Arthur P. Mizzi National Center for Atmospheric Research Boulder, CO 80307
303-497-8987 mizzi@ucar.edu
In previous work (Mizzi, 2011), we reported on the results obtained from the GSI/ETKF regional hybrid with WRF/ARW and: (i) conducting a comparison of different ETKF schemes and (ii) reducing and holding the number of ETKF observations constant. Those results showed that: (i) the ETKF scheme requiring the least amount of inflation provided the lowest 12-hr forecast RMSEs (ii) holding the number of ETKF observations constant removed the oscillation in the posterior ETKF ensemble spread noted by Bowler et al., (2008), and (iii) reducing the number of ETKF observations lowered the 12-hr forecast RMSEs.
In this paper, we compare the results from the GSI/ETKF regional hybrid and the preferred ETKF scheme from our previous study with the results from a GSI/LETKF regional hybrid based on the LETKF of Ott et al. (2004) and from a GSI/EnKF regional hybrid based on the DART EnKF (Anderson et al., 2009). Compared to the GSI/ETKF scheme, the GSI/LETKF and GSI/EnKF schemes generally require less ensemble spread inflation. Consequently, our earlier results suggest that the GSI/LETKF and GSI/EnKF schemes should provide lower 12-hr forecast RMSEs compared to the GSI/ETKF. Our preliminary results are consistent that that supposition.
References:
Anderson, J., T. Hoar, K.Raeder, H. Liu, N. Collins, R. Torn, and A. Arellano: 2009: The Data Assimilation Research Testbed: A community facility. Bul. Amer. Met. Soc., 90, 1283-1296.
Bowler, N.E., A. Arribas, K.R. Mylne, K.B. Robertson, and S.E. Beare, 2008: The MOGREPS short-range ensemble prediction system. Quart. J. Meteor. Soc., 134, 703-722.
Mizzi, A.P. 2011: A hybrid GSI/ETKF data assimilation scheme for the WRF/ARW model. (To be submitted to Mon. Wea. Rev.).
Ott, E., B.R. Hunt, I Szunyogh, A.V. Zimin, E.J.Kstelich, M. Corazza, E.Kalnay, D.J. Patil, and J.A. Yorke, 2004: A local ensemble Kalman filter for atmospheric data assimilation. Tellus 56A, 415-428.
Supplementary URL: