颱風Bavi(2020)的強度於8月25日18UTC時增強了100節(3級)，並且在通過東海的淺海區時其強度維持6小時，對朝鮮半島和中國東北地區造成相當大的災害。本研究基於衛星、氣候再分析資料與IORS測站資料所觀測出的海洋溫度結構和海洋數值模擬實驗，來研究颱風Bavi在東海淺海地區的海洋-颱風之間的相互作用。由於颱風在東海淺海區增強時，引起了較大的海表溫度冷卻(約8℃)。根據數值實驗指出，這歸因於異常的海洋溫度結構:海表面溫度非常溫暖並且超過了30℃，以及水下存在著黃海底層冷水團，強烈的海洋層化效應可能限制了垂直混和。而且根據上層海洋1DPWP的模擬實驗指出，淺海並不是限制颱風所導致的海表溫度冷卻過程中的主要因素。另外，控制颱風加強的因素為海氣熱通量。IORS測站資料結果顯示，在颱風Bavi增強階段時的焓通量為+700 W/m2，海洋為颱風提供了相當巨大的能量。同樣地，大氣環境也為颱風Bavi的增強過程提供了有利條件。中低層的相對濕度（超過80%）近乎飽和，有利於颱風的強度增強，特別是當它強度達到Category-3時。然而，大氣的垂直風切強度並不利於颱風Bavi的增強，儘管垂直風切隨著颱風的增強而減弱（最小為11.7 m/s）。此外，對於颱風最大潛在強度的估計與Bavi颱風一致。 可以合理預期Bavi颱風可能會增強到Category-3。這項研究的結果能夠解釋為何颱風Bavi在淺海的影響下強度還能夠增強。

Typhoon Bavi (2020) intensified by 100 kt (Category-3) at 18Z 25 August and maintained in the shallow East China Sea region for 6 hours, causing considerable damage in the Korean Peninsula and Northeast China. Based on satellite, reanalysis data, and IORS in-situ station observed ocean thermal structure and numerical experimentsocean mixing models, in this study, we examined the ocean-typhoon interaction over around the shallow East China Sea region under Typhoon Bavi. Since this typhoon intensified over the shallow East China Sea region, typhoon-induced a large SST cooling effect (around 8℃oC), attributed to the abnormal ocean thermal structure, including over 30℃oC warming sea surface temperature and prevailing of the Yellow Sea Cold Bottom Water along with the strong stratification effects, which may prevent the vertical mixing process, based on numerical ocean mixing experimentsmodel. Moreover, the 1DPWP ocean mixing modelsimulation also emphasized that the shallow water was not the main factor in controlling typhoon-induced cooling. In addition, the typhoon’s typhoon’s response to the ocean regarding the air-sea heat flux-controlled typhoon intensification. The IORS observation results indicated that the air-sea heat flux enthalpy flux was generally +700 W/m2 during Typhoon Bavi’s Bavi’s intensification phase, which supplied the intense energy from the ocean to the typhoon. Likewise, the atmospheric environment also supported favorable conditions for the intensification process of Typhoon Bavi. Near-saturated relative humidity (over 80 %) at lower and mid-levels may contribute to the typhoon’s intensity evolution, notably as it reached a Category-3 state. However, the vertical wind shear was still high and did may not support Typhoon Bavi intensification, although it weakened (minimum was 11.74 m/s) as the typhoon intensified. Furthermore, the maximum potential intensity estimation was generally consistent with Typhoon Bavi in reality. It is reasonable to expect that this typhoon could intensify to Category-3. The results of this study could explain the intensification of Typhoon Bavi over this incredible region as well as the effect of shallow water in this case.

摘要 i
ABSTRACT ii
ACKNOWLEDGMENTS iii
TABLES OF CONTENTS iv
LIST OF FIGURES vii
LIST OF TABLES xv
LIST OF ABBREVIATIONS xvii
CHAPTER 1. INTRODUCTION 1
1.1 Motivation 1
1.2 Literature Review 4
1.2.1 The importance of forecast typhoon intensity 4
1.2.2 The physical mechanism behind typhoon intensification 6
1.2.3 Numerical models 11
1.2.4 Maximum potential intensity (MPI) estimation 14
1.2.5 Characteristics of ECS 16
1.3 Scope of Present Study 18
CHAPTER 2. DATASETS 29
2.1 Typhoon Best Track Dataset 29
2.2 Satellite Dataset 31
2.3 Oceanic Reanalysis Datasets 33
2.3.1 HYbrid Coordinate Ocean Model (HYCOM) 33
2.3.2 Simple Ocean Data Assimilation, version 3 (SODA3) 34
2.3.3 Global Ocean Data Assimilation System (GODAS) 36
2.4 Monthly Climatology for Oceanic Parameters 38
2.5 Atmospheric Reanalysis Datasets 39
2.5.1 ECMWF Reanalysis version 5 (ERA5) 39
2.5.2 National Centres for Environmental Prediction Reanalysis and National Center for Atmospheric Research (NCEP/NCAR Reanalysis 1) 40
2.6 In-situ Observation 41
CHAPTER 3. METHODOLOGY 55
3.1 Upper Ocean Heat Content and Depth-average temperature (Td ) 55
3.2 Price 2009 model 58
3.3 One-dimensional Price-Weller-Pinkel (1DPWP) simulation 60
3.4 Air-sea enthalpy flux estimation 61
3.5 Vertical wind shear (VWS) estimation 63
3.6 Maximum Potential Intensity (MPI) estimation 64
CHAPTER 4. RESULTS 71
4.1 Ocean response to Typhoon Bavi 71
4.2.1 Satellite observation 71
4.2.2 Reanalysis 73
4.2.3 In-situ observation 77
4.2.4 1DPWP simulation 82
4.2 Response of Typhoon Bavi (2020) to the Ocean 87
4.3 Atmosphere environment 91
4.4 The MPI estimation 93
CHAPTER 5. DISCUSSION AND CONCLUSION 133
BIBLIOGRAPHIES 136
ABSTRACT ii
ACKNOWLEDGMENTS iii
TABLES OF CONTENTS iv
LIST OF FIGURES vii
LIST OF TABLES xiv
LIST OF ABBREVIATIONS xvi
CHAPTER 1. INTRODUCTION 1
1.1 Motivation 1
1.2 Literature Review 4
1.2.1 The importance of forecast typhoon intensity 4
1.2.2 The physical mechanism behind typhoon intensification 6
1.2.3 Numerical models 11
1.2.4 Maximum potential intensity (MPI) estimation 14
1.2.5 Characteristics of ECS 16
1.3 Scope of Present Study 18
CHAPTER 2. DATASETS 29
2.1 Typhoon Best Track Dataset 29
2.2 Satellite Dataset 31
2.3 Oceanic Reanalysis Datasets 33
2.3.1 HYbrid Coordinate Ocean Model (HYCOM) 33
2.3.2 Simple Ocean Data Assimilation, version 3 (SODA3) 34
2.3.3 Global Ocean Data Assimilation System (GODAS) 36
2.4 Monthly Climatology for Oceanic Parameters 38
2.5 Atmospheric Reanalysis Datasets 39
2.5.1 ECMWF Reanalysis version 5 (ERA5) 39
2.5.2 National Centres for Environmental Prediction Reanalysis and National Center for Atmospheric Research (NCEP/NCAR Reanalysis 1) 40
2.6 In-situ Observation 41
CHAPTER 3. METHODOLOGY 55
3.1 Upper Ocean Heat Content and Depth-average temperature (Td ) 55
3.2 Price 2009 model 58
3.3 One-dimensional Price-Weller-Pinkel (1DPWP) simulation 60
3.4 Air-sea enthalpy flux estimation 61
3.5 Vertical wind shear (VWS) estimation 63
3.6 Maximum Potential Intensity (MPI) estimation 64
CHAPTER 4. RESULTS 71
4.1 Ocean response to Typhoon Bavi 71
4.2.1 Satellite observation 71
4.2.2 Reanalysis 73
4.2.3 In-situ observation 77
4.2.4 1DPWP simulation 82
4.2 Response of Typhoon Bavi (2020) to the Ocean 87
4.3 Atmosphere environment 91
4.4 The MPI estimation 93
CHAPTER 5. DISCUSSION AND CONCLUSION 133
BIBLIOGRAPHIES 136

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