陳依涵,2016:發展地面資料同化方法以改善都卜勒雷達變分分析系統之分析與預報能力。國立中央大學大氣物理所碩士論文,1–95。賴佑晟,2017:海表面風場與通量於熱帶氣旋發展影響之探討。國立中央大學大氣物理所碩士論文,1–76。蘇俊瑋,2016:利用觀測資料與多都卜勒風場反演系統做垂直速度上的驗證。國立中央大學大氣物理所碩士論文,1–60。張少凡,2013:同化策略及冰相微物理對四維變分都卜勒雷達分析系統(VDRAS)於定量降雨預報之影響研究。國立中央大學大氣物理所博士論文,1–81。戴聖倫,2010:使用四維變分同化都卜勒雷達資料以改進短期定量降雨預報。國立中央大學大氣物理所碩士論文,1–86。楊靜伃,2012:使用四維變分都卜勒雷達變分分析系統(VDRAS)與WRF改善短期定量降水預報。國立中央大學大氣物理所碩士論文,1–83。Anton Verhoef, Marcos Portabella, Ad Stoffelen, 2012: High-Resolution ASCAT Scatterometer Winds Near the Coast. IEEE Trans. Geosci. Remote Sens., 50, 2481-2487.
Barnes, S. L., 1973: Mesoscale objective map analysis using weighted time series observations. NOAA Tech. Memo. Erl Nssl-62, 60pp.
Bi, L., J. Jung, M. Morgan, and J. L. Marshall, 2011: Assessment of Assimilating ASCAT Surface Wind Retrievals in the NCEP Global Data Assimilation System. Monthly Weather Review, 139, 3405-3421.
Chung, K.-S., I. Zawadzki, M. K. Yau, and L. Fillion, 2009: Short term forecasting of a midlatitude convective storm by the assimilation of single–Doppler radar observations. Mon. Wea. Rev., 137, 4115–4135.
Chou, K.H., C.-C. Wu, S.-Z. Lin 2013: Assessment of the ASCAT wind error characteristics by global dropwindsonde observations. Journal of Geophysical Research: Atmospheres, 118, 9011-9021.
Chang, S.-F., J. Sun, Y.-C. Liou, S.-L. Tai, and C.-Y. Yang, 2014: The influence of erroneous background, beam-blocking and microphysical nonlinearity on the application of a four-dimensional variational Doppler radar data assimilation system for quantitative precipitation forecasts. Meteor. Appl., 21, 444–458.
——, Y.-C. Liou, J. Sun, and S.-L. Tai, 2016: The implementation of the ice phase microphysical process into a four-dimensional Variational Doppler Radar Analysis System(VDRAS) and its impact on parameter retrieval and quantitative precipitation nowcasting. J. Atmos. Sci. 73, 1015-1038.
Chen, X. C., K. Zhao, J. Z. Sun, B. W. Zhou, and W. C. Lee, 2016: Assimilating surface observations in a four-dimensional Variational Doppler radar data assimilation system to improve the analysis and forecast of a squall line case. Adv. Atmos. Sci., doi: 10.1007/s00376-016-5290-0., in press.
Crook, N. A., and J. Sun, 2002: Assimilating radar, surface and profiler data for the Sydney 2000 forecast demonstration project. J. Atmos. Oceanic Technol., 19, 888–898.
——, and J. Sun, 2004 Analysis and Forecasting of the Low-Level Wind during the Sydney 2000 Forecast Demonstration Project. Weather and Forecasting., 19:1, 151-167.
EUMETSAT, ASCAT Products Guide, 2011. [Online]. Available: http://www.eumetsat.int.
Franke, R., 1982: Scattered data interpolation: Tests of some methods. Math. Comput., 38, 181–200.
Hersbach, H., and P. Janssen, 2007a: Preparation for assimilation of surface-wind data from ASCAT at ECMWF. ECMWF Research Department Memo., ECMWF, Reading, United Kingdom
Hsu, S. A., E. A. Meindl, and D. B. Gilhousen, 1994: Determining the Power-Law Wind-Profile Exponent under Near-Neutral Stability Conditions at Sea. Journal of Applied Meteorology, 33, 757-765.
Houze, R. A. 1989: Observed structure of mesoscale convective systems and implications for large-scale heating. Quart. J. Roy. Meteor. Soc., 115, 425-461.
——, Jr., S. A. Rutledge, M. I. Biggerstaff, and B. F. Smull, 1989: Interpretation of Doppler weather radar displays in midlatitude mesoscale convective systems. Bull. Amer. Meteor. Soc.,70, 608-619.
Kawabata J., H. Seko, K. Saito, T. Kuroda, K. Tamiya, T. Tsuyuki, Wakazuki,2007: An assimilation and forecasting experiment of the Nerima heavy rainfall with a cloud-resolving nonhydrostatic 4-dimensiojnal variational data assimilation system, J. Meteor. Soc. Japan,85, 255-276.
Klemp, Joseph B., Robert B. Wilhelmson, 1978: The Simulation of Three-Dimensional Convective Storm Dynamics. J. Atmos. Sci.,35, 1070-1096.
Kessler, E., 1969: On the Distribution and Continuity of Water Substancein Atmospheric Circulation. Meteor. Monogr., No. 32, Amer. Meteor. Soc., 84 pp.
Liu, C.-Y., G.-R. Liu, T.-H. Lin, C.-C. Liu, H. Ren, and C.-C. Young, 2014: Using Surface Stations to Improve Sounding Retrievals from Hyperspectral Infrared Instruments, IEEE Trans. Geosci. Remote Sens, 52, 11, 6957-6963, doi:10.1109/TGRS.2014.2305992.
——, J. Li, S.-P. Ho, G.-R. Liu, T.-H. Lin, and C.-C. Young, 2016: Retrieval of Atmospheric Thermodynamic State from Synergistic Use of Radio Occultation and Hyperspectral Infrared Radiances Observations, IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, Vol. 9, no. 2, doi:10.1109/JSTARS.2015.2444274.
Li, Y., X. Wang and M. Xue, 2012: Assimilation of radar radial velocity data with the WRF ensemble-3DVAR hybrid system for the prediction of hurricane Ike (2008) . Mon. Wea. Rev. , in press.
Liu, W. T., K. B. Katsaros and J. A. Businger, 1979: Bulk parameterization of air-sea exchanges of heat and water vapor including the molecular constraints at the interface. J. Atmos. Sci., 36, 1722–1735.
Lin, Y., P. Ray, and K. Johnson, 1993: Initialization of a modeled convective storm using Doppler radar derived fields. Mon. Wea. Rev.,121, 2757-2775.
Miller, M. J., and R. P. Pearce, 1974: A three-dimentional primitive equation model of cumulonimbus convection. Quart. J. Roy. Meteor. Soc., 100, 133–154.
OSI SAF, ASCAT Wind Product User Manual, SAF/OSI/CDOP/KNMI/ TEC/MA/126, San Francisco, CA, 2011. [Online]. Available: http://www. osi-saf.org.
Pan, X., X. Tian, X. Li, Z. Xie, A. Shao, and C. Lu (2012), Assimilating Doppler radar radial velocity and reflectivity observations in the weather research and forecasting model by a proper orthogonal-decomposition-based ensemble, three-dimensional variational assimilation method, J. Geophys. Res., 117, D17113, doi:10.1029/2012JD017684.
Peterson, E. W., and J. P. Hennessey, 2010: On the Use of Power Laws 557 for Estimates of Wind Power Potential. J. Appl. Meteor, 17, 390-394.
Snyder, C., and F. Zhang, 2003: Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 131,1663-1677.
Sun, J., and N. A. Crook, 1997: Dynamical and microphysical retrieval from Doppler radar observation using a cloud model and its adjoint. Part I:Model development and simulated data experiments. J. Atmos. Sci., 54, 1642-1661.
——, and N. A. Crook, 1998: Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part II: Retrieval experiments of an observed Florida convective storm. J. Atmos. Sci., 55, 835-852.
——, and N. A. Crook, 2001: Assimilating radar, surface, and profiler data for the Sydney 2000 forecast demonstration project. J. Atmos. Sci., 19, 888-898.
——, and Y. Zhang, 2008: Analysis and prediction of a squall line observed during IHOP using multiple WSR-88D observations, Mon. Wea. Rev., 136, 2364-2388.
——, and H. Wang, 2013: Radar data assimilation with WRF 4D-Var: Part II. Comparison with 3D-Var for a squall line over the U.S. Great Plains. Mon. Wea. Rev., 141, 2245-2264.
Tong, M., and M. Xue, 2005: Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model: OSS experiments. Mon. Wea. Rev., 133, 1789–1807.
Tripoli, G. J., and W. R. Cotton, 1981: The use of ice-liquid water potential temperature as a thermodynamic variable in deep atmospheric models. Mon. Wea. Rev., 109, 1094–1102.
Tseng, Y., and J. Ferziger, 2003: A ghost-cell immersed boundary method for flow in complex geometry. J. Comput. Phys., 192, 593–623, doi: 10.1016/ j.jcp. 2003.07.024.
Tai, S.-L., Y.-C. Liou, J. Sun., S.-F. Chang., and M. C. Kuo, 2011: Precipitation Forecasting Using Doppler Radar Data, a Cloud Model with Adjoint, and the Weather Research and Forecasting Model :Real Case Studies during SoWMEX in Taiwan. Wea. Forecasting, 26, 975-992.
——, Y.-C. Liou, J. Sun, S. –F. Chang, 2017: The Development of a Terrain-Resolving Scheme for the Forward Model and Its Adjoint in the Four-Dimensional Variational Doppler Radar Analysis System (VDRAS). J. Atmos. Sci., 145. 289-306.
Verspeek, J., M. Portabella, A. Stoffelen and A. Verhoef Calibration and Validation of ASCAT winds OSI SAF technical report, SAF/OSI/KNMI/TEC/TN/163, 2008.
Warner, T. T., E. E. Brandes, C. K. Mueller, J. Sun, and D. N. Yates, 2000: Prediction of a flash flood in complex terrain. Part I: A comparison of Rainfall estimates from radar, and very short range rainfall simulations from a dynamic model and an automated algorithmic system. J. Appl. Meteor, 39 ,815–825.
Xiao, Q., and J. Sun, 2007: Multiple radar data assimilation and short-range QPF of a squall line observed during IHOP_2002. Mon. Wea. Rev., 135, 3381–3404.
——, Y. H. Kuo, J. Sun, W. C. Lee, E. Lim, Y. R. Guo, and D. M. Barker, 2005: Assimilation of Doppler radar observations with a regional 3DVAR System: Impact of Doppler velocities on forecasts of a heavy rainfall case. J. Appl. Meteor., 44, 768-788.
Xue, M., M. Tong, and K. K. Droegemeier, 2006: An OSSE framework based on the ensemble square rootKalman filter for evaluating impact of data fromradar networks on thunderstorm analysis and forecast. J. Atmos. Oceanic Technol., 23, 46–66.