Dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg for the Degree of Master of Science / Various techniques and procedures suited to monthly forecasting are investigated and tested. These include using the products generated by atmospheric general circulation models during a 17-year hindcast experiment, and downscaling the forecast circulation to regional rainfall in South Africa using circulation indices and canonical correlation analysis. The downscaling methods are evaluated using the cross-validation technique. Various model forecast bias-correction methods and skill-enhancing ensemble techniques are employed to improve the 30-day prognosis of the model. Forecasts from the general circulation model and each technique are evaluated. Those demonstrating reasonable skill over the southern Africa region, and which are feasible when considering available resources, are adopted into a strategy which can be used operationally to produce monthly outlooks. Various practical issues regarding the operational aspects of long-term forecasting are also discussed. / Andrew Chakane 2019

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Thesis (M.S.)--University of Wisconsin--Madison, 1984. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaf 67).

Thesis (M.S.)--University of Wisconsin--Madison, 1982. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 75-76).

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves 49-53). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves 49-53). Also available on the Internet.

Tung Wai Lan, Iris. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1990. / Bibliography: leaves 92-101. / ACKNOWLEDGEMENTS / ABSTRACT / LIST OF FIGURES --- p.iii / LIST OF TABLES --- p.iv / CHAPTER / Chapter I --- INTRODUCTION --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Significance of the Research --- p.3 / Chapter 1.3 --- Objectives of the Research --- p.5 / Chapter 1.4 --- Organization of the Research --- p.5 / Chapter II --- LITERATURE REVIEW --- p.7 / Chapter 2.1 --- Introduction --- p.7 / Chapter 2.2 --- Development of Long-Range Forecasting Technique --- p.8 / Chapter 2.3 --- Available Techniques of Long-Range Forecast --- p.9 / Chapter 2.3.1 --- Analogs and persistence --- p.10 / Chapter 2.3.2 --- Statistical modelling --- p.12 / Chapter 2.3.3 --- Atmosphere-ocean interaction --- p.17 / Chapter 2.3.4 --- Cycles and time series --- p.18 / Chapter 2.3.5 --- Numerical modelling --- p.19 / Chapter 2.4 --- Rainfall Prediction in Hong Kong --- p.21 / Chapter III --- RAINFALL OF HONG KONG --- p.24 / Chapter 3.1 --- Climatic Feature --- p.24 / Chapter 3.2 --- The Causes of Hong Kong Rainfall --- p.26 / Chapter 3.2.1 --- Tropical cyclone --- p.26 / Chapter 3.2.2 --- Trough or front --- p.28 / Chapter IV --- METHODOLOGY --- p.31 / Chapter 4.1 --- Introduction --- p.31 / Chapter 4.2 --- Empirical Orthogonal Function (EOF) Analysis --- p.32 / Chapter 4.2.1 --- What's EOF --- p.32 / Chapter 4.2.2 --- Why use EOF --- p.34 / Chapter 4.3 --- Discriminant Analysis --- p.36 / Chapter 4.4 --- Data Base --- p.37 / Chapter 4.5 --- Computation Procedures --- p.40 / Chapter 4.6 --- Analysis of Forecast Capability --- p.44 / Chapter V --- THE RESULT AND ANALYSIS OF PREDICTION MODEL --- p.48 / Chapter 5.1 --- The result of EOF analysis --- p.48 / Chapter 5.1.1 --- Extraction of eigenvectors and eigenvalues --- p.48 / Chapter 5.1.2 --- Spatial and Temporal variation of eigenvector pattern --- p.52 / Chapter 5.2 --- Accuracy of the prediction model --- p.53 / Chapter 5.2.1 --- Introduction --- p.53 / Chapter 5.2.2 --- The forecast accuracy from each month --- p.54 / Chapter 5.2.2.1 --- The forecast accuracy made by October --- p.54 / Chapter 5.2.2.2 --- The forecast accuracy made by November --- p.56 / Chapter 5.2.2.3 --- The forecast accuracy made by December --- p.58 / Chapter 5.2.2.4 --- The forecast accuracy made by January --- p.58 / Chapter 5.2.2.5 --- The forecast accuracy made by February --- p.61 / Chapter 5.2.2.6 --- The forecast accuracy made by March --- p.61 / Chapter 5.2.2.7 --- The forecast accuracy made by April --- p.64 / Chapter 5.2.3 --- Optimal length of dependent data --- p.64 / Chapter 5.2.4 --- Analysis the prediction results --- p.67 / Chapter 5.2.5 --- Comparison between the method used in this study with those methods adopted by ROHK --- p.69 / Chapter 5.2.5.1 --- Introduction --- p.69 / Chapter 5.2.5.2 --- Comparison of the forecast accuracy between two studies --- p.70 / Chapter VI --- CONCLUSION --- p.73 / Chapter 6.1 --- Summary of Findings --- p.73 / Chapter 6.2 --- Limitations of the Research --- p.75 / Chapter 6.3 --- Prospects of the Research --- p.76 / APPENDICES --- p.78 / LIST OF CITED REFERENCES --- p.92 / LIST OF READING MATERIALS --- p.97

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy. July 2014. / South Africa’s climate is highly variable, implying that the national agricultural sector should make provision to have early warning services in place in order to reduce the risks of disasters. More than 70% of natural disasters worldwide are caused by weather and climate or weather and climate related hazards. Reliable Seasonal Climate Forecasting (SCF) for South Africa would have the potential to be of great benefit to users in addressing disaster risk reduction. A disaster is a serious disruption of the functioning of a community or a society, causing widespread human, material, economic or environmental losses, which exceed the ability of the affected community or society to cope when using their own resources. The negative impacts on agricultural production in South Africa due to natural disasters including disasters due to increasing climate variability and climate change are critical to the sector. The hypothesis assumed in the study is the improved early warning service and better SCF dissemination lead to more effective and better decision making for subsequent disaster risk reduction in the agricultural sector. The most important aspect of knowledge management in early warning operations is that of distributing the most useful service to the target group that needs it at the right time. This will not only ensure maximum performance of the entity responsible for issuing the early warnings, but will also ensure the maximum benefit to the target group. South Africa is becoming increasingly vulnerable to natural disasters that are afflicted by localised incidents of seasonal droughts, floods and flash floods that have devastating impacts on agriculture and food security. Such disasters might affect agricultural production decisions, as well as agricultural productivity. Planting dates and plant selection are decisions that depend on reliable and accurate meteorological and climatological knowledge and services for agriculture. Early warning services that could be used to facilitate informed decision making includes advisories on iv future soil moisture conditions in order to determine estimated planting times, on future grazing capacity, on future water availability and on forecasts of the following season’s weather and climate, whenever that is possible. The involvement of government structures, obviously, is also critical in immediate responses and long term interventions. The importance of creating awareness, of offering training workshops on climate knowledge and SCF, and of creating effective early warning services dissemination channels is realized by government. This is essential in order to put effective early warning services in place as a disaster-risk coping tool. Early warning services, however, can only be successful if the end-users are aware of what early warning systems, structures and technologies are in place, and if they are willing that those issuing the early warning services become involved in the decision-making process. Integrated disaster-risk reduction initiatives in government programmes, effective dissemination structures, natural resource-management projects and communityparticipation programmes are only a few examples of actions that will contribute to the development of effective early warning services, and the subsequent response to and adoption of the advices/services strategies by the people most affected. The effective distribution of the most useful early warning services to the end-user, who needs it at the right time through the best governing structures, may significantly improve decision making in the agricultural, food security and other water-sensitive sectors. Developed disaster-risk policies for extension and farmers as well as other disaster prone sectors should encourage self-reliance and the sustainable use of natural resources, and will reduce the need for government intervention. The SCF producers (e.g. the South African Weather Service (SAWS)) have issued new knowledge to intermediaries for some years now, and it is important to determine whether this knowledge has been used in services, and if so whether these services were applied effectively in coping with disaster-risks and in disaster v reduction initiatives and programmes. This study for that reason also intends to do an evaluation of the knowledge communication processes between forecasters, and intermediaries at national and provincial government levels. It therefore, aims to assess and evaluate the current knowledge communication structures within the national agricultural sector, seeking to improve disaster-risk reduction through effective early warning services. A boundary organisation is an organization which crosses the boundary between science, politics and end-users as they draw on the interests and knowledge of agencies on both sides to facilitate evidence base and socially beneficial policies and programmes. Reducing uncertainty in SCF is potentially of enormous economic value especially to the rural communities. The potential for climate science to deliver reduction in total SCF uncertainty is associated entirely with the contributions from internal variability and model uncertainty. The understanding of the limitations of the SCFs as a result of uncertainties is very important for decision making and to end-users during planning. Disappointing, however, is that several studies have shown a fairly narrow group of potential users actually receive SCFs, with an even a smaller number that makes use of these forecasts In meeting the objectives of the study the methodology to be followed is based on knowledge communication. For that reason two types of questionnaires were drafted. Open and closed questionnaires comprehensively review the knowledge, understanding, interpretation of SCFs and in early warning services distribution channels. These questionnaires were administered among the SCF producers and intermediaries and results analysed. Lastly the availability of useful SCFs knowledge has important implications for agricultural production and food security. Reliable and accurate climate service, as one of the elements of early warning services, will be discussed since they may be used to improve agricultural practices such as crop diversification, time of planting vi and changes in cultivation practices. It was clear from the conclusions of the study that critical elements of early warning services need to receive focused attention such as the SCF knowledge feedback programme should be improved by both seasonal climate producers and intermediaries, together with established structures through which reliable, accurate and timely early warning services can be disseminated. Also the relevant dissemination channels of SCFs are critical to the success of effective implementation of early warning services including the educating and training of farming communities. The boundary organisation and early warning structures are important in effective implementation of risk reduction measures within the agricultural sector and thus need to be prioritised. Enhancing the understandability and interpretability of SCF knowledge by intermediaries will assist in improving action needed to respond to SCFs. Multiple media used by both SCF producers and intermediaries in disseminating of SCFs should be accessible by all users and end-users. The Government should ensure that farming communities are educated, trained and well equipped to respond to risks from natural hazards.

Thesis (Ph.D.)--University of Delaware, 2009. / Principal faculty advisor: Daniel J. Leathers, Dept. of Geography. Includes bibliographical references.

Thesis (Ph. D.)--Rijksuniversiteit te Utrecht, 1946. / Vita. Summary in Dutch. Includes bibliographical references.