Triggered

This post was triggered by the thought of a cold shower.

I react to triggers. I guess we all do. I saw a vlog about someone with Trichotillomania who was negatively triggered by the new Doctor Who (whereas Doctor Who should, of course, trigger lots of positive reactions)!

Not long after this I was in the Bristol climate change protest march and wondered “What triggers these people to get off their behinds and actually take action?” Even more bizarre was the recent London naked bike ride – which I happened to encounter while strolling through Trafalgar square – this was a protest against car culture and oil dependency. What triggers someone enough that they would strip off their clothes and ride naked through London (or perhaps in this case it was motivated by mere exhibitionism)?

I applied this idea to the emerging changes in climate research, and the new regional and international institutional developments that are steering research agendas. Substantial new challenges are being posed to the business-as-usual model for climate research. Climate scientists are increasingly being placed under pressure to engage in new territory – territory they’re not well equipped to enter.  Research outputs are rapidly adopted in real world decision making (prematurely so?); the normative silo’d approach to disciplinary science is being stretched with expectations that climate scientists are able to communicate and defend their results across a wide range of user communities.  Accompanying this are a diversity of new international initiatives including the Global Framework on Climate Services, Future Earth, PROVIA, Africa Climate Policy Center, Climate Services Partnership, and many more. And finally, paralleling this is the acceleration of consultancy services and boundary organizations with commercial overtones who are seeking to bridge the science society interface. Partner all this with the fact that the ability to collect and analyze massive amounts of data is transforming science, industry and everyday life.

These developments are changing the enabling environment of climate science, with new and evolving debates such as the ethics of climate information, accountability, and climate scientist accreditation.  In parallel is the articulation of new grand challenges on the fundamental physical climate science and the complex issues of analysis of interpretation — the latter so badly lagging our fixation on producing ever increasing quantities of numbers from our models.

All this comes back to one thing: Risk.  Firstly, risk is now the new driver of climate science, it’s a “policy first rather than science first” approach, and “my risk must inform how you conduct your research!” This stands in stark contrast to the traditional paradigm of producing papers in the vague hope that the trickle down effect will change something in society, while saying “their problem is not my problem”.

We’ve long been serving “average” information to “average” users which is then typically over-interpreted!

Secondly, this brings new risks for the research community: for example, possible backlash over poorly communicated and erroneous model output, decision maker confusion about contradictions in the science, and rapidly changing terms of reference from funding agencies.

Africa climate science is well positioned to engage in this changing landscape – we’re closer to the decision makers than most in the western world – but we need to pro-actively recognize the changing dimensions of the agenda drivers in order to effectively contribute, and also to appropriately develop the next generation of scientists.

Take an example: let’s consider the seasonal forecasting domain where we already expend great effort on generating pretty maps with ambiguous (to others and ourselves) probabilities and associated uncertainties, measured with integrative but misleading metrics such as ROC scores.

Now consider a decision maker – it doesn’t matter what sector – take maize, take disaster management, any sector with climate sensitivities. In any given context there is a ratio of information about the evolving climate stressors versus the risks being faced.  The decision maker responds subjectively, triggered by some threshold of this information:risk ratio.

For example, if we have no robust climate information about projected changes on relevant decision-scales, but we are faced with very high risks, then an action will likely be implemented because the consequence of no action is too threatening. Conversely, say we have lots of relevant and highly robust climate information on the forthcoming season, but our risk factors are low, then action will still likely be taken because the strong information allows one to optimize the outcomes.  In each case the risk:information ratio meets a threshold of decision.

But what when we have moderate risk levels?  Then there is some threshold of confidence in the information that is required before it will trigger an action. There is a “trigger threshold”, and if the information does not reach this threshold of relevance and robustness, no action may be triggered – leading potentially to a paralysis of indecisiveness.

Do our the seasonal forecasts contain enough relevant information to trigger a value response when set against the risk factors?

Critically, how do we measure this?

There is a urgent need to measure the information content against the decision trigger thresholds in the context of all the non-climate externalities that govern decision. How do we assess the climate information trigger points to, in turn, inform our formulation of research output, and how to do this in a way that is transferable across sectors.

Until we wrestle with this issue our seasonal forecasting (or any other societally relevant climate research) will forever remain a case of “well I hope someone finds this useful”.

Let me finish by mentioning one other trigger: what will it take to catalyze the climate community to apply their minds to finding ways of examining our research priorities and outputs in the light of the decision makers risk:information thresholds?  Perhaps a series of cold showers?