Generalized exponential Markov and model output statistics: a comparative verification

The authors perform a comparative verification of model output statistics (MOS) against generalized exponential Markov (GEM), a single station forecasting technique that uses only surface observation and climatology as input. The verification was performed under three conditions: a scientific comparison, where both techniques use the same observation as input; an operational comparison, where GEM uses a later observation than MOS, to simulate the situation where a National Weather Service (NWS) forecaster preparing to make an aviation forecast has a later observation; and a special operational comparison, pitting GEM against MOS derived from the previous limited area fine mesh (LFM) cycle, to simulate the midmorning update operational situation in the NWS where the aviation forecast must be made by using previous LFM cycle MOS guidance. Verifications for ceiling, visibility, total cloud amount, temperature, dew-point depression, and wind speed-direction were performed on a full year of data (a warm and a cool season) for 21 stations across the U.S. GEM demonstrates improvement over MOS for the operational and special operational comparisons, with strongest showing on the major aviation elements: ceiling, visibility, and total cloud amount. For these major aviation elements, a skill crossover between GEM and MOS lies between 5 and 8 hr and between 3 and 5 hr for the remaining elements. For ceiling and visibility, experiments were performed blending the GEM and MOS probabilities, and the resulting categorical and probabilistic forecasts superior to those produced by GEM or MOS alone were found.