William R. Moninger

A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh

AbstractThe Rapid Refresh (RAP), an hourly updated assimilation and model forecast system, replaced the Rapid Update Cycle (RUC) as an operational regional analysis and forecast system among the suite of models at the NOAA/National Centers for Environmental Prediction (NCEP) in 2012. The need for an effective hourly updated assimilation and modeling system for the United States for situational awareness and related decision-making has continued to increase for various applications including aviation (and transportation in general), severe weather, and energy. The RAP is distinct from the previous RUC in three primary aspects: a larger geographical domain (covering North America), use of the community-based Advanced Research version of the Weather Research and Forecasting (WRF) Model (ARW) replacing the RUC forecast model, and use of the Gridpoint Statistical Interpolation analysis system (GSI) instead of the RUC three-dimensional variational data assimilation (3DVar). As part of the RAP development, modif...

Effects of improved information on the components of skill in weather forecasting

Abstract The relation between the amount and quality of information available to meteorologists and the accuracy of their forecasts of a highly uncertain event (severe weather) was investigated. In three studies, meteorologists made forecasts under a total of four different information conditions. Forecast accuracy was low, and as the amount and quality of the information increased substantially, there was a modest increase in the accuracy of forecasts. The results suggest that subjective factors, particularly the reliability of forecasts, deteriorated with additional information.

Analysis of Expert Judgment in a Hail Forecasting Experiment

Abstract This study compared meteorologists, an expert system, and simple weighted-sum models in a limited-information hail forecasting experiment. It was found that forecasts made by meteorologists were closely approximated by an additive model, and that the model captured most of their forecasting skill. Furthermore, the additive model approximated the meteorologists’ forecasts better than the expert system did. Results of this study am consistent with the results of extensive psychological research on judgment and decision making processes. Potential implications are discussed.

Evaluation of Regional Aircraft Observations Using TAMDAR

Abstract A multiyear evaluation of a regional aircraft observation system [Tropospheric Aircraft Meteorological Data Reports (TAMDAR)] is presented. TAMDAR observation errors are compared with errors in traditional reports from commercial aircraft [aircraft meteorological data reports (AMDAR)], and the impacts of TAMDAR observations on forecasts from the Rapid Update Cycle (RUC) over a 3-yr period are evaluated. Because of the high vertical resolution of TAMDAR observations near the surface, a novel verification system has been developed and employed that compares RUC forecasts against raobs every 10 hPa; this revealed TAMDAR-related positive impacts on RUC forecasts—particularly for relative humidity forecasts—that were not evident when only raob mandatory levels were considered. In addition, multiple retrospective experiments were performed over two 10-day periods, one in winter and one in summer; these allowed for the assessment of the impacts of various data assimilation strategies and varying data re...

Shootout–89, A Comparative Evaluation of Knowledge-based Systems That Forecast Severe Weather

During the summer of 1989, the Forecast Systems Laboratory of the National Oceanic and Atmospheric Administration sponsored an evaluation of artificial-intelligence-based systems that forecast severe convective storms. The evaluation experiment, called Shootout-89, took place in Boulder, Colorado, and focused on storms over the northeastern Colorado foothills and plains. Six systems participated in Shootout-89: three traditional expert systems, a hybrid system including a linear model augmented by a small expert system, an analogue-based system, and a system developed using methods from the cognitive science/judgment analysis tradition. Each day of the exercise, the systems generated 2–9-h forecasts of the probabilities of occurrence of nonsignificant weather, significant weather, and severe weather in each of four regions in northeastern Colorado. A verification coordinator working at the Denver Weather Service Forecast Office gathered ground-truth data from a network of observers. The systems were evalu...

The Weather Information and Skill Experiment (WISE): The Effect of Varying Levels of Information on Forecast Skill

Abstract The relationship between the quality and quantity of information available to meteorologists and the skill of their forecasts was investigated. Twelve meteorologists were asked to make probabilistic forecasts of significant and severe weather events under three information conditions. Forecast accuracy was generally low. As the amount and quality of the information increased substantially, there was a modest increase in the accuracy of the forecasts. However, the results suggest that the forecasters were least consistent when they had the most information to work with, partially reducing the benefits of the increased information.