Presentation PDF (1.2 MB)
First, we consider benefits quantification based on feedback from experienced users of a system. Feedback on average benefits from a system at the end of a test period was used to generate delay reduction estimates for the Integrated Terminal Weather System (ITWS), the ASR-9 Weather System Processor (WSP), and the Weather and Radar Processor (WARP). A new refinement to that procedure augments the approach by analyzing flight tracks during convective weather before and after the system under testing was deployed. This end-of-season interview approach was found not to be viable in highly congested en route airspace. Hence, a new approach was developed for Corridor Integrated Weather System (CIWS) benefits assessment that uses real time observations of product usage during convective weather events, coupled with in depth analysis of specific cases.
Several recent initiatives that attempted to quantify delay reduction benefits by comparing flight delays before and after a system deployment are discussed. This seemingly simple approach has proven very difficult in practice because the convective weather events in the different time periods are virtually never identical , and because other aspects of the NAS may also have changed (e.g., user demand, fleet mix, and other systems that impact convective weather delays). It has become clear that one needs a quantitative model for the NAS that permits adjustment of measured delay data to account at least for the differences in convective weather and changes in user demand (i.e., flight scheduling).
We describe a model under development for estimating NAS delays in the presence of convective weather that can be used as a tool for assessing delay reduction benefits of specific systems, estimating the available pool for convective weather delay reduction, and determining if the overall NAS is performing better in management of convective weather over time. This model considers:
both en route and terminal capacity loss due to convective weather,
the non linear dependence of queue delays on demand and capacity, and
detailed knowledge of the NAS route structure.
The paper concludes with recommendations for measuring near term benefits of various classes of convective weather decision support systems.