Rethinking global optimization for climate resilience

AI is now turning decades of "fragmented reports" into a foundation for global resilience. For many climate hazards, the high-fidelity historical data needed to train predictive models simply didn't exist. Today, Google Research is introducing Groundsource to bridge that gap. While we are starting with urban flash floods, the broader opportunity is to create a rigorous scientific baseline for hazards that traditional sensors often miss. By using Google Gemini to synthesise over 25 years of public information in 80 languages, we’ve demonstrated a scalable way to turn unstructured history into actionable intelligence. How this AI-driven methodology scales climate adaptation: 🧩 Solving the Data Gap: It creates a "ground truth" for regions lacking physical infrastructure, ensuring that no community is left behind in the era of AI-driven resilience. 🗺️ A Scalable Blueprint: This framework is a catalyst; while we've mapped 2.6 million flood events, the same methodology can be applied to landslides, heat waves, and other climate-related threats. 🔮 Predictive Power: This research is already powering 24-hour lead times for flash flood alerts on Flood Hub, giving cities a critical head start. By open-sourcing this benchmark, we are inviting the global sustainability community to help turn the records of the past into a more resilient future. https://lnkd.in/eSRvneuE #ClimateResilience #Sustainability #GoogleResearch #FlashFlood #Gemini #Adaptation

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)

Every year, natural disasters hit harder and closer to home. But when city leaders ask, "How will rising heat or wildfire smoke impact my home in 5 years?"—our answers are often vague. Traditional climate models give sweeping predictions, but they fall short at the local level. It's like trying to navigate rush hour using a globe instead of a street map. That’s where generative AI comes in. This year, our team at Google Research built a new genAI method to project climate impacts—taking predictions from the size of a small state to the size of a small city. Our approach provides: - Unprecedented detail – in regional environmental risk assessments at a small fraction of the cost of existing techniques - Higher accuracy – reduced fine-scale errors by over 40% for critical weather variables and reduces error in extreme heat and precipitation projections by over 20% and 10% respectively - Better estimates of complex risks – Demonstrates remarkable skill in capturing complex environmental risks due to regional phenomena, such as wildfire risk from Santa Ana winds, which statistical methods often miss Dynamical-generative downscaling process works in two steps: 1) Physics-based first pass: First, a regional climate model downscales global Earth system data to an intermediate resolution (e.g., 50 km) – much cheaper computationally than going straight to very high resolution. 2) AI adds the fine details: Our AI-based Regional Residual Diffusion-based Downscaling model (“R2D2”) adds realistic, fine-scale details to bring it up to the target high resolution (typically less than 10 km), based on its training on high-resolution weather data. Why does this matter? Governments and utilities need these hyperlocal forecasts to prepare emergency response, invest in infrastructure, and protect vulnerable neighborhoods. And this is just one way AI is turbocharging climate resilience. Our teams at Google are already using AI to forecast floods, detect wildfires in real time, and help the UN respond faster after disasters. The next chapter of climate action means giving every city the tools to see—and shape—their own future. Congratulations Ignacio Lopez Gomez, Tyler Russell MBA, PMP, and teams on this important work! Discover the full details of this breakthrough: https://lnkd.in/g5u_WctW  PNAS Paper: https://lnkd.in/gr7Acz25

🌎 Climate risk isn’t a future scenario — it’s already a financial reality reshaping the built environment. Hamoda Youssef and I recorded this during Greenbuild because we’re seeing the same pattern across portfolios everywhere: climate risks are accelerating faster than owners are able to implement mitigation and adaptation strategies. We fully acknowledge the challenges owners are facing today: 📉 a capital-constrained market, 📊 competing priorities across portfolios, 🏗️ limited bandwidth for project delivery, and 💵 rising costs of debt, insurance, and operations. But the message throughout the Sustainable Finance and Investing Forum was clear: • Insurance markets are repricing risk — premiums are spiking, coverage is shrinking, and many assets are becoming uninsurable. • Transition risk is now a balance-sheet issue — carbon-intensive and inefficient buildings face escalating fines, energy volatility, and valuation pressure. • Delay is the highest-cost strategy — stranded assets, climate-driven capex shocks, and preventable downtime are already eroding returns. • Capital is available for the right projects — from resilience-linked loans and C-PACE to incentives, structured finance, and the new generation of performance-based funding models. And most importantly: 💡 Owners do not need to solve everything at once. Practical steps — from operational optimization and climate risk screening to electrification planning, BPS compliance prep, and resilience upgrades — can be staged, sequenced, and financed over time. 💸 Every $1 invested in adaptation saves up to $10 in avoided losses. The ROI is real, measurable, and happening now. Even in a tight market, inaction is simply too risky — financially, operationally, and competitively. Resilience is no longer optional. It’s risk management. It’s fiduciary duty. And it’s the smart business move. Greenbuild showed that the momentum, tools, and capital are here. Now the industry needs leaders ready to move from intention to implementation. Resiliency now.

The order of decisions is the real Climate Policy. We often talk about sustainability as if it were an added layer or some sort of a checklist, a certification, a department. But cities are shaped long before sustainability enters the conversation. First, we fix traffic flow. Then -  we maximize floor area. Then -  we calculate parking ratios. Then-  we align utilities. And only after that, do we ask: “Where can water infiltrate?” “Where can canopy grow?” “Where can soil remain alive?” By then, unfortunately, the hierarchy is already set. Climate resilience is not determined by how many trees appear on a plan. It is determined by the order in which decisions are made. If mobility geometry is locked before ecological capacity is assessed, green becomes residual. It becomes merely unusable, incidental open space. That cannot be named “infrastructure”. If zoning is finalized before hydrology is mapped, water becomes a problem to pipe away. If underground infrastructure claims the entire section, soil becomes symbolic. The challenge is not only technical. It is procedural and it´s in fact, a planning matter. What if every masterplan began with three maps before anything else was drawn: – soil depth and permeability – surface water flow paths – heat exposure and canopy gaps What if buildable area were calculated after ecological capacity, not before it? We don’t lack solutions. We lack a reordered starting point. Retrofitting the city is necessary. But redesigning the sequence of decisions is transformative. The climate crisis is not only testing our infrastructure. It is testing our priorities and our adaptability.

Business Climate Resilience 🌎 Climate-related disruptions are increasing in frequency and severity, creating material risks for business operations, supply chains, and local communities. Addressing these challenges requires a structured and forward-looking approach to climate resilience. The World Economic Forum presents a framework that outlines ten key actions across three pillars: enhancing resilience, capitalizing on opportunities, and shaping collaborative outcomes. These actions are designed to help organizations avoid economic loss, drive sustainability-linked value, and strengthen systemic responses. Enhancing resilience involves asset-level climate hazard mapping, crisis response planning, and contingency strategies for workforce productivity during extreme weather. Addressing single points of failure and diversifying service delivery and supply chain models is essential to minimize operational disruption. Capturing new opportunities requires understanding long-term consumption shifts, adapting local business models, and directing R&D toward sustainable materials, circular models, and resilient infrastructure. Climate-smart portfolio strategies can position climate adaptation as a source of competitive advantage. Systemic resilience depends on coordinated action across the value chain. Collaboration with public, private, and grassroots stakeholders can unlock shared value frameworks, support regenerative practices, and enable the deployment of early warning systems and nature-based financial mechanisms. To operationalize these priorities, businesses are encouraged to activate key enablers within 24 months. These include integrating climate risk into enterprise risk management, conducting detailed audits of capabilities, and aligning capital investment decisions with resilience objectives. Data intelligence, scientific partnerships, and responsible use of technology—particularly AI—will be critical to improve foresight, enable adaptive planning, and enhance the quality of strategic decision-making in the context of escalating climate volatility. #sustainability #sustainable #business #esg

Flood Resilience, Vienna's 500-Year Perspective. Why we should rethink current approaches and lessons for Resilience Management. Our approach to flood protection is dangerously flawed. Relying on 100-year flood events (HQ100) for planning assumes a predictability that doesn’t exist. We must confront a hard truth: Extreme events are far more unpredictable, and far more devastating, than our models suggest. Vienna's flood protection system, started in 1977, is a case study in long-term resilience. Instead of relying only on recent data, Vienna’s engineers looked back 500 years to the catastrophic 1501 flood. That flood wasn’t just any event—it forced 14,000 cubic meters of water per second through the city, far beyond typical HQ100 projections. Why is this important? During normal times, the Danube Canal, key to Vienna’s defenses, often looks vastly oversized, tempting some to see it as wasted space. There’s always a risk that people will try to repurpose or "optimize" it for other uses. But what seems like overkill during calm periods is what saves the city during a massive flood. Its value only becomes clear when it’s truly tested. In the 1970s, people maybe had a stronger connection to the memory of past disasters. This raises key points: Extreme events are rarer than we think, but more severe: Mega-floods can take centuries to happen, but when they do, they are catastrophic. Are we prepared for such long timescales in our planning? Annual averages mislead: A 1% annual chance of a flood seems small, but over 80 years, it’s a 55% chance. This reveals the true, long-term risk we face. Climate change increases unpredictability: Historical patterns are no longer reliable. With the climate changing rapidly, we’re entering unknown territory regarding flood frequency and severity. Resilience requires ongoing adaptation. Vienna regularly upgrades its system to stay prepared. How many cities can say the same? The cost of preparing may seem high, but very is low compared to being unprepraed when it matters. Vienna’s system has withstood floods that devastated other cities, showing the value of integrating historical knowledge with solid engineering. What looks oversized today may save lives tomorrow. We need to rethink our planning. Instead of preparing for the expected, we must prepare for the extreme events that history, and now climate science, warn us about. It's time to think bigger, plan smarter, and build stronger. Our cities, lives (and companies) depend on it. Video Source (DW News on X) ------------ 1. ♻️ Repost to help 1 person prepare 2. 🔔Follow me Marco Felsberger

Global infrastructure resilience isn’t a distant academic concern; it’s a more tangible pressing call to action. Here are three articles from the last few months that collectively underscore why we must rethink how we design, govern, and stress‑test the systems our societies depend on: The Risks and Challenges of Globally Critical Infrastructure (Risk Analysis) Defines globally critical infrastructure (GCI) as assets so vital worldwide that their disruption cascades across nations. Think the Suez and Panama Canals, undersea cables, GPS, Taiwan’s semiconductor industry, or the Svalbard Seed Vault. The article highlights the sovereignty dilemmas and geopolitical leverage risks when nations depend on infrastructure beyond their borders, and calls for new international governance mechanisms to manage these interdependencies. Link: https://lnkd.in/eEz_sSDE Rethinking Infrastructure Design from Component Failure to Systemic Resilience (Nature Communications) Using the Francis Scott Key Bridge collapse as a case study, the authors show how traditional risk‑based design misses the compounding economic and social impacts of interconnected failures. Their simulations reveal GDP and employment losses lasting decades, illustrating the need to shift toward resilience‑based frameworks that quantify recovery capacity and account for interdependencies across transport, supply chains, and communities. Link: https://lnkd.in/eeN4K8sE Reverse Stress Testing for Supply Chain Resilience (Cornell University) Introduces a methodology that flips conventional stress testing on its head. Instead of predicting threats, it identifies which supply chain changes are most likely to trigger disruptions of varying severity. Applied to U.S. copper wire production, the model shows how different countries emerge as critical risk drivers depending on the scale of disruption, offering decision‑makers a sharper tool for designing adaptive, robust supply chains. Link: https://lnkd.in/e-mhDhWA When viewed together, a new picture emerges that highlights the need to rethink our approach to infrastructure, advocating against seeing it as an isolated asset at different lifecycle phases. It emphasises that the risks linked to infrastructure are global and have cascading effects. Therefore, tackling these challenges requires governance, design, and stress-testing strategies that match the scale of the issues. This shift calls for a systemic, international, and adaptable perspective to improve infrastructure resilience. #Risk #Resilience #Infrastructure