The Role of Local High Resolution Models in the Evolving National Weather Service: Decision Support and Situational Awareness

Weather forecasters have a number of tools at their disposal, including an expansive network of near real-time meteorological observations, satellite, and radar data to depict the current state of the atmosphere -- and global and regional numerical forecast models to depict the future state of the atmosphere. Advances in computer and network technologies in recent decades have facilitated rapid growth in the field of meteorological modeling. These advancements have yielded numerous benefits to operational meteorologists. Of these, the capability to develop and implement high-resolution models has become a vital asset. Models with grid-spacing less than 4 km and update latency less than 3 hr have become a cornerstone of short-range forecasting in National Weather Service field offices. These models have been particularly helpful in developing heightened situational awareness, resulting in enhanced decision support services to end users, particularly during high impact weather events.

Over the last decade, the role of NWS meteorologists has evolved from primarily composing short and long-term forecasts to providing time-sensitive and detailed short-fuse forecast updates during high impact weather events. These updates require knowledge of both the current and expected future state of the atmosphere. High-resolution models have allowed forecasters to go beyond the observed, predicting the evolution of critical weather features out to several hours, in time intervals of 15 min or less. This degree of detail is essential in developing robust decision-making aids intended for dissemination to our primary partners during life-threatening events.

Since 2007, the NWS forecast office in Norman, Oklahoma has run a localized Weather Research and Forecasting (WRF) model. This model, known as the OUNWRF, is a convection-allowing model capable of depicting derived reflectivity, updraft helicity, maximum wind speed, and many other useful fields. During active severe weather outbreaks, these data have proved essential in enhancing both situational awareness and decision support at the Norman office.

Selected cases have been analyzed to showcase the effectiveness of the OUNWRF in depicting the timing, evolution, and mode of convection during high impact severe weather events. Model output was interpreted and used to develop graphicasts, Web briefings, and other products to relay to the primary partners in the NWS Norman county warning area. This presentation will show the effectiveness of the OUNWRF in enhancing situational awareness and providing decision support to primary partners that have a common goal of protecting life and property from threatening weather.