I read this taxonomy of “narratives” about climate change at ImpactAlpha by Bob Eccles and Melita Leousi, hoping that it would produce more light than heat but having read it I’m not so sure. Here’s it’s opening passage:
ImpactAlpha, September 18 — The climate discourse by individuals and groups typically involves five narratives about the import and response to climate change. Some people are scientific, others skeptical. Some make moral arguments, others tout the opportunities. And, increasingly, many are warning of “doomsday” to spur urgency – or defeatism.
These narratives are “ideal types” that express themselves to varying degrees and in various combinations. We believe that recognizing the existence of these types can be helpful in fostering dialogue between people and groups who are addressing the challenges and opportunities of climate change (engaging with climate change deniers might naturally be harder).
with the following conclusion:
These are “ideal types” which we think can be a useful framing for fostering dialogue between people and groups who are addressing the challenges and opportunities of climate change.
To paint a stark example, take two groups that both use the Scientific Foundation as their dominant narrative, but one supplements it with the Doomsday Narrative and the other the Opportunity Narrative.
It would be natural for the Doomsayers to view the Opportunists as being overly optimistic and not having the proper sense of urgency. In contrast, adherents of the Opportunity view may find those warning of climate apocalypse to be shrill and failing to take a pragmatic view about the continued use of fossil fuels and the need for technological breakthroughs.
If well-meaning people who are concerned about climate change can’t talk to others simply because they talk about it in a different way, we will not be able to establish the social and political consensus necessary to address an issue that confronts us all, whatever our narrative.
The “narratives” are
For details on what is meant by each see the cited article. IMO framing the taxonomy in that way is itself somewhat argumentative.
My own view is that climate change models are weakly predictive, they are too susceptible to gaming, and that many of the strategies for dealing with anthropogenic climate change are questionable and/or are scams even if well-meaning, I don’t think that any strategy that does not involve nuclear energy, requiring China and India to reduce their carbon emissions, and, in all likelihood, carbon capture and sequestration are particularly serious. I think that some action is worthwhile but much of what is proposed is either ill-considered, regressive, or trying to accomplish something other than ameliorating climate change.
To understand why I say “weakly predictive”, cf. this passage by an article by Chad Small in the Bulletin of Atomic Scientists:
Global climate models and real-world observations mostly agree on average ocean warming over the last 40 years. But this agreement breaks down when you peel back that average and look at regional snapshots of sea surface temperature.
“If you have ever looked at [sea surface temperature] linear trend over the past 40 years, since 1979, where we have the set of products with a more accurate [sea surface temperature] estimate, you can see everywhere is warming—of course not uniformly,” Yue Dong, a postdoctoral research scientist at Lamont-Doherty Earth Observatory at Columbia University, and one of the primary authors of a recent paper on this topic, said.
She adds that observed trends show a strong cooling trend in the Eastern Pacific and Southern Ocean, which goes against what the models predicted.
Putting it a little less kindly if the calculations to send a rocket to the moon had been as inaccurate as climate change models we’d have never reached the moon. Thousands of everyday industrial processes would be starting massive fires and explosions. Getting the directionality correct on average is not a high standard of accuracy let alone the “pretty accurate” assessment the models are frequently given.
In addition they are far too dependent on how and where measurements are taken. Moving sensors should not affect the predictions but they would. Too many are located near cities which means they’re measuring something else.
And, finally, the strategies proposed are guesstimates if not outright scams. Take carbon offsets, for example. The most recent scholarship suggests they don’t do much. Microsoft (or Google) shutting down its operations might have an impact; using carbon offsets to facilitate their emitting at will not so much.