2021 could be the year that adaptation tops the agenda at COP. Not that the task of getting to Net Zero is done and dusted – far from it – but after a year of wildfires, heat waves and floods, the imperative to adapt to our changing climate is finally being treated with the urgency it merits. Until recently, the focus (rightly) has been on mitigating climate change through cutting emissions, but with atmospheric concentrations of CO2 now higher than in the past 2 million years (IPCC, 2021), we must also adapt to the changes in weather and climate that are already underway, and which will continue even if we succeed in meeting the most ambitious carbon targets.
With each additional layer [of models], our grip on reality becomes a little more tenuous
The Task Force on Climate-related Financial Disclosures (TCFD) is bringing the adaptation imperative to the forefront in the private sector. Moreover, companies and financial institutions are beginning to recognise that the risks and opportunities relating to physical changes in the climate system are material and require action, not just disclosure.
We now need a level of ambition on adaptation comparable to that on mitigation, with organisations pledging to improve resilience to physical climate risks in their own organisations as well as in their communities and the wider economy on which they depend.
In moving from high-level adaptation targets to concrete action, one very quickly trips over the thorny issue of data. To understand and ultimately manage physical climate risks, we must be able to measure and price them. Hence the boom we are seeing in the market for physical climate risk analytics, with scarcely a week passing by without a new product or service being announced. The goal of this growing market is to provide data on the physical and financial impacts of climate change on firms, and on the financial institutions that lend, invest and insure companies and people. For most sectors (insurance being the exception) analytics focus on long-term scenario analysis using climate model projections.
But there is a difference between data and models. As Gavin Schmidt, chief scientist at the NASA Goddard Institute of Space Studies, put it in his TED Talk “observations of the future are not available at this time.”
The tools available to examine these longer timescales are built by layering up models – models of future climate change, models of hydrological and other environmental systems that mediate the climate’s impacts on the planet and models that attempt to fill the huge data gaps relating to the impacts of the climate on society, the macroeconomy and the people and businesses within it. The data available to test and calibrate these models, especially those relating to societal impacts, are scant, and the complex ‘black box’ nature of the resulting tools can make them impenetrable to decision-makers. With each additional layer, our grip on reality becomes a little more tenuous, and the possibility increases of further embedding climate risks through maladaptive strategies built on inaccurate information.
How do we ensure that our approach to physical climate risks minimises the potential of maladaptation and maximises our ability to capitalise on climate-related opportunities? One approach is to root our assessment of climate risks in the present day – that is, in actual observations.
To focus exclusively on projected trends is to miss the bulk of the problem
This is not to diminish the importance of scenario analysis for future planning. A forward-looking perspective is clearly essential in a changing climate in which the future will differ from the past. As decision-making tools, however, climate model projections are useless unless they build on an understanding of how climate affects you right now. Put simply, how can you interpret a potential change in climate unless you know how climate impacts your organisation now? None of this should be news – the recommendations of the TCFD include assessing actual not just potential risks – but it is not yet standard practice.
Turning our attention to observations exposes the huge gaps in data that exist across the full system of climate and its impacts, from upstream meteorological observations, particularly in the Global South, to downstream data that can be analysed to determine how, and at what thresholds, exposure to climate and weather affects organisations. Filling these gaps will require deep engagement from organisations to determine how weather and climate have affected them to date, a commitment to measuring these impacts going forwards, as well as novel methods to determine impacts using participatory processes and tertiary data sources. Those who embrace this challenge will be best placed to survive (and thrive) on the road ahead.
Another major incentive for looking at historical and present-day data is that, in most of the world, climate variability (i.e. across seasons, from year-to-year and on multi-decadal cycles) is much more significant than climate change trends and will remain so for the next few decades, especially in relation to precipitation. Thus, the impacts of climate on these time horizons will come from weather and climate variability, with a smaller contribution from underlying trends due to climate change. To focus exclusively on projected trends is to miss the bulk of the problem. Given that the most common timeframe for scenario analysis was 10-30 years among the financial firms consulted in GARP’s 2021 climate risk management survey, it is clear that we cannot afford to ignore climate variability.
Mark Carney’s ‘Tragedy on the Horizon’ is real, but by training our eyes on the horizon alone, we miss the terrain
Even in the longer term, when climate change trends will be more prominent, climate variability remains a critical consideration in adaptation planning. No-one experiences the average climate; we experience the weather, the seasons and the large-scale, longer-term swings in prevailing conditions from year to year and over decades. Managing this variability is the route to dealing with most aspects of the physical risks associated with climate change, while ignoring it and optimising long-term strategies around projected trends will only enhance vulnerability. For example, climate scenarios project an increase in precipitation in East Africa, but the extreme droughts of recent decades are entirely consistent with those scenarios. Mark Carney’s ‘Tragedy on the Horizon’ is real, but by training our eyes on the horizon alone, we miss the terrain, as well as many of the opportunities available to build resilience by managing climate variability along the way.
The goal of climate risk analytics should not be to give the (false) impression of certainty, but to support decision-makers to explore the robustness of various adaptation strategies through more transparent tools that make clear the strengths and limitations of available data and models.
The new generation of analytics must embrace this complexity, integrating analyses of climate variability and change and drawing on the full breadth of information and evidence, including observed data and scientific understanding as well as modelled future scenarios.
