13th Conference on Applied Climatology and the 10th Conference on Aviation, Range, and Aerospace Meteorology

Thursday, 16 May 2002: 8:45 AM
Predicting Clear-Air Turbulence from Diagnosis of Unbalanced Flow
Steven E. Koch, NOAA/FSL, Boulder, CO; and F. Caracena
Poster PDF (1.9 MB)
The FAA Aviation Weather Research Program has funded the Turbulence Product Development Team (PDT) to produce forecasts of clear-air turbulence (CAT) with the Rapid Update Cycle (RUC) model developed at Forecast Systems Laboratory and run operationally at the National Centers for Environmental Prediction (NCEP). Diagnostic algorithms applied to the RUC model 0-12h forecasts have been developed by the PDT and incorporated into a fuzzy logic process known as the Integrated Turbulence Forecast Algorithm (ITFA), which has been shown to be statistically superior to any single one of its component algorithms. Unfortunately, moderate-or-greater pilot reports of turbulence (MOG PIREPS) often tend to fall in the margin areas of the ITFA patterns. In addition, most of the algorithms typically predict patterns that are rather similar to one another, and they display essentially identical Probability of Detection curves (with considerable room for improvement). These deficiencies likely exist because the current algorithms share a fundamentally similar physical basis related to the destabilizing dynamics of vertical wind shear — either directly (as with the Richardson Number), or implied (as in the case of Ellrod’s frontogenetic forcing or the formulation of the DTF Turbulent Kinetic Energy approach).

We have developed a turbulence prediction scheme that produces patterns systematically different from the current methods and have shown its ability to predict the occurrence of MOG PIREPS missed by those methods. Our scheme is based on the notion that mesoscale gravity waves (MGW) systematically occur when an unbalanced jet streak propagates toward an inflection axis in the upper-level height field. Results from several detailed case studies show that PIREPS and MGW diagnosed from surface mesoanalysis both consistently occur just downstream of the region of diagnosed flow imbalance, provided that an efficient wave duct is present. Mesoscale models like RUC have been found to be very useful for diagnosing the flow imbalance regions, though not the details of the gravity waves themselves.

The residual of the nonlinear balance equation and other methods are being investigated to arrive at the optimum method for diagnosing imbalance. Real-time evaluation of the best imbalance methods will be performed in the very near future in preparation for its implementation and full evaluation within ITFA in 2003, and will be reported on at the conference. Future research will be performed using idealized modeling studies to develop a basic understanding of the nonlinear scale contraction process by which MGW (with wavelengths of ~100 km) may steepen and saturate, leading to turbulence production.

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