環境資源報告成果查詢系統

空氣品質預報動力模式及紫外線預報發展與驗證

中文摘要 1. 維護現有「空氣品質預報輔助系統及紫外線預報系統」,更新預報輔助系統資料庫。 2. 配合本署大陸沙塵影響台灣地區之預報作業,進行大陸沙塵起沙及傳輸預報模擬,綜合預報模式與氣象預報之結果,推估沙塵侵台時間、影響範圍及濃度分布狀況,對可能侵台的大陸沙塵事件提供24至48小時之預警。今年TAQM/kosa模式對沙塵的掌握仍比NRL模式為略佳,但整體而言,今年的評分比2003年為差,這是由於1月及4月各有一個漏報與虛報的個案,一月個案的漏報原因是大氣中相對濕度及24小時溫差未達起沙條件。 3. 協助發展空氣品質動力預報模式,以模擬包括生質燃燒等等本土以及外來空氣污染物濃度,提供24至48小時預測,以輔助例行性空氣品質預報作業,目前已針對本年度五個高污染個案進行模擬測試,也已將模式移植至本署機器進行自動化測試。也將化學動力預報模式資料加入改進複迴歸分析法,結果顯示有改進複迴歸分析法。 4. 利用本署逆溫儀觀測資料,作為預報改進之參考依據。針對2003年逆溫儀資料與探空資料進行比對,顯示逆溫儀資料值得採用。使用逆溫層高度為變數加以改進複迴歸預報法,顯示逆溫層高度在某些個案具有很高的相關性。
中文關鍵字 大氣沙塵、生質燃燒、大氣穩定度,

基本資訊

專案計畫編號 EPA-93-U1L1-02-102 經費年度 093 計畫經費 2950 千元
專案開始日期 2004/03/11 專案結束日期 2004/12/31 專案主持人 陳正平
主辦單位 監資處 承辦人 執行單位 國立台灣大學 大氣科學系

成果下載

類型 檔名 檔案大小 說明
期末報告 0000040315.pdf 6MB [期末報告]公開完整版

Development and Verification of Forecasting Models For Air Quality and UV Index

英文摘要 (1) Provide hardware and software maintenance of EPA’s “Air Quality Forecast Auxiliary System” and update relevant database in order to facilitate the operation of daily forecast of air quality and UV index; (2) Perform daily simulation of atmospheric dust deflation and transport from East Asia to the Taiwan area, predict the arrival time, duration, concentration and extent of dust incursion so as to provide a 48-hr advance notice. An overall evaluation of the forecast results was conducted. It was found that the TAQM/kosa model performed slightly better than the dust forecast model of US Naval Research Laboratory for the spring of 2004. However, the performance of TAQM/kosa in 2004 degraded somewhat from 2003, owing to a complete miss of a case in January and an overestimation of a case in April. For the former, we found the causes to be errors in the relative humidity and temperature fields in TAQM/kosa. (3) Develop a dynamic air quality model to provide simulations of local and foreign air pollutants including those from biomass burning in East Asia, in order to provide 24 to 48 hr forecasts to assist routine operation of air quality forecasts in the future. Five highly polluted cases have been tested with the dynamic air quality model. The model has been installed on EPA’s operation computer, and pre-operation tests of automatic daily forecasts have been performed. (4) Analyze the data quality EPA’s boundary layer temperature profiler, and analyze the applicability of these data in improving air quality forecasts. The data quality looks fine according to our preliminary analysis. We also found significant positive correlation between the inversion height that derived from the data and the concentrations of major air pollutants. However, further application of these data in the forecasts of air pollution requires in-depth understanding of the causes of the correlation.
英文關鍵字 dust, biomass burning,stability,air pollution ,UV