高解析衛星資料在颱風降雨估算技術評估及其應用

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：14

、訪客IP：3.135.216.174

姓名

蔡伊其(I-Chi Tsai) 查詢紙本館藏

畢業系所

大氣科學學系

論文名稱

高解析衛星資料在颱風降雨估算技術評估及其應用
(Evaluation of high resolution satellite data in typhoon rainfall estimation and its application.)

相關論文

★ 應用SSM/I衛星資料於西太平洋颱風特性之分析	★ 應用衛星資料於熱帶氣旋之環境場分析
★ 衛星資料反演海氣參數及其在梅雨期海上中尺度對流系統生成發展之應用	★ 應用SSM/I衛星資料分析桃芝與納莉颱風之降雨及海氣參數的變化
★ 利用Spot 4衛星的Vegetation資料比較NDVI, ARVI, 及AFRI植被指數與氣溶膠厚度之關係	★ 應用衛星資料分析颱風降雨與颱風強度變化之關係
★ 應用SSM/I衛星資料於颱風中心定位及最大風速估算	★ 應用衛星資料分析海氣參數與颱風強度變化之關係
★ MODIS在生質燃燒監測之應用研究	★ 應用SSM/I衛星觀測資料估算颱風定量降水
★ AMSU衛星資料反演大氣溫濕剖面及其在颱風強度估算上之應用	★ 利用HHT之EMD方法分析SSM/I資料估算之客觀指數與颱風強度年際變化關係
★ 模式和SSM/I客觀潛力指數在中尺度對流系統預報上之應用	★ SSM/I衛星資料估算之客觀潛力指數與颱風強度變化之關係
★ 應用SSM/I衛星資料分析颱風形成之激發機制	★ 衛星資料估算颱風旋轉及強度變化在熱帶氣旋定量降雨預測之研究

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)

Kidder et al.(2005)提出 TRaP 方法，將衛星反演之降雨分佈平移，迅速估算熱帶氣旋未來可能帶來的降雨。陳(2010)修正 TRaP 方法，考量台灣地形效應的影響，並根據測站歷史降雨資料重新估算颱風降雨，稱為 I-TRaP。由於 I-TRaP 使用反演之降雨分布進行計算，如何獲得更好的颱風降雨分布仍然是很重要的課題。
在先前的研究中僅使用單一衛星的降雨產品，受限於掃描之時間解析度，隨著許多研究的發展，高解析多衛星合成之降雨產品已經有越來越好的表現，本研究比較幾種常見的全球多衛星產品(GSMaP、IMERG、PERSIANN)，考慮於西北太平洋上的颱風強降雨之表現，結果以 GSMaP為最佳。微波反演過程的判定降雨型態，確實會對層狀性降雨與對流性降雨的分類產生錯誤判定，但對於降雨結果的影響不大。進一步討論於強降雨造成誤差的可能原因，與目前的輻射方法仍難以準確估計大氣液態水含量，在降雨誤差越大時大氣液態水含量的差異越大。
使用 GSMaP 降雨產品以 I-TRaP 估算台灣地區的颱風降雨，為了將不同降雨產品的結果突顯而對現行 I-TRaP 的版本進行調整，修正以往僅使用衛星平移後的總降雨量進行回歸，新增以個別資料點回歸，能夠有效增加大雨的預報結果。GSMaP 相較先前使用 SSMIS 的方法能有效預報較大降雨，同時由於 GSMaP 的高解析時空分布，更有利於台灣的颱風降雨預報。

摘要(英)

The Tropical Rainfall Potential (TRaP) technique presented by Kidder et al. in 2005, shifting rainfall distribution from satellite retrieval, and forecasting rainfall for tropical cyclone. Chen(2010) improved TRaP rainfall forecast practicality by adding orographic effect with historical rainfall distribution(I-TRaP). Since I-TRaP forecast uses rainfall distribution from satellite, how to get better rainfall distribution is an important issue.
There is only single satellite rainfall product in past study, limited by temporal resolution. For many study, The performance of multi-satellite rainfall products with high spatial-temporal resolution(0.1°-0.25°, 0.5-3h) are getting better recently but less discussed on heavy rainfall especially for typhoon. This study compares few common multi-satellite products (GSMaP, IMERG, PERSIANN) with typhoon heavy rainfall in the North-West Pacific, GSMaP is better. There are different performance between convective and stratiform rainfall. Indeed, the PMW retrieval fail to classification in rainfall type determination during microwave rainfall retrieving, but not cause rainfall error. In addition, compare liquid water content and rainfall error, the PMW retrieval still cannot estimate liquid water accurately in moderate to heavy rainfall.
Apply GSMaP to I-TRaP and calculate typhoon rainfall forecast over Taiwan. In order to highlight satellite rainfall distribution, modify earlier method only revising total rainfall and using historical rainfall distribution, calculate rainfall regression by individual point. This method will predict more heavy rainfall but more false alarm. Compare earlier I-TRaP using SSMIS, GSMaP with high spatial-temporal resolution is more useful for I-TRaP forecast, and more prediction of heavy rainfall.

關鍵字(中)

★ 熱帶氣旋降雨潛勢
★ 全球衛星降雨產品

關鍵字(英)

★ I-TRaP
★ GSMaP

論文目次

摘要 I
Abstract II
致謝 III
目錄 IV
表目錄 VII
圖目錄 VIII
縮寫表 XII
衛星產品比較表 XIII
第一章緒論 1
1.1 前言 1
1.2 文獻回顧 1
1.3 研究目的 5
第二章資料蒐集與處理 6
2.1 SSM/I與SSMIS微波衛星資料 6
2.2 GSMaP全球衛星降雨資料 7
2.3 GPM全球降雨觀測任務衛星 10
2.3.1 雙波段降水雷達(Dual-frequency Precipitation Radar, DPR) 10
2.3.2 微波輻射儀(GPM Microwave Imager, GMI) 11
2.3.3 多衛星反演降雨整合產品(Integrated Multisatellite Retrievals for GPM, IMERG) 12
2.4 PERSIANN-CCS衛星(紅外線)影像估計降雨產品 13
2.5 JTWC颱風最佳路徑資料 13
2.6 中央氣象局觀測站雨量資料 14
第三章研究方法 15
3.1 衛星資料估算颱風降雨及I-TRaP預報之校驗方法 15
3.2 I-TRaP理論基礎 17
3.2.1 TRaP(Tropical Rainfall Potential, 熱帶降雨潛勢) 17
3.2.2 I-TRaP 17
3.2.2.1 網格資料庫 18
3.2.2.2 降雨估計修正方法 19
第四章衛星反演降雨結果與討論 21
4.1 單元衛星差異比較 21
4.2 颱風之衛星降雨結果 22
4.3 衛星反演降雨誤差討論 24
4.3.1 降雨分類 24
4.3.2 回波頂高度(echo top height, ETH) 25
4.3.3 Precipitation Water Integrated(PWI) - Liquid 26
第五章衛星反演降雨之應用比較 28
5.1 整體比較 28
5.2 個案探討 29
5.2.1 2016年梅姬颱風 29
5.2.2 2016年莫蘭蒂颱風 30
第六章結論與未來展望 32
6.1 結論 32
6.2 GSMaP用於預報之討論 33
6.3 未來展望 34
參考文獻 36
參考網站 47
附表 48
附圖 56

參考文獻

李天浩，2009：應用克利金法建立高解析度網格點氣象數據之研究。交通部中央氣象局研究計畫成果報告（MOTC-CWB-98-2M-03），134頁。
李清勝與蔡德攸，1995，利用CAA都卜勒雷達資料分析四個侵台颱風伴隨雨帶之特徵。大氣科學，23，209-235。
邱清安、林博雄、謝旻耕，2005︰台灣地區氣象測站之詮釋資料與日氣溫、日降水之資料檢定。氣象學報，第45卷第3期，33-45。
張怡鈴，2013：應用GSMaP 全球降雨資料及颱風強度變化改善颱風降雨潛勢預報之研究。國立中央大學大氣物理研究所碩士論文，中壢市。
陳冠儒，2010：考量地形與環境風場輻合效應改進TRaP 估算侵台颱風降雨預報之研究。國立中央大學大氣物理研究所碩士論文，中壢市。
葉天降、吳石吉與謝信良，1999: 簡單統計方法於台灣地區颱風降水預測之研究(一)預測方法與台北颱風降雨之預測校驗。大氣科學，27，395-412。
葉天降、謝信良與吳石吉，2000: 簡單統計方法於台灣地區颱風降水預測之研究(二)預測結果隨區域之分布。大氣科學，28，263-279。
蔡明達，陳萬金，方錫棋，劉振榮，李慶忠，2006：TRMM/PR降雨估算之驗證及其應用－台灣陸地降雨之研究。大氣科學， 34，1-24。
賴慧文，2014：Applying Ensemble Forecast Technique to Improve Typhoon Rainfall Potential with Satellite Data over Taiwan。國立中央大學大氣物理研究所碩士論文，中壢市。
Adler, R. F., G. Gu, and G. J. Huffman, 2012: Estimating climatological bias errors for the Global Precipitation Climatology Project (GPCP). J. Appl. Meteor. Climatol., 51, 84–99.
Aonashi, K. and G. Liu, 2000: Passive Microwave Precipitation Retrievals Using TMI during the Baiu Period of 1998. Part I: Algorithm Description and Validation. J. Appl. Meteor., 39, 2024-2037.
Aonashi, K., and Coauthors, 2009: GSMaP passive microwave precipitation retrieval algorithm: Algorithm description and validation. J. Meteor. Soc. Japan, 87A, 119-136.
Awaka, J., T. Iguchi, and K. Okamoto, 2009: TRMM PR standard algorithm 2A23 and its performance on bright band detection. J. Meteor. Soc. Japan, 87A, 31-52.
Berg, W., T. L’Ecuyer, and C. Kummerow, 2006: Rainfall climate regimes: The relationship of regional TRMM rainfall biases to the environment. J. Appl. Meteor. Climatol., 45, 434–454.
Brown P. J., C.D. Kummerow, and David L, Randel, 2016, Hurricane GPROF: An Optimized Ocean Microwave Rainfall Retrieval for Tropical Cyclones. J. Atmos. Oceanic Technol., 33, 1539-1556.
DeMaria, M., M. Mainelli, L.K. Shay, J.A. Knaff, and J. Kaplan, 2005: Further improvements to the updated Statistical Hurricane Intensity Prediction Scheme (SHIPS). Wea. Forecasting, 20, 531–543.
Ebert, E. E., J. E. Janowiak, and C. Kidd, 2007: Comparison of near-real-time precipitation estimates from satellite observations and numerical Models. Bull. Amer. Meteor. Soc., 88, 47-64.
Ebert, E.E., M. Turk, S.J. Kusselson, J. Yang, M. Seybold, P.R. Keehn, R.J. Uligowski, 2011: Ensemble tropical rainfall potential (eTRaP) forecasts. Wea. Forecasting, 26, 213-224.
Elsaesser, G. S., and C. D. Kummerow, 2013: A multisensor observational depiction of the transition from light to heavy rainfall on subdaily time scales. J. Atmos. Sci., 70, 2309–2324.
Elsaesser, G. S., T. S. L’Ecuyer, Y. N. Takayabu, and S. Shige, 2010: Observed self-similarity of precipitation regimes over the tropical oceans. J. Climate, 23, 2686–2698.
Elsaesser, G. S., and C. D. Kummerow, 2015: The sensitivity of rainfall estimation to error assumptions in a Bayesian passive microwave retrieval algorithm. J. Appl. Meteor. Climatol., 54, 408–422.
Ferraro, R. R., 1997: SSM/I derived global rainfall estimates for climatological applications. J. Geophys. Res., 102, 16715-16735
Gottschalck, J., J. Meng, M. Rodell, and P. Houser, 2005: Analysis of multiple precipitation products and preliminary assessment of their impact on Global Land Data Assimilation System land surface states. J. Hydrometeor., 6, 573–598.
Grody, N. C.,1991: Classification of snow cover and precipitation using the Special Sensor Microwave Imager. J. Geophys. Res., 96, 7423-7435.
Hence, D. A., and R. A. Houze, Jr., 2011: Vertical structure of hurricane eyewalls as seen by the TRMM Precipitation Radar. J. Atmos. Sci., 68, 1637-1652.
Hence, D. A., and R. A. Houze, Jr., 2012a: Vertical structure of tropical cyclones with concentric eyewalls as seen by the TRMM Precipitation Radar. J. Atmos. Sci., 69, 1021-1036.
Hence, D. A., and R. A. Houze, Jr., 2012b: Vertical structure of tropical cyclone rainbands as seen by the TRMM Precipitation Radar. J. Atmos. Sci., 69, 2644-2661.
Hollinger, J., R. Lo, G. Poe, R. Savage, and J. Pierce, 1987: Special Sensor Microwave/Imager user’s guide. Naval Research Laboratory Washington, D.C., 120 pp.
Hong, Y., K. Hsu, S. Sorooshian, and X. Gao, 2004: Precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system. J. Appl. Meteor., 43, 1834-1852.
Hou, A. Y., and Coauthors, 2014: The Global Precipitation Measurement mission. Bull. Amer. Meteor. Soc., 95, 701–722.
Houze, R. A., Jr., 2010: Clouds in tropical cyclones. Mon. Wea. Rev., 138, 293-344.
Houze, R. A., S. Brodzik, C. Schumacher, S. E. Yuter, and C. R. Williams, 2004: Uncertainties in oceanic radar rain maps at Kwajalein and implications for satellite validation. J. Appl. Meteor., 43, 1114–1132.
Hsu, K. L., X. Gao, S. Sorooshian, and H. V. Gupta, 1997: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks. J. Appl. Meteor., 36, 1176-1190.
Huffman, G.J., D.T. Bolvin, D. Braithwaite, K. Hsu, R. Joyce, C. Kidd, E.J. Nelkin, S. Sorooshian, J. Tan, P. Xie, 2017a: GPM Integrated Multi-Satellite Retrievals for GPM (IMERG) Algorithm Theoretical Basis Document (ATBD) Version 5.1. PPS, NASA/GSFC. https://pmm.nasa.gov/sites/default/files/document_files/IMERG_ATBD_V5.1_0.pdf
Huffman, G.J., D.T. Bolvin, E.J. Nelkin, E.F. Stocker, 2017b: V04 IMERG Final Run Release Notes. PPS, NASA/GSFC. https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/IMERG_FinalRun_V04_release_notes.pdf
Huffman, G.J., R.F. Adler, D.T. Bolvin, G. Gu, E.J. Nelkin, K.P. Bowman, Y. Hong, E.F. Stocker, D.B. Wolff, 2007: The TRMM Multi-satellite Precipitation Analysis: QuasiGlobal, Multi-Year, Combined-Sensor Precipitation Estimates at Fine Scale. J. Hydrometeor., 8, 38-55.
Iguchi, T., S. Seto, R. Meneghini, N. Yoshida, J. Awaka, T. Kubota, 2010: GPM/DPR Level-2 Algorithm Theoretical Basis Document. PPS, NASA/GSFC. https://pmm.nasa.gov/sites/default/files/document_files/ATBD_GPM_DPR_n3_dec15.pdf.
Iguchi, T., T. Kozu, R. Meneghini, J. Awaka, and K. I. Okamoto, 2000: Rain-pro?ling algorithm for the TRMM precipitation radar. J. Appl. Meteor., 39, 2038–2052.
Janowiak J. E., R. J. Joyce, and Y. Yarosh, 2001: A Real-Time Global Half-hourly Pixel-Resolution Infrared Dataset and Its Applications. Bull. Amer. Meteor. Soc., 82, 205-217.
Jiang, H., 2012: The relationship between tropical cyclone intensity change and the strength of inner-core convection. Mon. Wea. Rev., 140, 1164–1176.
Jiang, H., C. Liu, and E. J. Zipser, 2011: A TRMM-based tropical cyclone cloud and precipitation feature database. J. Appl. Meteor. Climatol., 50, 1255–1274.
Joyce, R. J., J. E. Janowiak, P. A. Arkin, and P. Xie, 2004: CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J. Hydrometeor., 5, 487–503
Kachi M., T. Kubota, T. Ushio, S. Shige, S. Kida, K. Aonashi, and K. Okamoto, 2011: Development and utilization of “JAXA Global Rainfall Watch” system. IEEJ Trans. Fund. Mater., 131, 729-737.
Kidder, S. Q., S. J. Kusselson, J. A. Knaff, R. R. Ferraro, R. J. Kuligowski, and M. Turk, 2005: The tropical rainfall potential (TRaP) technique. Part I: description and examples. Wea. Forecasting, 20, 456-464.
Kim, M.-J., J. A. Weinman, and R. A. Houze Jr., 2004: Validation of maritime rainfall retrievals from the TRMM-microwave radiometer. J. Appl. Meteor., 43, 847–859.
Kim, J.-H., D.-B. Shin, and C. Kummerow, 2013: Impacts of a priori databases using six WRF microphysics schemes on passive microwave rainfall retrievals. J. Atmos. Oceanic Technol., 30, 2367–2381.
Knaff, J. A., C. R. Sampson, and M. DeMaria, 2005: An operational Statistical Typhoon Intensity Prediction Scheme for the western North Pacific. Wea. Forecasting, 20, 688–699.
Kozu, T.; Kawanishi, T.; Kuroiwa, H.; Kojima, M.; Oikawa, K.; Kumagai, H.; Okamoto, K.; Okumura, M.; Nakatsuka, H. and Nishikawa, K., 2001: Development of precipitation radar onboard the Tropical Rainfall Measuring Mission satellite, IEEE Trans. Geosci. Remote Sens., 39, 102–116.
Kubota, T., S. Shige, H. Hashizume, K. Aonashi, N. Takahashi, S. Seto, M. Hirose, Y. N. Takayabu, K. Nakagawa, K. Iwanami, T. Ushio, M. Kachi, and K. Okamoto, 2007: Global Precipitation Map using Satelliteborne Microwave Radiometers by the GSMaP Project : Production and Validation. IEEE Trans. Geosci. Remote Sens., 45, 2259-2275.
Kubota, T., T. Ushio, S. Shige, S. Kida, M. Kachi, and K. Okamoto, 2009: Verification of high resolution satellite-based rainfall estimates around Japan using gauge-calibrated ground radar dataset. J. Meteor. Soc. Japan, 87A, 203-222.
Kummerow, C. D., S. Ringerud, J. Crook, D. Randel, and W. Berg, 2011: An observationally generated a priori database for microwave rainfall retrievals. J. Atmos. Oceanic Technol., 28, 113–130.
Kummerow, C. D., D. L. Randel, M. Kulie, N.-Y. Wang, R. Ferraro, S. J. Munchak, and V. Petkovic, 2015: The evolution of the Goddard profiling algorithm to a fully parametric scheme. J. Atmos. Oceanic Technol., 32, 2265–2280.
Liao L, Meneghini R., 2009, Validation of TRMM precipitation radar through comparison of its multiyear measurements with ground based radar. J Appl Meteorol Climatol, 48, 804–817.
Liu, C., E. J. Zipser, D. J. Cecil, S. W. Nesbitt, and S. Sherwood, 2008: A cloud and precipitation feature database from nine years of TRMM observations. J. Appl. Meteor. Climatol., 47, 2712–2728.
Liu, J., C. D. Kummerow, and G. S. Elsaesser, 2017: Identifying and analysing uncertainty structures in the TRMM Microwave Imager precipitation product. Int. J. Remote Sens., 38, 23–42.
Lonfat, M., F. D. Marks, and S. S. Chen, 2004: Precipitation distribution in tropical cyclones using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager: A global perspective. Mon. Wea. Rev., 132, 1645–1660.
Maggioni, V., M. R. P. Sapiano, and R. F. Adler, 2016: Estimating uncertainties in high-resolution satellite precipitation products: Systematic or random error? J. Hydrometeor., 17, 1119– 1129.
McCollum, J. R., and R. R. Ferraro, 2005: Microwave rainfall estimation over coasts. J. Atmos. Oceanic Technol., 22, 497–512.
Mega, T., and S. Shige, 2016: Improvements of rain/no-rain classification methods for microwave radiometer over coasts by dynamic surface-type classification. J. Atmos. Oceanic Technol., 33, 1257–1270.
Okamoto, K. and S. Shige, 2008: TRMM precipitation radar and its observation results, IEICE Trans. Commun., J91-B, 723–733, (in Japanese).
Okamoto, K., 2003: A short history of the TRMM precipitation radar, Meteorol. Monogr., 29, 187–195.
Petkovi?, V., and C. D. Kummerow, 2017: Understanding the sources of satellite passive microwave rainfall retrieval systematic errors over land. J. Appl. Meteor. Climatol., 56, 597-614.
Ren, D., M. Lynch, L. Leslie, and J. Lemarshall, 2014: Sensitivity of tropical cyclone tracks and intensity to ocean surface temperature: Four cases in four different basins. Tellus, 66A, 24212.
Schumacher, C., and R. A. Houze Jr., 2000: Comparison of radar data from the TRMM satellite and Kwajalein oceanic validation site. J. Appl. Meteor., 39, 151-2164.
Seo, E.-K., and M. I. Biggerstaff, 2006: Impact of cloud model microphysics on passive microwave retrievals of cloud properties. Part II: Uncertainty in rain, hydrometeor structure and latent heating retrievals. J. Appl. Meteor. Climatol, 45, 955–972.
Shige S., S. Kida, H. Ashiwake, T. Kubota, and K. Aonashi, 2013: Improvement of TMI rain retrievals in mountainous areas. J. Appl. Meteor. Climatol., 52, 242-254.
Shige, S., T. Yamamoto, T. Tsukiyama, S. Kida, H. Ashiwake, T. Kubota, S. Seto, K. Aonashi and K. Okamoto, 2009: The GSMaP precipitation retrieval algorithm for microwave sounders. Part I: Over-ocean algorithm. IEEE Trans. Geosci. Remote Sens, 47, 3084-3097.
Sorooshian, S., K. Hsu, X. Gao, H.V. Gupta, B. Imam, and D. Braithwaite, 2000: Evaluation of PERSIANN system satellite-based estimates of tropical rainfall. Bull. Amer. Meteor. Soc., 81, 2035-2046.
Takahashi N., and J. Awaka, 2005: Introduction of a melting layer model to a rain retrieval algorithm for microwave radiometers. Geoscience and Remote Sensing Symposium, IGARSS ′05. Proceedings, 5, 3404–3409.
Takayabu Y. N., 2008: Observing Rainfall Regimes Using TRMM PR and LIS Data. GEWEX Newsletter, 18, 9-10.
Taniguchi A., S. Shige, M. K. Yamamoto, T. Mega, S. Kida, T. Kubota, M. Kachi, T. Ushio, and K. Aonashi, 2013: Improvement of high-resolution satellite rainfall product for Typhoon Morakot (2009) over Taiwan. J. Hydrometeor., 14, 1859-1871.
Tian, Y., C. D. Peters-Lidard, J. B. Eylander, R. J. Joyce, G. J. Huffman, R. F. Adler, K. Hsu, F. J. Turk, M. Garcia, and J. Zeng, 2009: Component analysis of errors in satellite-based precipitation estimates. J. Geophys. Res., 114, D24101.
Turk, F. J., E. E. Ebert, H-J. Oh, and B-J. Sohn, 2002: Validation and applications of a realtime global precipitation analysis. Proc. IGARSS′02, 2, Toronto, ON, Canada, IEEE, 705–707.
Ushio, T., T. Tashima, T. Kubota, and M. Kachi, 2013: Gauge Adjusted Global Satellite Mapping of Precipitation (GSMaP_Gauge). Proc. 29th ISTS, 2013-n-48.
Ushio, T., and Coauthors, 2009: A Kalman filter approach to the Global Satellite Mapping of Precipitation (GSMaP) from combined passive microwave and infrared radiometric data. J. Meteor. Soc. Japan, 87A, 137–151.
Wang, J., and D. B. Wolff, 2012: Evaluation of TRMM rain estimates using ground measurements over central Florida. J. Appl. Meteor. Climatol., 51, 926–940.
Yamamoto, M. K., F. A. Furuzawa, A. Higuchi, and K. Nakamura, 2008: Comparison of diurnal variations in precipitation systems observed by TRMM PR, TMI, and VIRS. J. Climate, 21, 4011–4028.

指導教授

劉振榮(Gin-Rong Liu)

審核日期

2018-7-23

推文