| 研究生: |
江秉儒 Ping-Ju Chiang |
|---|---|
| 論文名稱: |
利用以GSI-3DVar為基礎的系集變分混合同化系統探討GPS掩星觀測對熱帶氣旋模擬之影響 Assimilation of GPS RO Data for Tropical Cyclone Based on GSI 3DVar-Based Ensemble-Variational Hybrid DA System |
| 指導教授: |
黃清勇
Ching-Yuang Huang |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
地球科學學院 - 大氣科學學系 Department of Atmospheric Sciences |
| 論文出版年: | 2016 |
| 畢業學年度: | 104 |
| 語文別: | 中文 |
| 論文頁數: | 61 |
| 中文關鍵詞: | 無線電衛星掩星觀測 、系集變分混合資料同化系統 |
| 外文關鍵詞: | GPSRO, Ensemble-Variational Hybrid DA System |
| 相關次數: | 點閱:12 下載:0 |
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一個結合變分方法與系集卡曼方法的混合(Hybrid)資料同化方法將在本研究運用。在此,系集所計算的背景誤差協方差會透過變分資料同化求得最佳解,使所求得的最佳分析場同時具有傳統變分資料同化以及系集卡曼資料同化的雙重優點,以達成混合(Hybrid)的目的。
本研究中沒有使用任何虛擬渦旋方法並透過以GSI 3DVAR為基礎的混合資料同化系統,且在中央氣象局的全球預報模式來運行以了解其對於改善颱風預報準確度的影響。而熱帶氣旋主要的生命周期是以海上為主,在一般同化所需的觀測資料中,傳統觀測一直是模式初始分析最主要的資料來源,一般衛星觀測則為輔助來源,但在海上是缺乏傳統觀測資料的。近年發展的GPS掩星觀測主要是利用無線電波掩星折射觀測原理,得到「偏折角」及「折射率」資料,進而推求得知大氣層溫度、氣壓、乃至水汽等垂直剖面,由於其高垂直解析之優勢,更可涵蓋傳統觀測方式不易取得的海上資訊。
本研究所選取的個案為2015年中度颱風蘇迪勒(Soudelor),並使用ERA Interim 的再分析資料來做為驗證場,實驗共分為兩個部分,第一部分比較運用混合資料同化系統相較於傳統三維變分資料同化方法對於預報準確度的關係,結果指出使用混合資料同化系統有效地改善全球環境場,進而使預報準確度提升。第二部分的實驗探討分別同化GPS掩星觀測資料裡的折射率以及偏折角對全球模擬結果以及颱風周圍環境場的改善和颱風模擬的影響,結果顯示在同化中加入GPSRO的觀測資訊會讓模擬更接近驗證場。
An ensemble -variational hybrid data assimilation (DA) system based on Ensemble Kalman filter (EnKF) and three-dimensional variational data assimilation (3DVar) system was applied in this study. In this hybrid system, flow-dependent ensemble covariances were estimated from an EnKF-generated ensemble and incorpotated into the variational minimization. In order to understand the improvement of the analysis for forecast of tropical cyclone (typhoon) in hybrid system , gridpoint statistical interpolation (GSI) 3DVar-based hybrid system were executed in CWB global forecast system model(CWB/GFS) without employing any bogus schemes .
Conventional observation data are the main source for the model initialization in the DA method , but there is lack of conventional data over the ocean where the typhoon evolves. GPSRO data was developed recently , which makes use of radio signals transmitted by the global positioning system (GPS) satellites and then obtains the data of bending angle and refractivity to estimate temperature , pressure and vapor in the global atmosphere with high precision and vertical resolution over the entire ocean .
In this study , the hybrid system is used to improve the forecast of Typhoon Soudelor(2015/08) and the ERA Interim data is regarded as the verification field.
There are two main experiment in the research. One is the comparison of hybrid system and conventional 3DVar system on the impact of forecast accuracy. The result shows that using hybrid system would have a better performance than using 3DVar system in global domain. The other is the impact of assimilating GPSRO data (bending angle and refractivity) for the forecast accuracy. Sensitivity tests indicated that assimilation of GPSRO data would have a positive impact both on the prediction in global domain and typhoon domain.
王潔如,2004年:侵台颱風之 GPS 折射率 3DVAR 資料同化及數值模
擬。國立中央大學,大氣物理研究所,碩士論文,108 頁。
黃振星,2011年:同化FORMOSAT-3/COSMIC 及Follow-on 掩星觀測資
料對颱風預報之影響。國立中央大學,大氣物理研究所,碩士論文,
108頁。
迮嘉欣,2009年:資料同化對臺灣地區颱風和梅雨模擬之影響。國立中
央大學,大氣物理研究所,碩士論文,81 頁。
陳冠翰,2014年:利用系集卡曼同化和四維變分同化系統探討GPS掩星
觀測對颱風梅姬(2010)模擬之影響。國立中央大學,大氣物理研究
所,碩士論文,80頁。
趙竑,2015年:利用WRF 3DVAR Hybrid 資料同化系統探討GPS掩星觀
測對颱風海燕及梅姬模擬之影響。國立中央大學,大氣物理研究所,
碩士論文,101頁。
吳俊澤,2007年:利用MM5 4DVAR 模式同化掩星折射率資料及虛擬渦旋
探討颱風數值之影響。國立中央大學,大氣物理研究所,碩士論
文,70頁。
陳怡孜,2013年:GNSS RO 觀測資料對颱風莫拉克預報之影響:觀測系統
模擬實驗。國立中央大學,大氣物理研究所,碩士論文,89頁。
呂佳龍,2010年:同化GPS掩星及其他觀測資料對梅雨模擬之影響。國立
中央大學,大氣物理研究所,碩士論文,118頁。
陳舒雅,2008年:GPS 掩星觀測資料同化及對區域天氣預報模擬之影響。
國立中央大學,大氣物理研究所,博士論文,154頁。
交通部中央氣象局委託辦理研究計畫期末報告系集變分混合資料同化系統
之發展:黃清勇、楊明仁,計畫編號: MOTC-CWB-103-M-08。
Anisetty, S. K. A. V. P. R., C.-Y. Huang, and S.-Y. Chen,
2014: Impact of FORMOSAT-3/COSMIC radio occultation
data on the prediction of super cyclone Gonu (2007):
A case study. Nat. Hazards, 70, 1209–1230.
Chen, S.-Y., C.-Y. Huang, Y.-H. Kuo, Y.-R. Guo, and S.
Sokolovskiy, 2009:
Assimilation of GPS refractivity from FORMOSAT-3/ COSMIC
using a nonlocal operator with WRF 3DVAR and its
impact on the prediction of a typhoon event. Terr.
Atmos. Oceanic Sci., 20, 133–154.
Chien, F.-C., and Y.-H. Kuo, 2010: Impact of FORMOSAT-3/
COSMIC GPS radio occultation and dropwindsonde data
on regional model predictions during the 2007 Mei-yu
season. GPS Solutions, 14, 51–63.
Cucurull, L., Y.-H. Kuo, D. Barker, and S. R. H. Rizvi,
2006: Assessing the
impact of simulated COSMIC GPS radio occultation data on
weather analysis over the Antarctic: A case study.
Mon. Wea. Rev., 134, 3283-3296.
Cucurull, L., 2010: Improvement in the use of an
operational constellation of GPS radio occultation
receivers in weather forecasting. Wea. Forecasting,
25, 749–767.
Cucurull, L., J. C. Derber, and R. J. Purser, 2013: A
bending angle forward operator for global positioning
system radio occultation measurements. J. Geophys.
Res. Atmos., 118, 14–28.
Dee, D. P., and Coauthors, 2011: The ERA-Interim
reanalysis: Configuration and performance of the data
assimilation system. Quart. J. Roy. Meteor. Soc.,
137,553–597.
Healy, S. B., 2008: Forecast impact experiment with a
constellation of GPS radio occultation receivers.
Atmos. Sci. Lett., 9, 111– 118.
Huang, C.-Y., Y.-H. Kuo, S.-H. Chen, and F. Vandenberghe,
2005: Improvements on typhoon forecast with
assimilated GPS occultation refractivity. Wea.
Forecasting, 20, 931–953.
Huang,C.-Y., S.-Y. Chen, S. K. A. V. P. R, Anisetty, S.-
C. Chen, and L.-F.Hsiao,2016:An Impact Study of GPS
Radio Occultation Observations on Frontal Rainfall
Prediction with a Local Bending Angle Operator. Amer.
Meteor. Soc., 31, 129–151.
Huang,C.-Y.,and Coauthors, 2010: Impact of GPS radio
occultation data assimilation on regional weather
predictions. GPS Solutions, 14, 35–49.
Kleist, D. T., D. F. Parrish, J.C. Derber, R. Treadon,
R.M. Errico, and R.Yang, 2009a: Improving incremental
balance in the GSI 3DVar analysis system. Mon. Wea.
Rev., 137, 1046–1060.
Snyder, C., F. Zhang, 2003:Assimilation of Simulated
Doppler Radar observation with an Ensemble Kalman
Filter. J.Atmos. Sci., 131,1663-1677.
Wu, W.-S., R. J. Purser, and D. F. Parrish, 2002: Three-
dimensional variational analysis with spatially
inhomogeneous covariances. Mon. Wea. Rev., 130, 2905–
2916.
Wu, C.-C., G.-Y. Lien, J.-H. Chen, and F. Zhang, 2010:
Assimilation of Tropical Cyclone Track and Structure
Based on the Ensemble Kalman Filter (EnKF). J. Atmos.
Sci., 67, 3806–3822.
Wang, X., 2010: Incorporating ensemble covariance in the
Gridpoint Statistical Interpolation (GSI) variational
minimization: A mathematical framework. Mon. Wea.
Rev., 138,2990–2995.
Wang, X., D. Parrish, D. Klesist, and J. Whitaker ,
2012:GSI 3DVar-Based Ensemble–Variational Hybrid Data
Assimilation for NCEP Global Forecast System: Single-
Resolution Experiments. Mon.Wea. Rev., 141,4098–4117
Wang, X., T. Lei, 2014:GSI-Based Four-Dimensional
Ensemble-Variational (4DEnsVar) Data Assimilation:
Formulation and Single-Resolution Experiments with
Real Data for NCEP Global Forecast System. Mon.Wea.
Rev., 142, 3303–3325.
Zhang, X., Y.-H. Kuo, S.-Y. Chen, X.-Y. Huang, and L.-F.
Hsiao, 2014:Parallelization strategies for the GPS
radio occultation data assimilation with a nonlocal
operator. J. Atmos. Oceanic Technol., 31, 2008–2014