Simultaneous modelling of rainfall occurrence and amount using a hierarchical nominalordinal support vector classifier
In this paper we propose a novel computational system for simultaneous modelling and prediction of rainfall occurrence and amount. The proposed system is based on a hierarchical system of nominalordinal support vector classifiers, the former focussed on the prediction of the rainfall occurrence, and the latter centered in the expected rainfall amount from a set of three different ordinal classes. In addition to the proposed model, we use a novel set of predictive meteorological variables, which improve the classifiers performance in this problem. We evaluate the proposed system in a real problem of rainfall forecast at Santiago de Compostela airport, Spain, showing that the system is able to obtain an accurate prediction of occurrence and rainfall amount, and we discuss the usefulness of the proposed system as part of the airport weather forecast and warning system, in order to improve airport operations.
rainfall occurrence rainfall amount nominal and ordinal classifiers ordinal regression