The participation of the first author was funded by National Science Foundation Grants ATM-0205612, ATM-0205655, and a NOAA THORPEX grant. We thank Syed Rizvi and John Bray for their help with technical problems of WRF VAR at the early stages of the study. We appreciate Yongsheng Chen for sharing the WRF LBC ensemble perturbation scripts. Discussions with Jeff Whitaker improved the manuscript. We also appreciate the constructive comments from the reviewers.
Barker, D. M., 1999: Var scientific development paper 25: The use of synoptic-dependent error structure in 3DVAR. Met Office Tech. Rep., 2 pp. [Available from Met Office, FitzRoy Rd., Exeter, Devon EX1 3PB, United Kingdom.].
Barker, D. M., W. Huang, Y-R. Guo, and A. Bourgeois, 2003: A three-dimensional variational (3DVAR) data assimilation system for use with MM5. NCAR Tech. Note NCAR/TN-453+STR, 68 pp. [Available from UCAR Communications, P.O. Box 3000, Boulder, CO 80307.].
Barker, D. M., W. Huang, Y-R. Guo, A. Bourgeois, and Q. N. Xiao, 2004: A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Mon. Wea. Rev., 132 , 897–914.
Buehner, M., 2005: Ensemble-derived stationary and flow-dependent background-error covariances: Eevaluation in a quasi-operational NWP setting. Quart. J. Roy. Meteor. Soc., 131 , 1013–1043.
Caya, A., D. M. Barker, and C. Snyder, 2004: An ensemble Kalman filter for WRF and a comparison with the WRF three-dimensional variational assimilation scheme. Proc. First Int. Science Symp., Montreal, Canada, THORPEX. [Available online at http://www.mmm.ucar.edu/people/snyder/papers/CayaBarkerSnyder2004.pdf.].
Cohn, S. E., D. M. da Silva, J. Guo, M. Sienkiewiez, and D. Lamich, 1998: Assessing the effects of data selection with the DAO physical space statistical analysis system. Mon. Wea. Rev., 126 , 2913–2926.
Courtier, P., and Coauthors, 1998: The ECMWF implementation of three-dimensional variational assimilation (3D-Var). I: Formulation. Quart. J. Roy. Meteor. Soc., 124 , 1783–1807.
Dirren, S., R. D. Torn, and G. J. Hakim, 2007: A data assimilation case study using a limited-area ensemble Kalman filter. Mon. Wea. Rev., 135 , 1455–1473.
Dowell, D. C., F. Zhang, L. J. Wicker, C. Snyder, and N. A. Crook, 2004: Wind and temperature retrievals in the 17 May 1981 Arcadia, Oklahoma, supercell: Ensemble Kalman filter experiments. Mon. Wea. Rev., 132 , 1982–2005.
Etherton, B. J., and C. H. Bishop, 2004: Resilience of hybrid ensemble/3DVAR analysis schemes to model error and ensemble covariance error. Mon. Wea. Rev., 132 , 1065–1080.
Evensen, G., 1994: Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res., 99 , C5. 10143–10162.
Gaspari, G., and S. E. Cohn, 1999: Construction of correlation functions in two and three dimensions. Quart. J. Roy. Meteor. Soc., 125 , 723–757.
Gauthier, P. C., L. Cherette, L. Fillion, P. Koclas, and S. Laroche, 1998: Implementation of a 3D variational data assimilation system at the Canadian Meteorological Center. Part I: The global analysis. Atmos.–Ocean, 37 , 103–156.
Hamill, T. M., 2006: Ensemble based atmospheric data assimilation. Predictability of Weather and Climate, R. Hagedorn and T. N. Palmer, Eds., Cambridge Press, 124–156.
Hamill, T. M., and C. Snyder, 2000: A hybrid ensemble Kalman filter-3D variational analysis scheme. Mon. Wea. Rev., 128 , 2905–2919.
Hamill, T. M., J. S. Whitaker, and C. Snyder, 2001: Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter. Mon. Wea. Rev., 129 , 2776–2790.
Hayden, C. M., and R. J. Purser, 1995: Recursive filter objective analysis of meteorological fields: Applications to NESDIS operational processing. J. Appl. Meteor., 34 , 3–15.
Houtekamer, P. L., and H. L. Mitchell, 1998: Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Rev., 126 , 796–811.
Houtekamer, P. L., and H. L. Mitchell, 2001: A sequential ensemble Kalman filter for atmospheric data assimilation. Mon. Wea. Rev., 129 , 123–137.
Houtekamer, P. L., H. L. Mitchell, G. Pellerin, M. Buehner, and M. Charron, 2005: Atmospheric data assimilation with an ensemble Kalman filter: Results with real observations. Mon. Wea. Rev., 133 , 604–620.
Keppenne, C. L., and M. M. Rienecker, 2002: Initial testing of a massively parallel ensemble Kalman filter with the Poseidon Isopycnal Ocean General Circulation Model. Mon. Wea. Rev., 130 , 2951–2965.
Liu, H., J. Anderson, Y-H. Kuo, C. Snyder, and A. Caya, 2008: Evaluation of a nonlocal quasi-phase observation operator in assimilation of CHAMP radio occultation refractivity with WRF. Mon. Wea. Rev., 136 , 242–256.
Lorenc, A. C., 2003: The potential of the ensemble Kalman filter for NWP—A comparison with 4D-VAR. Quart. J. Roy. Meteor. Soc., 129 , 3183–3203.
Lorenc, A. C., and Coauthors, 2000: The Met. Office global three-dimensional variational data assimilation scheme. Quart. J. Roy. Meteor. Soc., 126 , 2991–3012.
Majumdar, S. J., C. H. Bishop, B. J. Etherton, I. Szunyogh, and Z. Toth, 2001: Can an ensemble transform Kalman filter predict the reduction in forecast-error variance produced by targeted observations? Quart. J. Roy. Meteor. Soc., 127 , 2803–2820.
Meng, Z., and F. Zhang, 2008: Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part III: Comparison with 3DVAR in a real-data case study. Mon. Wea. Rev., 136 , 522–540.
Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center’s spectral statistical interpolation analysis system. Mon. Wea. Rev., 120 , 1747–1763.
Reichle, R. H., J. P. Walker, R. D. Koster, and P. R. Houser, 2002: Extended vs. ensemble Kalman filtering for land data assimilation. J. Hydrometeor., 3 , 728–740.
Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers, 2005: A description of the Advanced Research WRF Version 2. NCAR Tech. Note 468+STR, National Center for Atmospheric Research, Boulder, CO, 88 pp. [Available from UCAR Communications, P. O. Box 3000, Boulder, CO, 80307.].
Snyder, C., and F. Zhang, 2003: Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 131 , 1663–1677.
Szunyogh, I., E. J. Kostelich, G. Gyarmati, D. J. Patil, B. R. Hunt, E. Kalnay, E. Ott, and J. A. York, 2005: Assessing a local ensemble Kalman filter: Perfect model experiments with the NCEP global model. Tellus, 57A , 528–545.
Szunyogh, I., E. J. Kostelich, G. Gyarmati, E. Kalnay, B. R. Hunt, E. Ott, E. Satterfield, and J. A. Yorke, 2008: A local ensemble transform Kalman filter data assimilation system for the NCEP global model. Tellus, 60A , 113–130.
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.
Torn, R. D., and G. J. Hakim, 2008: Performance characteristics of a pseudo-operational ensemble Kalman filter. Mon. Wea. Rev., 136 , 3947–3963.
Torn, R. D., G. J. Hakim, and C. Snyder, 2006: Boundary conditions for limited area ensemble Kalman filters. Mon. Wea. Rev., 134 , 2490–2502.
Wang, X., and C. H. Bishop, 2003: A comparison of breeding and ensemble transform Kalman filter ensemble forecast schemes. J. Atmos. Sci., 60 , 1140–1158.
Wang, X., C. H. Bishop, and S. J. Julier, 2004: Which is better, an ensemble of positive–negative pairs or a centered spherical simplex ensemble? Mon. Wea. Rev., 132 , 1590–1605.
Wang, X., T. M. Hamill, J. S. Whitaker, and C. H. Bishop, 2007a: A comparison of hybrid ensemble transform Kalman filter-OI and ensemble square-root filter analysis schemes. Mon. Wea. Rev., 135 , 1055–1076.
Wang, X., C. Snyder, and T. M. Hamill, 2007b: On the theoretical equivalence of differently proposed ensemble/3D-Var hybrid analysis schemes. Mon. Wea. Rev., 135 , 222–227.
Wang, X., D. M. Barker, C. Snyder, and T. M. Hamill, 2008: A hybrid ETKF–3DVAR data assimilation scheme for the WRF Model. Part II: Real observation experiments. Mon. Wea. Rev., 136 , 5132–5147.
Whitaker, J. S., and T. M. Hamill, 2002: Ensemble data assimilation without perturbed observations. Mon. Wea. Rev., 130 , 1913–1924.
Whitaker, J. S., G. P. Compo, and T. M. Hamill, 2004: Reanalysis without radiosondes using ensemble data assimilation. Mon. Wea. Rev., 132 , 1190–1200.
Whitaker, J. S., T. M. Hamill, X. Wei, Y. Song, and Z. Toth, 2008: Ensemble data assimilation with the NCEP Global Forecast System. Mon. Wea. Rev., 136 , 463–482.
Wu, W., R. J. Purser, and D. F. Parrish, 2002: Three-dimensional variational analysis with spatially inhomogeneous covariances. Mon. Wea. Rev., 130 , 2905–2916.