published_or_final_version / abstract / toc / Geography / Master / Master of Geographic Information System

published_or_final_version / Physics / Master / Master of Philosophy

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

published_or_final_version / Applied Geosciences / Master / Master of Science