One of the most difficult meteorological variables to skillfully predict with objective methods (predict subjectively, for that matter) is cloud amount and height, which are critical weather elements for the aviation industry. Most efforts in the past have concentrated on ceiling height, and these have seen some modest success. However, cloud layer information is important for producing a TAF (Terminal Aerodrome Forecast) and in-route forecasts. Producing these products is a challenging task for forecasters, and there has been little improvement in skill or accuracy over the past decade.

A new approach is being taken in LAMP to predict cloud layer information and ceiling height. As input, this approach will blend 10-km radar data, satellite data, and METAR observations with Model Output Statistics (MOS) guidance from the Aviation Model and other model data to predict both the amount and height of cloud layers and a consistent ceiling height. The statistical methods used will be presented along with examples and an assessment of success of the new approach.