Balloons and Quadcopters: Intercomparison of Two Low-Cost Wind Profiling Methods

Experimental field campaigns are an essential part of atmospheric research, as well as of university education in the field of atmospheric physics and meteorology. Experimental field observations are needed to improve the understanding of the surface-atmosphere interaction and atmospheric boundary layer (ABL) physics and develop corresponding model parameterizations. Information on the ABL wind profiles is essential for the interpretation of other observations. However, wind profile measurements above the surface layer remain challenging and expensive, especially for the field campaigns performed in remote places and harsh conditions. In this study, we consider the experience of using two low-cost methods for the wind profiling, which may be easily applied in the field studies with modest demands on logistical opportunities, available infrastructure, and budget. The first one is a classical and well-known method of pilot balloon sounding, i.e., when balloon is treated as a Lagrangian particle and tracked by theodolite observations of angular coordinates. Second one is based on a vertical sounding with a popular and relatively cheap mass-market quadcopter DJI Phantom 4 Pro and utilizes its built-in opportunity to restore the wind vector from quadcopter tilt angles. Both methods demonstrated reasonable agreement and applicability even in harsh weather conditions and complex terrain. Advantages and shortcomings of these methods, as well as practical recommendations for their use are discussed. For the drone-based wind estimation, the importance of calibration by comparison to high-quality wind observations is shown.

Dynamic Outlier Detection in the Calibration by Comparison Method Applied to Strain Gauge Weight Sensors

The present work proposes a robust method of analyzing sets of data series shifted in time in respect to each other utilizing the process of dynamic calibration by comparison. Usually the Pearson’s correlation analysis coefficient is applied for this purpose. However, in some cases the method does not bring satisfactory results, as it can be seen in the results of the research conducted for the purpose of this paper. The Dynamic Time Warping method may be the solution to this problem, as it appears to be more efficient while comparing the shapes of calibration characteristics done with the use of the Pearson’s method. The presented method may also be applied to eliminate dynamic outliers collected in the process of recurrence examination or the analysis of strain gauge weight sensors hysteresis. This fact also makes the method a good tool for eliminating improper data series which might appear in the calibration process due to, e.g., malfunctioning devices installed in the calibration stand. The article presents an example of using the proposed method in eliminating improper dynamic characteristics obtained in a simulated calibration stand. Moreover, a comparative analysis performed on the simulation data is also presented in the article, as well as the result of the laboratory experiment.