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Referencias:

• Aksoy, A., Parameter estimatio (2015) Encyclopedia of Atmospheric Sciences, 4, pp. 181-186. , 2nd ed. G. R. North, J. Pyle, and F. Zhang, Eds, Academic Press
• Aksoy, A., Zhang, F., Nielsen-Gammon, J., Ensemble-based simultaneous state and parameter estimation in a two-dimensional sea-breeze model (2006) Mon. Wea. Rev, 134, pp. 2951-2969
• Aksoy, A., Zhang, F., Nielsen-Gammon, J., Ensemble-based simultaneous state and parameter estimation with MM5 (2006) Geophys. Res. Lett, 33
• Anderson, J.L., An ensemble adjustment Kalman filter for data assimilation (2001) Mon. Wea. Rev, 129, pp. 2884-2903
• Anderson, J.L., Spatially and temporally varying adaptive covariance inflation for ensemble filters (2009) Tellus, 61A, pp. 72-83
• Annan, J.D., Parameter estimation using chaotic time series (2005) Tellus, 57A, pp. 709-714
• Annan, J.D., Hargreaves, J.C., Edwards, N.R., Marsh, R., Parameter estimation in an intermediate complexity earth system model using an ensemble Kalman filter (2005) Ocean Modell, 8, pp. 135-154
• Baek, S.-J., Hunt, B.R., Kalnay, E., Ott, E., Szunyogh, I., Local ensemble Kalman filtering in the presence of model bias (2006) Tellus, 58A, pp. 293-306
• Bellsky, T., Berwald, J., Mitchell, L., Nonglobal parameter estimation using local ensemble Kalman filtering (2014) Mon. Wea. Rev, 142, pp. 2150-2164
• Buizza, R., Miller, M., Palmer, T.N., Stochastic representation of model uncertainties in the ECMWF ensemble prediction system (1999) Quart. J. Roy. Meteor. Soc, 125, pp. 2887-2908
• Cornick, M., Hunt, B., Ott, E., Kurtuldu, H., Schatz, M.F., State and parameter estimation of spatiotemporally chaotic systems illustrated by an application to Rayleigh-Bénard convection (2009) Chaos, 19
• Danforth, C., Kalnay, E., Miyoshi, T., Estimating and correcting global weather model error (2007) Mon. Wea. Rev, 135, pp. 281-299
• Dee, D., da Silva, A., Data assimilation in the presence of forecast bias (1998) Quart. J. Roy. Meteor. Soc, 124, pp. 269-295
• Fertig, E., Hunt, B., Ott, E., Szunyogh, I., Assimilating non-local observations with a local ensemble Kalman filter (2007) Tellus, 59A, pp. 719-730
• Greybush, S.J., Kalnay, E., Miyoshi, T., Ide, K., Hunt, B.R., Balance and ensemble Kalman filter localization techniques (2011) Mon. Wea. Rev, 139, pp. 511-522
• Greybush, S.J., Wilson, R.J., Hoffman, R.N., Hoffman, M.J., Miyoshi, T., Ide, K., McConnochie, T., Kalnay, E., Ensemble Kalman filter data assimilation of Thermal Emission Spectrometer temperature retrievals into aMars GCM (2012) J. Geophys. Res, 117
• Hamill, T., Whitaker, J.S., Snyder, C., Distance dependent filtering of background-error covariance estimates in an ensemble Kalman filter (2001) Mon. Wea. Rev, 129, pp. 2776-2790
• Houtekamer, P.L., Mitchell, H.L., Deng, X., Model error representation in an operational ensemble Kalman filter (2009) Mon. Wea. Rev, 137, pp. 2126-2143
• Hunt, B.R., Kostelich, E.J., Szunyogh, I., Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter (2007) Physica D, 77, pp. 437-471
• Jakob, C., Accelerating progress in global atmospheric model development through improved parameterizations (2010) Bull.Amer. Meteor. Soc, 91, pp. 869-875
• Jazwinski, A.H., Stochastic and Filtering Theory (1970) Mathematics in Sciences and Engineering Series, 64, p. 376. , Academic Press
• Jung, Y., Xue, M., Zhang, G., Simultaneous estimation of microphysical parameters and the atmospheric state using simulated polarimetric radar data and an ensemble Kalman filter in the presence of an observation operator error (2010) Mon. Wea. Rev, 138, pp. 539-562
• Kang, J.S., Kalnay, E., Liu, J., Fung, I., Miyoshi, T., Ide, K., "Variable localization" in an ensemble Kalman filter: Application to the carbon cycle data assimilation (2011) J. Geophys. Res, 116
• Kondrashov, D., Sun, C., Ghil, M., Data assimilation for a coupled ocean-atmosphere model. Part II: Parameter estimation (2008) Mon. Wea. Rev, 136, pp. 5062-5076
• Koyama, H., Watanabe, W., Reducing forecast errors due to model imperfections using ensemble Kalman filtering (2010) Mon. Wea. Rev, 138, pp. 3316-3332
• Li, H., Kalnay, E., Miyoshi, T., Danforth, C.M., Accounting for model errors in ensemble data assimilation (2009) Mon. Wea. Rev, 137, pp. 3407-3419
• Meng, Z., Zhang, F., Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part II: Imperfect model experiments (2007) Mon. Wea. Rev, 135, pp. 1403-1423
• Miyoshi, T., (2005) Ensemble Kalman filter experiments with a primitive-equation global model, p. 197. , Ph.D. thesis, University of Maryland, College Park
• Miyoshi, T., The Gaussian approach to adaptive covariance inflation and its implementation with the local ensemble transform Kalman filter (2011) Mon. Wea. Rev, 139, pp. 1519-1535
• Miyoshi, T., Yamane, S., Local ensemble transform Kalman filtering with an AGCM at a T159/L48 resolution (2007) Mon. Wea. Rev, 135, pp. 3841-3861
• Miyoshi, T., Yamane, S., Enomoto, T., Localizing the error covariance by physical distanceswithin a local ensemble transform Kalman filter (LETKF) (2007) SOLA, 3, pp. 89-92
• Molteni, F., Atmospheric simulations using a GCM with simplified physical parametrizations. I: Model climatology and variability in multi-decadal experiments (2003) Climate Dyn, 20, pp. 175-191
• Pulido, M., Thuburn, J., Gravity wave drag estimation from global analyses using variational data assimlation principles. Part II: Case study (2006) Quart. J. Roy. Meteor. Soc, 132, pp. 1527-1543
• Ruiz, J., Pulido, M., Miyoshi, T., Estimating model parameters with ensemble-based data assimilation: A review (2013) J. Meteor. Soc. Japan, 91, pp. 79-99
• Ruiz, J., Pulido, M., Miyoshi, T., Estimating model parameters with ensemble-based data assimilation: Parameter covariance treatment (2013) J. Meteor. Soc. Japan, 91, pp. 453-469
• Schirber, S., Klocke, D., Pincus, R., Quaas, J., Anderson, J.L., Parameter estimation using data assimilation in an atmospheric general circulation model: From a perfect towards the real world (2013) J. Adv.Model. Earth Syst, 5, pp. 58-70
• Shutts, G., A kinetic energy back scatter algorithm for use in ensemble prediction systems (2005) Quart. J. Roy. Meteor. Soc, 131, pp. 3079-3102
• Stainforth, D.A., Uncertainty in predictions of the climate response to rising levels of greenhouse gases (2005) Nature, 433, pp. 403-406
• Tong, M., Xue, M., Simultaneous estimation of microphysical parameters and atmospheric state with simulated radar data and ensemble square root Kalman filter. Part II: Parameter estimation experiments (2008) Mon.Wea. Rev, 136, pp. 1649-1668
• Whitaker, J.S., Hamill, T.M., Evaluating methods to account for system errors in ensemble data assimilation (2012) Mon. Wea. Rev, 140, pp. 3078-3089
• Whitaker, J.S., Hamill, T.M., Wei, X., Song, Y., Toth, Z., Ensemble data assimilation with the NCEP global forecasting system (2008) Mon. Wea. Rev, 136, pp. 463-482
• Wu, X., Zhang, S., Liu, Z., Rosati, A., Delworth, T.L., Liu, Y., Impact of geographic dependent parameter optimization on climate estimation and prediction: Simulation with an intermediate coupled model (2012) Mon. Wea. Rev, 140, pp. 3956-3971
• Yang, S.-C., Kalnay, E., Miyoshi, T., Improving EnKF spin up for typhoon assimilation and prediction (2012) Wea. Forecasting, 27, pp. 878-897
• Zhang, S., Liu, Z., Rosati, A., Delworth, T., A study of enhancive parameter correction with coupled data assimilation for climate estimation and prediction using a simple coupled mode (2012) Tellus, 64A

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