Keeping the lights on during Hurricane Ian: reflections from a climate-tech founder

Hurricane Ian represents a new normal under climate change for companies. Here’s how AI can help build supply chain resilience.

ClimateAi
4 min readOct 7, 2022

When my wife, my dog, and I moved back to Tampa early in the pandemic to be closer to family, a major hurricane had not hit the city in more than a century. As I write this, however, Hurricane Ian has just narrowly avoided Tampa Bay, making landfall 80 miles south of my new home: The category 4 storm with 150-mph winds tied records as the fifth-strongest hurricane on record to hit the contiguous U.S., and 2.5 million fellow Floridians were under evacuation orders. Hurricane Ian had threatened such massive damage and losses that Bloomberg has called it potentially “the costliest storm” in US history, and experts are expecting shortages of food, fuel, and potentially drinkable water.

As the CTO of ClimateAi, a climate adaptation technology company, I’ve been remotely running my team from a cafe an hour drive north, where the electricity stayed on after ours shut off for days. I experienced firsthand how climate analytics can help those affected like me prepare better for disasters like this, and help us rebuild better after disasters.

At ClimateAi, we provide AI-enhanced weather forecasting translated into demand planning for companies in agriculture, building materials, energy, and more. We help companies get ready for crisis situations like these — especially as climate change accelerates and means they are more frequent and severe. Climate change means that hurricanes are warmer, wetter, and windier, enabling them to cause greater damage when they make landfall.

We help companies get ready for crisis situations like these — especially as climate change accelerates and means they are more frequent and severe.

Forecasting the exact timing and impact of hurricanes more than two to three days out is scientifically challenging to do. However, understanding seasonal hurricane risks to supply chains based on forecasts has been made feasible by AI. AI-enhanced risk forecasts that show seasonal hurricane intensity and probability broken down by key regions provide actionable outlooks for companies to help plan inventory and logistics more effectively. For example, a company that sells or manufactures generators can stock them or produce them closest to the most at-risk locations earlier in the season, so that my neighbors and I can prepare ahead of time. A utility company could make choices to weatherproof the most at-risk infrastructure or hire more employees for crews in areas that will likely be affected.

Translating the impact of hurricanes to demand forecasts is critical to effectively orchestrating upstream activities for companies. In particular, corporates can derisk key supply chain decisions ahead of time around production to meet anticipated increased demand and hold the right inventory at key locations to ship to hurricane-affected areas quickly and cost-effectively. That way, people affected can keep the lights on, get dinner on the table, and rebuild their houses. While uncertainty still exists — no forecast is a crystal ball — leading companies are already using these probability-based forecasts to make active decisions on subsequent demand for certain goods/resources in specific regions.

Corporates can derisk key supply chain decisions ahead of time around production to meet anticipated increased demand and hold the right inventory at key locations to ship to hurricane-affected areas quickly and cost-effectively.

For the short-term, companies and manufacturers that understand seasonal risks can place more inventory in places that will be affected, so they can be quicker to react and go to market to help customers with disaster preparedness. In the long-term, knowing which regions will be hit more frequently and severely will be key for expansion plans — companies can be proactive in siting new manufacturing plants or distribution centers. Local resilience centers are key for enabling agility and resilience for supply chains, especially under climate change. Risk estimates then tell customers how to move inventory around to help those affected maintain food and water access, as well as rebuild and recover.

To keep the lights on and get dinner on table, the private sector has more of a role to play than most realize — but by being able to get the necessary supplies in the right places before the start of hurricane season, both communities and companies can win.

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Max Evans is the CTO and Co-Founder of ClimateAi. From a lineage of Ecuadorian pineapple farmers, he graduated with a BA in Applied Mathematics at Harvard University and pursued a joint MBA and MS of Stanford University where his focus was on machine learning applications to climate science. He co-founded ClimateAi from his Stanford dorm room in 2017. ClimateAi is a first-of-its-kind climate-based decision tool that leverages cutting-edge AI to deliver actionable insights to help mitigate climate risk and identify opportunities for supply chains, 1 day — 40 years out. This technology is bringing foundational change to predictive analytics and is creating a new class of decision-focused climate resilience tools. With a team of over 40 people around the world, it has raised $16 million to date.

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ClimateAi

Accelerating climate resilience in food, water, and energy www.climate.ai