Browsing by Author "Jack, Christopher"

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    A CMIP5 Model Selection Specific to South Africa's Winter Rainfall Zone
    (2022) Marsh, Peter; Jack, Christopher
    This study undertakes a CMIP5 model selection specific to the Winter Rainfall Zone (WRZ) of South Africa, seeking to reduce the range of future climate projections through identifying a subset of models with increased realism and independence. In order to navigate the subjectivity in identifying relevant circulation metrics to assess models against, the ‘Day Zero' drought is used as a characteristic episode. Here initially the extensive literature produced subsequent to the drought has been drawn on to identify and evaluate relevant regional process metrics, before utilising the anomalous conditions during the drought to validate various assessment methods. The dynamics subsequently identified as being most influential to rainfall supply in the WRZ include the South Atlantic subtropical jet stream responsible for steering of mid-latitude storm systems, the South Atlantic subtropical high, and the presence, or preferably absence, of precipitation blocking subsidence, and the prevalence of mid-latitude storm systems, critical for transport and upliftment of moisture to the region. Models were subsequently assessed against these metrics and scored following the technique of McSweeney et al. (2015). Unrealistic models were removed from the ensemble while significantly biased models were also excluded as their absence did not significantly reduce the range of future projections. The same scoring methods were then utilised to create a genealogy of models attaining similar results to that of Knutti, Masson & Gettelman (2013). A subset of 6 CMIP5 models which are more independent and historically more realistic than that of the full ensemble were subsequently identified. While the range of future temperature projections of the final ensemble are somewhat constrained in comparison to the full ensemble, the primary utility is argued to be the reduced number of models where a future researcher may consider each model's projected future climate pathway individually before selecting a model, or models, which best informs their use case, whilst being assured that this model performs suitably well in the region and that the initial ensemble considered adequately represents model uncertainty, while strong similarity between two or more models within the ensemble will not be unduly biasing results.
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    Application of Systems-Approach in Modelling Complex City-Scale Transdisciplinary Knowledge Co-Production Process and Learning Patterns for Climate Resilience
    (2021-01-22) Mkandawire, Burnet; Thole, Bernard; Mamiwa, Dereck; Mlowa, Tawina; McClure, Alice; Kavonic, Jessica; Jack, Christopher
    Literature shows that much research has been conducted on the co-production of climate knowledge, but it has neither established a standardized and replicable model for the co-production process nor the emergent learning patterns as collaborators transition from the disciplinary comfort-zone (disciplinary and practice biases) to the transdisciplinary third-space. This study combines algorithmic simulation modelling and case study lessons from Learning Labs under a 4-year (2016–2019) climate change management project called Future Resilience of African CiTies and Lands in the City of Blantyre in Malawi. The study fills the research gap outlined above by applying a systems-approach to replicate the research process, and a Markov process to simulate the learning patterns. Results of the study make a number of contributions to knowledge. First, there are four distinct evolutionally stages when transitioning from the disciplinary comfort-zone to the transdisciplinary third-space, namely: Shock and resistance to change; experimenting and exploring; acceptance; and integration into the third-space. These stages are marked by state probabilities of the subsequent stages relative to the initial (disciplinary comfort-zone) state. A complete transition to the third-space is marked by probabilities greater than one, which is a system amplification, and it signifies that there has been a significant increase in learning among collaborating partners during the learning process. Second, a four-step decision support tool has been developed to rank the plausibility of decisions, which is very hard to achieve in practice. The tool characterizes decision determinants (policy actors, evidence and knowledge, and context), expands the determinants, checks what supports the decision, and then rates decisions on an ordinal scale of ten in terms of how knowledge producers and users support them. Third, for a successful transdisciplinary knowledge co-production, researchers should elucidate three system-archetypes (leverage points), namely: Salient features for successful co-production, determinant of support from collaborators, and knowledge co-production challenges. It is envisioned that academics, researchers, and policy makers will find the results useful in modelling and replicating the co-production process in a methodical and systemic way while solving complex climate resilience development problems in dynamic, socio-technical systems, as well as in sustainably mainstreaming the knowledge co-produced in policies and plans.
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    Dynamics of co-behaviour of climate processes over Southern Africa
    (2021) Quagraine, Kwesi Akumenyi; Hewitson, Bruce; Jack, Christopher; Lennard, Christopher
    Large-scale climate processes such as El Niño-Southern Oscillation (ENSO), Antarctic Oscillation (AAO), and many others, play varying roles in regional climate variability across the world. While the role of singular processes have been explored in many studies, the combined influence of multiple large-scale processes has received far less attention. Key to this is the challenge of developing methodologies to support the analysis of multiple processes interacting in potentially non-linear ways (co-behaviour) in a particular region. This study details the development of such a methodology and demonstrates its utility in the analysis of the co-behaviour of largescale process interactions on regional precipitation and temperature variability over southern Africa. The study defines co-behaviour as the interaction of large-scale processes that may influence regional circulation leading to climate variability. A novel methodology which involves a combination of analysis techniques such as Self-Organizing Maps (SOM) and Principal Component Analysis (PCA) is developed to identify and quantify such co-behaviour which accommodates potentially non-linear interactions. This methodology is evaluated in the context of southern African regional climate using three key processes, namely ENSO, AAO and Inter-tropical Convergence Zone (ITCZ), and characterizations of regional circulation, and temperature and rainfall variability. Analysis of co-behaviour under observed conditions identifies results that concur with prior studies, in particular the dominant regional response to ENSO, but also establishes key examples of co-behaviour such as the role of the AAO in moderating and altering the regional response to ENSO which is important for understanding regional climate variability. Application of the approach to Global Climate Model (GCM) simulations of past climate reveals that while many GCMs are able to capture individual processes, in particular ENSO, they fail to adequately represent regional circulation variability and key observed co-behaviour. The study therefore clearly demonstrates the importance of co-behaviour in understanding regional climate variability as well as showing the usefulness of the new methodology in investigating co-behaviour. Finally, the new insights into evaluating model performance through the lens of core climate processes and their interaction provides a significant step forward in both model development and application for decision making.
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    The role of values, norms and affect in relation to water-scarcity risk perceptions and water conservation behaviours in the Western Cape
    (2024) Tredoux, Aimée; Pasquini, Lorena; Enqvist, Johan; Steynor, Anna; Jack, Christopher
    The effects of accelerating climate change are already being felt globally. Sub-Saharan Africa is at high risk of extreme hydrological events, and increasingly severe and frequent droughts pose a threat to water security in the region. As the impacts of climate change are expected to increase, it is important to promote adaptation to drought events by studying the factors that can influence water saving behaviour. The present work studied how three categories of risk perception determinants namely values, social norms and affect, influenced water scarcity risk perceptions and water saving behaviour during the Western Cape drought of 2014-2017 in an urban population living in formal housing in the City of Cape Town. The outcomes of this study are two-fold. Firstly, this research provides evidence for the usefulness of a conceptual framework rooted in risk perceptions literature for understanding how affect, social norms and values fit together with risk perceptions to explain pro-environmental (water saving) behaviour. Secondly, the findings add to the literature on risk perception determinants, water scarcity risk perceptions, and water saving behaviour by showing that fear, self-transcending values, hedonism, and descriptive and prescriptive norms were important factors in shaping water scarcity risk perceptions and water conservation behaviour during the drought. In future drought contexts, the revised framework and the risk perception determinant findings could be drawn on to help understand how values, social norms and affect interact with water scarcity risk perceptions to influence water conservation behaviour.