Articles | Volume 12, issue 12
Methods for assessment of models
11 Dec 2019
Methods for assessment of models |  | 11 Dec 2019

Algorithmic differentiation for cloud schemes (IFS Cy43r3) using CoDiPack (v1.8.1)

Manuel Baumgartner, Max Sagebaum, Nicolas R. Gauger, Peter Spichtinger, and André Brinkmann


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Manuel Baumgartner on behalf of the Authors (24 Oct 2019)  Author's response    Manuscript
ED: Publish as is (12 Nov 2019) by David Topping
Short summary
Numerical models in atmospheric sciences need to include physical processes through parameterizations, which are not explicitly resolved, e.g., the formation of clouds. As a consequence, the parameterizations contain uncertain parameters. We suggest using the technique of algorithmic differentiation (AD) to identify the most uncertain parameters within parameterizations. In this study, we illustrate AD by analyzing a scheme for liquid clouds incorporated into a parcel model framework.