The GEM workshop rolls on; here's an update from the world of space environment modeling.
GEM is very busy; there are several sessions, or "break-out sessions", occurring at one time. Because of the concentration of the material, you're always missing something that is both interesting and relevant to your research. The meeting is supposed to be in "workshop mode", which means talks are short and discussion is long. There is typically a 50% compliance rate with this.
Probably the most interesting information coming out of the workshop so far is how separate space weather models handle the same events. While there are some large-scale similarities, there are many important differences. These differences come up in the three major MHD models in the community - or, in plain-speak, three numerical models, relying on the same underlying physics, all give different results for the same solar driving conditions.
This is a somewhat scary revelation, though not at all surprising. In essence, it means that what we think we know, what the model is actually doing, and what we think the model is doing can all be conflated together and not consistently with each other. Much of this comes with the differences in the way the physics are implemented in the different codes and the different parameters you can change within a single code.
The solution is a lot of work: model parameter space mapping, data-model comparisons, and comparisons to other models. Within a single modeling group, this is a fine solution, but sharing and comparing such results is not always a welcome proposition. As funding can depend on model performance, teams are often reluctant to share these verification and validation results to the world even though it is a necessary step towards better science.
Such was the case this week: modelers could not settle on a set of community-wide verification/validation methods and metrics. This is, of course, a case of history repeating. Some groups do understand the importance of these comparisons and are making concessions and contributing, but others are clamming up as hard as they can.
I demand more open source science modeling!
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