This work was supported in part by Award KUS-C1-016-04 made by King Abdullah University of Science and Technology (KAUST). Mikyoung Jun's research was also partially supported by NSF Grants DMS-0906532 and DMS-1208421. Istvan Szunyogh acknowledges the support from ONR Grant N000141210785.
Burgers, G., P. J. van Leeuwen, and G. Evensen, 1998: Analysis scheme in the ensemble Kalman filter. Mon. Wea. Rev., 126, 1719–1724.
Calvet, L. E., V. Czellar, and E. Ronchetti, cited 2012: Robust filtering. [Available online at http://ssrn.com/abstract=2123477.]
Daley, R., 1991: Atmospheric Data Analysis. Cambridge Atmospheric and Space Science Series, Cambridge University Press, 457 pp.
Fahrmeir, L., and H. Kaufmann, 1991: On Kalman filtering, posterior mode estimation and Fisher scoring in dynamic exponential family regression. Metrika, 38, 37–60.
Genton, M. G., 2003: Breakdown-point for spatially and temporally correlated observations. Developments in Robust Statistics, R. Dutter et al., Eds., Springer, 148–159.
Genton, M. G., and A. Lucas, 2003: Comprehensive definitions of breakdown-points for independent and dependent observations. J. Roy. Stat. Soc., B65, 81–94.
Hampel, F. R., 1968: Contributions to the theory of robust estimation. Ph.D. thesis, University of California.
Harlim, J., and B. R. Hunt, 2007: A non-Gaussian ensemble filter for assimilating infrequent noisy observations. Tellus, 59A, 225–237.
Houtekamer, P. L., and H. L. Mitchell, 1998: Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Rev., 126, 796–811.
Huber, P. J., 1981: Robust Statistics. Wiley, 308 pp.
Ingleby, N. B., and A. C. Lorenc, 1993: Bayesian quality control using multivariate normal distributions. Quart. J. Roy. Meteor. Soc., 119, 1195–1225.
Lorenz, E. N., and K. A. Emanuel, 1998: Optimal sites for supplementary weather observations: Simulation with a small model. J. Atmos. Sci., 55, 399–414.
Luo, X., and I. Hoteit, 2011: Robust ensemble filtering and its relation to covariance inflation in the ensemble Kalman filter. Mon. Wea. Rev., 139, 3938–3953.
Maronna, A., R. D. Martin, and V. J. Yohai, 2006: Robust Statistics: Theory and Methods. Wiley, 436 pp.
Ruckdeschel, P., 2010: Optimally robust Kalman filtering. Berichte des Fraunhofer ITWM 185, 53 pp.
Schick, I. C., and S. K. Mitter, 1994: Robust recursive estimation in the presence of heavy-tailed observation noise. Ann. Stat., 22, 1045–1080.
Schlee, F. H., C. J. Standish, and N. F. Toda, 1967: Divergence in the Kalman filter. Amer. Inst. Aeronaut. Astronaut. J., 5, 1114–1120.
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, 60, 113–130.
Tavolato, C., and L. Isaksen, 2010: Huber norm quality control in the IFS. ECMWF Newsletter, No. 122, ECMWF, Reading, United Kingdom, 27–31.
Tukey, J. W., 1970: Exploratory Data Analysis. Vol. 1. Addison-Wesley, 688 pp.
West, M., 1983: Generalized linear models: Scale parameters, outlier accommodation and prior distributions. Bayesian Stat., 2, 531–558.
Whitaker, J. S., and T. M. Hamill, 2002: Ensemble data assimilation without perturbed observations. Mon. Wea. Rev., 130, 1913–1924.