Estimating Model Parameters with Ensemble-Based Data Assimilation: A Review

JUAN JOSE RUIZ; MANUEL PULIDO; TAKEMASA MIYOSHI

JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN

METEOROLOGICAL SOC JPN

Año: 2013

0026-1165

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 the model parameters using data assimilation techniques. This paper provides a review of the previous studies and illustrate the application of the 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 produce a positive impact upon short to medium- range numerical weather prediction.