Over the last few decades, weather systems have evolved from centralized functions within large data centers using mainframe computers to more distributed architectures. In this evolutionary process, systems grew to accommodate the latest scientific or technological advances. Some systems expanded methodically through planned growth, others as a necessity to keep up with the ever-increasing need to achieve more processing capacity from incremental improvements through life-cycle replacement of hardware.

On the technology side, software development has evolved from proprietary operating systems and applications to more open source development with greater platform and operating system independence. Requirements on weather systems are also evolving from a state of “weather data and products for weather forecasters” to “environmental data and impacts analyses for decision makers.” The forecaster still plays a key role in applying human intelligence in the forecasting process, but the requirement on systems creates a greater need for automated processes using a common, open architectural framework. These systems will feed environmental data and impacts to operational systems making decisions on resource protection, emergency management and other operation concerns within federal, state and local governments as well as in the private sector.

This paper describes a systematic approach to modernize weather systems using structured processes for requirements analysis, Use Case driven design and examples of practical applications to build future weather, water and climate processing systems. These systems must account for the continued need for weather data and products as we know them today while at the same time providing, as an example, geospatial data and products depicting environmental impacts for use by emergency managers.