We’ve been discussing the RCP 8.5 issue in climate modeling, this week and earlier, which reminded me of this story. A few years ago, I attended a reunion (my class’s 40th) at the Yale School of Forestry (cl and Environmental Studies (now School of the Environment). Jerry Melillo, of Woods Hole, gave a talk about climate modelling.
Jerry showed a slide of “protected areas,” and of course, having worked on the Colorado Roadless Rule for years, I could see from the map that I might not agree with the boundaries. At least not in terms of physically meaningful differences for input into climate models. Imagine how hard it would be to take the non-Wilderness parts of your neighboring forest and make assumptions about what they would or would not contribute to climate change in the next fifty years or more? My question to Jerry was “forest management is a sliding scale, from planting trees after fires and leaving them alone thereafter, to intensive forest management as practiced in the southeastern US with loblolly pine. It’s a dial not a toggle, so how do models of future land use reflect that?” His answer was that IUCN had made the determination of what was protected, and he was using their numbers. Of course, determining something is a toggle when it is a dial is a value judgment, not a scientific finding. And folks might choose toggle due to computational convenience, not proximity to validity.
Roger Pielke, Jr. and Justin Ritchie wrote a comprehensive historical account of the development and use of RCP’s, including definitions of the relevant jargon. From a history of science/sociology of science perspective. It has been the best guide I’ve found to try to understand “is our work (land-use) an input, output or both?” There are even flowcharts! Roger and Justin have a few suggestions (these are only some):
*Despite the presence of thousands of IAM scenarios in the community, and the motivation to proceed with ‘one model one vote’ dynamics where all models are assessed equally with no explicit probability statements, more regular attention needs to be given to a much simplified set of near-term, policy relevant scenarios, similar to how IEA issues three scenarios on an annual basis: a Current Policies Scenario (high), a Stated Policies Scenario (baseline) and a Sustainable Development (policy) scenario.
(I see this as fewer but more realistic options, done more frequently to reflect changes and course-correct assumptions, some of the same preferences we would have for any planning effort.)
*More work is needed to reconcile long-term narrative pathways based on an idealized year 2100 end-point with what policy makers need to know about the next few years and decades. While there are an increasing number of scenarios focused on the role of Paris Agreement NDCs through 2030, there is a significant gap in the literature for scenarios that address developments before 2050 in the context of today’s policy environment. This gap is created by an excessive focus on long-run, full century scenarios, driven in large part by the needs of the physical science modeling community.
There seems to be a need for policy folks to say “nope, that solution isn’t working for us, how about trying …?” Not sure that there is the direct connection among groups for this discussion to take place. Remember the idea of “co-designed, co-produced research” with stakeholders and policy makers?
* Climate research and assessment would benefit from a more ecumenical and expansive view on relevant knowledge. The IPCC scenario process has been led by a small group of academics for more than a decade, and decisions made by this small community have profoundly shaped the scientific literature and correspondingly, how the media and policy communities interpret the issue of climate change. The dominant role of this small community might be challenged in order to legitimize a broader perspective of views, approaches and methods.
It would be handy IMHO if that were to be a role of (at least some of) the new climate $ in the President’s budget proposal. I can imagine a multi-stakeholder group at the regional level asking questions like “what do we want from climate models to help us plan mitigation and adaptation strategies?”. How can we use our local and regional knowledge as input into the process? What have scientists learned that can be helpful to us, and what else do we need to know?
As it turns out there is quite a bit of literature on co-design and co-production of climate science. You can go into Google Scholar and search on “climate science co-production.” That’s how I found the Alison et al. paper that yielded the Table 2 above.