The clear-air turbulence (CAT) forecast displayed in this web page is generated using the Graphical Turbulence Guidance (GTG) algorithm developed at the National Center for Atmospheric Research, Research Applications Program (NCAR/RAP) in Boulder, CO under sponsorship of the Federal Aviation Administration (FAA) Aviation Weather Research (AWR) Program and National Science Foundation (NSF). The algorithm is described in detail in Sharman and Cornman, "An Integrated Approach to Clear-Air Turbulence Forecasting," AIAA-98-0382.

The algorithm takes as input forecasted fields from the National Centers for Environmental Prediction (NCEP) Rapid Update Cycle (RUC-2) gridded aviation forecast model and turbulence observations within the last 1 1/2 hours and diagnoses CAT potential for the RUC-2 forecast times. These forecasts are updated every 3 and 6 hours. The turbulence diagnostic is a combination of some 23 common turbulence diagnostics or turbulence indices (e.g., wind shear, Richardson's number, Ellrod Indices, etc.) optimized to give the best agreement with available observations. These indices are most useful in forecasting upper level CAT associated with mountain waves, upper level fronts, and jet streams. Some of the more common diagnostics that were used in the GTG combination are displayed as contour maps of the maximum value of that index anywhere above 20,000 ft. The resulting GTG combination is shown as contour maps of predicted CAT intensity at flight levels 10,000 to 45,000 ft at 4,000 foot intevals. The prediction can be interpreted roughly as follows:

Note: This product is still experimental and presently under intensive evaluation. These predictions should therefore be used only with sufficient understanding of the atmospheric processes involved and errors inherent in their prediction. Note also this algorithm is presently intended to identify regions of upper-level CAT only, and is not intended to predict turbulence associated with convection and thunderstorm clouds. Future versions will include convective turbulence forecasts as well. Comments and suggestions should be addressed to sharman@ucar.edu.