| 04 Aug 2026
Multi-Rotor UAV Observations of the Atmospheric Boundary Layer over Complex Terrain: Accuracy Validation and Dynamic Mechanisms of Flight Disturbances
Abstract. Unmanned aerial vehicle (UAV)-based sounding has become a flexible and cost-effective approach for probing the atmospheric boundary layer (ABL), yet its measurement credibility over complex terrain and the dynamic response of UAV flight attitude to boundary-layer dynamics remain insufficiently quantified. Here, we implement multi-rotor UAV field campaigns equipped with well-calibrated meteorological payloads, including co-located intercomparison observations against a 100-m gradient meteorological tower at the Xingtai Field Scientific Experiment Base, and vertical-profile surveys across the lower ABL over the eastern Taihang piedmont. The comparative observations demonstrate excellent agreement between UAV and tower measurements: vertical profiles of wind speed, wind direction, air temperature, and relative humidity exhibit strong correlations, negligible systematic biases, and coherent vertical structures. Stability parameters derived from high-frequency hovering observations, including potential temperature and gradient Richardson number (Ri), also closely match tower references, verifying the platform’s capability to reliably resolve ABL thermal stratification and dynamic stability. Three successive evening soundings capturing the transition from a convective to a stable boundary layer reveal that UAV attitude disturbances are strongly suppressed within stably stratified layers, but markedly amplified in near-neutral to weakly unstable layers where intense vertical wind shear coincides with weak thermal suppression, with the most severe perturbations occurring near the cloud base. The joint distribution of Ri and vertical wind shear further indicates that turbulence-induced flight bumpiness generally intensifies with increasing shear and peaks under unstable stratification, while a localized anomaly suggests possible resonance-like coupling between turbulent eddy scales and airframe dynamics. These findings establish a quantitative observational basis for reliable UAV-based ABL sensing and low-altitude flight-safety assessment over complex terrain.
General Evaluation
This study employs a DJI M350 RTK multi-rotor UAV to investigate the reliability of atmospheric boundary layer (ABL) observations and flight safety over complex terrain. The authors conducted comparative observations against a 100-m gradient meteorological tower and vertical-profile surveys over the eastern Taihang piedmont. They first demonstrated that the UAV platform can accurately measure both basic meteorological variables (temperature, wind, humidity) and derived stability parameters (potential temperature and gradient Richardson number). Furthermore, the study quantitatively reveals the combined effects of vertical wind shear and stratification stability on UAV attitude disturbances, and proposes a possible vortex-airframe resonance-like mechanism, which is a novel contribution to UAV-based meteorological applications. Notably, the paper employs a sample-pairwise finite-difference method for Ri calculation, which preserves the distribution information of parameters between stratified layers and better captures turbulence details than conventional layer-averaging approaches.
The topic is well within the scope of AMT. The experimental design is rigorous, the dataset is substantial, and the analytical framework is logically structured. The findings provide valuable references for improving UAV-based ABL observations and low-altitude flight safety over complex terrain. The manuscript is well written and the figures are of high quality. Before formal acceptance, I recommend that the authors address the following specific issues.
Scientific comments
1. The logical chain from observational results to conclusions needs to be strengthened
The authors describe the time-height evolution of the large-scale wind shear field based on Figure 5c, and further analyze the shear characteristics during three flight periods (18:24-18:43, 18:55-19:22, and 19:43-19:55 BJT) in Section 3.2 (starting from page 12, line 328; page 13, line 365; and page 14, line 400, respectively). However, in the detailed discussion of these three cases, the authors do not explicitly link the temporal evolution of the large-scale shear field revealed in Figure 5c with the vertical distribution characteristics of UAV attitude responses during each period.
For example, during the first flight (18:24-18:43), which positive/negative large-scale shear zones did the ascending and descending segments (black solid and dashed lines in Figure 5c) traverse? Could the difference in this large-scale background shear be a significant cause of the asymmetry in flight disturbances between the ascending and descending profiles (Figure 7)? I suggest that the authors actively reference Figure 5c when discussing each case, and superimpose the flight trajectories onto the large-scale shear background for joint analysis. This would significantly strengthen the logical chain connecting the macro-scale background to the local disturbance responses.
2. The evidence supporting the "resonance-like amplification" hypothesis needs to be reinforced
On pages 16-17, lines 465-470, the authors propose a "resonance-like amplification" conjecture based on Figure 12. This is an interesting speculation, but it is currently supported only by anomalous data points in a specific regime (vertical wind shear approximately 0.007-0.010 s⁻¹ combined with near-zero to negative Ri). The evidence appears somewhat thin. I recommend that the authors: (1) adopt a more cautious tone when presenting this viewpoint, clearly stating that this is a preliminary hypothesis requiring further verification; and (2) if possible, provide additional supportive analysis—for instance, by roughly estimating the characteristic scale of turbulent eddies under this specific shear range and discussing whether this scale is comparable in magnitude to the airframe dimensions or the natural frequencies of the MATRICE 350 RTK in pitch/roll directions. If such analysis cannot be provided, I suggest relocating this discussion to the end of the Discussion section as an outlook for future research directions.
3. Inconsistency in the description of cloud-layer vertical extent
On page 15, line 405, the authors state "in the cloud layer (approximately 900-1200 m) and outside the cloud layer." However, on page 16, line 437, they mention "In the stable cloud-top layer above 1000 m." There is ambiguity and inconsistency between the description of the "cloud layer" (900-1200 m) and the "cloud-top layer" (above 1000 m). I suggest that the authors clarify and unify the vertical distribution and extent of the cloud layer, as this directly affects the accurate interpretation of the conclusion that "stable stratification suppresses disturbances."
Minor Comments:
1. The terms "flight bumpiness" (e.g., page 2, line 49; page 14, line 391) and "flight disturbance" (e.g., page 2, line 33; page 16, line 461) are used interchangeably throughout the manuscript. I recommend standardizing to "flight disturbance" or the more precise term "attitude disturbance" to maintain terminological consistency.
2. Figure formatting details：
1）In Figures 4, 6, 8, and 10, the variable names on the x-axes (e.g., theta, Ri , etc ) should be by mathematical variable formatting and italicized to comply with conventions, like: θ and Ri.
2）In the captions of Figures 7, 9, and 11, the repeated use of "profile" could be simplified; for example, change to "Same as Figure 6, but for the vertical response of UAV attitude parameters during ...".