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姓名	林其彥(Chi-Yen Lin)  查詢紙本館藏	畢業系所	太空科學研究所
論文名稱	應用地面GPS觀測以及掩星觀測進行電離層資料同化分析 (Ionospheric Data Assimilation Analysis Using Ground-based GPS and Radio Occultation Observations)
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摘要(中)	電離層資料同化模式將離層觀測資料代入背景模式重建電離層三維分佈電子密度的方法。其以高斯馬爾可夫卡爾曼濾波器（Gauss-Markov Kalman filter）同化背景模型國際參考電離層模式（International Reference Ionosphere），同化地面GPS觀測以及福爾摩沙三號（FORMOSAT-3/COSMIC）無線電掩星觀測兩種不同類型的全電子含量觀測資料。電離層背景模式誤差和觀測誤差之共變異數矩陣在電離層資料同化的過程中佔有舉足輕重的作用。隨空間位置變化的相關性矩陣則採用來自國際參考電離層模式輸出之電子濃度分佈，並經由經驗正交函數計算建模。觀測系統模擬實驗顯示透過隨空間位置變化之相關性矩陣，建制電離層背景模式誤差共變異數矩陣，應用於同化全電子含量觀測資料，可以獲得較高品質的電離層資料同化電子濃度分佈結果。代入地面GPS觀測以及福衛三號無線電掩星觀測之電離層全電子含量資料同化結果，並與Millstone Hill異調散射雷達之電子濃度垂直結構相互比較顯示同化福衛三號掩星觀測全電子含量資料可改進電離層資料同化電子濃度垂直結構。另外，藉由觀測系統模擬實驗，探討阿貝爾反演以及電離層資料同化電子濃度垂直剖面結構之精確度，並比較兩種方法所獲得之電離層電子濃度結構。電離層資料同化模式加入卡爾曼濾波器預測步驟，配合著卡爾曼濾波器觀測更新步驟，以地面GPS和福衛三號無線電掩星資料，進行全球三維電離層重建。電離層資料同化模擬結果顯示，於數據同化過程中，卡爾曼濾波器預測和測量更新步驟，可以有效增加三維全球電離層資料同化模式的準確性。此外，本研究也進行以福爾摩沙七號(FORMOSAT-7/COSMIC-2) 無線電掩星觀測以及地面GPS觀測，進行三維全球電離層資料同化模式的觀測系統模擬實驗。結果說明同化福衛七號無線電掩星觀測，可以增加電離層資料同化模式的精準度明顯超過原使用福衛三號無線電掩星觀測結果。總結，電離層資料同化模式採用隨空間位置變化之背景模型誤差共變異數矩陣，卡爾曼濾波預測步驟，以及卡爾曼濾波觀測更新步驟，可以同化地面GPS觀測以及無線電掩星觀測，重建三維電離層電子密度分佈。
摘要(英)	Ionospheric data assimilation is a powerful approach to reconstruct the three-dimensional distribution of ionospheric electron density from various types of observations. The ionospheric data assimilation model based on the Gauss-Markov Kalman filter with the International Reference Ionosphere (IRI) as the background model is used to assimilate two different types of total electron content (TEC) observations from ground-based GPS and space-based FORMOSAT-3/COSMIC (F3/C) radio occultation. Covariance models for the background model error and observational error play important roles in data assimilation. Location-dependent correlations are modeled using empirical orthogonal functions computed from an ensemble of the IRI outputs, while location-independent correlations are modeled using a Gaussian function. Observing System Simulation Experiments (OSSEs) suggest that assimilation of TEC data facilitated by the location-dependent background model error covariance yields considerably higher quality assimilation analyses. Results from assimilation of real ground-based GPS and F3/C radio occultation (RO) observations over the continental United States are presented as TEC and electron density profiles. Validation with the Millstone Hill incoherent scatter radar data and comparison with the Abel inversion results are also presented. The ionospheric electron density structures, including the Weddell Sea Anomaly, are reconstructed from electron density profiles retrieved by the Abel inversion techniques and obtained using the Kalman filter data assimilation measurement update are compared to each other in OSSEs and real data analysis. The Kalman filter forecast step is incorporated into the data assimilation procedure made only of the Kalman filter measurement update step in order to reconstruct the ionosphere globally by assimilating both ground-based GPS and RO observations. The OSSE results show that the data assimilation procedure, consisting of both the forecast and measurement update steps of the Kalman filter, can increase the accuracy of the data assimilation model over the procedure consisting of the Kalman filter measurement update step alone. Finally, the OSSEs of assimilating FORMOSAT-7/COSMIC-2 (F7/C2) RO and ground-based GPS data in the data assimilation model are implemented, the OSSEs results demonstrate that the F7/C2 RO data can increase model accuracy more than assimilating F3/C RO data. The new ionospheric data assimilation model that employs the location-dependent background model error covariance, Kalman filter forecast step, and Kalman filter measurement update step could reconstruct the three-dimensional ionospheric electron density distribution satisfactorily from both ground- and space-based GPS observations.
關鍵字(中)	★ 電離層 ★ 資料同化分析 ★ 地面全球定位系統衛星觀測 ★ 福衛三號掩星觀測 ★ 福衛七號掩星觀測	關鍵字(英)	★ Ionosphere ★ Data Assimilation Analysis ★ Ground-based GPS Observation ★ FORMOSAT-3/COSMIC Radio Occultation Observation ★ FORMOSAT-7/COSMIC-2 Radio Occultation Observation
論文目次	摘要 i Abstract iii 誌謝 vi Acknowledgement viii Table of Contents ix List of Figures xi Chapter 1. Introduction 1 1.1 Ionosphere 1 1.2 Ionospheric Model 7 1.3 Ionospheric Data Assimilation Model and Kalman Filter 10 1.4 Ionospheric Observation Data 15 1.5 Motivation and Objective 21 Chapter 2. Data Assimilation Approach Part 1. 22 2.1 Kalman Filter Measurement Update Step 23 2.2 Error Covariance 24 Chapter 3. Assimilation Analysis for F3/C 35 3.1 Assimilation Experiments with Synthetic Data 35 3.2 Assimilation Results: TEC Maps 40 3.3 Validation with ISR Data and Comparison with F3/C profile 43 Chapter 4. Comparison of Abel Inversion Data Assimilation Method 47 4.1 Background Model Bias Correction 50 4.2 Observing Simulation System Experiments 55 4.3 Real Satellite Data Analysis for the Abel Inversion and Data Assimilation 74 Chapter 5. Data Assimilation Approach Part 2. 80 5.1 Kalman Filter Forecast Step 80 5.2 Ionosphere Relaxation Time Scale 81 5.3 Kalman Filter Measurement Covariance Update 86 5.4 Observing System Simulation and Assimilation Experiments for FORMOSAT3/COSMIC Radio Occultation Satellite Data 88 Chapter 6. OSSEs for the FORMOSAT-7/COSMIC-2 Mission 105 Chapter 7. Discussion 136 Chapter 8. Conclusions 143 References 147
參考文獻	Araujo-Pradere, E. A., T. J. Fuller-Rowell, P. S. J. Spencer, and C. F. Minter (2007), Differential validation of the USTEC model, Radio Sci., 42, RS3016, doi:10.1029/2006RS003459. Austen, J. R., S. J. Franke, and C. H. Liu (1988), Ionospheric Imaging Using Computerized Tomography, Radio Sci. 23, 299-307. Bilitza, D., International Reference Ionosphere—Status 1995/96 (1997), Adv. Space Res., 20, 1751–1754, doi:10.1016/S0273-1177(97)00584-X. Bilitza, D., International Reference Ionosphere 2000 (2001), Radio Sci., 36(2), 261–275, doi:10.1029/2000RS002432. Bilitza, D. and B. Reinisch, International Reference Ionosphere 2007: Improvements and new parameters (2008), J. Adv. Space Res., 42(4), 599-609, doi:10.1016/j.asr.2007.07.048. Bilitza, D., L.-A. McKinnell, B. Reinisch, and T. Fuller-Rowell, The International Reference Ionosphere (IRI) today and in the future (2011), J. Geodesy, 8585, 909–920, doi:10.1007/s00190-010-0427-x. Bellchambers, W., and W. Piggott (1958), Ionospheric measurements made at Halley Bay, Nature, 182, 1596–1597, doi:10.1038/1821596a0. Bevis, M., S. Businger, T. Herring, C. Rocken, R. Anthes, and R. Ware (1992), GPS meteorology: Remote sensing of atmospheric water vapor using the Global Positioning System, J. Geophys. Res., 97, 15787–15801, doi:10.1029/92JD01517. Bust, G. S., T. W. Garner, , and T. L. Gaussiran II (2004), Ionospheric Data Assimilation Three-Dimensional (IDA3D): A global, multisensor, electron density specification algorithm, J. Geophys. Res., 109, A11312, doi:10.1029/2003JA010234. Bust, G. S., G. Crowley, T. W. Garner, T. L. Gaussiran II, R. W. Meggs, C. N. Mitchell, P. S. J. Spencer, P. Yin, and B. Zapfe (2007), Four-dimensional GPS imaging of space weather storms, Space Weather, 5, S02003, doi:10.1029/2006SW000237. Chen, C. H., J. D. Huba, A. Saito, C. H. Lin, and J. Y. Liu (2011), Theoretical study of the ionospheric Weddell Sea Anomaly using SAMI2, J. Geophys. Res., 116, A04305, doi:10.1029/2010JA015573. Chen, C. H., A. Saito, C. H. Liu, and J. Y. Liu (2012), Long-term variations of the nighttime electron density enhancement during the ionospheric midlatitude summer, J. Geophys. Res., 117, A07313, doi:10.1029/2011JA017138. Chen, C. H., C. H. Lin, L. C. Chang, J. D. Huba, J. T. Lin, A. Saito, and J. Y. Liu (2013), Thermospheric tidal effects on the ionospheric midlatitude summer nighttime anomaly using SAMI3 and TIEGCM, J. Geophys. Res. Space Phys., 118, 3836–3845, doi:10.1002/ jgra.50340. Cheng, C. Z. F., Y. H. Kuo, R. A. Anthes, and L. Wu (2006), Satellite constellation monitors global and space weather, Eos Trans. AGU, 87(17), 166, doi:10.1029/2006EO170003. Davies, K. (1990), Ionospheric Radio, Peregrinus, London. Foster, J. C., A. J. Coster, P. J. Erickson, J. Goldstein, and F. J. Rich (2002), Ionospheric signatures of plasmaspheric tails, Geophys. Res. Lett., 29(13), 1623, doi:10.1029/2002GL015067. Fuller-Rowell, T., E. Araujo-Pradere, C. Minter, M. Codrescu, P. Spencer, D. Robertson, and A. R. Jacobson (2006), US‐TEC: A new data assimilation product from the Space Environment Center characterizing the ionospheric total electron content using real‐time GPS data, Radio Sci., 41, RS6003, doi:10.1029/2005RS003393. Gaspari, G., and Cohn (1999), Construction of correlation functions in two and three dimensions, S. E. Quart. J. Roy. Meteor. Soc., 125(554B), 723–757, doi:10.1002/qj.49712555417, 1999. Hajj, George A., et al. (1994), "Imaging the ionosphere with the Global Positioning System." International Journal of Imaging Systems and Technology 5.2: 174-187. Hajj, G.A., and L. J. Romans (1998), Ionospheric electron density profiles obtained with the global positioning system: results from the GPS/MET experiment, Radio Sci., 33(1), 175–190, doi:10.1029/97RS03183. Horvath, I. (2006), A total electron content space weather study of the nighttime Weddell Sea Anomaly of 1996/1997 southern summer with TOPEX/Poseidon radar altimetry, J. Geophys. Res., 111, A12317, doi:10.1029/2006JA011679. Horvath, I., and E. A. Essex (2003), The Weddell Sea Anomaly observed with the TOPEX satellite data, J. Atmos. Sol. Terr. Phys., 65(6), 693–706, doi:10.1016/S1364-6826(03)00083-X. Huba, J. D., G. Joyce, and J. A. Fedder (2000), Sami2 is Another Model of the Ionosphere (SAMI2), A new low-latitude ionosphere model, J. Geophys. Res., 105, 23035–23053, doi:10.1029/2000JA000035. Huba, J. D., G. Joyce, and J. Krall (2008), Three-dimensional equatorial spread F modeling, Geophys. Res. Lett., 35, L10102, doi:10.1029/2008GL033509. Hunsucker, R. D. (1991), Radio Techniques for Probing the Terrestrial Ionosphere, 293pp., Springer-Verlag, Berlin. Jee, G., A. G. Burns, Y.-H. Kim, and W. Wang (2009), Seasonal and solar activity variations of the Weddell Sea Anomaly observed in the TOPEX total electron content measurements, J. Geophys. Res., 114, A04307, doi:10.1029/2008JA013801. Kakinami, Y., C. H. Chen, J. Y. Liu, K. I. Oyama, W. H. Yang, and S. Abe (2009), Empirical models of Total Electron Content over Taiwan during geomagnetic quiet condition. Ann. Geophys., 27, 3321–3333, doi:10.5194/angeo-27-3321-2009. Kalman, R. E. (1960), A new approach to linear filtering and prediction problems, J. Basic Eng., 82(1), Series D, 34–45, doi:10.1115/1.3662552. Kalman, R. E., and R. Bucy (1961), New results in linear filtering and prediction theory, J. Basic Eng., 83(1), 95–108, doi:10.1115/1.3658902. Kelley, M. C. (1989), The Earth’s Ionosphere: Plasma Physics and Electrodynamics, 1st ed., Academic Press, San Diego, Calif. Kliore, A. J., D. L. Cain, G. S. Levy, V. R. Eshleman, G. Fjeldbo, and E. D. Drake (1965), Occultation experiment: Results of the first direct measurement of Mars’ atmosphere and ionosphere, Science, 149(3689), 1243–1248, doi:10.1126/science.149.3689.1243. Komjathy, A., B. Wilson, X. Pi, V. Akopian, M. Dumett, B. Iijima, O, Verkhoglyadova, and A. J. Mannucci (2010), JPL/USC GAIM: On the impact of using COSMIC and ground-based GPS measurements to estimate ionospheric parameters, J. Geophys. Res., 115, A02307, doi:10.1029/2009JA014420. Kursinski, E. R., G. A. Hajj, J. T. Schofield, R. Linfield, and K. R. Hardy (1997), Observing Earth′s atmosphere with radio occultation measurements using the Global Positioning System, J. Geophys. Res., 102(D19), 23,429–23,465, doi:10.1029/97JD01569. Lee, I. T., T. Matsuo, A. D. Richmond, J. Y. Liu, W. Wang, C. H. Lin, J. L. Anderson, and M. Q. Chen (2012), Assimilation of FORMOSAT-3/COSMIC electron density profiles into a coupled thermosphere/ionosphere model using ensemble Kalman filtering, J. Geophys. Res., 117(A10), doi:10.1029/2012JA017700. Lee, I. T., T. Matsuo, A. D. Richmond, J. Y. Liu, W. Wang, C. H. Lin, J. L. Anderson, and M. Q. Chen (2012), Assimilation of FORMOSAT-3/COSMIC electron density profiles into a coupled thermosphere/ionosphere model using ensemble Kalman filtering, J. Geophys. Res., 117(A10), doi:10.1029/2012JA017700. Lin, C. H., J. Y. Liu, C. Z. Cheng, C. H. Chen, C. H. Liu, W. Wang, A. G. Burns, and J. Lei (2009), Three-dimensional ionospheric electron density structure of the Weddell Sea Anomaly, J. Geophys. Res., 114, A02312, doi:10.1029/2008JA013455. Lin, C. Y., T. Matsuo, J. Y. Liu, C. H. Lin, H. F. Tsai, and E. A. Araujo-Pradere (2015), Ionospheric assimilation of radio occultation and ground-based GPS data using non-stationary background model error covariance, Atmos. Meas. Tech., 8, 171–182, doi:10.5194/amt-8-171-2015. Liu, H., S. V. Thampi, and M. Yamamoto (2010), Phase reversal of the diurnal cycle in the midlatitude ionosphere, J. Geophys. Res., 115, A01305, doi:10.1029/2009JA014689. Liu, J. Y., H. F. Tsai, and T. K. Jung (1996), Total electron content obtained by using the global positioning system, Terr. Atmos. Oceanic Sci., 7, 107–117. Liu, J. Y., C. Y. Lin, C. H. Lin, H. F. Tsai, S. C. Solomon, Y. Y. Sun, I. T. Lee, W. S. Schreiner, Y. H. Kuo (2010), Artificial plasma cave in the low-latitude ionosphere results from the radio occultation inversion of the FORMOSAT-3/COSMIC, J. Geophys. Res., 115, A07319, doi:10.1029/2009JA015079. Mannucci, A. J., B. D. Wilson, D. N. Yuan, C. H. Ho, U. J. Lindqwister, , and T. F. Runge, (1998), A global mapping technique for GPS-derived ionospheric total electron content measurements, Radio Sci., 33(3), 565–582, doi:10.1029/97RS02707. Nicolls, M. J., F. S. Rodrigues, G. S. Bust, and J. L. Chau (2009), Estimating E region density profiles from radio occultation measurements assisted by IDA4D, J. Geophys. Res., 114, A10316, doi:10.1029/ 2009JA014399. Pi, X., A. J. Mannucci, B. A. Iijima, B. D. Wilson, A. Komjathy, T. F. Runge, and V. Akopian (2009), Assimilative modeling of ionospheric disturbances with FORMOSAT‐3/COSMIC and ground‐based GPS measurements, Terr. Atmos. Ocean. Sci., 20(1), 273–285, doi:10.3319/TAO.2008.01.04.01(F3C). Pryse, S. E. (2003), Radio Tomography: A New Experimental Technique, Surv. Geophys., 24 , 1-38. Raymund, T. D., S. J. Franke and K. C. Yeh. (1994), Ionospheric Tomography: Its Limitations and Reconstruction Methods, J. Atmos. Phys. Vol. 56, pp. 637-657. Rishbeth, Henry, and Owen K. Garriott (1969), Introduction to ionospheric physics. IEEE Transactions on Image Processing 1. Sardón, E., A. Rius, and N. Zarraoa (1994), Estimation of the transmitter and receiver differential biased and the ionospheric total electron content from Global Positioning System Observations. Radio Sci., 29, 577–586, doi:10.1029/94RS00449. Schaer, S. (1999), Mapping and predicting the Earth’s ionosphere using the Global Positioning System, Ph.D. dissertation, Astron. Inst., Univ. of Bern, Bern. Scherliess, L., R. W. Schunk, J. J. Sojka, D. C. Thompson, and L. Zhu (2006), The USU GAIM Gauss-Markov Kalman filter model of the ionosphere: Model description and validation, J. Geophys. Res., 111, A11315, doi:10.1029/2006JA011712. Schreiner, W., C. Rocken, S. Sokolovskiy, S. Syndergaard, and D. Hunt (2007), Estimates of the precision of GPS radio occultations from the COSMIC/FORMOSAT-3 mission, Geophys. Res. Lett., 34, L04808, doi:10.1029/2006GL027557. Schunk, R. W., L. Scherliess, J. J. Sojka, D. Thompson, and L. Zhu (2005), Ionospheric weather forecasting on the horizon, Space Weather, 3, S08007, doi:10.1029/2004SW000138. Spencer, P. S. J., D. S. Robertson, and G. L. Mader (2004), Ionospheric data assimilation methods for geodetic applications, paper presented at IEEE PLANS 2004, Inst. Electr. Electron. Eng., Monterey, Calif., 26–29 April 2004. Wang, C., G. Hajj, X. Pi, I. G. Rosen, and B. Wilson (2004), Development of the global assimilative ionospheric model, Radio Sci., 39, RS1S06, doi:10.1029/2002RS002854. Welch, G., and G. Bishop (2000), An introduction to the Kalman filter, Tech. Rep. TR95041, Dept. Comput. Sci., Univ. North Carolina, Chapel Hill, Yue, X., W. S. Schreiner, Y. C. Lin, C. Rocken, Y. H. Kuo, and B. Zhao (2011a), Data assimilation retrieval of electron density profiles from radio occultation measurements, J. Geophys. Res., 116, A03317, doi:10.1029/2010JA015980. Yue, X., W. S. Schreiner, D. C. Hunt, C. Rocken, and Y. H. Kuo (2011b), Quantitative evaluation of the low Earth orbit satellite based slant total electron content determination, Space Weather, 9, S09001, doi:10.1029/2011SW000687. Yue, X., W. S. Schreiner, and Y. H. Kuo (2012), A feasibility study of the radio occultation electron density retrieval aided by a global ionospheric data assimilation model, J. Geophys. Res., 117, A08301, doi:10.1029/2011JA017446. Yue, X., W. S. Schreiner, Y.-H. Kuo, J. J. Braun, Y.-C. Lin, and W. Wan (2014), Observing System Simulation Experiment Study on Imaging the Ionosphere by Assimilating Observations From Ground GNSS, LEO-Based Radio Occultation and Ocean Reflection, and Cross Link. IEEE Trans. Geosci. Remote Sens., 52(7), 3759-3773, doi:10.1109/TGRS.2013.2275753.
指導教授	劉正彥、松尾朋子(Jann-Yenq Liu Tomoko Matsuo)	審核日期	2015-5-5
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