System identification, modeling, and prediction for space weather environments

By now nonlinear dynamical models and neural networks have been used to predict and model a wide variety of space weather environments. This review starts with the physical basis for and a brief description of the system approach. Following that, several examples illustrate practical issues in temporal and spatiotemporal prediction and modeling. The concluding remarks discuss the future developments in this research direction.