A meteorological conceptual modeling approach based on spatial data mining and knowledge discovery

Abstract

Conceptual models play an important part in a variety of domains, especially in meteorological applications. This paper proposes a novel conceptual modeling approach based on a two-phase spatial data mining and knowledge discovery method, aiming to model the concepts of the evolvement trends of Mesoscale Convective Clouds (MCCs) over the Tibetan Plateau with derivation rules and environmental physical models. Experimental results show that the proposed conceptual model to much extent simplifies and improves the weather forecasting techniques on heavy rainfalls and floods in South China. © Springer-Verlag Berlin Heidelberg 2005.