大氣邊界層觀測資料同化與多維尺度數值模擬-邊界層資料同化及其對近地表預報之影響(總計畫及子計畫二)(3/3)

This project aims to establish a high-resolution ensemble data assimilationsystem for the planetary boundary layer over the Taiwan complex terrain (PBLEDA system) by combining the intense observations in PBL and high-resolutionmeteorology and air-quality model. We plan to assimilate surface data, UAV,aerosol lidar, and regular and ship-based radiosondes. By taking advantage ofthe high vertical resolution of the observations, prediction initialized from the PBLEDA analysis can better represent the PBL variations under the complex terrainof Taiwan. Besides, the ensemble simulation helps to establish the sensitivity ofnear-surface prediction, which allows us to explore the possibility of installing theregular PBL observations.Based on the PBL DA framework, the 4-dimensional analysis product providesthe potential to understand the development of PBL under the complex terrain,the variability of leeside flow, and how these may modulate the transportation ofthe air pollutant in the PBL. The PBL EDA system allows building the key toimprove air quality and wind energy prediction. In order to mitigate the nearsurface model bias, this project will develop the bias correction methods basedon multi-variable regression and neural networks. These methods will beintegrated into the PBL data assimilation framework.