Articles | Volume 9, issue 10
Geosci. Model Dev., 9, 3639–3654, 2016
https://doi.org/10.5194/gmd-9-3639-2016

Special issue: The Modular Earth Submodel System (MESSy) (ACP/GMD inter-journal...

Geosci. Model Dev., 9, 3639–3654, 2016
https://doi.org/10.5194/gmd-9-3639-2016

Development and technical paper 13 Oct 2016

Development and technical paper | 13 Oct 2016

A diagnostic interface for the ICOsahedral Non-hydrostatic (ICON) modelling framework based on the Modular Earth Submodel System (MESSy v2.50)

Bastian Kern and Patrick Jöckel

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Cited articles

Ali, N., Carns, P., Iskra, K., Kimpe, D., Lang, S., Latham, R., Ross, R., Ward, L., and Sadayappan, P.: Scalable I/O forwarding framework for high-performance computing systems, in: 2009 IEEE International Conference on Cluster Computing and Workshops, 1–10, https://doi.org/10.1109/CLUSTR.2009.5289188, 2009.
Baker, A. H., Hammerling, D. M., Mickleson, S. A., Xu, H., Stolpe, M. B., Naveau, P., Sanderson, B., Ebert-Uphoff, I., Samarasinghe, S., De Simone, F., Carbone, F., Gencarelli, C. N., Dennis, J. M., Kay, J. E., and Lindstrom, P.: Evaluating Lossy Data Compression on Climate Simulation Data within a Large Ensemble, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-146, in review, 2016.
Baumgaertner, A. J. G., Jöckel, P., Kerkweg, A., Sander, R., and Tost, H.: Implementation of the Community Earth System Model (CESM) version 1.2.1 as a new base model into version 2.50 of the MESSy framework, Geosci. Model Dev., 9, 125–135, https://doi.org/10.5194/gmd-9-125-2016, 2016.
Bodas-Salcedo, A., Webb, M. J., Brooks, M. E., Ringer, M. A., Williams, K. D., Milton, S. F., and Wilson, D. R.: Evaluating cloud systems in the Met Office global forecast model using simulated CloudSat radar reflectivities, J. Geophys. Res.-Atmos., 113, D00A13, https://doi.org/10.1029/2007JD009620, 2008.
Buehler, S. and Russchenberg, H. (Eds.): HD(CP)2 Observational Prototype Experiment, Atmos. Chem. Phys., http://www.atmos-chem-phys.net/special_issue366.html, 2014.
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Input and output of large data limit the performance of numerical models on supercomputers. We present an interface for the calculation of online diagnostics in a weather and climate model. These diagnostics are calculated online during the simulation instead of as subsequent post-processing. Depending on the diagnostic, we can reduce the amount of model output.