Why climate averages hide extreme risks

𝗪𝗵𝘆 𝗲𝗰𝗼𝗻𝗼𝗺𝗶𝘀𝘁𝘀 𝘀𝘆𝘀𝘁𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹𝗹𝘆 𝘂𝗻𝗱𝗲𝗿𝗲𝘀𝘁𝗶𝗺𝗮𝘁𝗲 𝗰𝗹𝗶𝗺𝗮𝘁𝗲 𝗿𝗶𝘀𝗸𝘀 A new report (👉https://lnkd.in/eMsCKQuh) exposes a fundamental gap between what climate scientists expect and what economic models predict. 𝗧𝗵𝗲 𝗰𝗼𝗿𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺: 68 climate scientists from 12 countries were surveyed about economic damage estimates. Their insights differ radically from standard models: 🔴 At 3°C warming, experts estimate median GDP damage at ~35%. The Nordhaus DICE model predicts only ~3% 🔴 36% of scientists place the "collapse threshold" 𝘣𝘦𝘭𝘰𝘸 4°C, while many scenarios model up to 4°C and beyond 🔴 250 million people displaced by climate disasters in the past decade, impacts barely visible in GDP figures 𝗪𝗵𝘆 𝘄𝗲 𝗺𝗲𝗮𝘀𝘂𝗿𝗲 𝘄𝗿𝗼𝗻𝗴: We focus on global averages, but people experience 𝘭𝘰𝘤𝘢𝘭 𝘦𝘹𝘵𝘳𝘦𝘮𝘦𝘴: the 2021 Texas storm caused $195 billion damage while barely registering in global temperature statistics. GDP often 𝘳𝘪𝘴𝘦𝘴 after disasters (reconstruction spending) while real wealth declines – the "disaster industrial complex" accounts for 1/3 of US economic activity at 1.4°C warming Models assume smooth damage curves but ignore tipping points, cascades, and system failures 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: This gap determines how pension funds assess risks and how central banks conduct stress tests. The NGFS recently raised damage estimates from 7-14% to 30% GDP loss at 3°C, but climate scientists say even this underestimates. 𝗧𝗵𝗲 𝘂𝗻𝗱𝗲𝗿𝗹𝘆𝗶𝗻𝗴 𝗰𝗮𝘂𝘀𝗲: Research ( 👉 https://lnkd.in/eVsBapbT) shows "disciplinary asymmetries": economists seek optimization within existing systems; natural scientists see limits and tipping points. Where economists use GDP as proxy, scientists see missed impacts on health, ecosystems, and inequality. As a consequence, environmental scientist see degrowth as an option, while economist favour market based solutions 👇 . 𝗪𝗵𝗮𝘁 𝗻𝗼𝘄: The report calls for "recalibration toward precaution, robustness, and transparency": ✓ Report ranges instead of point estimates ✓ Acknowledge where models fail (especially above 2-3°C) ✓ Integrate metrics beyond GDP: mortality, inequality, ecosystem degradation ✓ Model cascades and second-order effects The crucial insight: climate change introduces risks exceeding existing economic frameworks. The response is not waiting for perfect models, but recognizing that avoiding irreversible outcomes is cheaper than pricing them after the fact. For long-term investors: climate risk cannot be fully diversified away. It's a systemic risk requiring fundamentally different strategies. #climaterisk #climateeconomics #systemchange #financialrisk #sustainablefinance

230 million people just learned the hard way that "I hope the forecast is wrong" is not a resilience plan. One winter storm, 2000 miles wide, just pressure tested North America. From northern Mexico, to Atlantic Canada: • record snow from Arkansas to Ontario • "catastrophic" ice across the South • freeze warnings as far as the Gulf Early damage estimates are in the tens of billions of dollars, with some projections cracking $100B On paper, a lot of this was "unlikely". But in reality, it was inevitable. Inevitable because we plan to the average in a world that’s ruled by extremes. We design subdivisions, houses, farms, and infrastructure using 30‑year normals and “100‑year” events… …in a climate that is no longer normal, and where “unprecedented” is getting precedent. We lean on: • 30 year climate "normals" • 100-year storm curves • historical snow loads and frost dates But these distributions are dynamic and shifting, and the tails of those curves are getting bigger. We've historically been optimizing for the middle of the bell curve, and pretend the edges are someone else's problem. Rather than asking: "What's typical here?" We need to be asking: "What's the worst plausible combinations this site could see in its lifetime?" If we want land systems that actually hold under pressure, we have to flip the script. We need to treat extremes as the design teacher and averages as background noise. We no longer have the luxury of designing for "normal". The pattern is already here, in plain sight. "Unprecedented" events are starting to arrive on a schedule. So, do we: keep designing for "normal" and acting surprised every time, or start designing for extremes and finally call it resilience? (screenshot credit: earth . nullschool . net -> link in comments)

The #parisagreement set 2°C as a warming limit to be on the "safe" climate. But as IPCC keep saying: every fraction of degree matters. And this is right... A study using 42 global climate models found that worst-case outcomes at 2°C are often more severe than average projections at 3°C or even 4°C. Drought in breadbasket regions. Flooding in densely populated areas. Wildfire risk across the world's forests. The World Meteorological Organization's State of the Global Climate 2025 report — released just this week — confirms that the past 11 years are the hottest on record, Earth's energy imbalance has hit a 65-year high, and climate extremes are already posing growing risks to food security, health, and economies worldwide. 👉 https://lnkd.in/eEuwv7tV The key insight? We've been planning around the average. Risk management demands we plan around the extremes. This is a call to action for leaders in policy, infrastructure, agriculture, finance, and urban planning: ✅ Risk frameworks need to account for worst-case climate scenarios, not just model averages ✅ Food systems and supply chains need stress-testing against high-impact drought projections ✅ Investment in climate adaptation can't wait for certainty — it needs to price in the tail risks The science is giving us better tools to understand what we're up against. Now it's on decision-makers to use them. 📄 Bevacqua et al. (2026), Nature https://lnkd.in/eGcH8rGS #ClimateRisk #Sustainability #ClimateAction #RiskManagement #Leadership

Important new study in 'Nature' showing that extreme climate impacts are possible even at 2°C of warming. Current risk assessments often focus on “most likely” average outcomes, but this can give a misleading sense of security. Looking beyond averages, the study finds that even at 2°C, plausible outcomes for extreme rainfall in populated areas, drought in key agricultural regions, and wildfire-conducive conditions in forests can exceed the average projections associated with 3–4°C warming. In other words, also at 2°C there is a meaningful probability of extreme outcomes, as climate risk is not linear and not well captured by averages alone. 👉 In many domains, businesses routinely plan against plausible worst-case scenarios. Time to also do exactly that for climate risk...

The world is in the climate storm - yet our radar is faulty This the central finding of a new report from Carbon Tracker and Green Futures Solutions (University of Exeter) We are currently living through a paradigm shift in the speed, scale, and severity of climate risk Yet we're not seeing a corresponding paradigm shift in how those risks are assessed and managed by key institutions around the world, from governments to financial firms A key reason: they depend on economic modelling that is not fit for purpose This has been increasingly pointed out by Carbon Tracker, Exeter, the UK Institute and Faculty of Actuaries, and many others It leads to the extraordinary situation where economic assessments tell us that 4C of global heating will only slightly reduce the growth rate of global GDP, a small reduction on a strong continuing trend line I think this new report adds three really important things to the discourse Firstly, it comes in the context of an ongoing escalation in the threat posed by climate change and wider Earth system destabilisation. There is just more evidence that the modelling is dangerously wrong. As the things missed by the assessments start to kick in - particularly the domino effects of climate shocks - the more costly climate change is proving. In turn, more important institutions are recognising that their assessments are badly biased. Secondly, the report doesn't just point this out, it explores it in more technical depth. To do this, the authors engaged with over 60 leading climate scientists to identify what's wrong with the 'damage functions' that underpin the economic models Key findings: 🔥 Climate damages are defined by extremes, not global averages, which the models focus on. The problem: the most serious heatwaves, floods and droughts can be obscured by mean temperature-based metrics. 🔥GDP can mask damages, giving a false sense of security. Recovery spending, for example, may lift GDP after disasters even as welfare, health, ecosystems and social stability deteriorate. 🔥Uncertainty rises sharply with warming. As tipping points and tail risks grow, assumptions of continuous economic growth – embedded in many models – look increasingly fragile. There are many more Thirdly, the report explores how we might practically develop alternatives. You can read them in the report 👇 It's an excellent piece of work and congrats to authors Jesse F Abrams, Xiaocheng (Sam) Hu, and Ben Dickenson Bampton https://lnkd.in/eFJs3HfX

"𝗘𝘅𝘁𝗿𝗲𝗺𝗲𝘀, 𝗻𝗼𝘁 𝗮𝘃𝗲𝗿𝗮𝗴𝗲𝘀, 𝗱𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲" ⁣ ⁣ 𝐆𝐫𝐞𝐞𝐧 𝐅𝐮𝐭𝐮𝐫𝐞𝐬 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 (University of Exeter) with Carbon Tracker, shows how economic 'damage' models used by governments, central banks and investors are increasingly understating risks as we head toward 2°C.⁣ ⁣ '𝗥𝗲𝗰𝗮𝗹𝗶𝗯𝗿𝗮𝘁𝗶𝗻𝗴 𝗖𝗹𝗶𝗺𝗮𝘁𝗲 𝗥𝗶𝘀𝗸' draws on expert judgement from 𝟲𝟬+ 𝗰𝗹𝗶𝗺𝗮𝘁𝗲 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀 across 𝟭𝟮 𝗰𝗼𝘂𝗻𝘁𝗿𝗶𝗲𝘀 to examine - in detail - the issues in current damage modelling.⁣ ⁣ Authored by Jesse F Abrams Xiaocheng (Sam) Hu and Ben Dickenson Bampton the report also sets out new measures to improve them, and the implications for regulators, investors and scenario providers.⁣ ⁣ A few findings leap out: ⁣ ⁣ 🔥 Climate damages are defined by extremes, not global averages. Heatwaves, floods and droughts drive disruption but can barely register in mean annual temperature metrics.⁣ ⁣ 💷 GDP can mask damages – giving a false sense of security. Recovery spending after disasters, for example, can actually spike GDP figures while welfare, health, ecosystems and social stability deteriorate.⁣ ⁣ 📈 Uncertainty rises sharply with warming. As tipping points and tail risks grow, the assumption of continuous economic growth - embedded in many models - becomes increasingly fragile.⁣ ⁣ The report underscores a clear message: improvements are essential, and closer collaboration between climate scientists and economists can make that happen.⁣ ⁣ But -- policymakers and investors should not wait for perfect models.⁣ ⁣ Under rising uncertainty, it’s critical to shift policy and investment practice towards precaution, robustness, and transparency.⁣ ⁣ For construction and built environment professionals, our action is even more urgent as what, where and how we build today impacts how we all live and prosper tomorrow👷♀️ 🏗️ 🪵 ⚡️ 🌎 ⁣ For politicians, please push for a broadcast National Emergency Briefing - society (voters) need to know the truth. 🔈 🎥 For much more, see the full report: ⁣ 👉 https://lnkd.in/ee7PjvZY #SustainableLeadership SDG 7, 9, 11, 12, 13, 14, 15, 17 (8 alone isn’t working)

Heat Didn’t Break Strategy. Planning for Averages Did.   Last year, I evacuated my home because of wildfire. No amount of climate work over the last 20 years made one iota of difference in that moment. No frameworks. No forecasts. No good intentions. Just heat, wind, smoke — and the realization that planning for “average conditions” had quietly failed. Here’s the idea: No one lives in an average world anymore. And strategy built on averages is breaking — in real time. I felt it first personally. Evacuation orders. Insurance uncertainty. Energy bills climbing. Then I saw the same pattern everywhere else. As CEO and co-founder of HeatWve, I now see this daily — working with leadership teams trying to adapt to a hotter, more volatile economy. Boards planning off smooth curves while the world delivers spikes. Cities managing ten-day heatwaves, not seasonal variation. Companies discovering that resilience isn’t theoretical — it’s operational. Heat doesn’t arrive as a decimal. It arrives as cancelled operations, withdrawn insurance, grid stress, and demand shocks. Yet most strategy still assumes: - average demand - average productivity - average risk That assumption no longer holds. Heat has become the operating condition of the economy — not a background variable. Which is why the old tools are failing. SWOT was built for a calmer planet. Scenario planning assumed the middle of the distribution still mattered. It doesn’t. We need a new instinct — one designed for volatility, not stability. I call it HEAT: - Hotspots — where you’re actually breakable - Economics — how heat reshapes the P&L - Actions — what you do now, not in 2030 - Traction — proof resilience creates value This isn’t climate disclosure. It’s competitive strategy. The hotter world isn’t coming. It’s already here. The only open question is: who’s adapting fast enough to matter? Curious where planning for “average conditions” has already failed for you. Robert Casamento, Eric Olson, John Klinke, HeatWve, Mary Catherine R. Fixel, Grant Ballard, Richard Notarianni, Tripp Borstel, Shaun Fernando,

July marks 30 years since the 1995 Chicago heatwave killed over 700 people, one of the deadliest disasters in the U.S. history. What made it especially tragic was how unequally the city suffered. Poorer neighbourhoods bore the brunt of the deaths, in part because of social isolation, poor housing conditions, and lack of access to cooling. But the story of that heatwave reveals even deeper lessons about risk that too often go ignored. Extreme heat doesn’t just stress people, it stresses systems. During the 1995 crisis, demand for electricity spiked as air conditioners ran around the clock, straining the grid and causing power failures. Public transportation infrastructure buckled, with rails warping in the heat. Social effects compounded the danger: fear of crime led many residents to keep their windows shut at night, turning their homes into ovens. In some neighbourhoods, fire hydrants were smashed open for relief, which lowered water pressure for everyone - just as firefighters and hospitals needed it most. Three decades on, you’d hope these lessons would have transformed how we think about heat risk. Yet there’s evidence they haven’t. 30 June reporting in the Wall Street Journal shows that companies in the U.S. are actually talking about heat stress less in their public disclosures, not more (https://lnkd.in/efUsh2wF). That doesn’t mean the risk has gone away. In fact, with rising global temperatures, the threat is arguably greater than ever. Financial institutions and companies often boast of asset-level assessments in their climate disclosures. That sounds impressively precise: knowing exactly where each building or investment is located should, in theory, allow for detailed climate-risk analysis. But location alone isn’t enough. The resolution of the hazard map itself is crucial. If the map you're using treats an entire city, like Chicago, as a single, uniformly “high-risk” zone for heat, you miss the real danger. You miss the urban heat islands, neighborhood-scale pockets where concrete and lack of trees trap deadly heat. You miss the social and demographic nuances that make some residents vastly more vulnerable than others. High-resolution maps and vulnerability indices do exist. Academic studies and local collaborations have produced neighborhood- and even block-level heat-risk maps for cities like Chicago, revealing exactly where the risks are concentrated. Yet these rarely make it into mainstream financial disclosures or stress tests. That’s the real danger: a false sense of precision that ignores critical detail. By leaning on low-resolution hazard maps, companies and investors may believe they’re prepared, while the real risk is quietly brewing in the data they chose to average away. As the climate warms, we can’t afford that kind of blindness. It’s time to bring the nuance and the hard, systemic lessons of past heatwaves back into focus.

Why There Are No “Average” Places Anymore We like to imagine that most of the country sits in a safe middle—average risk, average threat, nothing to worry about. But the 2025 National Risk Index update tells a different story. If you look closely at the data, you find that “average” counties are almost never average for long. The new NRI rates every U.S. county and census tract across 18 natural hazards—heat wave, wildfire, drought, river and coastal flooding, hurricane, tornado, wind, winter weather, earthquake, landslide, and more. For each hazard, it calculates a national percentile score—so you can see exactly where your county stands for, say, heat or wind compared to every other county in the country. Here’s the part most people miss: even the most ordinary-seeming county—someplace you’d never notice on a disaster map—can quietly be in the 80th percentile (or higher) for at least one major hazard. Maybe it’s extreme heat, maybe strong wind, flood, or drought. The composite score might look “moderate,” but for at least one risk, you’re sitting near the top of the chart. According to FEMA’s National Risk Index technical documentation, counties with moderate composite scores frequently rank above the 80th percentile for at least one major hazard, illustrating that multi-hazard exposure is the norm, not the exception. In practice, almost no county is “average” across the board. If you’re below the median for wildfire, you’re likely above it for heat, or wind, or flood. “Very few communities are below the national median for every risk factor.” Average is a statistical mirage. That means our old disaster playbook—one hazard at a time, in isolation—doesn’t hold up. “Average” isn’t safe, it’s just complicated. The days of betting on geography or past experience are mostly over. This shift isn’t just a data footnote. It changes how we should invest, insure, and plan. Multi-hazard adaptation is no longer a box to check. It’s the baseline. If you only protect against the risk you remember, you’re likely to lose to the one you overlooked. The smart communities—the ones that will draw capital, talent, and lower insurance rates—aren’t waiting for a major event to wake up. They’re looking at their full risk portfolio, finding their hidden outliers, and moving early. The future isn’t about living in a “safe” place. It’s about making your place safer across the board, hazard by hazard, before it makes the news. Source: FEMA National Risk Index, March 2025, Technical Documentation. https://lnkd.in/gj4Sp79S #ClimateRisk #Resilience #NationalRiskIndex #MultiHazard #Infrastructure #Insurance #Adaptation #DisasterPlanning

📊 The false comfort of averages A client once bragged to me about their “average customer satisfaction score.” On paper, it looked solid. In reality, two customers were thrilled, five were indifferent, and one, who happened to account for nearly 50% of their revenue, was furious. Six months later, that client was gone. The average looked fine. The reality was catastrophic. Nobody drowns in an average river depth of three feet. Leaders drown when they forget to look at the extremes. Averages feel safe. They simplify, they summarize, they give the illusion of certainty. But leadership doesn’t happen in the middle; it happens at the edges. Because outliers, not averages, are what actually decide the future. 🪞 The problem with “the middle” Executives love averages: average revenue per client, average employee engagement, average deal size. They look neat in Board decks. But averages hide the extremes: • The one client generating 40% of revenue. • The top 10% of employees creating disproportionate impact. • The tail risks that could sink the company in a week. When you manage to the mean, you miss the moments that matter. 📚 What the research says • Nassim Nicholas Taleb’s work (The Black Swan) shows how outliers, not averages, drive history, markets, and crises. • McKinsey research on performance distribution finds that the top 5% of employees often deliver up to 25% of total organizational output. • Risk studies confirm that companies fail not from the average risk, but from rare but catastrophic events. Translation: averages comfort, but outliers kill or save you. 😅 The reality check It’s like looking at the “average temperature” of your city. Sure, it’s 25°C, until you step outside and it's 42°C in the sun. Nobody packs for the average weather; they pack for the extremes. Yet somehow, leaders still run companies based on averages. 🧪 The leadership test Next time you see an “average” metric, ask: what’s hiding behind this number? Who’s skewing it? What extremes are buried under the mean? Leaders who dig into the edges see reality. Leaders who stop at averages live in fiction. 🚀 The takeaway to remember Averages soothe, but they don’t save. Leadership lives at the tails, the exceptional wins and the catastrophic risks. Don’t manage to the mean. Manage to the edges. #Leadership #Management #DecisionMaking #ExecutivePresence #Strategy #RiskManagement