Deterministic and Probabilistic prediction approaches in Seasonal to Inter-annual climate forecasting

Abstract

Many countries in Africa are prone to extreme weather and climate events and these events have in the past had major negative impacts on various sectors of the economy including agriculture, health, food security, energy and other key social and economic sectors of these countries. Floods and drought has been a common feature in the recent past resulting in massive destruction of property, loss of life, diseases, and food shortages among many other socio-economic miseries. Recent advances in the science of weather and climate prediction and in particular, seasonal to interannual prediction has made it possible to predict climate with improved accuracy in a time-spans ranging from seasons to over one year in advance. Such knowledge can successfully be used to enhance agricultural production and minimise loss of life and property as well as provide critical information for decision-making. The objective of this presentation is to highlight some of the approaches to deterministic and probabilistic seasonal to interannual climate prediction applicable to Africa. We shall briefly start by introducing some basic concepts of probability and statistics