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標題: | 弱縱觀天氣強迫與PM2.5濃度改變下台北盆地夏季午後強降水事件之合成分析研究 A Composite Analysis of Summer Afternoon Heavy Precipitation Events in the Taipei Basin Under Weak Synoptic Forcing and PM2.5 Changes |
作者: | 冉心瑩 Cidny A. Ramirez |
指導教授: | 楊明仁 Ming-Jen Yang |
共同指導教授: | Ryan Torn;Christopher Thorncroft Ryan Torn;Christopher Thorncroft |
關鍵字: | 台北盆地,夏季午後強降水,PM2.5濃度, rain,afternoon thunderstorm,Taipei Basin,weak synoptic forcing,PM2.5,aerosol, |
出版年 : | 2023 |
學位: | 碩士 |
摘要: | 台灣台北市是一個受各種降水影響的城市。 然而,最具影響力的短期降水來源之一是下午的午後雷陣雨。 了解這些午後雷陣雨的趨勢以及 PM2.5 對總降水量的影響程度對於改進預報和開發能夠對付上述天氣因素的城市基礎設施。
本研究著眼於 2005 年至 2015 年夏季 6 月、7 月和 8 月期間台北盆地前 5% 的暴雨 (HR) 事件。目的是了解 PM2.5 濃度的變化是否超過台北盆地對夏季的人力資源活動有影響,分析同期PM2.5總濃度,並與HR事件的各種特徵進行比較。 大雨事件的定義是總降雨量至少為81.24毫米/天,並且發生在弱綜觀環境下。 2005 年至 2015 年期間,55天符合上述標準,分析這55天每天的降雨量的時間和空間分佈, 將降雨趨勢與 PM2.5 趨勢進行比較,並對夏季和每個 HR 天的 PM2.5 趨勢進行時空分析進行比較。十年間(2005-2015)的背景夏季平均值用於作恆定背景狀態值來比較每日濃度波動。 研究發現,僅在某些事件中,PM2.5 濃度對降水有積極響應。 HR 日的總體濃度與夏季平均值沒有顯著差異。 此外,還選擇了三個降雨案例研究:梅雨事件、單個 HR 日和連續三個 HR 日。 每個案例研究的分析中均包括 HR 事件的前一天和後一天。 這些案例研究僅深入了解降雨對 PM2.5 濃度的影響,但沒有深入了解 PM2.5 對降雨的影響。 NTU WRF-ARW 用於模擬各種 PM2.5 濃度(清潔、平均、骯髒),並觀察降水空間和時間特徵是否變化。 研究結果顯示氣溶膠濃度的變化能影響降水,這些變化反映在降雨時間(開始時間和持續時間)和分佈(最強降雨地點)的變化上。因此推論PM2.5 可能影響了風暴雲發展的微觀物理,改變了風暴本身的初始條件。 雖然 PM2.5 影響 HR 發展的確切方式尚不清楚,但濃度的增加顯然會影響台北盆地的降雨率。 Taipei, Taiwan is a city affected by various types of precipitation. However, one of the most impactful short-term sources of precipitation is afternoon thunderstorms. Understanding the trends of these afternoon thunderstorms and the extent to which PM2.5 impacts precipitation totals is imperative for improving forecasting and developing urban infrastructure that can deal with said totals. The present study looks at the top 5% heavy rain (HR) events in the Taipei Basin during the summer months of June, July, and August from 2005 to 2015. The goal was to find out whether changes in the PM2.5 concentration over the Taipei Basin has had any impact on HR events in the summer months. The total PM2.5 concentration during the same period was analyzed and compared to various characteristics of the HR events. Heavy rain events were defined as having a total rainfall of at least 81.24 mm/day and occurred in a weak synoptic environment. 55 days met the criteria. The rainfall during each day was then analyzed by its temporal and spatial distribution. Rainfall trends were compared to PM2.5 trends. Spatial and temporal analyses of PM2.5 trends for the summer season and each of the HR days were used for comparison. A background summer mean was computed for the decade (2005-2015) and was used as a constant background state value to compare the daily concentration fluctuations. It was found that in only some events the PM2.5 concentrations responded actively to precipitation. Overall concentrations on HR days did not vary significantly from the summer mean. Further, three rainfall case studies were selected: a Mei-Yu event, a single HR day, and three consecutive HR days. The day before the HR event and the day after were included in the analysis for each case study. The case studies only provided insight into the effect that rainfall has on PM2.5 concentrations but not into the effect that PM2.5 may have on rainfall. NTU WRF-ARW was used to simulate various PM2.5 concentrations (clean, average, dirty) and see if precipitation spatial and temporal characteristics varied. Changes in aerosol concentrations affected precipitation. The changes were reflected by changes in the timing (initiation and duration) and distribution (location of heaviest rainfall) of the rain. PM2.5 likely affected the microphysics of the storm cloud development, changing the initial conditions for the storm itself. While the exact way that PM2.5 influences HR development is unknown, it is clear that increased concentrations affect rainfall rates in the Taipei Basin. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91534 |
DOI: | 10.6342/NTU202304114 |
全文授權: | 同意授權(全球公開) |
顯示於系所單位: | 大氣科學系 |
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