衛星輻射強度與反演產品之資料同化研究－－尼伯特颱風(2016)個案分析

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許慎哲(Shen-Cha Hsu) 查詢紙本館藏

畢業系所

大氣科學學系

論文名稱

衛星輻射強度與反演產品之資料同化研究－－尼伯特颱風(2016)個案分析
(Assimilation of Satellite Radiances and Retrieved Sounding for Typhoon Nepartak (2016) Forecasting)

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摘要(中)

提升數值天氣預報模式之預報力的方式，一直都在精進，其中一種改善方式為提供更合理的初始條件及邊界條件，而若使用星載之高光譜紅外線探空儀及微波探空儀，除了能夠提供三維大氣溫濕度狀態，亦可補足傳統觀測在時間及空間分布之不足。於實務上進行資料同化時，又可區分為使用輻射強度(radiances)資料與反演產品(retrieved products)，使用前者可兼顧即時性之需求，而使用後者與傳統觀測性質相近，原理也較為直觀。
過往研究曾指出，衛星遙測資料不論是輻射強度或反演產品，需考慮可能存在的系統性偏差問題。本篇研究使用美國「聯合繞極軌道衛星系統(JPSS)」中Suomi-NPP衛星上的先進技術微波探空儀(ATMS)與高光譜紅外線探空儀(CrIS)觀測資料，也將其反演產品藉由NCEP再分析資料(FNL)進行大氣熱力參數品質控制與偏差修正，結果可與歐洲中期預報中心(ECMWF)再分析資料比較後，可得到較低系統性偏差的三維大氣溫溼度剖線。
為進一步探討反演產品與輻射強度之差異及修正成效，研究中使用WRF Model及Gridpoint Statistical Interpolation(GSI)資料同化方法，探討尼伯特颱風(2016)之環境、路徑、強度變化與定量降水預報。結果顯示如能透過資料同化技術使用經誤差修正後的溫溼度反演產品於多個實驗組中，將能有較顯著的颱風預報結果，並且提高定量降水預報(QPFs)之技術得分。

摘要(英)

Improving numerical weather prediction (NWP) model are discussed uninterruptedly. One of ways to improve the performances of NWP model is providing more reasonable initial conditions and/or boundary conditions. The hyperspetrum infrared sounder and microwave sounder make up conventional observations on special and temporal distribution with three dimensional observations of atmospheric temperature and moisture. Both of radiances and retrieved products can be assimilated into NWP. The radiances usually used in operational center with its immediacy. The use of retrieved products more simple and similar to conventional observations.
Some previous works indicate that systematic bias is found in satellite observed radiance/retrieved products. In this study, we try to reduce the uncertainty of retrieved products from Advanced Technology Microwave Sounder (ATMS) and Cross-track Infrared Sounder (CrIS) onboard NOAA/JPSS Suomi-NPP. The bias correction mothed of moisture by refer to FNL data can makes bias close to zero.
We assimilate radiance and retrieved products in NWP during the period of Typhoon Nepartak (2016). The Weather Research and Forecasting (WRF) Model and Gridpoint Statistical Interpolation (GSI) system are adapted to investigate typhoon track, intensity, environmental fields and Quantitative Precipitation Forecasts (QPFs). The results show it has better forecasts and the skill scores of QPFs after implementing the bias correction.

關鍵字(中)

★ 星衛資料同化
★ 星載探空儀
★ 颱風

關鍵字(英)

論文目次

摘要 I
ABSTRACT II
誌謝 III
目錄 IV
表目錄 VII
圖目錄 VII
英文縮寫說明 XII
第一章緒論 1
1.1. 前言 1
1.2. 文獻回顧 2
1.3. 研究動機及目的 5
第二章資料使用及個案介紹 7
2.1. 傳統觀測 7
2.1.1. 全球通信系統GTS資料 7
2.1.2. 中央氣象局測站及自動雨量站 7
2.2. 美國環境預報中心(NCEP)之預報場與再分析場 8
2.2.1. 全球預報系統(GFS)資料 8
2.2.2. 大氣再分析(FNL)資料 9
2.3. 衛星觀測資料 9
2.3.1. 輻射強度Radiance資料 11
2.3.2. 大氣垂直溫溼度剖線NUCAPS資料 11
2.4. 歐洲中期天氣預報中心(ECMWF)分析場資料 13
2.5. 颱風路徑資料 14
2.6. 個案介紹 14
第三章模式介紹及實驗設計 15
3.1. 數值天氣預報模式 15
3.1.1. WRF 15
3.1.2. GSI 16
3.1.3. 預報系統 18
3.2. NUCAPS資料修正 19
3.2.1. 誤差分析 19
3.2.2. 反演產品處理方法 20
3.2.3. 修正成果 21
3.3. 實驗設計 22
第四章數值實驗 23
4.1. 觀測資料分布 23
4.2. 分析增量 23
4.3. 路徑及強度 24
4.4. 環境場誤差增長 26
4.5. 副熱帶高壓強度誤差 27
4.6. QPF與技術得分 28
第五章總結與未來展望 31
5.1. 結論 31
5.2. 未來展望 33
參考文獻 34
附表 39
附圖 42

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指導教授

劉千義(Chian-Yi Liu)

審核日期

2017-8-21

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