Improving forecasts of clear-air turbulence at NOAA's Aviation Weather Center with state-of-the-art diagnostics

The forecasting of clear air turbulence (CAT) remains a difficult problem in operational meteorology and has the highest priority for research in the current National Weather Service (NWS) Strategic Plan. Despite recent improvements in forecast techniques, commercial aircraft encounter severe, or greater, turbulence about 5000 times each year, the majority of which occur above FL 100. These incidents lead to tens of millions of dollars in injury claims per year and force commercial airlines to ground affected aircraft to inspect the airframes for damage, resulting in additional significant costs to the airlines.

We will discuss a cooperative COMET/NWS project that began in summer 2009 which is attempting to improve the accuracy of operational CAT forecasting at the NOAA/NWS/NCEP Aviation Weather Center (AWC). The project focuses on the implementation and testing of new state-of-the-art diagnostic indices. One of the new objective approaches involves application of the theory of spontaneous imbalance (Ford 1994; Knox et al. 2008) to predict regions of the atmosphere where the generation of intense gravity wave activity is likely to occur. Validation of this technique has shown higher skill than existing algorithms for moderate-or-greater turbulence.

A second approach to be tested is a modification of the deformation-vertical shear index (or TI as described by Ellrod and Knapp 1992) now in operational use at AWC and other global forecast centers. The TI is modified by a divergence trend term that may improve the performance of this index in both cyclonic and anticyclonic flows. Preliminary verification has shown that this approach has greater skill than the basic TI.

In collaboration with AWC meteorologists, both of the new diagnostics will be evaluated in the AWC Aviation Weather Testbed using state-of-the-art numerical models (GFS, NAM, RUC, SREF, etc.) over the two-year period of the project in parallel with current operational diagnostics. Initial results of the evaluation and operational examples will be presented.