Furthermore, the institutional support will also have to change dramatically. A system must be developed to identify the very best forecasters, train them, and monitor their progress. Such systems already exist in the public sector in areas such as the air traffic controllers of the Federal Aviation Administration. In many respects, the situation of air traffic controllers always on the alert for dangerous conditions and the operational meteorologists forecasting rare, severe events are similar. Although automated techniques can handle a large part of their duties, the human element remains essential, especially in situations in which failure to make a correct decision can result in significant danger to public safety.
Substantive training is a critical step in the process.
Since one effect of implementing our proposal would be a reduction in the number of meteorologists in the NWS, significantly more effort could be applied to the task of training entering meteorologists. Little effort has been made to date at identifying the traits that make a good weather forecaster. In fact, to our knowledge, no studies documenting how human beings make weather forecasts exist to show what skills, if any, good forecasters have in common. This seems to be an obvious place where effort should be expended if we are to expect human forecasters to make a difference in the quality and value of forecasts. During the initial training course, substantial time must be spent testing and evaluating a candidate's skill in forecasting.