Articles | Volume 12, issue 12
https://doi.org/10.5194/gmd-12-5197-2019
https://doi.org/10.5194/gmd-12-5197-2019
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

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Cited articles

Albring, T., Sagebaum, M., and Gauger, N. R.: Efficient Aerodynamic Design using the Discrete Adjoint Method in SU2, AIAA 2016-3518, 2016. a
Asai, T.: A Numerical Study of the Air-Mass Transformation over the Japan Sea in Winter, J. Meteorol. Soc. Jpn. Ser. II, 43, 1–15, 1965. a
Baumgartner, M.: Algorithmic Differentiation for Cloud Schemes using CoDiPack (v1.8.1), Zenodo, https://doi.org/10.5281/zenodo.3461483, 2019. a
Belikov, D. A., Maksyutov, S., Yaremchuk, A., Ganshin, A., Kaminski, T., Blessing, S., Sasakawa, M., Gomez-Pelaez, A. J., and Starchenko, A.: Adjoint of the global Eulerian–Lagrangian coupled atmospheric transport model (A-GELCA v1.0): development and validation, Geosci. Model Dev., 9, 749–764, https://doi.org/10.5194/gmd-9-749-2016, 2016. a
Bischof, C. H. and Eberhard, P.: Automatic differentiation of numerical integration algorithms, Math. Comp., 68, 717–731, https://doi.org/10.1090/S0025-5718-99-01027-3, 1999. a, b, c
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Numerical models in atmospheric sciences need to include physical processes through...
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