Judith Curry just recently asked the following question in her blog post “The 50-50 argument”:
“So, how to sort this out and do a more realistic job of detecting climate change and (…) attributing it to natural variability versus anthropogenic forcing? Observationally based methods and simple models have been underutilized in this regard.”
There is a very simple way of doing this that people at large still seem to be absolutely blind to. To echo the words of ‘Statistician to the Stars!’ William M. Briggs: “Just look at the data!” You have to do it in detail. Both temporally and spatially. I have done this already here, here and here + a summary of the first three here. In this post I plan to highlight even more clearly the difference between what an anthropogenic (‘CO2 forcing’) signal would and should look like and a signal pointing to natural processes.
Curry has many sensible points. She says among other things:
“Because historical records aren’t long enough and paleo reconstructions are not reliable, the climate models ‘detect’ AGW by comparing natural forcing simulations with anthropogenically forced simulations. When the spectra of the variability of the unforced simulations is compared with the observed spectra of variability, the AR4 simulations show insufficient variability at 40-100 yrs, whereas AR5 simulations show reasonable variability. The IPCC then regards the divergence between unforced and anthropogenically forced simulations after ~1980 as the heart of the their detection and attribution argument. (…)
The glaring flaw in their logic is this. If you are trying to attribute warming over a short period, e.g. since 1980, detection requires that you explicitly consider the phasing of multidecadal natural internal variability during that period (e.g. AMO, PDO), not just the spectra over a long time period. Attribution arguments of late 20th century warming have failed to pass the detection threshold which requires accounting for the phasing of the AMO and PDO. It is typically argued that these oscillations go up and down, in net they are a wash. Maybe, but they are NOT a wash when you are considering a period of the order, or shorter than, the multidecadal time scales associated with these oscillations.
Further, in the presence of multidecadal oscillations with a nominal 60-80 yr time scale, convincing attribution requires that you can attribute the variability for more than one 60-80 yr period, preferably back to the mid 19th century. Not being able to address the attribution of change in the early 20th century to my mind precludes any highly confident attribution of change in the late 20th century.“
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