89th American Meteorological Society Annual Meeting

Tuesday, 13 January 2009: 2:00 PM
NAS Weather Index: quantifying impact of actual and forecast en-route and surface weather on air traffic
Room 132A (Phoenix Convention Center)
Alexander Klein, Air Traffic Analysis, Inc, Fairfax, VA; and T. MacPhail, S. Kavoussi, D. Hickman, and M. Phaneuf
Poster PDF (1.1 MB)
The paper presents our accomplishments in the last 12 months in the development of the NAS Weather Index (NWX) based on actual en-route and surface weather as well as scheduled air traffic, and its Forecast Accuracy (NWX-FA) counterpart using forecast weather. This index is also known as the Weather Impacted Traffic Index, or WITI; the research, development and implementation activities are jointly funded by the FAA and NOAA/NWS. The NAS Weather Index quantifies the impact of en-route convective weather and surface weather on the nations's major airports and compares this "front-end" impact on the NAS with the operational outcomes such as delays, cancellations, etc. The index shows high correlation with these operational outcome metrics. The NWX-FA metric quantifies the perceived impact of the forecast en-route/surface weather on the same airports; we have developed methods that convert area-based or gridded probabilistic en-route weather forecasts (CCFP, NCWF, other) into gridded quasi-deterministic format (NCWD), and also convert a probabilistic surface weather forecast (TAF) into quasi-deterministic format (METAR). These methods have been validated in our prior research, and their description, as well as validation, is re-capped in this paper in brief.

The original NWX metric consists of three components: En-route WITI, Terminal WITI, and Airport Queuing Delay. The first two components are linear ("weather weighted by traffic" type) while the third, Airport Queuing Delay, captures the non-linear nature of response of a capacity-constrained airport to excess traffic demand. To this we have now added a fourth component, the Airspace Queuing Delay, which reflects the non-linear system response to airspace capacity degradation caused by convective weather. The complete NWX and its NWX-FA counterpart are tracked on a daily basis; detailed weekly reports, including in-depth analysis of specific days with heavy weather impact and/or major gaps between NWX and Delay, are provided to the FAA and the National Weather Service management. We also track NWX components (convective and non-convective) separately against their "FA" (forecast-based) counterparts and the NAS delays.

In case of non-convective weather impacts, we compute and report on individual weather factors, such as low ceilings, wind, snow and others, so that each weather factor's contribution to weather impact on the NAS, its regions or individual airports can be quantified on a daily or even hourly basis. The total of seven components that comprise the NWX for an airport are visualized as a "Airport Weather Impact Day-at-a-Glance" color charts / matrices. These matrices can be compared and for any given day / airport, a multi-year database can be searched to find days with most-similar weather impact. Then, system responses (e.g., delays) can be compared for sets of similar-impact days and their variability, as well as the role of weather forecast, can be studied.

We provide examples of in-depth analyses, including cases of over- or under-forecast of convective weather and the analysis of hourly airport arrival rates. The latter are computed and presented as four charts: scheduled arrival rates, actual arrival rates, as well as WITI model-estimated arrival rates based on actual (METAR) and forecast (TAF) weather. Cases are discussed where the actual arrival rates fall well short of scheduled and are aligned with TAF-based rates which are in turn lower than METAR-based rates; this would indicate an over-forecast that may have led to restrictive Ground Delay Programs at the affected airports.

Finally, new applications of the NAS Wx Index methodology are outlined. They represent work-in-progress as well as planned next steps and include the comparison of different convective forecast products and the logical extension of the historical analysis methodology into operational environment where the impact on traffic can be predicted based on the available weather forecast.

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