Meteorological measurements from Unmanned Aircraft Systems (UASs) increase the volume of observations available for validating and improving high-spatiotemporal-resolution models. Accurate model forecasts for UAS operations are essential to the successful development of the low-altitude economy (LAE). In this study, two UAS test flights were analyzed to assess the consistency between UAS measurements and Regional Atmospheric Modeling System model outputs, thereby evaluating model forecast skill. UAS measurements were compared with ground-based anemometer and radiosonde observations to meet the World Meteorological Organization observational requirements at both the Threshold and Goal levels. Model-forecast turbulence exhibited strong agreement with atmospheric turbulence derived from high-frequency UAS wind data. The numerical weather prediction model at high spatial and temporal resolution is found to have sufficiently accurate forecasts to support UAS operation. A computational fluid dynamics model was also tested for high-resolution wind and turbulence forecasting; however, it did not yield improvements over the meteorological model. This work represents the first study of its kind for LAE applications in Hong Kong, and further statistical analyses are planned.
Lam et al. (Tue,) studied this question.
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