products in the next 5 to 10 years. Current limitations in predictive capabilities due to uncertainties in initial conditions and model formulation will likely require a longer research effort to provide marked improvements. In the meantime, probabilistic approaches can provide meaningful information for managing the nation’s airspace.

The aviation traffic flow system is essentially a never-ending sequence of decisions. For such systems there is a wealth of information available on how to optimize decision making in a manner that minimizes costs, maximizes benefits, or both. For example, the utility and insurance industries routinely make decisions based on reliable1 probabilistic information. With probabilistic guidance and estimates of the respective costs of yes-or-no decisions, it is possible to determine threshold probabilities above which, when averaged over many events, the ratio of costs to benefits is optimized. Such threshold probabilities transform probabilistic guidance into optimal “black-white” decisions (e.g., whether to expect having to take an alternate route to avoid expected adverse weather and therefore having to load extra fuel). Moreover, reliable probabilistic guidance makes it possible to define a uniform and consistent set of criteria on which to base operational decisions.

For example, suppose the aviation traffic flow system mandated that pilots do not try to navigate through areas of thunderstorms once the percent-area coverage exceeds a certain threshold.2 If such a guideline were in place, it would be highly desirable to have aviation weather guidance that provides reliable probabilities of the critical percent-area coverage. This type of system is possible with current technology, though increased spatial resolution of the next generation of numerical models likely will allow much better guidance by better resolving the location, organization, and orientation of convection exceeding the critical percent-area coverage. With such

1  

As used here, “reliable” means that the probabilities are true (i.e., unbiased). For example, for a large sample of decisions, if one examines the subset of all events for which a probability of 40 percent was forecast, the event will occur 40 percent of the time if the probabilities are reliable.

2  

In practice, the choice of a percent-area coverage threshold would have to be based on air traffic control operational issues, such as the probability that principal routes in a region would be impacted by the weather and the effective tactical capacity of that region (e.g., whether planes could be expected to fly around convective cells in the region). To relate percent coverage to these air traffic control issues will require additional information on the type of convective weather forecast, the expected spatial orientation of the convective weather, and the dominant routes in a region (e.g., north-south, east-west, or all directions).



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