110-111年度空氣品質多模式與精緻化預報技術研發計畫
| 中文摘要 | 近年臺灣與離島地區空氣品質，除了受到季節性境外移入的中國沙塵暴與霾害影響外，本土排放污染源也是影響空氣品質重要的因素。為提升空氣品質預報能力，提供客觀空氣品質預報指引，前期計畫完成CMAQ-OP1.0空氣品質數值動力模式與其自動化預報流程，於中央氣象局超級電腦(CWB-HPC)上的建置，並每日定期提供預報結果；完成新一代數值動力模式CMAQ-OP2.0之評估，並在CWB-HPC上建置完成預報的自動化預報流程，提供有1日2次預報成果；利用統計校正方法DCA及DMOS，建置有動力模式的偏差校正預報；引入貝氏模型平均法，發展客觀整合多預報的綜合預報模式…等工作。本計畫延續過去工作成果，持續維運現行自動化空氣品質數值模式與偏差校正預報作業，並進一步拓展自動化預報作業，完成CMAQ-OP2.0的預報作業優化，使得CMAQ-OP2.0得將預報時間由舊有84小時擴充至120小時，並可由1日2次預報增加為1日4次預報。除了動力模式外，本計畫亦進行有機率預報、長天期空品預報的開發，以期能進一步改善目前的預報產品。 | ||
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| 中文關鍵字 | CMAQ空氣品質動力模式、機率預報、貝氏模型平均法 | ||
基本資訊
| 專案計畫編號 | EPA-074-110-016 | 經費年度 | 110 | 計畫經費 | 7800 千元 |
|---|---|---|---|---|---|
| 專案開始日期 | 2020/12/30 | 專案結束日期 | 2022/07/20 | 專案主持人 | 馮智勇 |
| 主辦單位 | 監資處 | 承辦人 | 陳荸之 | 執行單位 | 多采科技有限公司 |
成果下載
| 類型 | 檔名 | 檔案大小 | 說明 |
|---|---|---|---|
| 期末報告 | 期末報告全.pdf | 28MB |
110-111 year Multi-model Air Quality Forecast System and Forecast Elaboration
| 英文摘要 | In addition to seasonal transboundary pollution included sandstorm and haze from China, the local pollution also plays an important role in Taiwan. To improve the ability of air quality forecast and provide objective forecast guideline. The following works have been done in previous plans. Numerical dynamic air quality forecast model CMAQ-OP1.0 and its automatic forecasting procedures have been established on high performance computer facility in Central Weather Bureau (CWB-HPC), and providing forecast results every day. The assessment of next version numerical dynamic air quality model CMAQ-OP2.0 have been completed. And the automatic forecasting procedures also have been established on CWB-HPC. The statistical correction method DCA and DMOS were used to build up the correction forecast. To develop the objective composite forecast which integrate multi-forecast, the Bayesian model averaging method is also introduced. Following the results of pervious plan, this work continues maintaining and expanding existing automatic forecasting procedures. In this work, we keep maintaining of the operational air quality model and statistical correction forecast. Furthermore, optimize CMAQ-OP2.0 forecasting procedure to make forecast time extend from 84 to 120 hours and forecast times from twice a day to four times a time. Besides, we also develop air quality probability forecast, long-term air quality forecast to improve the existing forecast product. | ||
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| 英文關鍵字 | Community Multi-Scale Air Quality (CMAQ) modeling system, Community Multi-Scale Air Quality (CMAQ) modeling system, Bayesian model averaging (BMA) | ||