Using a Micro-UAV as a Portable Turbulence Profiler (PTP) for atmospheric research

Preliminary data from a Portable Turbulence Profiler (PTP) for atmospheric research is presented. The concept is that turbulence information is implicit in the avionics data from a micro-UAV (MAV); more specifically the output diagnostics of the control technology of a hovering mini-copter holds statistics on the local turbulence experience by the aircraft, and to which the avionics has reacted. When the micro-UAV is commanded to remain stationary relative to the earth surface (known as "loiter") the avionics uses sensors and motor control, connected in feedback loops via Kalman filters, to achieve this effect; diagnostics from these feedback loops are monitored and recorded by the avionics. These data from both the input (sensors) and output (motors) hold implicit information on the perturbing wind vector: hence the MAV itself constitute a turbulence sensor.

The Remotely Piloted Aircraft (RPA) Flight team at the host institute, the Scottish Association for Marine Science (SAMS) have made initial test flights of the system and the avionics data show an association with wind gusts at various heights. The link between wind vector and data is not linear, however, in part due to the non-linear effect of the gust on the complex and hovering airframe and also because of the non-linear behaviour of Kalman filters systems. A subset of the avionics data will be optimised and calibrated so the platform can give quantitative estimates of turbulent kinetic energy (TKE).

The proposed system is relatively inexpensive because the avionic software, "ArduPilot", is an open source product and freely available. The "loiter" capability of ArduPilot exists already and the Remotely Piloted Aircraft (RPA) Flight team at the host institute, the Scottish Association for Marine Science (SAMS) have made initial test flights of the system at a range of coastal sites in Argyll.

Once calibrated, this PTP will be used to estimate of boundary layer depth and local turbulent mixing efficiency in the planetary boundary layer (PBL), thereby validating or constraining PBL parameterisation schemes as used in numerical weather forecasts, meso-scale, pollution dispersion and climate models. PBL depth and diffusion efficiency is still poorly understood in many model schemes, especially under stable stratification, heterogeneous terrain (patched or mountainous) or at evening transition; PBL depth and local diffusivity largely control near-surface trace gas concentration, humidity and sensible heat in numerical environmental models.