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Original Articles

Assimilating non-local observations with a local ensemble Kalman filter

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Pages 719-730 | Received 20 Oct 2006, Accepted 18 May 2007, Published online: 15 Dec 2016

References

  • Anderson, J. L. 2001. An ensemble adjustment Kalman filter for data assimilation. Mon. Wea. Re v. 129, 2884–2903.
  • Anderson, J. L. 2003. A local least squares framework for ensemble filtering. Mon. Wea. Re v. 131, 634–642.
  • Bishop, C. H., Etherton, B. and Majumdar, S. J. 2001. Adaptive sampling with the ensemble transform Kalman filter. Part I: theoretical aspects. Mon. Wea. Re v. 129,420–436.
  • Burgers, G., van Leeuwen, P. J. and Evensen, G. 1998. Analysis scheme in the ensemble Kalman filter. Mon. Wea. Re v. 126, 1719–1724.
  • Evensen, G. 1994. Sequential data assimilation with a nonlinear quasigeostropic model using Monte Carlo Methods to forecast error statistics. J. Geophys. Res. 99, 10143–10162.
  • Gaspari, G. and Cohn, S. E. 1999. Construction of correlation functions in two and three dimensions. Q. J. Roy. Met. Soc. 125, 723–757.
  • Hamill, T., Whitaker, J. and Snyder, C. 2001. Distant-dependent filtering of background covariance estimates in an ensemble Kalman filter. Mon. Wea. Re v. 129, 2776–2790.
  • Harlim, J. and Hunt, B. R. 2007 A non-Gaussian ensemble filter for assimilating infrequent noisy observations. Tellus A. 59A, 225-237.
  • Houtekamer, P. L. and Mitchell, H. L. 1998. Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Re v. 126, 796–811.
  • Houtekamer, P. L. and Mitchell, H. L. 2001. A sequential ensemble Kalman filter technique. Mon. Wea. Re v. 129, 123–137.
  • Houtekamer, P. L. and Mitchell, H. L. 2006. Ensemble Kalman Filtering. Q. J. Roy. Met. Soc. 131, 3269–3289.
  • Houtekamer, P. L., Mitchell, H. L., Pellerin, G., Buehner, M., Charron, M. and co-authors 2005. Atmospheric data assimilation with the ensemble Kalman filter: results with real observations.Mon. Wea. Rev. 133, 604-620.
  • Hunt, B. R., Kostelich, E. J. and Szunyogh, I. 2007. Efficient data assimilation for spatiotemporal chaos: a local ensemble transform Kalman filter. Physica D. 230, 112–126.
  • Joiner, J. and da Silva, A. M. 1998. Efficient methods to assimilate remotely sensed data based on information content. Q. J. Roy. Met. Soc. 124, 1669–1694.
  • Kalman, R. E. 1960. A new approach to linear filtering and prediction problems. J. Basic Eng. 82D, 35–45.
  • Kalman, R. E. and Bucy, R. S. 1961. New results in linear filtering and prediction theory. J. Basic Eng. 83D, 95–107.
  • Kalnay, E. 2003. Atmospheric Modelling, Data Assimilation, and Predictability. Cambridge University Press, New York.
  • Keppenne, C. 1999. Data assimilation into a primitive-equation model with a parallel ensemble Kalman filter. Mon. Wea. Re v. 128, 1971–1981.
  • Kuhl, D., Szunyogh, I., Kostelich, E. J., Patil, D. J., Gyarmati, G. and co-authors. 2006. Assessing predictability with a local ensemble Kalman filter. J. Atmos. Sci. 64, 1116-1140.
  • Liou, K. 2002. An Introduction to Atmospheric Radiation. Academic Press, New York, Second Edition.
  • Miyoshi, T. 2005. Ensemble Kalman filter experiments with a primitive-equation global model. PhD thesis, University of Maryland.
  • Molteni, F. 2003. Atmospheric simulations using a GCM with simplified physics parameterizations I: model climatology and variability in multi-decadal experiments. Clim. Dyn. 20, 175–191.
  • Oczkowski, M., Szunyogh, I. and Patil, D. J. 2005. Mechanisms for the development of locally low dimensional atmospheric dynamics. J. Atmos. Sc i. 62, 1135–1156.
  • Ott, E., Hunt, B. R., Szunyogh, I., Zimin, A., Kostelich, E. J. and co-authors. 2004. A local ensemble Kalman filter for atmospheric data assimilation. Tellus 56A, 415-428.
  • Parrish, D. E and Cohn, S. E. 1985. A Kalman filter for a two-dimensional shallow-water model: formulation and preconditioning experiments. Office Note 304, National Meteorological Center, Washington, DC.
  • Patil, D. J., Hunt, B. R., Kalnay, E., Yorke, J. A. and Ott, E. 2005. Local low dimensionality of atmospheric dynamics. Physical Review Letters 86, 5878–5881.
  • Rodgers, C. D. 2000. Inverse Methods for Atmospheric Sounding: Theory and Practice. World Scientific Publishing.
  • Szunyogh, I., Kostelich, E. J., Gyarmati, G., Patil, D. J., Kalnay, E. and co-authors. 2005. Assessing a local ensemble Kalman filter: perfect model experiments with the National Centers for Environmental Prediction global model. Tellus 57A, 528-545.
  • Szunyogh, I., Kostelich, E. J., Gyarmati, G., Kalnay, E., Hunt, B. R. and co-authors. 2007. A local ensemble transform Kalman filter data assimilation system for the NCEP global model. Tellus, 59A, in press.
  • Whitaker, J. S. and Hamill, T. M. 2002. Ensemble data assimilation without perturbed observations. Mon. Wea. Re v. 130, 1913–1924.
  • Whitaker, J. S., Hamill, T. M., Wei, X., Song, Y. and Toth, Z. 2007. Ensemble data assimilation with the NCEP global forecast system. Mon. Wea. Rev., in press.