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Predictability of nonlinear dynamical systems is related to ensemble forecasting. In turn, ensemble forecasting is an essential component of ensemble data assimilation, making a firm link between ensemble data assimilation and predictability. The chaotic nature of nonlinear dynamical systems is typically understood as a predictability limit. However, if one accepts the non-deterministic nature of weather and climate, the stability of strange attractors may be an indication of non-deterministic predictability.
We are interested in research dealing with both deterministic and non-deterministic predictability.
This research topic is a component of other research topics
- Applications with Complex Models
- Applications with Simple Models
- Basic Development of Ensemble Data Assimilation
- Information Content and Measures
- Dimension Reduction in Dynamical Systems
and research projects
- Research and development for GOES-R risk reduction
- Ensemble Kalman filtering for Army-scale meteorology
- Impact of fundamental assumptions of probabilistic data assimilation/ensemble forecasting: condition mode vs. conditional mean