Dealing with bugs is part of climate modeling

Numerical models are not just numerical representations of physical phenomena. They are also software files written by humans. As such they contain unintended coding errors, termed bugs. While the size of climate model code and human imperfection suggest that these are frequently present in climate models (Pipitone and Easterbrook, 2012), bugs are seldom acknowledged in the literature. However, missing understanding of model bugs hinders our understanding of model results as well as our ability to improve modeling workflows.

With a case study of the ICON general circulation model (GCM), I elucidate the practices and considerations around model debugging. Specifically, I give examples for bugs detected in that GCM's development and report on qualitative in-depth interviews I conducted with 11 model developers (domain scientists and scientific programmers). The interviews show that dealing with bugs is not a standardised process. While the technical testing of ICON code developments is highly standardised, and for example the assignment of responsibility is standardised implicitly, the scientific testing resists standardisation. The missing standardisation makes dealing with bugs a laborious process that takes time and effort and where human influence is common.

While this study focusses on the meaning of bugs for GCMs, similar considerations may be at play for models from different rugs of the model hierarchy. Where they differ, the model hierarchy may offer a way to more systematically detect and fix bugs in models of any rug.

 

 

Pipitone, J. and Easterbrook, S.: Assessing climate model software quality: a defect density analysis of three models, Geosci. Model Dev., 5, 1009–1022, https://doi.org/10.5194/gmd-5-1009-2012, 2012.