We’re in a global #polycrisis, and the world’s volatility, uncertainty, complexity and ambiguity (#VUCA) can’t be fully captured in IAMs. 2/11
Enormously impressive strides are being made in IAM development - and btw I’m talking about detailed process IAMs here (e.g. MESSAGE, REMIND etc), rather than benefit-cost IAMs (DICE, FUND etc). 3/11
But, using three examples over different timescales, the paper argues it’s not going to be easy, or quick, to incorporate all of the nuances of possible societal, political, technological, economic and environmental developments in IAMs. 4/11
They’re currently too structurally rigid to capture all of the details of these changes. Meanwhile, we need to develop a large range of new low-carbon pathways quickly, to explore how to mitigate climate change in various future scenarios (including extreme scenarios). 5/11
The paper recommends three actions: 1. First and foremost, funders need to make sure there’s money going towards social and political scientists and others exploring low-carbon pathways outside of the IAM frameworks. 6/11
2. Secondly, non-IAM pathways need to be quantified, reporting key variables to allow them to sit alongside IAM-developed pathways in IPCC and other scenario databases. This will of course need funding, and perhaps relevant tools (like accounting and spreadsheet models). 7/11
3. Thirdly, IPCC reports should (continue to) emphasise illustrative scenarios rather than the full “splurge” of IPCC database pathway ranges, to give a coherent sense of the possibilities whilst not “drowning out” interesting non-IAM scenarios with the full IAM range. 8/11
To be clear, as an integrated assessment modeller of 10+ years, I see the importance of these “internally self-consistent” IAM frameworks and support their further use and development.
GPTchat agrees. 9/11
But I also feel we need to remind ourselves when it’s time to “escape from model land” (thank you @H4wkmoth) and think outside the IAM box. IAMs are a powerful hammer, but not every question around climate change and sustainability is a nail. 10/11
A thread on forecasting low-carbon technology costs, to accompany this paper with @michaelgrubb9, @DrRobertGross, Richard Green, Phil Heptonstall and Charlie Wilson. Doing this well is important if we’re going to get a handle on the net benefits of climate change mitigation. 1/10
There are – broadly speaking – three ways in which future technology costs tend to be estimated:
1.Extrapolate past trends (learning curves)
2.Ask experts (in elicitations)
3.Forecast how the costs of key parts of the technology will change (engineering assessments)
2/10
We also have a number of different technology innovation frameworks to help us contextualise how low-carbon technologies develop, reduce in cost and penetrate into energy systems.
3/10