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姓名 蘇奕叡(Yi-Jui Su) 查詢紙本館藏 畢業系所 大氣物理研究所 論文名稱 颱風路徑、降雨及水位之系集模擬研究： 以凡那比(2010)颱風個案為例
(Typhoon’s track, precipitation and water stage ensemble simulation study: Typhoon Fanapi (2010) case)相關論文 檔案 [Endnote RIS 格式]
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摘要(中) 本論文研究使用單向耦合(one-way coupled)的大氣水文模式系統，進行颱風的系集模擬研究，以瞭解颱風路徑與降雨間的關係，並探討降水之不確定性在集水區河川水位模擬中所扮演的角色。本文欲探討之颱風為2010年的凡那比颱風，該颱風於9月19日登陸台灣，於南部地區造成嚴重的豪雨及淹水災情，故本研究選擇受災嚴重的高屏溪流域來進行水文模擬的討論。
本文利用WRF中尺度模式以四層巢狀網格架構，模擬72小時的颱風路徑及降水預報，並以物理參數化方案的變異度使用不同的積雲、微物理及邊界層等物理參數法建立24組系集成員，從不同的系集特性來評估其路徑預報跟降雨預報的表現，建立兩種系集成員組合：1)依照不同的路徑偏向歸納出兩組系集組合及2)改變單一參數法得到的物理參數組合，利用不同的系集組合以討論其不確定性範圍。最後將各個系集成員降雨模擬結果代入WASH123D水文模式中，當作其降雨資訊的輸入場，來進行集水區的系集水位模擬，藉此評估氣象模式的降水預報誤差在水位預報的影響程度。
從颱風路徑偏差的系集結果發現，路徑較佳的系集成員亦有較佳的降雨預報跟水位預報結果。而對於改變物理參數方案的系集成員(特別是積雲系集組合)，因為不同物理參數法的變異性導致系集成員間的路徑結果差異大，這樣的變異性也同樣反映在降水預報跟水位預報結果中。又因為集水區的降雨誤差和水文模擬結果是緊密相關的，藉由將當地地區之降雨預報資訊輸入水文模式中，可發現降雨系集預報的變異性會反應在水位模擬的變異性上。從相關性分析中可得知，颱風路徑的預報誤差會明顯反應在預報降雨的誤差上，且在主要降雨區域中誤差會被放大。在水位的模擬中，降雨預報誤差變異度較大的系集會有較大的水位預報誤差範圍，且會受到降雨誤差範圍的影響，其誤差範圍有小幅度放大的現象。但對於一些系集組合此放大現象不明顯，這可能是該系集組合間成員數不足或本身誤差特性類似之關係。
摘要(英) This thesis utilized one-way coupled meteorhydrology simulation system for typhoon’s ensemble forecast to know the relationship between Typhoon’s track and precipitation and investigate what role uncertainty of precipitation does in the watershed river stage simulation. Typhoon Fanapi (2010) landfall Taiwan in September 19th and produced heavy rainfall that resulted flooding disaster in south Taiwan. Therefore, this study discusses the Kao-Pin river basin as hydrological model’s study area where the typhoon
disaster affected.
This study uses WRF mesoscale model with four nested domain to simulated typhoon’s 72-hour track and precipitation forecast. Using variability of the physical parameters, including different cumulus, microphysics and boundary layer physical scheme, establishes the 24 members of the group ensemble. From different ensemble features, we assess the performance of its path forecast with rainfall forecast, and establish two ensemble composition：1) track ensemble：according to different paths tend to summarize the two ensemble groups and 2)physical ensemble：changing a single type physical parameter scheme to set the ensemble groups, using different combinations of ensemble set to discuss its range of uncertainty. Finally, taking each ensemble member’s rainfall forecast into WASH123D hydrological model, as rainfall information input, to simulate the water stage forecast in the Kao-pin river watershed. Therefore, we can assess the weather patterns of precipitation forecast errors
impact on the water stage forecast.
From the result of track ensemble, the group with better track forecast also have better rainfall and water stage forecast result. For the physical group, especially the cumulus ensemble, because of the variability of physical parameter, there are more variability between the track forecast of each ensemble members, so as in the rainfall and stage simulation result. Rainfall errors and hydrological simulation results in the watershed are closely related, so the local region can be found that the rainfall variability of ensemble forecast will be reflected in the variability of simulating water stage. From the correlation analysis, we can find that the typhoon track forecast errors will be significantly reflected in the rainfall forecast errors, and errors in the main rainfall area will be magnified. For the flow stage forecast, the ensembles with larger rainfall forecast error variance have larger stage forecast error range, and the flow stage forecast error range will be have small amplification by the rainfall error range. But for some ensemble group setting, the amplification phenomenon isn’t as obvious as others. It may be due to the lack of ensemble members in ensemble group or
the similar error properties.
關鍵字(中) ★ 系集預報
★ 降雨預報
★ 水位模擬
★ 颱風路徑
★ WASH123D
★ 高屏溪集水區關鍵字(英) ★ Ensemble forecast
★ Precipitation forecast
★ Flow stage simulation
★ Typhoon track
★ WASH123D
★ Kao-Pin river watershed論文目次 目錄
中文摘要 ………………………………………………………………....... i
英文摘要 ………………………………………………………………....... iii
致謝 ………………………………………………………………....... v
目錄 ………………………………………………………………....... vi
表目錄 ………………………………………………………………....... viii
圖目錄 ………………………………………………………………....... ix
一、 緒論…………………………………………………………....……..... 1
1-1 文獻回顧……………………………………………………....... 1
1-2 研究目的……………………………………………………....... 2
1-3 論文架構……………………………………………………....... 3
二、 背景描述………………………………………………………………. 4
2-1 颱風個案：凡那比颱風…………………………………………. 4
2-2 地理描述：高屏溪下游集水區…………………………………. 4
三、 數值模式介紹………………………………………………………… 6
3-1 氣象模式...……………………………………………………… 6
3-2 水文模式...……………………………………………………… 6
四、 研究方法……………………………………………………………… 10
4-1 颱風模擬實驗...………………………………………………… 10
4-1-1 系集模式建立………………………………………...... 10
4-1-2 系集組合設定………………………………………… 11
4-2 集水區水文模擬實驗...………………………………………… 12
4-2-1 水文模式設定………………………….. ……………... 12
4-2-2 降雨資料輸入………………………………………….. 13
4-3 分析評估方法…………………………………………………... 13
4-3-1 技術得分評估…………………………………………. 13
4-3-2 統計評估………………………………………………. 16
四、 結果與討論...……………………………………………......………… 18
5-1 氣象模式模擬…………………………………………………... 18
5-1-1 颱風模擬結果………………………………………… 18
5-1-2 路徑偏向系集………………………………………… 19
5-1-3 物理參數法系集：積雲系集…………………………... 21
5-1-4 物理參數法系集：微物理系集……………………....... 22
5-2 集水區模擬結果………………………………………………... 23
5-2-1 高屏地區之降雨模擬結果…………………………..... 23
5-2-2 水位模擬結果…………………………………………. 24
5-3 誤差討論………………………………………………………... 27
5-3-1 相關性分析…………………………………………..... 27
5-3-2 誤差範圍分析…………………………………………. 28
六、 結論……………………………………………………………………. 30
參考文獻 …………………………………………………………………... 32
表附錄 …………………………………………………………………... 36
圖附錄 …………………………………………………………………... 40
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指導教授 楊明仁(Ming-Jen Yang) 審核日期 2014-7-17 推文 plurk
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