The main challenges in predicting the weather are insufficient computational power and gaps in our understanding of the complex dynamics of atmospheric phenomena. There are comparatively straightforward solutions to these problems: enough teraflops, the right equations. But what happens when you have neither? This is the problem facing aviation turbulence forecasters, who are charged with the task of predicting turbulent conditions that would affect aircraft, but who have neither the computational resources to predict it explicitly nor a complete understanding of how to derive it accurately from available observation data. Yet, commercial and private aviation communities expect accurate, timely turbulence forecasts. The automated turbulence forecasting system currently funded by the Federal Aviation Administration's Aviation Weather Research Program (FAA/AWRP) and used by the National Oceanic and Atmospheric Administration's Aviation Weather Center (NOAA/AWC) integrates qualitative and quantitative reasoning about atmospheric conditions and observations to produce a forecast. This tool, called Graphical Turbulence Guidance (GTG), was developed by the National Center for Amospheric Research (NCAR) and NOAA's Global Systems Division (NOAA/GSD). This paper describes the structure and function of GTG and explores how to improve its turbulence forecasting using better data.
Full paper here.