FORMOSAT-3 GPS RO觀測資料之校驗及其對東亜地區梅雨季天氣分析與預報之系統性影響

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：8

、訪客IP：18.222.119.148

姓名

吳家苓(Chia-Ling Wu) 查詢紙本館藏

畢業系所

大氣物理研究所

論文名稱

FORMOSAT-3 GPS RO觀測資料之校驗及其對東亜地區梅雨季天氣分析與預報之系統性影響

相關論文

★ 1999年與2000年二月台灣地區異常降水之分析探討	★ 台灣地區模式降雨預報之校驗評估
★ 東亞夏季季風肇始之探討	★ 1998年夏季季風肇始期間南海地區之熱力與水汽分析
★ MYEX98梅雨鋒面個案之模擬探討	★ 2004年台灣北部九一一豪雨個案探討
★ 台灣中南部地區梅雨季豪大雨天氣型態之合成分析	★ FORMOSAT-3 GPS RO資料對東亞地區梅雨天氣系統診斷分析之影響評估
★ 台灣北部地區梅雨季豪大雨天氣型態之合成分析

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

本研究之主要工作分成兩部分：其一為對FORMOSAT-3 GPS RO反演探空資料與無線電探空觀測之校驗，校驗時間從2006年12月至2007年11月為期一年的全球GPS RO觀測資料，目的在於校驗反演探空資料的可靠性；其二為探討FORMOSAT-3 GPS RO觀測資料對東亞地區梅雨季天氣分析與模式預報之系統性影響，使用客觀分析方法及模式預報誤差統計分析，以有無加入GPS RO觀測資料分析2007年梅雨季的模式預報誤差，目的在於評估引進GPS RO衛星觀測資料對東亜地區梅雨天氣系統研究的影響並探討其應用性。
GPS RO反演探空之垂直校驗結果顯示，基本上在對流層內等壓面高度場的平均差異幾近於零，標準偏差由地面往上增加，但都未超過100m，20hPa以上略為偏高，但差異都非常小。溫度場在20hPa 以下平均偏差值雖有正值與負值，但都小於0.5°C，標準偏差值約1.5-2°C。水氣壓場的校驗分析整體來說GPS RO的水氣量觀測都偏低，在熱帶地區低對流層尤其近地表在夏季平均偏差可高達3hPa，其他季節則少於2hPa。分析結果顯示GPS RO反演探空觀測品質是可以值得信賴的。
在GPS RO觀測應用在梅雨季天氣分析與模式預報方面，其一為經由最佳客觀分析方法直接將GPS RO反演探空資料融入氣象場分析，比較分析結果發現加入GPS RO反演探空資料在陸地上差異不大，但在海面上太平洋副高脊延伸地區確有明顯的差異，主要原因可能是做為客觀分析初始猜測場與實際大氣狀態不符所導致。其二為經由WRF模式及3DVAR資料同化技術將GPS RO觀測資料融入模式初始分析場，經模式初始化過程後差異並不明顯，即使使用update cycling run的方式，仍對東亞梅雨季天氣預報影響不大。同化GPS RO觀測資料後，一開始模式預報場的RMSE較大，但隨著模式積分時間到60小時後，RMSE開始小於未加入GPS RO觀測資料的實驗組。若只校驗海洋上之RMSE，則可發現在模式積分24小時之後，加入GPS RO觀測資料之RMSE將會比未加入小，這也表示GPS RO觀測資料在缺乏傳統觀測的海面上有正面的幫助。

摘要(英)

The contents of this paper are divided into two parts. One is the verification of FORMOSAT-3 GPS radio occultation (RO) retrieved data. The time period of verification is from December 2006 to November 2007. The goal of this part is to verify the reliability of the GPS RO retrieved data as compared with radiosonde observations. The other is to examine whether there is improvement on weather analysis and model forecast during the Mei-Yu season in the East Asian area by the aid of FORMOSAT-3 GPS RO data. In this part, objective data analysis method and error statistics of model forecasts are adopted.
The results of vertical profile verification show that the averaged differences of isobaric geopotential height between the GPS RO data and the radiosonde data are nearly zero in the troposphere, and the standard deviations of differences increase with height and have values less than 100m. The mean differences of temperature below 20hPa show positive and negative values with magnitude smaller than 0.5°C. The standard deviations of the temperature differences are approximately 1.5-2°C. The verification results of water vapor pressure indicate that the GPS RO observations are usually drier than the radiosonde data. The mean difference between them can reach 3hPa near the surface in the tropics during summer, while in other seasons the mean difference is usually smaller than 2hPa. The results of verification suggest that the quality of the GPS RO retrieved data is reliable.
In the impact study of the GPS RO data on the diagnosis and model forecast of the Mei-Yu weather system, we use two methods in applying the GPS RO data. One of them is using optimum interpolation method with and without GPS RO data to investigate their influences on weather analysis. The results show very little differences over the land, but distinct differences in the location of Western Pacific subtropical ridge. The major cause may be probably due to the first guess used in the objective analysis not agreeing with real atmospheric condition. The other one is using WRF-3DVAR model to investigate the impact of applying the GPS RO data. The difference is not obvious after initialization process of the model. Even though we used method of update cycling run, it affected only slightly in the model forecast of Mei-Yu development in the East Asian area. At the beginning of the model run, the RMSE of forecasts with GPS RO data is somewhat larger than that without GPS RO data. But with the model integration time longer than 60 hours, the RMSE starts to be smaller than that without GPS RO data. If we only verify the forecast results over the sea, then we can detect that after integrating 24 hours the RMSE with the GPS RO data are smaller than that excluding the GPS RO data. It suggests that the GPS RO observational data are useful for weather prediction over the sea where the traditional observational data are almost absent.

關鍵字(中)

★ 梅雨季預報校驗
★ 衛星資料校驗

關鍵字(英)

★ GPS RO

論文目次

中文摘要 ……………………………………………………………i
英文摘要 ……………………………………………………………iii
致謝 …………………………………………………………………v
目錄 …………………………………………………………………vi
圖表說明 …………………………………………………………viii
一、前言………………………………………………………………… 1
二、資料來源與研究方法 …………………………………………… 5
2.1 資料來源 ………………………………………………………… 5
2.2 GPS RO反演探空觀測資料之校驗方法 ……………………… 6
2.3 客觀分析方法 …………………………………………………… 9
2.4 模式模擬與實驗設計 ……………………………………………11
2.4.1 模式介紹 ……………………………………………………11
2.4.2 三維變分資料同化系統（3DVAR） …………………………12
2.4.3 實驗設計 ……………………………………………………14
三、GPS RO反演探空資料與radiosonde統計校驗結果分析 ………17
3.1 資料統計特徵 …………………………………………………17
3.2 緯度區域校驗統計分析 ………………………………………18
3.3 探空系統校驗統計分析 ………………………………………21
四、客觀分析與模式預報誤差的統計分析 ………………………24
4.1 客觀分析的統計分析 …………………………………………24
4.1.1 高度場 ……………………………………………………24
4.1.2 溫度場 ……………………………………………………25
4.1.3 水氣場 ……………………………………………………25
4.1.4 小結 ………………………………………………………26
4.2 模式預報誤差的統計分析 ……………………………………27
4.2.1 模式同化6小時後預報誤差分析……………………………27
4.2.2 模式同化12小時後預報誤差分析 ………………………29
4.2.3 模式預報與探空觀測之間的距平相關（AC） …………30
4.2.4 小結 ………………………………………………………31
五、結論與未來展望 ……………………………………………………32
參考文獻 ………………………………………………………………36
附表 ……………………………………………………………………39
附圖 ……………………………………………………………………40

參考文獻

陳正祥，1957：台灣氣候之分類。氣象學報，第三卷第二期，1-7頁。
陳泰然與紀水上，1978：台灣梅雨鋒面之中尺度結構。大氣科學，5，35-47。
蔡清彥與陳正改，1980：影響台灣北部地區之梅雨系統。大氣科學，7，49-58。
林松錦與陳雯美，1987：Barnes客觀分析法中影響半徑的選擇。大氣科學，15，59-68。
黃清勇與朱延祥，2004：FORMOSAT-3/COSMIC科學研究簡介。大氣科學，32， 293-328。
林松錦與周思運，1985；最佳客觀分析法之模擬實驗。氣象預報與分析，103，56-63。
林松錦，2006：福衛三號IOP觀測資料對東亞地區梅雨研究的影響評估與分析應用。國家實驗研究院國家太空中心專題研究報告，94-NSPO(B)-IOP-FA07-01，52頁。
洪景山、林得恩、劉素屏、周仲島、簡芳菁、張文錦、林沛練、繆璿如、陳致穎與
雷銘中，2006：WRF模式之敏感度測試第一部分：探空測站上的校驗。大氣科學，34，261-274。
Anthes, R. A., C. Rocken, and Y. H. Kuo, 2000: Applications of COSMIC to meteorology and climate. TAO, 11, 115-156.
——, P. A. Bernhardt, Y. Chen, L. Cucurull, K. F. Dymond, D. Ector, S. B. Healy, S.-P. Ho, D. C. Hunt, Y.-H. Kuo, H. Liu, K. Manning, C. McCormick, T. K. Meehan, W. J. Randel, C. Rocken, W. S. Schreiner, S. V. Sokolovskiy, S. Syndergaard, D. C. Thompson, K. E. Trenberth, T.-K. Wee, N. L. Yen, and Z. Zeng, 2008：The COSMIC/FORMOSAT-3 mission：early results, Bull. Amer. Meteor. Soc. 89, 313-333.
Barker, D., W. Huang, Y.-R. Guo and Al. Bourgeois, 2003: A three-dimensional variational (3DVAR) data assimilation system for use with MM5. NCAR Technical Note (NCAR/TN-453+STR), 68 pp.
Chang, C.-P., S. C. Lin, C. S. Liou, and W.T. Liu, 1999: An experiment using NSCAT winds in tropical mesoscale numerical weather prediction. Geophy. Res. Lett., 26, 311-314.
Chen, G.. T. J., and C. P. Chang, 1980: The structure and vorticity budget of an early summer monsoon trough (Mei-Yu) over southeastern China and Japan. Mon. Wea. Rev., 108, 942-953.
Chen, G.. T. J., 1992: Mesoscale features observed in the Taiwan Mei-Yu season. J. Meteor. Soc. Japan, 70, 497-516.
Gandin, L. S., 1963: Objective Analysis of Meteorological Fields. 242pp. Translated from Russian, 1965.
Hong, S.-Y., and H.-L. Pan, 1996: Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon. Wea. Rev., 124, 2322-2339.
Kain, J. S., and J. M. Fritsch, 1990: A one-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sci., 47, 2784-2802.
——, and J. M. Fritsch, 1993: Convective parameterization for mesoscale models: The Kain-Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, edited by K. A. Emanuel and D. J. Raymond, Amer. Meteor. Soc., 246 pp.
Kuo, Y. H., S. Sokolovskiy, R. A. Anthes, and F. Vandenberghe, 2000: Assimilation of GPS radio occultation data for numerical weather prediction. TAO, 11, 157-186.
——, and T.K. Wee, S. Sokolovskiy, C. Rocken, W. Schreiner, and D. Hunt, 2004: Inversion and error estimation of GPS radio occultation data. J. Meteor. Soc. Japan, 82, 507-531.
——, and W. S. Schreiner, J. Wang, D. L. Rossiter, and Y. Zhang, 2005: Comparison of GPS radio occultation soundings with radiosondes. Geophy. Res. Lett., 32, L05817, doi: 10.1029/2004GL021443.
——, and X. Zou, S.-J. Chen, Y.-R. Guo, W. Huang, R. Anthes, D. Hunt, M. Exner, C. Rocken, and S. Sokolovskiy, 1998: A GPS/MET sounding through an intense upper-level front, Bull. Amer. Meteor. Soc., 79, 617-626.
Kursinski, E. R., G. A. Hajj, K. R. Hardy, L. J. Romans, and J. T. Schofield, 1995: Observing tropospheric water vapor by radio occultation using the global positioning system, Geophs. Res. Lett., 22, No. 17, 2365-2368.
Lin, S. C., Y. T. Yen, C. L. Wu, and Y. J. Chou, 2006: A preliminary comparison of FORMOSAT-3 GPS radio occultation soundings with radiosondes. FORMOSAT- 3/COSMIC Workshop 2006, Nov. 28 – Dec. 1, 2006, Taipei, Taiwan, 37-38.
Liu, H., X. Zou, H. Shao, R. A. Anthes, J. C. Chang, J. H. Tseng, and B.Wang, 2001: Impact of 837 GPS/MET bending angle profile on assimilation and forecast for the period June 20-30, 1995. J. Geophy. Res., Atmospheres, 106, 31771-31786.
Lin, Y. L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Clim. Appl. Meteor., 22, 1065-1092.
Parrish, D. F., and J. Derber, 1992: The National Meteorological Center’s spectral and statistical interpolation analysis system. Mon. Wea. Rev., 120, 1747-1763
Rocken, C., R. Anthes, M. Exner, D. Hunt, S. Sokolovskiy, R. Ware, M. Gorbunov, W. Schreiner, D. Feng, B. Herman, Y.H. Kuo, and X. Zou, 1997: Analysis and validation of GPS/MET data in the neutral atmosphere. J. Geophy. Res., 102, 29849-29866.
Schlatter, T. W., 1975: Some experiments with a multivariate statistical objective analysis scheme. Mon. Wea. Rev., 103, 246-257.
Thayer, D., 1974: An improved equation for the radio refractive index of air. Radio Sci., 9, 803-807.
Wickert, J., T. Schmidt, 2004: Comparison of vertical refractivity and temperature profiles from CHAMP with radiosonde measurements. Scientific Report No. 04-19, Danish Meteorological Institute, 38pp.
——, and T. Schmidt, G. Beyerle, R. , C. Reigber, and N. Jakowski, 2004: The radio occultation experiment aboard CHAMP: Operational data analysis and validation of vertical atmospheric profiles. J. Meteor. Soc. Japan, 82, 381-395.
Ware, R., M. Exner, D. Feng, M. Gorbunov, K. Hardy, B. Herman, Y. Kuo, T. Meehan, W. Melbourne, C. Rocken, W. Schreiner, S. Sokolovskiy, F. Solheim, X. Zou, R. Anthes, S. Businger, and K. Trenberth, 1996: GPS soundings of the atmosphere from low earth orbit: Preliminary results. Bull. Amer. Meteor. Soc., 77, 19-40.
Yeh, H.-C., and Y.-L. Chen, 1998: Characteristics of the rainfall distribution over Taiwan Island during TAMEX. J. Appl. Meteor., 27, 1457–1469.
Zou, X., H. Liu, R. A. Anthes, H. Shao, J. C. Chang, and Y.-J. Zhu, 2004: Impact of CHAMP radio occultation observations on global analyses and forecasts in the absence of AMSU radiance data. J. Meteor. Soc. Japan, 82, 533-549

指導教授

林松錦(Song-Chin Lin)

審核日期

2008-7-18

推文