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We are also interested in applications of ensemble methods to simple models. These applications are useful for initial testing of new ideas, before complex high-dimensional models and real observations are used. The simple model applications are also beneficial for educational purposes, since they facilitate the participation of graduate students and postdoctoral researchers in this challenging interdisciplinary research endeavor. Important components of these applications include the development of easily transferable ensemble data assimilation code, that could be used on a desktop or a laptop computer.
Presently, we have the Maximum Likelihood Ensemble Filter (MLEF) system in use with the following simple models:
- Korteweg-de-Vries-Burgers one-dimensional model
- Lorenz 40-variable model
- Lorenz63 chaotic model
- NASA GOES-5 column model
