Articles | Volume 25, issue 2
Nonlin. Processes Geophys., 25, 355–374, 2018
https://doi.org/10.5194/npg-25-355-2018
Nonlin. Processes Geophys., 25, 355–374, 2018
https://doi.org/10.5194/npg-25-355-2018

Research article 03 May 2018

Research article | 03 May 2018

Feature-based data assimilation in geophysics

Matthias Morzfeld et al.

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Cited articles

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Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical weather prediction, Nature, 252, 45–55, 2015. a
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Many applications in science require that computational models and data be combined. In a Bayesian framework, this is usually done by defining likelihoods based on the mismatch of model outputs and data. However, matching model outputs and data in this way can be unnecessary or impossible. This issue can be addressed by selecting features of the data, and defining likelihoods based on the features, rather than by the usual mismatch of model output and data.