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Investigating the Relationships Between Wheat-Specific Rainfall Characteristics, Large-Scale Modes of Climate Variability and Wheat

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Investigating the Relationships Between Wheat-Specific Rainfall Characteristics, Large-Scale Modes of Climate Variability and Wheat Investigating the relationships between wheat-specific rainfall characteristics, large-scale modes of climate variability and wheat yields in the Swartland region, South Africa. by Pierre-Louis Kloppers Supervisor: Peter Johnston, PhD Co-Supervisor: Mark Tadross, PhD Dissertation presented for the degree of Master of Science April 2014 Univeristy of Cape Town Department of Environmental & Geographical Science University of Cape Town The copyright of this thesis vests in the author. No quotation from it or information derived from it is to be published without full acknowledgement of the source. The thesis is to be used for private study or non- commercial research purposes only. Published by the University of Cape Town (UCT) in terms of the non-exclusive license granted to UCT by the author. University of Cape Town Abstract ABSTRACT Wheat producers in the South Western Cape (SWC) of South Africa need to cope with biophysical and socio-economic systems exposing farmers to a multidimensional decision- making environment. The rainfed wheat production in the Swartland region is highly susceptible to the interannual variability of winter rainfall. Producers, therefore, need relevant climatic information to identify ways to improve profitability and to make sound economic decisions. Seasonal forecasting has the potential to provide wheat producers with invaluable information regarding the climatic conditions. However, due to the complex nature of the atmospheric dynamics associated with winter rainfall in South Africa, seasonal forecasting models have been found to have very little skill in predicting the variability of winter rainfall. Such a shortfall has created a gap for which this study has attempted to bridge. This study aimed to investigate the relationship between wheat-specific rainfall characteristics, large-scale modes of climate variability and wheat yields in the Swartland region to assess whether these relationships could provide useful climatic information to the wheat farmers. Six wheat-specific rainfall characteristics (total rainfall; number of wet days; number of ‘good’ rainfall events; number of heavy rainfall events; percentage ‘good’ rainfall; and the number of dry dekads) on various time scales (winter; seasonal; monthly and dekadal) were correlated against wheat yield records over a 17 year period from 1994 to 2010. From this analysis, the distribution and timing of the rainfall throughout the wheat growing season (April to September) emerged as an important determinant of wheat yield. An accurate statistical wheat prediction model was created using farmer stipulated rainfall- wheat yield thresholds. Three teleconnections (El Niño-Southern Oscillation [ENSO], Antarctic Oscillation [AAO] and South Atlantic sea surface temperatures [SSTs]) represented by eight climate indices (Nino3.4 Index, Ocean Nino Index [ONI], Southern Oscillation Index [SOI], AAO index, Southern Annular Mode Index [SAM], South Atlantic Dipole Index [SADI], South Western Atlantic SST Index [SWAI] and South Central Atlantic SST Index [SCAI]), were correlated against wheat yield data over a 17 year period from 1994 to 2010. The relationships between the three teleconnections and wheat yield in the Swartland were established. Teleconnection-wheat yield correlations were found to be limited, with regards to the application of this information to farmers, due to the lack of a comprehensive understanding of the dynamics of how the three teleconnections influence the local climate and, therefore, the wheat yield in the Swartland. The eight climate indices, representing the three teleconnections, were correlated against the six wheat-specific rainfall characteristic indices from each of the three study areas over the period from 1980 to 2012. The state of ii Abstract ENSO during the first half of the year was shown to be correlated with rainfall characteristics during both the first (April to July) and second (July to September) halves of the wheat growing season; however, these correlations differed in their sign. Correlations suggested a negative phase of AAO was associated with above normal rainfall throughout the year across the Swartland region. Sea surface temperatures in the central South Atlantic during March to October showed significant negative correlations with rainfall during the latter half of the wheat growing season (July to October) across the Swartland region. This study presented evidence supporting the plausibility and validity for the use of the state of large-scale modes of variability in the prediction of wheat-specific rainfall characteristics and aggregated yields in the Swartland region. This has the potential to provide useful information to wheat farmers in the Swartland to aid in their decision making process. iii Table of Contents TABLE OF CONTENTS ABSTRACT .................................................................................................................................................ii TABLE OF CONTENTS ............................................................................................................................... iv LIST OF FIGURES ..................................................................................................................................... vii LIST OF TABLES ........................................................................................................................................ ix ACKNOWLEDGEMENTS ........................................................................................................................... xi PLAGIARISM DECLARATION.................................................................................................................... xii CHAPTER 1: INTRODUCTION ................................................................................................................... 1 1.1 Aim and objectives .................................................................................................................. 4 1.2 Thesis outline .......................................................................................................................... 5 CHAPTER 2: LITERATURE REVIEW............................................................................................................ 6 2.1 Wheat production in South Africa .......................................................................................... 6 2.1.1 The Swartland region ............................................................................................... 10 2.2 Climate and drivers ............................................................................................................... 12 2.3 Interannual rainfall variability ............................................................................................... 14 2.3.1 South Atlantic sea surface temperatures ................................................................ 14 2.3.2 Antarctic Oscillation ................................................................................................. 16 2.3.3 Antarctic sea ice extent ........................................................................................... 17 2.3.4 El Niño-Southern Oscillation .................................................................................... 17 2.4 Seasonal forecasting in South Africa ..................................................................................... 18 CHAPTER 3: METHODOLOGY ................................................................................................................. 24 3.1 Statistical methods ................................................................................................................ 24 3.1.1 Standardizing ........................................................................................................... 24 3.1.2 Correlation ............................................................................................................... 24 3.1.3 Linear detrending ..................................................................................................... 25 3.2 Datasets ................................................................................................................................. 25 3.2.1 Weather station data ............................................................................................... 25 3.2.2 Climate indices data ................................................................................................. 29 3.3 Data analysis ......................................................................................................................... 32 3.3.1 Association of precipitation with wheat yields ........................................................ 32 3.3.1.1 Winter rainfall ............................................................................................. 32 3.3.1.2 Seasonal rainfall.......................................................................................... 32 iv Table of Contents 3.3.1.3 Monthly rainfall .......................................................................................... 33 3.3.1.4 Dekadal rainfall and wheat thresholds ....................................................... 33 3.3.2 Association of climate indices with wheat yield ...................................................... 34 3.3.2.1 Correlation analysis .................................................................................... 34 3.3.2.2 Large-scale surface and atmospheric circulation pattern analysis ............ 34
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