| dc.description.abstract | The Planetary Boundary Layer is located at the bottom of the Earth′s atmosphere. Its structural development is closely related to solar radiation heating, human economic activities, and vegetation distribution. The evolution of day and night also affects small-scale weather and air quality. However, in the past studies, the data of the atmospheric boundary layer was limited by observation techniques, lacking high-resolution time and space data. Whether meteorological tower, radiosonde, tethered balloon or aircraft observation, both have advantages, disadvantages and use restrictions. Considering the cost of manpower and usage, many observation methods are unable to observe normal or daily normal observations. At present, the vertical distribution of the thermal structure of the atmospheric boundary layer and air pollutants is mostly detected by sounding data or ground-based remote sensing in Taiwan. Unmanned aerial vehicle (UAV) is one of the new observing platforms in recent years. The cost is much cheaper and the manpower needed is relatively simple. Therefore, the purpose of this study is to construct the UAV observation system for the atmospheric boundary layer and to explore the vertical structure of the boundary layer and the change of the air pollutants. It will help to establish the parameterized boundary layer mechanism and improve the prediction of the weather and air pollution model.
The system is equipped with meteorological and aerosol optical instruments on three kinds of drones to obtain the vertical distribution data of atmospheric boundary layer temperature, humidity, pressure, wind direction, wind speed, aerosol particles concentration and size distribution. In order to reduce the error of the instrument used in the measurement, the parallel comparison between indoor and outdoor has been carried out. The root-mean-square error (RMSE) of indoor temperature, humidity, and the pressure is 0.30 °C, 1.84%, 0.11 hPa, respectively. The RMSE of outdoor temperature and humidity within 3 km during outdoor day and night are 0.74 °C, 3.54% and 0.21 °C, 3.34%, respectively. The error is within a reasonable range and the data are highly correlated in actual observation, since 2017, this study focuses on the case for long-range transport, local pollution and the development structure of northern Taiwan boundary layer in summer, and integrates the data of sounding, wind profiler and the vertical distribution of the aerosol which is inversion by lidar to verify the practicality and reliability of the system. The results show that the meteorological observation results of the system within 0-3 km are in good agreement with the sounding observations by the central weather bureau. The detection of the boundary layer height is almost consistent with the polarization depolarization data. The main error source is the radiant heating and the response time of the sensor. The aerosol measurement results compare the continuous observation data of the backscattering signal. In addition, the aerosol results compared with the continuous observation data of the light backscattering. The vertical distribution of the aerosol distribution is similar to that of the system, except that the vertical distribution discontinuity is consistent with the temperature inversion observed by the system. Compared with the wind field inversion with the wind profiler, the wind direction and wind speed RMSE measured by the drone after 100 m from the ground are 19.02° and 1.91 m s-1 respectively, so there are still errors to be evaluated and corrected. As a whole, this study proves that the unmanned aerial vehicle (UAV) system and technology developed by our team can be applied to the atmospheric boundary layer to explain the relationship between the development of atmospheric boundary layer and the vertical distribution of air pollution, and can be used as a verification tool for remote sensing. | en_US |