Why Climate Models Are Becoming Critical Economic Infrastructure
France has once again faced major fires in the Gironde, despite the extensive prevention measures introduced after the catastrophic events of 2022. Spain has seen fires threaten the outskirts of Madrid. Across the Mediterranean - and even beyond, from the Maghreb to Canada's province of Ontario - wildfire activity has highlighted a common reality: physical climate hazards are becoming more widespread, more volatile and more difficult to anticipate.
The most important lesson, however, is not about wildfire. It is about information.
Climate change is fundamentally increasing uncertainty. It is changing where hazards occur, when they emerge, how they interact and how costly they become. As a result, one of the defining economic challenges of the coming decades will be the ability to translate increasingly complex physical phenomena into meaningful financial information.
This is why a new generation of climate models is rapidly becoming strategic infrastructure - not only for governments and emergency services, but also for investors, insurers, banks and businesses.
For decades, modern economies have relied on sophisticated models to understand inflation, productivity, interest rates and economic growth. Tomorrow's economy will increasingly depend on another class of models: those capable of explaining how changes in the physical environment affect economic activity. That transformation is already underway.
Weather forecasts have never been more accurate. Yet weather is not risk.
Knowing that temperatures will reach 40°C tomorrow says remarkably little about the resulting economic consequences. Whether that heatwave disrupts industrial production, damages infrastructure, reduces labour productivity or has almost no measurable impact depends on many additional variables: local geography, infrastructure quality, adaptation measures, vegetation, exposure and vulnerability.
The same applies to wildfire.
Two neighbouring municipalities exposed to identical meteorological conditions may experience completely different fire behaviour because of differences in topography, fuel conditions, land management or emergency response capacity. Likewise, the same flood or drought can generate radically different economic losses depending on what is exposed and how resilient those assets are.
Moving from weather to risk therefore requires combining several layers of scientific information.
Climate projections describe how meteorological conditions evolve under different warming pathways. Physical models explain how hazards develop. Satellite observations continuously monitor vegetation, land cover and soil moisture. Exposure databases identify the location of infrastructure, businesses and populations. Damage functions estimate how physical hazards translate into economic losses.
Only when these elements are combined does weather become economically meaningful.
The scientific frontier is therefore no longer weather forecasting itself. It is the ability to model how changing physical conditions reshape economic systems.
This represents a profound shift in the way economies function.
Macroeconomic models became indispensable because they helped governments and investors understand how economic systems evolve. Climate models are beginning to play a similar role for the physical systems on which those economies depend.
The questions they seek to answer are increasingly economic rather than meteorological.
How does a succession of wet winters followed by drought alter wildfire behaviour six months later? Which transport corridors remain operational under repeated flooding? Which industrial facilities become vulnerable under chronic heat stress? Which regions remain attractive for investment as climatic conditions evolve?
These are no longer scientific curiosities. They are investment questions.
Understanding them is becoming essential for infrastructure planning, insurance pricing, corporate strategy and financial regulation.
Physical climate models are therefore evolving into a new form of analytical infrastructure, capable of translating changes in the natural environment into economically relevant information.
Financial markets often identify strategic infrastructure before policymakers do.
Over the past decade, billions of dollars have flowed into companies specialising in Earth observation, satellite constellations, weather intelligence and geospatial analytics. Firms such as Planet Labs, Tomorrow.io, Spire Global and ICEYE are building increasingly sophisticated capabilities to observe the physical planet in real time.
Their rapid growth reflects a broader economic transformation.
Agriculture depends on anticipating water availability. Electricity systems require increasingly accurate forecasts of heat stress and renewable energy production. Logistics operators need to understand flood exposure. Insurers require ever more granular catastrophe models. Financial institutions increasingly seek to distinguish resilient assets from vulnerable ones before losses materialise.
Weather intelligence is becoming economic intelligence.
The value of these technologies lies not simply in predicting atmospheric conditions more accurately, but in helping organisations understand the consequences of those conditions for economic activity.
Financial economics has traditionally treated physical climate risks as distant, difficult to quantify and largely diversifiable. That assumption is becoming increasingly difficult to sustain.
Research suggests that equity markets continue to price physical climate risks only imperfectly, despite growing evidence that these risks are becoming increasingly material for long-term cash flows and corporate valuations.
Recent disasters illustrate why.
The Los Angeles wildfires demonstrated how physical hazards can rapidly evolve into systemic financial events. Beyond insured losses, they affected municipal finances, utilities, housing markets and regional economic activity. Physical damages propagated through interconnected economic systems, extending far beyond the fire perimeter itself.
Academic research increasingly points in the same direction. Bilal and Känzig argue that the macroeconomic costs of climate change may materialise substantially earlier - and prove significantly larger - than conventional estimates suggest. A recent analysis by the EDHEC Climate Institute reaches a complementary conclusion: regardless of the precise magnitude of global damages, understanding how those damages are distributed across regions, sectors and assets is likely to become just as important as estimating their aggregate size.
For investors, the implication is clear. Climate change is no longer simply an environmental issue. It is becoming a source of financial differentiation.
Traditional macroeconomic analysis often begins with countries. Climate risk increasingly begins with places.
Two factories producing identical products may face very different futures because one sits in an area exposed to recurrent flooding while the other does not. Two property portfolios may diverge in value because one is located in regions where adaptation remains effective while the other is increasingly exposed to wildfire. Two electricity networks may experience very different operating costs under the same national climate scenario.
National averages conceal precisely the information financial markets increasingly require.
Capital allocation is becoming progressively more dependent on understanding climate risks at the geographical scale where investment decisions actually occur: individual assets, industrial sites, transport corridors, municipalities and regions.
One illustration of this approach is EDHEC-CLIRMAP (Climate-Induced Regional Macroimpacts Projector), which combines climate projections, spatial econometrics and high-resolution geographical information to estimate how physical climate risks reshape regional economic activity under different warming scenarios. Rather than asking how climate change affects a country on average, the objective is to understand how local physical changes alter local economic performance.
Climate change will inevitably create both vulnerable and comparatively resilient regions. Identifying them may become one of the defining challenges of twenty-first century finance.
As physical climate risks become increasingly material, the debate is shifting from whether economies should adapt to how adaptation capital should be allocated. Wildfires illustrate why.
Fuel management, strategic vegetation clearance, firebreaks or revised building standards can all reduce losses, but their effectiveness varies considerably across locations. An intervention that substantially lowers wildfire risk in one region may deliver only marginal benefits elsewhere, depending on topography, vegetation, climate conditions, asset exposure and the evolution of future hazards.
Adaptation therefore cannot rely on generic best practices. It requires robust scientific frameworks capable of evaluating competing strategies, quantifying their effectiveness under different climate scenarios and comparing their economic returns in terms of avoided losses. By integrating climate projections, fire propagation models, satellite observations and damage functions, the next generation of physical climate models makes it possible not only to identify where risks are greatest, but also where adaptation capital is likely to generate the highest return.
For investors, insurers and public authorities alike, the challenge is no longer simply to spend more on resilience. It is to build decision frameworks that allocate scarce capital to the adaptation measures that preserve the greatest long-term economic value.
Europe's 2026 wildfire season may ultimately be remembered for more than the number of hectares burned. It marks another step in a much deeper transformation.
For most of modern financial history, weather was treated as background noise. Climate change is turning it into one of the defining determinants of economic value.
The challenge facing financial markets is therefore no longer simply to acknowledge physical climate risks. It is to understand them with sufficient precision to inform investment decisions at the level where capital is actually allocated.
That requires a new generation of scientific tools.
The future of finance will increasingly depend on models capable of explaining not only markets, but the physical world on which markets depend.
Europe's wildfires are not simply revealing a changing climate. They are revealing the emergence of a new economic infrastructure - one in which the ability to translate physics into finance may become as important as the ability to translate macroeconomics into markets.
Camille Angué,
Director, EDHEC Climate Institute