An Automated, Observations-Based System for Short-Term Prediction of Ceiling and Visibility

Abstract

Several methods of generating very short term (0?6 h) probabilistic forecasts of ceiling and visibility are investigated: 1) an observations-based (OBS-based) system in which potential predictors consist of weather observations from a network of surface stations along with several climatic terms; 2) the traditional model output statistics (MOS)-based approach in which potential predictors consist of nested grid model (NGM) output, the latest observation from the forecast site, and climatic variables; and 3) persistence climatology in which potential predictors consist of the latest observation of the predictand variable from the forecast site and several climatic terms. Forecasts are generated for each technique on 2 yr (1993?94) of independent data for 25 stations in the eastern United States. Two variables (ceiling and visibility) are forecasted for eight thresholds, two initial times (0300 and 1500 UTC), and three lead times (1, 3, and 6 h). Results show that the OBS-based method is superior to persistence climatology at all lead times and all variable thresholds. This is encouraging since persistence climatology is widely recognized as a formidable benchmark for very short range prediction of ceiling and visibility. Verifications also show that the OBS-based system outperforms the traditional MOS-based technique at the 1- and 3-h lead times with skill improvements of four percentage points. Based upon historical values of improvements in skill, this gain corresponds to roughly a half decade of scientific advancement. Performance of the OBS- and MOS-based systems are similar at the 6-h projection, which appears to be near the crossover point when the NGM guidance becomes more important than the observations in terms of predictive input. These findings indicate that traditional MOS-based techniques for the very short term prediction of aviation weather parameters can be improved significantly by considering information from a network of surface observations. Furthermore, the improvements of the OBS-based system over the MOS-based method represent the minimum that can be expected since the test comparison of the two methods was intentionally constructed to maximize the performance of the MOS-based procedure. Still further, forecasts from an OBS-based system can be available within seconds of receiving the observations. Therefore, OBS-based systems are likely to be of far greater utility for making very short term forecasts than other traditional forms of guidance.