大氣邊界層觀測資料同化與多維尺度數值模擬-大氣邊界層觀測資料同化與多維尺度數值模擬(總計畫及子計畫一);Observations, Data Assimilation and Multidimensional Numerical Model Simulation of the Atmospheric Planetary Boundary Layer

NCUIR > College of Earth Sciences > Department of Atmospheric Sciences > Research Project > Item 987654321/84459

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Title:	大氣邊界層觀測資料同化與多維尺度數值模擬-大氣邊界層觀測資料同化與多維尺度數值模擬(總計畫及子計畫一);Observations, Data Assimilation and Multidimensional Numerical Model Simulation of the Atmospheric Planetary Boundary Layer
Authors:	鄭芳怡;賴信志;莊秉潔
Contributors:	大氣科學學系
Keywords:	大氣邊界層;系集資料同化系統;高解析度氣象模式;光達;無人機;空氣品質;污染物傳輸過程;綠能;深度學習;atmospheric planetary boundary layer;ensemble data assimilation system;high resolution meteorological model;lidar;UAV;air quality;air pollution dispersions;green energy;deep learning
Date:	2020-12-08
Issue Date:	2020-12-09 09:22:07 (UTC+8)
Publisher:	科技部
Abstract:	此整合型計畫，透過系集資料同化系統，整合大氣邊界層觀測資料以及WRF氣象模式、CMAQ空氣品質模式，來建構具備高準確度的高解析度大氣邊界層分析場資料，包含氣象場以及污染物濃度場四維資料。預計部署從從近海、到西部平原、再進到內陸山區的橫向大氣邊界層觀測實驗，此四維觀測資料，有助於釐清臺灣複雜環流結構與地形之間的交互作用，以及後續對污染物水平傳輸及垂直擴散過程的了解。過去臺灣鮮少有研究學者進行邊界層內的觀測數據同化，而本計畫預計結合無人機觀測數據、剖風儀垂直觀測、探空氣球、地面觀測數據，以及臺灣光達分佈網之觀測訊號，並搭配衛星觀測資料，藉由系集資料同化系統，來提升臺灣各地區域大氣邊界層模擬性能，並藉由此模擬系統，來建構高解析度大氣邊界層分析場資料。並提出一套結合數值模式預報的邊界層觀測策略，以提升未來臺灣氣象、空氣品質模式預報效能，以及提升臺灣綠能如風能、光電能源的推估技術。而高解析度分析場資料以及大氣邊界層觀測資料之診斷分析結果，能協助釐清臺灣大氣邊界層結構特性，科學議題包含：(1)解析混合層與穩定邊界層結構特性及其對局地環流於複雜地形生成之熱、動力機制; (2)探討山谷風、海陸風、背風渦漩於複雜地形之熱、動力特性; (3)解析污染物於複雜環境之傳輸與擴散過程。另外，本計畫也結合資料科學方法，從深度學習來了解大氣模式所無法解析的小尺度傳輸特性如何谷盆地尺度、街廓尺度等傳輸行為，預計從多個面向來釐清污染物於複雜環境的傳輸特性。 ;The study proposes to utilize the ensemble data assimilation system to assimilate the comprehensive planetary boundary layer observation datasets into Weather Research and Forecasting (WRF)model and to develop a high-resolution boundary layer analysis dataset.The intensive field observations will be conducted to establish the atmospheric planetary boundary layer observations including the wind profiler, sounding, unmanned aerial vehicle (UAV), lidar, surface datasets and satellite datasets. The sounding and UAV observation will be deployed over the ocean, western Taiwan, and the inland mountainous area. The high-resolution analysis datasets are expected to provide a comprehensive understanding of the development of the atmospheric dynamic/thermodynamic processes over the complex topography, and to figure out the formation mechanisms of the leeside wake/vortex/land-sea breeze/mountain-valley flow structures. The interaction between the wind circulations and complex terrain will be investigated through the analysis of the fine scale meteorological and air quality modeling and the observed datasets. Furthermore, the air pollution transport processes can be illustrated in a detailed manner.Moreover, the data science and deep learning algorithms will be conducted to study the air pollution dispersion processes that is unable to be resolved from the dynamic model. The objective of this study is to provide a high-resolution planetary boundary layer analysis datasets; furthermore, to propose a data assimilation strategy that is helpful to enhance the weather and air quality forecasting system predictability, and to support the assessment of the use of the green energy.
Relation:	財團法人國家實驗研究院科技政策研究與資訊中心
Appears in Collections:	[Department of Atmospheric Sciences] Research Project

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