This paper examines the life cycle of actionable weather information from the time of raw observations to the time a user receives the actionable information. Specific emphasis is placed on the challenges of providing timely warning information and how different segments or components of the life cycle impact the amount of time available to generate the warning. The life cycle is broken into components and the interactions and contributions of the components are examined with regard to the overall life cycle. Several example types of specific warnings are examined to analyze the user impact.

The analysis of specific warnings includes a look at the types of observations and the time component of assimilating these observational data into the different types of predictions models. In addition, some warnings rely on the timely dissemination of observational data for geospatial evaluation by a field expert. Each of these prediction processing methods affects the overall actionable weather information life cycle.

A connection between the potential improvements for each portion of the life cycle and the user is also discussed. The emphasis is how to improve each life cycle component to ultimately provide more timely warning information to the end user. The consideration of these improvements will potentially lead to further technical studies leading to extended lead times and the increased likelihood of protecting life and property.