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How Climate Insights Helped a Roofing Materials Retailer Come Out on Top After Hurricane Ian

Himanshu Gupta • October 25th, 2022.

Comparison between ClimateAi's predictions and other forecasting tools

After Hurricane Ian, one of the most destructive storms in U.S. history, pummeled West Florida in late September, communities are now looking to recover and rebuild. The Category 4 storm tied for the fifth-strongest hurricane that made landfall in the United States, causing potentially billions of dollars of damage throughout the Southeast and leaving a tragic death toll in the triple digits.

What’s left in the wake of a hurricane like Ian is anything but a “calm after the storm:” Homeowners and business owners face difficulties finding building materials and labor amid the mass destruction, and often, power remains out for days, if not weeks. Rebuilding can take anywhere from months to years. Sadly, in some locations, where climate change has led to sea level rise and an elevated risk of more severe and frequent hurricanes in the future, it doesn’t even make sense to rebuild at all.

Climate change means that hurricanes are warmer, wetter, and windier, enabling them to cause greater damage when they make landfall. While hurricane forecasting is key to disaster preparedness, historically, technology has fallen short in predicting the regions most likely to be hit and just how badly these storms will impact them — preventing decision-makers from making the best-informed plans in advance. Existing hurricane tools tell us for example, to expect increased hurricane activity for the upcoming hurricane season, but not necessarily where they will hit and what the damage might be — failing to provide the level of specificity, granularity, or accuracy needed to take action.

Without this information, corporate and community leaders are left in the dark (often literally) about the potential risks from a hurricane season, from infrastructure damage to hunger and thirst to injury and death.

A better solution exists: At the start of September, ClimateAi issued a forecast for a large building materials company, assessing the impacts of the upcoming hurricane season on the demand for building materials to inform better supply planning. Fast forward a few weeks — and Hurricane Ian became active and quickly made landfall. 

ClimateAi had successfully predicted a substantially elevated risk of hurricane impacts in Florida, well before Ian became active (see the image below — ClimateAi predicted ~30-50% higher risk than normal in Florida). Because we had translated this hurricane risk into probabilistic insights that were meaningful for the company (i.e. estimated damage and subsequent demand for roofing products), the company was able to adjust its tactical decisions and get ready for the increased chances of a landfalling hurricane in or around Florida.

In preparation, it gathered the relevant resources at its nearby facilities to ramp up the production of its Florida-specific roofing shingles once the hurricane was en route. Once the hurricane became active and was tracking toward Florida, they were able to take swift action to meet the increased demand whereas many other companies were left flat-footed. As their VP of supply chain put it, “ClimateAi’s forecasts allowed us to react faster.”

Our ability to simulate and probabilistically forecast the impacts of hurricanes over the coming season enables a new paradigm in disaster response efforts, as people seek to rebuild homes and livelihoods after a hurricane, and companies and governments seek to meet that need.

The image on the left shows a 60-80% chance of destructive winds (strong enough to damage roofs) in Florida. This is 30-50% higher risk than normal (as depicted in the image on the right). 

Artificial intelligence and machine learning have unlocked this new paradigm in actionable forecasts that enable unprecedented risk management and preparation. Using these technologies, ClimateAi forecasts the impacts of hurricanes and hurricane season at large in specific regions. For the first time, this hurricane tool, which integrates vast amounts of data on environmental conditions leading up to the season with proprietary algorithms, is able to generate reliable forecasts of overall hurricane activity in an oceanic basin (for example, the North Atlantic), as well as the risk of specific hurricane impacts (for example, extreme and destructive winds) in specific regions.

While uncertainty still exists — no forecast is a crystal ball — leading companies are already using these unique probability-based forecasts to make tactical decisions on subsequent demand for certain goods/resources in specific regions (e.g. building materials). 

For example, if a big regional building material player had been expecting a normal year when a destructive hurricane threatened, it won’t be able to capitalize on the increased demand from homes needing to be rebuilt in time — and even more critically, people won’t have a roof over their heads. Better forecasting allows companies to not only hedge around stocking inventory, but also to manufacture the right building materials based on the forecasted region of impact. Different U.S. states have region-specific building code criteria (many Florida buildings are required to use unique types of shingles, for example). If the forecast were to show that Florida was in for a bad hurricane season, the company could produce and allocate more materials needed for Floridian roofs to its plants in close proximity to the state. Then, based on the certainty of the storm’s forecasted point and size of impact, manufacturing these specific roofing materials could commence ahead of time. This foresight and preparedness make all the difference in disaster-recovery time.

Building materials is only one application for this tool. Home improvement retailers, for example, are also looking to this tool for predicting region-specific demand for generators, while manufacturers are using it to better understand supply chain disruptions during hurricane season.  

Hurricanes are consistently some of the costliest and most deadly natural disasters: Of the 310 billion-dollar weather disasters between 1980 and 2021, they averaged about $20.5 billion per event, and also caused the highest number of deaths (6,697 between 1980 and 2021). As climate change threatens to increase their intensity and frequency in the coming years, accurate and actionable hurricane forecasting is the key to mitigating this risk, recovering faster, and ultimately saving both lives and livelihoods. Climate intelligence will only become more valuable as weather becomes more unpredictable into the future. Decision-makers that take advantage of quickly advancing technology and climate adaptation insights can create a safer, more resilient environment when disaster strikes. 

If you are looking to build hurricane resilience in your business and for the people/communities you serve, please don’t hesitate to reach out.

 

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