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Objetivo Geral:

Bibliografia Básica:

• [1] BOUTTIER, F.; COURTIER, P. Data assimilation concepts and methods. Meteorological Training Course Lecture Series, ECMWF. 2002. Disponível em: https://www.ecmwf.int/sites/default/files/elibrary/2002/16928-data-assimilation-conceptsand-methods.pdf. Acesso em: 19 out. 2022.
• [2] HOLTON, J. R. An Introduction to Dynamic Meteorology. 4. ed. Burlington: Elsevier, 2004. 535 p. (International geophysics series. v. 88) ISBN 0123540151.
• [3] KALNAY, Eugenia. Atmospheric modeling, data assimilation and predictability. Cambridge: Cambridge University, 2011. 341 p. ISBN 9780521796293.

Bibliografia Complementar:

• [1] Eugênia Kalnay Home Page. Disponível em: http://www.atmos.umd.edu/~ekalnay/. Acesso em: 19 out. 2022.
• [2] MIYOSHI, T. Ensemble Kalman filter experiments with a primitive-equation global model. Ph.D. dissertation, University of Maryland, College Park, 2005. 197pp. Disponível em: http://drum.lib.umd.edu//handle/1903/3046. Acesso em: 19 out. 2022.
• [3] PRESS, W. H; TEUKOLSKY, S. A.; VETTERLING, W. T; FLANNERY, B. P. Numerical Recipes: The art of Scientific Computing Third Edition, 1235 pp. Cambridge University Press. ISBN: 9780521880688, 1996.
• [4] RABIER, F.; JÄRVINEN, H.; KLINKER, E., MAHFOUF, J.F., SIMMONS, A. The ECMWF operational implementation of four-dimensional variational assimilation. I: Experimental results with simplified physics. Quarterly Journal of the Royal Meteorological Society. DOI: https://doi.org/10.1002/qj.49712656415, 2007.
• [5] EVENSEN, G. Data Assimilation, The Ensemble Kalman Filter, 2.ed. Norway: Springer. 2009. 330p. ISBN 3642037100.