This article is part of the ISC’s Transform21 series, which features resources from our network of scientists and change-makers to help inform the urgent transformations needed to achieve climate and biodiversity goals.
The climate risks facing societies today are increasingly complex, frequent and unpredictable. For the 170 million inhabitants of the Ganges-Brahmaputra-Meghna (GBM) delta, the world’s largest and most populous delta system, regular flooding is already a reality. A combination of hazards including rising sea levels, fluctuating river flows, intense monsoon rainfall, land subsidence and cyclonic storms, as well as social vulnerabilities associated with poverty, mean that the delta is one of areas most vulnerable to climate risks. However, separating out the different impacts of each of those factors and understanding how they relate to each other is a challenge, and subject to a lot of uncertainty. Locals know when the monsoon season will arrive, and when cyclones tend to occur, but it’s very difficult to know exactly when or where extreme climate events will take place, and who or what might be affected.
The latest scientific evidence continues to provide new insights that help to predict and understand such risks, but confronting complex, systemic risks also means getting used to uncertainty.
Many potential future risks, such as how ecological degradation might lead to the emergence of new zoonotic diseases, cannot be predicted. The COVID-19 pandemic has demonstrated how connected risks can cascade across different systems and sectors, such as when health risks lead to school closures that affect education, or to border closures that affect freight of essential goods.
“The new normal is complexity and also uncertainty. That means we cannot measure everything. Of course we have lots to do still to measure and understand better systemic risk, in order to model and forecast certain risks, but we have to embrace the fact that we are not able to model and measure everything”.
Jana Sillmann, University of Hamburg, Germany, and Center for International Climate Research (CICERO), Norway.
This lack of certainty can be a challenge for policy-making, which typically relies on numerical indicators and fixed timelines. Given that different government departments or ministries tend to be responsible for managing the different factors that could be affected by emerging risks – such as health systems, flood defences, electricity or transport networks – dealing with interconnected and cascading risks demands joined-up planning that is equipped to grapple with evidence coming from many different sources, and mainstreaming risk reduction as an integral part of sustainable development.
‘Policy-makers and decision-makers really need systemic risk information in a really concise way, but what they’re used to is a numerical representation of direct risk – heatwaves, flooding etc – but systemic cascading risk can’t be quantified,’ said Daniel Quiqqin, Senior Research Fellow at Chatham House,
Quiggin was the host of a special event at the recent COP26 meeting co-organized by the ISC, Chatham House and Climate Central, in which representatives from UNDRR, Future Earth, Climate Central and the World Climate Research Programme (WCRP) shared information on how innovative methods of presenting information can help to support the kind of engagement between policy-makers and scientists needed to tackle complex, systemic risks.
Ben Strauss, CEO and Chief Scientist of Climate Central, opened the session with a series of powerful images showing how our climate and energy choices over the decade are likely to influence sea level rise affecting city centres and landmarks across the globe.
These shocking visualisations immediately engage the viewer on a personal level, with a tangible idea of what climate risk could entail in a location they already know.
Several speakers emphasised the importance of providing relatable, locally relevant information in a way that can be easily digested. Using a narrative style of presenting results and drawing on lived experiences are some of the ways to go beyond numerical explanations of risk.
“A well-told story can be much more actionable than a complex quantitative analysis. Decision-makers respond to key things relevant to them and their context,” said Tim Benton, Research Director at Chatham House.
We can now use narrative scenarios, or point to historical examples of risks, such as the effects of a typhoon in a certain place, and imagine what might happen if such events took place every five years, or more frequently.
While this kind of radical uncertainty can be frightening for scientists used to quantifying specific risks, said Benton, scientists have a crucial role to play in capacity building on dealing with systemic cascading risks, and on integrating qualitative, value-based knowledge within risk analysis and response.
Photo: Syed Touhid Hassan via Flickr.
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