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Abstract:

Weather forecast and earth system models usually have a number of parameters, which are often optimized manually by trial and error. Several studies have proposed objective methods to estimate model parameters using data assimilation techniques. This paper provides a review of the previous studies and illustrates the application of ensemble-based data assimilation to the estimation of temporally varying model parameters in a simple low-resolution atmospheric general circulation model known as the SPEEDY model. As shown in previous studies, our results highlight that data assimilation techniques are efficient optimization methods which can be used for parameter estimation in complex geophysical models and that the estimated parameters have a positive effect on short-to medium-range numerical weather prediction. © 2013, Meteorological Society of Japan.

Registro:

Documento: Artículo
Título:Estimating model parameters with ensemble-based data assimilation: A review
Autor:Ruiz, J.J.; Pulido, M.; Miyoshi, T.
Filiación:Department of Physics, FACENA, Universidad Nacional del Nordeste, Corrientes, Argentina
CIMA, UMI-IFAECI/CNRS, CONICET, Buenos Aires, Argentina
Department of Physics, FACENA, Universidad Nacional del Nordeste, Corrientes, Argentina
IMIT, UMI-IFAECI/CNRS, CONICET, Argentina
Department of Atmospheric andOceanic Science, University of Maryland, College Park, MD, United States
Palabras clave:Data assimilation; Ensemble Kalman filter; Parameter estimation; atmospheric general circulation model; climate prediction; data assimilation; ensemble forecasting; Kalman filter; weather forecasting
Año:2013
Volumen:91
Número:2
Página de inicio:79
Página de fin:99
DOI: http://dx.doi.org/10.2151/jmsj.2013-201
Título revista:Journal of the Meteorological Society of Japan
Título revista abreviado:J. Meteorol. Soc. Jpn.
ISSN:00261165
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00261165_v91_n2_p79_Ruiz

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Citas:

---------- APA ----------
Ruiz, J.J., Pulido, M. & Miyoshi, T. (2013) . Estimating model parameters with ensemble-based data assimilation: A review. Journal of the Meteorological Society of Japan, 91(2), 79-99.
http://dx.doi.org/10.2151/jmsj.2013-201
---------- CHICAGO ----------
Ruiz, J.J., Pulido, M., Miyoshi, T. "Estimating model parameters with ensemble-based data assimilation: A review" . Journal of the Meteorological Society of Japan 91, no. 2 (2013) : 79-99.
http://dx.doi.org/10.2151/jmsj.2013-201
---------- MLA ----------
Ruiz, J.J., Pulido, M., Miyoshi, T. "Estimating model parameters with ensemble-based data assimilation: A review" . Journal of the Meteorological Society of Japan, vol. 91, no. 2, 2013, pp. 79-99.
http://dx.doi.org/10.2151/jmsj.2013-201
---------- VANCOUVER ----------
Ruiz, J.J., Pulido, M., Miyoshi, T. Estimating model parameters with ensemble-based data assimilation: A review. J. Meteorol. Soc. Jpn. 2013;91(2):79-99.
http://dx.doi.org/10.2151/jmsj.2013-201