Abstract: An important step in understanding the climate system is simulating and studying the past climate variability, using oceanic models, atmospheric models, or both. Toward this goal, long-term wind stress data, as the forcing ...

Abstract: n this study, the predictability of the Pacific?North American (PNA) pattern is evaluated on time scales from days to months using state-of-the-art dynamical multiple-model ensembles including the Canadian Historical ...

Abstract: In this study, a breeding analysis was conducted for a hybrid coupled El Niño?Southern Oscillation (ENSO) model that assimilated a historic dataset of sea surface temperature (SST) for the 120 yr between 1881 and 2000. ...

Abstract: Performance of an advanced, derivativeless, sigma-point Kalman filter (SPKF) data assimilation scheme in a strongly nonlinear dynamical model is investigated. The SPKF data assimilation scheme is compared against standard ...

Abstract: The advent of the feed-forward neural network (N) model opens the possibility of hybrid neural?dynamical models via variational data assimilation. Such a hybrid model may be used in situations where some variables, difficult ...

Abstract: A challenging problem on observerbased, integrated fault diagnosis and faulttolerant control for linear systems subject to actuator faults and control input constraints is studied in this paper. An adaptive observer approach ...