Articles | Volume 22, issue 5
https://doi.org/10.5194/npg-22-601-2015
https://doi.org/10.5194/npg-22-601-2015
Research article
 | 
09 Oct 2015
Research article |  | 09 Oct 2015

A framework for variational data assimilation with superparameterization

I. Grooms and Y. Lee

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Short summary
Superparameterization is a multiscale computational method that significantly improves the representation of cloud processes in global atmosphere and climate models. We present a framework for assimilating observational data into superparameterized models to initialize them for forecasts. The framework is demonstrated in the context of a new system of ordinary differential equations that constitutes perhaps the simplest model of superparameterization.