An approach for meteorological data integration and stream processing

Abstract

Real-time big data processing is a crucial need of meteorology today. As a matter of fact, the weather is a determining factor in decision making in different areas such as air or sea transport, so acquiring knowledge of the environment in real time is a consequential question. A promising approach for big data treatment in real time is based on the concept of complex events processing CEP). The CEP aims to identify significant events in a cloud of simple and individually detectable events in real time. The meteorological variables, constituting simple event's spaces, offer significant flow of data to be processed using CEP technologies. This real-time data processing is done by phase of their integration with weather systems. This paper discusses the big data's meteorological aspects, and shows the architectural model for integration of weather data and its processing in real time.