.2.7 Principle Component Analysis . 27 2.3 Atmospheric Growth Factors . 29 v CONTENTS 2.3.1 Equivalent Potential Temperature . 29 2.3.2 Maximum Eady Growth Rate . 30 2.3.3 Upper-tropospheric Divergence and Jet Stream . 31 3 Tropospheric Growth Factors 33 3.1 Introduction . 33 3.2 Wind Storms in Specific Months . 35 3.3 Composites for ETCs and Wind Storms . 41 3.3.1 Different Composite Sets . 41 3.3.2 Composites for All Cyclones . 44 3.3.3 Comparison of different Composite Sets . 50 3.4 Event to Event Variability . 55 3.5 Principle Component Selection . 59 3.6 Summary and Discussion . 62 4 Waves and Storms 68 4.1 Introduction . 68 4.2 FFT for a single storm . 71 4.3 Results . 76 4.3.1 From Storms to Wave Anomalies . 76 4.3.2 From Wave Anomalies to Storms . 82 4.4 Summary and Discussion . 85 5 Seasonal Skill in ETCs and Wind Storms 91 5.1 Introduction . 92 5.2 Data . 94 5.3 Identification and Tracking Algorithms . 94 5.4 Cyclones and Wind Storms in the NH . 97 5.5 Forecasted Cyclones and Wind Storms - Direct Method . 101 5.5.1 Temporal Variability . 101 5.5.2 Spatial Variability . 103 5.6 Forecasted Cyclones and Wind Storms - Indirect Method . 105 5.7 Summary and Discussion . 109 6 Sea Surface Temperatures in Relation to Storms 114 6.1 Potential Predictability on Seasonal Scale . 114 6.2 NAH and Wind Storm in ERA-I . 117 6.2.1 Definition of the Horseshoe-Index . 117 6.2.2 Relation of HSI and Wind Storms . 119 6.2.3 HSI and Growth Factors in ERA-I . 121 6.2.4 Summary of HSI results in ERA-I . 126 6.3 NAH and Wind Storms in ECHAM5 . 129 6.3.1 Set-Up of ECHAM5 Simulations . 129 6.3.2 HSI and Growth Factors in ECHAM5 . 131 6.3.3 Summary of HSI results in ECHAM5 . 136 6.4 Discussion . 137 vi CONTENTS 7 Conditions in Winter 2013/14 140 7.1 Introduction . 140 7.2 Data and Methods . 141 7.3 Results . 144 7.3.1 The winter 2013/14 over the British Isles and upstream conditions . 144 7.3.2 The Role of the PNA . 147 7.4 Discussion and Attribution to Climate Change . 147 8 Synthesis 151 8.1 Summary and Discussion . 151 8.2 Outlook . 157 Bibliography 159 APPENDIX: Different trends in ERA-20C and NOAA-20CR 185 9.1 Introduction . 186 9.2 Data and Methods . 188 9.3 Results . 190 9.3.1 Northern Hemisphere . 190 9.3.1.1 All cyclone events . 190 9.3.1.2 Extreme Cyclone Events . 193 9.3.1.3 Wind Storm Events . 195 9.3.2 Southern Hemisphere . 195 9.3.2.1 All Cyclone Events . 195 9.3.2.2 Extreme Cyclone Events . 197 9.3.2.3 Wind Storm Events . 198 9.4 Discussion and Conclusion . 198 vii LIST OF FIGURES LIST OF FIGURES 1 Begr¨ußung(Greeting) by Paul Klee, 1922 . xiii 1.1 Track density and Frequency of Wind Storms between 1979 and 2013 4 3.1 Cyclone-, Wind Storm Tracks and Growth Factors in January 2007 38 3.2 Cyclone-, Wind Storm Tracks and Growth Factors in February 2008 39 3.3 Cyclone-, Wind Storm Tracks and Growth Factors in January 2009 40 3.4 Composites for ΘE at 850hPa for ETCs with p < 1000hP a . 45 3.5 Composites for σBI at 775hPa for ETCs with p < 1000hP a . 46 3.6 Composites for σBI at 400hPa for ETCs with p < 1000hP a . 47 3.7 Composites for UTD for ETCs with p < 1000hP a . 48 3.8 Composites for ΘE at 850hPa for all Event Sets . 51 3.9 Composites for σBI at 775hPa for other Event Sets .
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