Hi Stephen, I think this is just a signal to noise question, looking at the part of the response that is correlated with the input (which means its only noise on the same time-scales that matters). There are some fancier things that can be done in some limited cases where a lot is known about the characteristics of the unknown noise (e.g. in extracting speech from wind noise on your cell phone mic) that I don't think apply here. So the detection improves linearly with the amplitude of the signal, and with the square root of the time you're averaging over. For any meaningful global detection experiment (i.e., looking at understanding the effect on climate, rather than a process question like say measuring the change in cloud albedo) should be thinking at least some fraction of a W/m2, and at least a decade or two or more, depending on what confidence you want on what variable. Any experiment that doesn't produce a significant radiative forcing is unlikely to be detectable on any practical time-scale. (And insert obvious caveats that we should proceed with modeling first, and process-level experiments... but I do think it is worth asking the question about testing in order to get the right mindset with regards to how long this takes if we want confidence in the results.)
As for your question about chaos, I can't answer that (and agree with you on principle), though as an engineer then in the limited context of whether we can test geoengineering, I don't think it matters whether the noise is truly unknowable (stochastic) vs hypothetically knowable (some chaotic component). doug -- You received this message because you are subscribed to the Google Groups "geoengineering" group. To post to this group, send email to [email protected]. To unsubscribe from this group, send email to [email protected]. For more options, visit this group at http://groups.google.com/group/geoengineering?hl=en.
