In the original sense, "cybernetics" means optimal use of information in decisionmaking.
It emerges that to develop a statistics of information requires a change of perspective from the simple one where developing the model is informed by the system under study to one where the model and the system under study are two components of a larger system. The Wiener filter and its descendant the Kalman filter are the best known examples of this approach but it is more general.
I believe this use of the word "model" is not entirely coincident with the software engineering sense as in "model-driven development" though it does mesh more or less well with "Model-View-Controller". In our world the View is relatively trivial and usually done offline as postprocessing; it's the utter absence of the Controller that troubles me.
(Update: That last is really a stretch on second thought. Probably more sellable is the idea that the M in MVC corresponds to system state (variables) and the C corresponds to executable code (statements). In the end the word "model" is just as much a source of confusion as ever.)
Anyway I think the cybernetic perspective has value in getting climate modeling unstuck.