Corresponding author address: Dr. Youmin Tang, Environmental Science and Engineering, University of Northern British Columbia, 3333 University Way, Prince George, BC V2N 4Z9, Canada. Email: ytang@unbc.ca
Ambadan, J. T., and Y. Tang, 2009a: Sigma-point Kalman filter data assimilation methods for strongly nonlinear systems. J. Atmos. Sci., 66 , 261–285.
Evensen, G., 1997: Advanced data assimilation for strongly nonlinear dynamics. Mon. Wea. Rev., 125 , 1342–1354.
Hamill, T. M., 2006: Ensemble-based atmospheric data assimilation. Predictability of Weather and Climate, T. N. Palmer and R. Hagedorn, Eds., Cambridge University Press, 124–156.
Hamill, T. M., J. S. Whitaker, J. L. Anderson, and C. Snyder, 2009: Comments on “Sigma-point Kalman filter data assimilation methods for strongly nonlinear systems”. J. Atmos. Sci., 66 , 3498–3500.
Houtekamer, P. L., and H. L. Mitchell, 2001: A sequential ensemble Kalman filter for atmospheric data assimilation. Mon. Wea. Rev., 129 , 123–137.
Hunt, B. R., E. J. Kostelich, and I. Szunyogh, 2007: Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter. Physica D, 230 , 112–126.
Julier, S., J. Uhlmann, and H. Durrant-Whyte, 1995: A new approach for filtering nonlinear systems. Proc. American Control Conf., Seattle, WA, IEEE, 1628–1632.
Tippett, M. K., J. L. Anderson, C. H. Bishop, T. M. Hamill, and J. S. Whitaker, 2003: Ensemble square-root filters. Mon. Wea. Rev., 131 , 1485–1490.
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Corresponding author address: Dr. Youmin Tang, Environmental Science and Engineering, University of Northern British Columbia, 3333 University Way, Prince George, BC V2N 4Z9, Canada. Email: ytang@unbc.ca
Corresponding author address: Dr. Youmin Tang, Environmental Science and Engineering, University of Northern British Columbia, 3333 University Way, Prince George, BC V2N 4Z9, Canada. Email: ytang@unbc.ca
Ambadan, J. T., and Y. Tang, 2009a: Sigma-point Kalman filter data assimilation methods for strongly nonlinear systems. J. Atmos. Sci., 66 , 261–285.
Evensen, G., 1997: Advanced data assimilation for strongly nonlinear dynamics. Mon. Wea. Rev., 125 , 1342–1354.
Hamill, T. M., 2006: Ensemble-based atmospheric data assimilation. Predictability of Weather and Climate, T. N. Palmer and R. Hagedorn, Eds., Cambridge University Press, 124–156.
Hamill, T. M., J. S. Whitaker, J. L. Anderson, and C. Snyder, 2009: Comments on “Sigma-point Kalman filter data assimilation methods for strongly nonlinear systems”. J. Atmos. Sci., 66 , 3498–3500.
Houtekamer, P. L., and H. L. Mitchell, 2001: A sequential ensemble Kalman filter for atmospheric data assimilation. Mon. Wea. Rev., 129 , 123–137.
Hunt, B. R., E. J. Kostelich, and I. Szunyogh, 2007: Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter. Physica D, 230 , 112–126.
Julier, S., J. Uhlmann, and H. Durrant-Whyte, 1995: A new approach for filtering nonlinear systems. Proc. American Control Conf., Seattle, WA, IEEE, 1628–1632.
Tippett, M. K., J. L. Anderson, C. H. Bishop, T. M. Hamill, and J. S. Whitaker, 2003: Ensemble square-root filters. Mon. Wea. Rev., 131 , 1485–1490.
All Time | Past Year | Past 30 Days | |
---|---|---|---|
Abstract Views | 0 | 0 | 0 |
Full Text Views | 370 | 297 | 113 |
PDF Downloads | 33 | 21 | 2 |