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The main objectives of a meteorological service are the development, implementation and delivery of weather forecasts. Weather predictions are broadcasted to society through different channels, i.e. newspaper, television, radio, etc. Today, the use of the Web through personal computers and mobile devices stands out. The forecasts, which can be presented in numerical format, in charts, or in written natural language, have a certain margin of error. Providing automatic tools able to assess the precision of predictions allows to improve these forecasts, quantify the degree of success depending on certain variables (geographic areas, weather conditions, time of year, etc.), and focus future work on areas for improvement that increase such accuracy. Despite technological advances, the task of verifying forecasts written in natural language is still performed manually by people in many cases, which is expensive, time-consuming, and subjected to human errors. On the other hand, weather forecasts usually follow several conventions in both structure and use of language, which, while not completely formal, can be exploited to increase the quality of the verification. In this paper, we describe a methodology to quantify the accuracy of weather forecasts posted on the Web and based on natural language. This work obtains relevant information from weather forecasts by using ontologies to capture and take advantage of the structure and language conventions. This approach is implemented in a framework that allows to address different types of predictions with minimal effort. Experimental results with real data are promising, and most importantly, they allow direct use in a real meteorological service.

AEMIX: Semantic Verification of Weather Forecasts on the Web