The usefulness of RAPT guidance is dependent upon both the accuracy of the CWAM and the accuracy of the weather forecasts provided by CIWS. Significant efforts are underway to understand and validate the CWAM models. However, to date, limited effort has been invested in providing a measure of the weather forecast accuracy that can be readily translated into impact uncertainty. The best modeling of pilot behavior in the presence of convective weather is of limited use when forecasting future route blockage or sector capacity if the forecasted weather is inaccurate.
In this paper, we will begin to look at novel ways to provide information on the accuracy of a weather forecast and a measure of the forecast's ability to predict convective weather impacts on airways and air traffic flows. This will require two areas of effort needed to improve the usefulness of these planning tools.
The first area of effort involves developing new techniques to score the weather forecasts that are specific to Air Traffic Management (ATM) applications. Current methods to score the accuracy of weather forecasts use very specific localized comparisons of precipitation levels or apply very broad measures to large areas. Comparing high resolution (1 km) data from a system such as CIWS produces results which can be affected by small variations in the weather which may not be of concern to ATM operations. However, applying broad measures such as the area coverage of VIP level 3 Precipitation do not take into account the spatial scale and geometric orientation of air routes.
The second area of effort involves developing methods to predict the accuracy of weather forecasts from current information. To date, systems such as CIWS provide forecast accuracy information based upon scoring the algorithms performance over the past 15-120 minutes. Analysis has shown that the past performance of the forecast do not necessarily reflect the future performance. Any attempt to provide a user or decision support tool with the uncertainty of a forecast must be able to predict the uncertainty based upon the current state of the weather conditions, such as weather type, time of day, etc.
This work was sponsored by the Federal Aviation Administration under Air Force Contract No. FA8721-05-C-0002. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the United States Government.