發展渦流相關法之潛熱與二氧化碳通量補遺技術

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姓名

陳觀印(Kuan-Yin Chen) 查詢紙本館藏

畢業系所

水文與海洋科學研究所

論文名稱

發展渦流相關法之潛熱與二氧化碳通量補遺技術
(Developing Gap Filling Techniques for Latent Heat and Carbon Fluxes Measured by the Eddy Covariance Method)

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摘要(中)

潛熱、可感熱和碳通量是大氣和陸域生態系間重要的水氣、熱和碳交互作用，但往往因為儀器故障或觀測條件不佳而導致資料品質缺失，以渦流相關法計算的陸表通量資料，遺失率往往高達50-60%不等，通量資料大量遺失對於區域水文收支、能量收支和碳收支的長期計算會有極大的誤差。先前研究(陳奕穎，2012)已經利用主成分分析法和多元回歸式發展潛熱通量補遺方法，本研究使用類似的架構發展蓮華池通量觀測資料補遺方法，主要改進在加入能量閉合率和摩擦風速來預先篩選品質較好的通量資料以建立缺補模式，並使用主成分分析法解析影響通量資料變異之微氣象資料主成分，再將這些主成分與通量資料建立多元回歸關係式來建立通量缺補模式。
分析蓮華池長期通量資料在水文收支部分，即使是較乾燥的季節或年份，森林有蒸發散量並未有太大差異，仍可有效運用土壤水分。在能量平衡部分，渦流相關法所觀測的潛熱與可感熱在小時尺度約達可用能量的0.79-1.0，所發展之通量缺補技術在能量閉合度有不錯表現，在年尺度、乾季、溼季的Bowen Ratio分別為 0.87、1.19、0.64，在碳收支部分，透過資料補遺後的二氧化碳通量，發現於颱風事件時，颱風導致樹木或葉子掉落，使其光合作用的能力降低，而落葉被微生物分解產生二氧化碳，使得森林白天的碳匯能力下降。

摘要(英)

Data gaps in flux measurements are continuous challenges in flux communities. Robust and consistent gap-filling techniques are essential to the integrated synthesis among different sites. In our previous studies (Chen et al., 2012), a gap-filling model for eddy covariance latent heat (LE) fluxes was developed by integrating the principal component analysis (PCA) and a nonlinear interpolation approach for resolving the multi-collinearity relationships between environmental variables measured by low frequencies instruments and LE fluxes estimated with high frequencies data. Several strategies, such as using a friction velocity as a threshold for data QC/QA or selecting different environmental variables for building the PCA model, have been tested to improve the skill of the PCA gap-filling model built. In this study, the range of Energy Closure Fraction (ECF) was proposed as an essential and effective threshold on building the PCA gap-filling model for EC fluxes. The range of ECF values between 0.5 and 1.5 was used as thresholds after conventional QC/QA procedures to select EC data. Also, temperature differences between canopy and atmosphere were used to replace the LAI, used in the previous study, as one of the environmental variables in view of resolving interactions between H fluxes and LE fluxes. After PCA gap-filling model, the results of energy balance could prove the PCA gap-filling model was successful.
In water budget part, it shows that the forest has strong water ability. The forest could effectively use soil water. It didn’t find the drought even when the precipitation is greatly reduced. In the carbon budget part, this study will discuss the carbon flux in the wet season. Through the complete carbon flux, it’s found that typhoon will cause to reduce the carbon sink capacity of the forest.

關鍵字(中)

★ 渦流相關法
★ 主成分分析法
★ 潛熱通量
★ 顯熱通量
★ 二氧化碳通量
★ 通量資料補遺

關鍵字(英)

★ eddy covariance
★ principal component analysis
★ latent heat flux
★ sensible heat flux
★ carbon dioxide

論文目次

摘要 I
ABSTRACT II
致謝 III
目錄 IV
圖目錄 VII
表目錄 XI
一、緒論 1
1.1前言 1
1.2研究目的 2
二、文獻回顧 4
2.1渦流相關法 4
2.2潛熱通量資料補遺 6
2.2.1日循環插補法(mean diurnal variation) 6
2.2.2查表法(Look up table) 7
2.3二氧化碳通量資料補遺 8
2.4主成分分析法 8
2.5多元回歸法 9
三、實驗場址與儀器介紹 11
3.1實驗場址 11
3.2儀器架設 13
3.2.1高頻儀器系統 13
3.2.2低頻觀測系統 13
四、研究方法 15
4.1渦流相關法 15
4.1.1概念與假設 15
4.1.1.1泰勒假設 15
4.1.1.2雷諾分解 15
4.1.2渦流相關法之資料缺失 16
4.1.2.1大氣條件之因素 17
4.1.2.2儀器測量之因素 17
4.1.2.3人為操作因素 18
4.2通量資料計算 20
4.2.1Flux Calculator 20
4.2.1.1剔除異常值 20
4.2.1.2座標軸旋轉 20
4.2.2通量計算步驟 22
4.3潛熱通量資料補遺方法 22
4.3.1微氣象資料 23
4.3.2標準化 23
4.3.3主成分分析法(Principle Component Analysis, PCA) 23
4.3.4多元回歸 24
4.3.5潛熱通量轉換 25
4.3.6能量閉合率(Energy Closure Fraction，ECF) 25
4.4可感熱通量資料補遺方法 26
4.5二氧化碳通量資料補遺方法 27
4.5.1微氣象資料 28
4.5.2資料分類 28
4.5.3主成分分析法與多元回歸 28
五、結果與討論 30
5.1潛熱通量資料補遺 30
5.1.1以摩擦風速大小篩選資料 30
5.1.2 以能量閉合度篩選資料 31
5.1.3資料補遺結果 33
5.1.4計算蒸發散 46
5.2可感熱通量資料補遺與蓮華池各年能量平衡 47
5.2.1 Bowen Ratio 54
5.3二氧化碳通量資料補遺 55
5.4颱風二氧化碳通量之變化 64
六、結論與建議 67
6.1結論 67
6.2建議 68
參考文獻 69
附錄A 潛熱通量資料補遺補充 77
附錄B 二氧化碳通量資料補遺補充 77

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指導教授

李明旭(Ming-Hsu Li)

審核日期

2019-7-26

推文