Meteorological bulletin automatic generation based on spatio-temporal reasoning

Meteorological bulletin has more and more diversified, large scale, highly integrated requirements and potential demands from whole society. The strong professional efforts involved in transforming the variety of special meteorological data to natural language text are becoming more challenging in providing sophisticated and easily understood weather features. This paper presents a new Meteorological bulletin automatic generation method based on spatio-temporal reasoning. To enhance an exact and non-redundant description for complex meteorological data, and for special future tendency dynamics in emerged interesting areas. We also evaluate this method with real data from National Meteorological Center and prove that it's feasible and effective after implementing.