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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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GMD | Articles | Volume 11, issue 9
Geosci. Model Dev., 11, 3781–3794, 2018
https://doi.org/10.5194/gmd-11-3781-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 11, 3781–3794, 2018
https://doi.org/10.5194/gmd-11-3781-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model description paper 18 Sep 2018

Model description paper | 18 Sep 2018

sympl (v. 0.4.0) and climt (v. 0.15.3) – towards a flexible framework for building model hierarchies in Python

Joy Merwin Monteiro et al.

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Revised manuscript accepted for GMD
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Cited articles

Alpire, A.: Predicting Solar Radiation using a Deep Neural Network, available at: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215715 (last access: 20 August 2018), 2017. a
Clough, S. A., Shephard, M. W., Mlawer, E. J., Delamere, J. S., Iacono, M. J., Cady-Pereira, K., Boukabara, S., and Brown, P. D.: Atmospheric radiative transfer modeling: a summary of the AER codes, J. Quant. Spectrosc. Ra., 91, 233–244, https://doi.org/10.1016/j.jqsrt.2004.05.058, 2005. a, b, c
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Donahue, A. S. and Caldwell, P. M.: Impact of Physics Parameterization Ordering in A Global Atmosphere Model, J. Adv. Model. Earth Sy., 10, 481–499, https://doi.org/10.1002/2017MS001067, 2018. a
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In the same way that the fruit fly or the yeast cell serve as model systems in biology, climate scientists use a range of computer models to gain a fundamental understanding of our climate system. These models range from extremely simple models that can run on your phone to those that require supercomputers. Sympl and climt are packages that make it easy for climate scientists to build a hierarchy of such models using Python, which facilitates easy to read and self-documenting models.
In the same way that the fruit fly or the yeast cell serve as model systems in biology, climate...
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