By Neil Palmer
Accurately predicting tomorrow’s weather is notoriously difficult. So what are we to make of climate change studies that make predictions for 50 years’ time?
According to three new reports from the Consultative Group on International Agricultural Research’s Climate Change, Agriculture and Food Security (CCAFS) research program, the models commonly used for predicting future climates were pretty wide of the mark when they were tested to see if they correctly anticipated some well-documented changes in climate up to now.
But that’s no reason to sign-up for membership of the Heartland Foundation just yet, for two main reasons.
Firstly, different climate models enjoy some synergy when their results are combined. Sometimes up to 20 models are used to check and balance each other, before any predictions are made. The International Center for Tropical Agriculture’s (CIAT’s) climate scientists do this as a matter of course.
And as new data emerges, combined with quantum leaps in computer processing power, there’s time to develop and refine what could be called “supermodels”, to showcase future climate trends more accurately. Most climate scientists I know would jump at the chance of spending time with a supermodel.
UNCERTAINTY IS CERTAIN
But perhaps more fundamental is this: no matter how precisely we try to quantify future climate change and its effects on agriculture, there will always be a margin for error. But this shouldn’t stop us planning for uncertainty itself.
That’s because for doomsdayers, naysayers and all their acolytes, uncertainty is the unifying principle of all climate research.
Only by recognising the certainty of uncertainty – the inevitability of change itself – and letting that drive the research agenda, will we give ourselves the greatest possible chance of boosting food production, and the resilience of the billions of people inextricably linked to it. That means us, by the way. All of us.
It means making sure we have every weapon in our armory: it means planning for drought, planning for flooding, planning for pests and diseases that were not previously thought to be a threat. It means improving on-farm practices, conserving water, protecting soils, introducing concepts of eco-efficiency at all levels of food production, processing and distribution. It means building adaptive capacity, and developing the largest possible portfolio of responses, together with the willingness and ability to put them into practice.
It also means finding ways of sharing this knowledge and these technologies globally, for whoever needs them.
Professor Mark New, of the University of Cape Town, put it very well during a web-streamed discussion on the findings of the CCAFS report on climate models. “We have to think about sub-optimal information, and therefore actually make decisions based on a spread of possibilities.”
In true Cub Scout spirit, it simply means being prepared.
If this in turn means focusing more attention and resources on climate change research, than the search for, say, the elusive Higgs boson, as Oxford University’s Richard Washington suggested, then so be it.
Climate models have never masqueraded as infallible crystal balls and CIAT’s own studies – which have rightly raised the alarm about potential threats to tea, chocolate and cassava production, amongst others – have always acknowledged the margin for error. But this uncertainty does not mean they are without useful application. Quite the opposite: They are prudent reminders of the pressing need to hedge our bets.
We should therefore be grateful to climate models and modelers for preparing us for what could happen, just as we’re grateful to weather forecasters doing their best to prepare us for the possibility of tomorrow’s thundery showers.
Surely the most unhelpful response is inaction due to uncertainty, which would deny the role of constant change in shaping the entirety of human history.
That, at least, is certain.
Neil Palmer is a communications officer at the International Center for Tropical Agriculture (CIAT), in Colombia. This blog first appeared on the CIAT website.