Fuzzy logic and case-based reasoning are leading methodologies for the application of artificial intelligence. We describe a system, WIND-1, that combines fuzzy logic and case-based reasoning to produce forecasts of airport cloud ceiling and visibility. Knowledge about meteorological and temporal features that experienced forecasters use to construct analogous climatological scenarios is encoded in a fuzzy similarity measure. The fuzzy similarity measure is used to locate k-nearest neighbors from airports' historical databases. These nearest neighbors are adapted to produce values of forecast parameters. Experiments show that the WIND-1 system produces highly accurate forecasts. It takes about one second for WIND-1 to produce a forecast.