Response to the discussion on “4-D-Var or EnKF?” by Nils Gustafsson

Eugenia KalnayUniversity of Maryland, College Park, 3431 CSS building, MD 20742-2425, USA;Correspondencee-mail: [email protected]

Hong LiUniversity of Maryland, College Park, 3431 CSS building, MD 20742-2425, USA;

Takemasa MiyoshiNumerical Prediction Division, Japan Meteorological Agency,Tokyo,Japan;

Shu-Chih YangUniversity of Maryland, College Park, 3431 CSS building, MD 20742-2425, USA;

Joaquim Ballabrera-PoyInstitut de Ciències del Mar (CSIC),Barcelona, Spain

References

Cardinali, C., Pezzuli, S. and Andersson, E. 2004. Influence matrix diag-nostic of a data assimilation system. Q. J. R. Meteo. Soc. 130, 2767–2786.
Web of Science ®Google Scholar
Desroziers G., Berre, L., Chapnilc, B. and Poli, P. 2005. Diagnosis of observation, background and analysis error statistics in observation space. Q. J. R. Meteor Soc. 131, 3385–3396.
Web of Science ®Google Scholar
Gustafsson, Nils 2007. Discussion. Tellus 59A, this issue.
Google Scholar
Kalnay, E., Li, H. and Miyoshi, T. 2007. Adaptive estimation of back-ground and observation errors within the Local Ensemble Trans-form Kalman Filter. Preprints of the 11th Symposium on Inte-grated Observing and Assimilation Systems, Paper 7.2A, 87th AMS Annual Meeting, San Antonio, TX, January 2007. Available at: http://ams.confex.com/ams/pdfpapers/120864.pdf.
Google Scholar
Miyoshi, T. and Aranami, K. 2006. Applying a Four-dimensional local ensemble transform Kalman filter (4-D-LETKF) to the .IMA nonhy-drostatic model (NIAM). SOLA 2, 128–131.
Web of Science ®Google Scholar
Navascues, B., Lindskog, M., Yang, X. and Amstrup, B. 2006. Diag-nosis of error statistics in the I-BRLAM 3D-Var. I-BRLAM Technical Report #66. Available at: I-BRLAM.org.
Google Scholar