Estimates of upper level turbulence based on second order structure functions derived from numerical weather prediction model output

Estimates of small-scale turbulence from numerical model output are produced from local estimates of the spatial structure functions of model variables such as the velocity and temperature. The key assumptions used are the existence of a universal statistical description of small-scale turbulence and a locally universal spatial filter for the model variables. The shape of the model spatial filter is determined by comparisons with published results for the spatial structure functions derived from the GASP and MOZAIC aircraft data collected at cruising altitudes. This universal filter is used to estimate the magnitude of the small-scale turbulence, i.e., scales smaller than filter scale. A simple yet universal description of the basic statistics (such as the probability density function and the spatial correlation) of these small-scale turbulence levels in the upper troposphere and lower stratosphere is proposed. This technique can be used to diagnose and forecast upper level turbulence, and statistical evaluations of its performance in that regard are presented.