Attempting to understand the vertical distribution of turbulence in the surface layer from multi-camera time-lapse imagery

Abstract

In an earlier work, we demonstrated a method to profile turbulence using time-lapse imagery of a distant target from five spatially separated cameras. Extended features on the target were tracked and by measuring the variances of the difference in wavefront tilts sensed between cameras due to all pairs of target features, turbulence information along the imaging path could be extracted. The method is relatively low cost and does not require sophisticated instrumentation. Turbulence can be sensed remotely from a single site without deployment of sources or sensors at the target location. Additionally, the method is phase-based, and hence has an advantage over irradiance-based techniques which suffer from saturation issues. The same concept has been applied to understand how turbulence changes with altitude in the surface layer. Short exposure images of a 30 m tall water tower were analyzed to obtain turbulence profiles along the imaging path. The experiment was performed over two clear days from mid-morning to early afternoon. The turbulence profiles show a drop in turbulence with altitude as expected. However, the rate at which turbulence decreased with altitude was different close to the ground from at higher altitudes.