臺灣博碩士論文加值系統

此研究將美國國家大氣研究中心所發展之都卜勒雷達變分分析系統（VDRAS）大幅
改進，成為一個可解析地形之雷達資料四維變分同化系統。其建置方式主要利用虛網格沉浸邊界法（GCIBM），將原來架構在笛卡爾座標上之向前（forward）及向後（backward）積分模式進行修改，不需要改變模式座標，即可於分析及預報中同時納入地形效應的影響。改進而成之新系統被命名為IBM_VDRAS，其擁有在各種複雜地形上進行雲模式向前預報及其伴隨模式之向後積分的能力，陡峭程度自平緩山坡至水平方向急遽變化高度之流體障礙物如建築物等，皆可合理進行解析。

為了評估建置後向前預報模式在地行解析能力之表現，吾人進行三種理想個案模擬實驗，包含（1）二維線性山嶽波、（2）三維背山渦旋及（3）對流不穩定情況下與WRF 模式平行預報。實驗結果顯示，更新後之向前積分模式可以正確及合理解析大氣流體在流經理想地形時所產生之擾動。另外，建築物尺度的模擬實驗，也展示了新的模式在解析地形上具有很大的彈性。除此之外，為了能同時測試修正後之伴隨模式之成果，吾人也進行了一個觀測系統實驗（OSSE）。在此實驗中，將WRF 模式預報資料當作真實場（Truth），取出其中部分資料，做成理想雷達觀測資料，最後利用IBM_VDRAS 同化資料後，檢視分析場與真實場之差異。評估結果顯示，不論在大氣動力、熱動力和微物理場量，IBM_VDRAS之反演結果皆存在相當準確性。

此外，IBM_VDRAS 也應用於一個真實個案的降雨過程分析。此劇烈降雨事件發生於2008 年6 月14 日，剛好處於當年西南氣流實驗（SoWMEX），第八個加強觀測期間 （IOP8）中。當時主要因為梅雨鋒面前方之雨帶通過台灣，而造成明顯降雨。從多變數分析驗證結果顯示，分析量皆與各種現地觀測資料如地面站、剖風儀、探空及徑向風吻合。利用高時空解析度分析場進行統計及探討發現，位於台灣西南沿海之低層輻和帶及其相關之局地環流可能是造成此降雨事件之主要機制。為了能夠了解其中繁雜之物理過程，吾人進行一系列敏感性實驗，主要能夠將地形效應、降水蒸發冷卻過程，以及兩者非線性交互作用所產生之影響程度分離出來，以利後續深入探討。經由將各個分量所造成之增量分析後發現，地形效應相較於蒸發冷卻過程，對於此天氣系統之發展影響較為明顯許多。然而，兩種效應單獨來說，皆與多變數分析中，與主要降雨機制有關之場量分布沒有太大相關，反而是兩者所產生之非線性交互作用與其有極高的相關性。從交互作用所造成的各場量之增量分
布，吾人發現到與此個案降雨機制非常接近之配置，自迎風坡延伸至臺灣西南沿岸之相對低溫區域，同時也是相對高壓分布的範圍，此機制形成沿岸之輻合，也影響了降雨的分布。由此可證明，地形效應與蒸發冷卻之交互作用，在這次降雨事件中扮演了極為重要的角
色。

The four-dimensional Variational Doppler Radar Analysis System (VDRAS) developed at the National Center for Atmospheric Research (NCAR) is significantly improved by
implementing a terrain-resolving scheme to its forward model and adjoint based on the Ghost Cell Immersed Boundary Method (GCIBM), which allows the topographic effects to be considered without the necessity to re-build the model on a terrain-following coordinate system. The new system, called IBM_VDRAS, is able to perform forward forecast and backward adjointmodel integration over non-flat lower boundaries, ranging from mountains with smooth slopes to buildings with sharp surfaces. To evaluate the performance of the forward model over complex terrain, idealized numerical experiments of a two-dimensional linear mountain wave and three-dimensional lee side vortices are first conducted, followed by a comparison with a simulation by the Weather Research and Forecasting (WRF) model. In addition, the building-scale simulation demonstrates its flexibility in resolving terrain as well. An Observation Simulation System Experiment (OSSE) is also conducted with the assimilation of simulated radar data to examine the ability of IBM_VDRAS in analyzing orographically forced moist convection. It is shown that the IBM_VDRAS can retrieve terrain-influenced three-dimensional
meteorological fields including winds, thermodynamic and microphysical parameters with reasonable accuracy.

This new system is utilized to study precipitation process in a real case of pre-frontal rainbands passed over southern Taiwan on June 14 of 2008, collected by IOP 8 of the 2008
Southwest Monsoon Experiment (SoWMEX). Prior to physical discussion, the multivariate analysis is verified by various types of measurements including mesonet stations, wind profiler, radiosonde and Doppler radar radial velocity. It shows that IBM_VDRAS has robust performance in retrieving the meteorological states. Further examinations on the frequent updated analyses demonstrate the importance of quasi-steady convergence line near southwestern coast of Taiwan.

The major mechanisms leading to the formation and maintenance of this convergence line is decomposed into pure topographic, pure evaporation cooling, nonlinear interactive effect, and is further explored through a series of sensitivity experiments. Pure topographic effect is found to
be the dominant factor in modulating the convection development. However, the contributions from nonlinear interaction and pure evaporation, although with weaker magnitudes, cannot be neglected. A schematic diagram is formulated to explain how a local circulation system is built and maintained to support the above mentioned quasi-stationary coastal convergence line, which is responsible for a long-lasting severe precipitation event. It is clear that the interaction among mountain blockage, evaporation cooling effect, and the development of an enhanced widespread high pressure zone over the southwest plain area, are the key factors to modulate the evolution of the convective system.

Chinese Abstract………………………………………………………………………………………………I
English Abstract………………………………………………………………………………………………III
Acknowledgments…………………………………………………………………………………………………V
Table of Contents……………………………………………………………………………………………VI
List of Tables……………………………………………………………………………………………………X
List of Figures…………………………………………………………………………………………………X
Chapter 1 Introduction………………………………………………………………………………1
Chapter 2 Descriptions of Variational Doppler Radar Analysis
System (VDRAS)……………………………………………………………………………………………………5
2.1 Forward model……………………………………………………………………………………………5
2.2 Cost function and adjoint model……………………………………………6
Chapter 3 Implementation of terrain-resolving scheme by the
Ghost-Cell Immersed Boundary Method……………………………………………9
3.1 Ghost-Cell Immersed Boundary Method…………………………………9
3.2 Steps of the implementation………………………………………………………10
3.2.1 Identification of terrain boundary and grids classification……………………………………………………………………………………………………10
3.2.2 Interpolation for the image point…………………………………10
3.2.3 Ghost-Cell variable update……………………………………………………12
3.2.4 Implementation for adjoint model……………………………………13
Chapter 4 Tests on modified forward model……………………………15
4.1 Two-dimensional linear mountain wave………………………………15
4.2 Three-dimensional lee side vortex………………………………………16
4.3 Parallel forecast comparison with WRF……………………………17
4.4 Building-scale simulation……………………………………………………………20
Chapter 5 An Observation Simulation System Experiment(OSSE) with radar data assimilation………………………………………………………………22
5.1 Pseudo observation………………………………………………………………………………22
5.2 Experimental design……………………………………………………………………………22
5.3 Results of retrieval…………………………………………………………………………23
Chapter 6 Real case analysis: precipitation process analysis …………………………………………………………………………………………………………………………………………25
6.1 Overview of the real case……………………………………………………………25
6.1.1 Synoptic environment……………………………………………………………………26
6.1.2 Prefrontal rainbands evolution…………………………………………26
6.2 Radar data assimilation experiment……………………………………27
6.2.1 Data sources of the mesoscale background and assimilation…………………………………………………………………………………………………………27
6.2.2 Experiment design and assimilation strategy………29
6.2.3 Verification of multivariate analysis………………………30
6.2.4 Multivariate analysis…………………………………………………………………33
6.3 Sensitivity diagnosis in radar data assimilation experiments……………………………………………………………………………………………………………37
6.3.1 Design of sensitivity experiments…………………………………39
6.3.2 Increments over surface layer……………………………………………42
6.3.3 Increments of cross-mountain Y-axis average………43
6.3.4 Role played by evaporation process………………………………45
6.4 Schematic Diagram…………………………………………………………………………………46
Chapter 7 Summary and future work…………………………………………………48
7.1 Summary and conclusions…………………………………………………………………48
7.2 Future work…………………………………………………………………………………………………50
References………………………………………………………………………………………………………………51
Tables…………………………………………………………………………………………………………………………55
Figures………………………………………………………………………………………………………………………56

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