Seven months ago, Hurricane Melissa made landfall near Black River, Jamaica as a Category 5 storm. It was the strongest hurricane ever to strike the island. Forty-five people died. One and a half million Jamaicans were impacted. Five major hospitals were damaged. The total destruction reached US$8.8 billion, equal to 41 percent of Jamaica's entire GDP. The island's quarterly economic output contracted by up to 13 percent in those final months of 2025. And now, just days from now, the 2026 Atlantic hurricane season opens on June 1.
One week ago, on May 18, 2026, the World Meteorological Organization released a report issuing one of its starkest warnings yet. Faster-than-average sea level rise, intensifying hurricanes, extreme heat, and worsening swings between drought and flooding are accelerating across Latin America and the Caribbean. CARICOM nations already lose an estimated 2 percent of their infrastructure capital stock every single year to climate-related damage. The WMO warned that climate shocks are increasingly disrupting food production, straining healthcare systems, and threatening access to clean water across our region.
I am Adrian Dunkley. I founded the Caribbean's first AI company. I have spent nearly two decades building AI systems, training thousands of Caribbeans in artificial intelligence, and advocating for our region to harness technology as a tool for survival and growth. And I am writing this article today because the Caribbean is about to enter another hurricane season without the AI tools it desperately needs. That must change. Here is how.
Hurricane Melissa: The Warning We Cannot Afford to Ignore
Understanding the Hurricane Melissa disaster in full is essential before talking about solutions. The storm made initial landfall near Black River in southwestern Jamaica on October 28, 2025. The damage assessment by the World Bank and Inter-American Development Bank found physical damage totaling US$8.8 billion. That figure breaks down as follows: 41 percent to residential buildings, 33 percent to infrastructure, 21 percent to non-residential buildings, and 5 percent to agriculture.
But the numbers alone do not capture what happened to real people. Five major hospitals and more than 100 health centers were damaged, severely compromising access to care and essential medications across the island at a time when people needed healthcare most. Hundreds of thousands of Jamaicans lost their homes or had them severely damaged. Agricultural losses disrupted food supply chains for months. Tourism, Jamaica's largest foreign exchange earner, collapsed as hotels sustained severe damage. Jamaica secured US$6.7 billion in international support over three years for recovery, including from the IMF, IDB, and World Bank. The economy is projected to contract 4.5 percent in fiscal year 2025/26 before recovering to 3.3 percent growth in 2027/28.
Climate scientists at World Weather Attribution confirmed that climate change enhanced the intensity of Hurricane Melissa beyond what it would have been in a pre-industrial climate. This is not an anomaly. This is the new normal for the Caribbean unless we act.
Colorado State University is forecasting a below-average 2026 hurricane season with 13 named storms and 6 hurricanes. Yet that same forecast puts the probability of a major hurricane making landfall in the Caribbean at 35 percent. Below-average is not the same as safe. Hurricane Melissa was the most destructive storm in Jamaican history in a year that was not considered an exceptionally active season. One storm is all it takes.
The Good News: AI Already Helped With Melissa
Before I explain what needs to happen next, it is important to recognize what AI already demonstrated during the 2025 hurricane season. According to the National Hurricane Center's review of that season, Google DeepMind's GDMI suite of AI models, introduced in June 2025, provided very valuable guidance early on for Hurricane Melissa's likely track and intensity, even though the storm was described as very difficult to forecast. AI models provided forecasters with useful signal days before traditional numerical weather models locked in on the storm's path.
Separately, the University of Miami developed and deployed a new AI tool in 2025 that is the first automated system capable of distinguishing and tracking tropical easterly waves in the Caribbean and Atlantic basin. Tropical easterly waves are the atmospheric disturbances that seed many Caribbean hurricanes. No automated method for tracking these systems had previously existed. The University of Miami AI tool is now in use at the National Hurricane Center.
These are not small achievements. AI is already making Caribbean hurricane forecasting better. The question is why these capabilities are not yet fully integrated into Caribbean national meteorological services, disaster management agencies, and community early warning systems. The technology works. The deployment is lagging behind.
AI for Early Warning: Giving Caribbean People More Time
The most important application of AI for Caribbean hurricane protection is early warning. Every additional hour of advance warning translates directly into lives saved and property protected. People who have more time to evacuate survive storms that kill those who had no warning. Communities that can board windows, move livestock to high ground, and transport valuables to safety before a storm suffers far less loss than those caught unprepared.
Current early warning in most Caribbean islands relies on meteorological service bulletins distributed through radio, television, and social media. This approach depends on residents actively monitoring news channels and understanding what forecast categories mean for their specific location. It is broad, slow, and imprecise.
An AI-powered early warning system would work completely differently. It would integrate real-time weather model output, river level sensors, coastal surge predictions, and rainfall data into a machine learning platform capable of generating location-specific, personalized alerts delivered via SMS, WhatsApp, and automated phone calls directly to residents in identified high-risk zones. A farmer in St. Elizabeth would receive a message telling her that flood water is expected to reach her property within 18 hours and that the closest shelter is 4.3 kilometers east. A business owner in Portmore would receive an alert that storm surge is projected to reach 2.4 meters at his location and that he has 12 hours to secure his ground floor assets.
This kind of targeted, actionable early warning is not futuristic. It is deployable today with existing AI and telecommunications technology. Several Caribbean governments already have the WhatsApp and SMS infrastructure from COVID-19 communication campaigns. The missing piece is the AI backend that turns weather model data into precise, location-specific, plain-language alerts for every household in the region.
AI Hurricane Forecasting: Seeing Storms Before They Kill
Global AI weather forecasting has transformed over the past two years. Google DeepMind's GDMI models, Huawei's Pangu-Weather, and NVIDIA's FourCastNet can all produce 10-day global weather forecasts in seconds that match or exceed the accuracy of traditional numerical models that take hours to run on supercomputers. These models process satellite data, ocean surface temperature measurements, atmospheric pressure fields, and wind shear data to generate probabilistic forecasts of hurricane track and intensity with lead times previously impossible.
For the Caribbean, this is a major advance. Instead of the three to five day cone of uncertainty that currently governs emergency response decisions, AI models can provide useful hurricane track guidance at seven to ten days. That additional time window changes what is possible for preparedness. Seven days of warning is enough to safely evacuate coastal communities, pre-position emergency supplies at strategic locations across an island, coordinate regional response resources, and implement building protections that take more than a weekend to complete.
But there is a critical challenge specific to our region. Global AI weather models are trained primarily on data from the Northern Hemisphere, where weather observation networks are far denser. The Caribbean is underrepresented in global training datasets, meaning these models are less accurate for our basin than they are for the United States or Europe. Building a Caribbean-tuned AI weather layer, trained specifically on Caribbean observational data and validated against Caribbean storm behavior, would significantly improve forecast accuracy for our islands. This is regional AI infrastructure that CARICOM should be funding jointly today.
AI Damage Prediction: Positioning Resources Before the Storm
Knowing that a major hurricane will hit is only part of the battle. Knowing where it will cause the most damage, and positioning resources there before impact, is what separates a competent disaster response from a chaotic one. AI makes predictive damage assessment possible.
Machine learning models can combine incoming storm forecasts with detailed building inventory data, infrastructure vulnerability assessments, topographic flood modeling, and historical damage records from past storms to generate parish-by-parish, community-by-community predictions of where damage will be worst. For Jamaica, a model trained on Hurricane Ivan in 2004, Hurricane Dean in 2007, Hurricane Beryl in 2024, and Hurricane Melissa in 2025 would have substantial Caribbean-specific training data to work from.
The practical application is this: 72 hours before a major hurricane, an AI damage prediction system gives ODPEM and the Jamaica Defence Force a ranked list of the communities most likely to need search and rescue, the roads most likely to be blocked, the communities most at risk of becoming isolated, and the health facilities most likely to lose power and water. Emergency commanders can pre-position personnel, vehicles, and supplies based on AI-predicted need rather than waiting for damage reports to come in after the storm passes. The difference between pre-positioned and reactive disaster response, in lives saved and suffering reduced, is enormous.
AI Disaster Response: Logistics That Save Lives
After a hurricane strikes, the logistics of distributing water, food, medical supplies, tarpaulins, and generators across a damaged island with blocked roads, downed bridges, and overwhelmed responders is genuinely one of the hardest operational challenges any government faces. It has been done with spreadsheets and phone calls for decades. AI makes it dramatically better.
AI logistics optimization systems already power global supply chains for companies like Amazon and DHL. These same algorithms, adapted for disaster response conditions, can continuously calculate the optimal allocation of limited relief supplies across dozens of affected communities, updating routing recommendations in real time as new damage information arrives, roads reopen, or supply inventories change. A system that can tell an ODPEM coordinator: "Based on current damage reports and available supplies, send truck convoy three to Content in Clarendon before St. Elizabeth because the bridge at Gutters will be passable for the next six hours" saves time, saves fuel, and saves lives.
AI-powered damage assessment using satellite imagery and drone footage completes this picture. Machine learning models trained to identify damaged rooftops, flooded areas, blocked roads, and destroyed buildings can process imagery of an entire island within hours of a storm's passage, generating a comprehensive damage map that tells responders exactly where to go first. This capability, which took weeks of manual assessment after Hurricane Melissa, can now be compressed into hours with the right AI systems in place.
AI for Agricultural Recovery: Feeding Our Islands Faster
Agriculture took 5 percent of the direct damage in Hurricane Melissa but a far larger share of the economic disruption. Crop losses ripple through Caribbean economies for months after a storm. Farmers lose income. Markets lose supply. Food prices rise. Rural communities that depend on farming as their primary livelihood face compounding hardship long after the physical cleanup is complete.
AI can accelerate agricultural recovery in ways that were not possible before. Drone-based AI assessment can map crop damage across an entire farming district within 24 hours of a storm, allowing insurance adjusters to process claims in days rather than the months it currently takes. AI soil analysis and weather modeling can give farmers precise replanting recommendations based on post-storm soil conditions and projected rainfall patterns for the recovery period. Agricultural supply chain AI can reconnect disrupted food networks by identifying alternative supply sources and distribution routes more quickly than human coordinators can.
Looking further ahead, AI climate modeling can give Caribbean farmers the information they need to adapt to permanently shifting weather patterns. Which crops will remain viable in eastern Jamaica as rainfall patterns change over the next 20 years? Which farming regions in Trinidad face the greatest risk of drought intensification? AI can answer these questions with specificity that global climate models cannot, and those answers should be informing Caribbean agricultural policy and farmer training programs right now.
A CARICOM AI Hurricane Shield: The Regional Case
Individual Caribbean nations cannot build world-class AI disaster management systems alone. The costs are too high relative to the size of our economies. But CARICOM as a collective can. A shared regional AI hurricane preparedness platform, built jointly by and for all CARICOM member states, would distribute costs across the region while creating a system more powerful than any single island could afford.
This platform would include: a Caribbean-tuned AI hurricane forecasting model fed by weather stations, ocean buoys, and radar systems across the entire basin; a regional early warning alert system capable of delivering targeted messages to residents in any CARICOM territory; shared damage assessment AI that activates for any member state immediately after a storm; and a regional supply network optimization system that coordinates relief resources across national boundaries when any island is struck.
Caribbean Airlines could integrate AI flight optimization during hurricane evacuations. CARICOM's Caribbean Catastrophe Risk Insurance Facility could use AI damage assessment to accelerate insurance payouts to affected governments. The Caribbean Development Bank could fund the platform development with donor support from multilateral partners who already invest in Caribbean disaster resilience.
The technical foundation exists. The regional institutional framework exists through CARICOM. What is needed is political will and the recognition that AI is not optional technology for the Caribbean. It is survival infrastructure.
What Caribbean Leaders Must Do Before June 1
The 2026 hurricane season begins in days. Not everything can be built before June 1. But these actions can begin immediately.
First: Contact meteorological services at Google DeepMind and the University of Miami today to begin licensing and integrating their AI hurricane tools into national forecasting operations. The tools exist. They are available. The integration conversation should start this week.
Second: Activate AI-powered SMS and WhatsApp alert infrastructure for high-risk coastal and river-adjacent communities before June 1. If the communications infrastructure from COVID-19 campaigns exists, it can be repurposed for hurricane alerts with minimal lead time.
Third: Commission AI flood mapping for national coastlines and major river basins. Companies with the technical capability to build this exist in the region. Give them the contract. Give them the data. Have a working system before the peak of the season in August and September.
Fourth: Task CARICOM's Caribbean Disaster Emergency Management Agency with developing a proposal for a joint regional AI disaster platform, with a target for funding and implementation within 18 months.
The cost of acting is real but manageable. The cost of not acting was demonstrated in October 2025 when US$8.8 billion and 45 lives were lost to a storm that AI tools were already beginning to forecast better than anything that came before.
Frequently Asked Questions
How can AI help the Caribbean prepare for the 2026 hurricane season?
AI can help the Caribbean prepare for the 2026 hurricane season in several critical ways: improving hurricane track and intensity forecasts up to 10 days in advance using models like Google DeepMind's GDMI, generating real-time flood risk maps for vulnerable coastal and inland communities, optimizing pre-positioning of emergency supplies across islands, providing automated early warnings via SMS and WhatsApp to residents in high-risk areas, and predicting which infrastructure is most vulnerable to incoming storm surge and wind damage. All of these capabilities exist today. Deployment is the only gap.
How much damage did Hurricane Melissa cause in Jamaica?
Hurricane Melissa made landfall as a Category 5 storm near Black River, Jamaica on October 28, 2025, causing US$8.8 billion in physical damage, equivalent to 41 percent of Jamaica's 2024 GDP. The storm killed at least 45 people, displaced 1.5 million, damaged five major hospitals and over 100 health centers, and caused quarterly GDP to contract between 8 and 13 percent in Q4 2025. Total damage and losses reached US$12.2 billion. It is the costliest hurricane in Jamaica's recorded history.
What did the WMO report say about Caribbean climate in 2026?
The World Meteorological Organization released a major report on May 18, 2026 warning that faster-than-average sea level rise, intensifying hurricanes, extreme heat, and worsening drought and flooding cycles are escalating across Latin America and the Caribbean. CARICOM countries already lose an estimated 2 percent of their infrastructure capital stock each year to climate-related damage. The report warns that climate shocks are increasingly disrupting food production, straining healthcare systems, and threatening access to clean water across the region.
What is the 2026 Caribbean hurricane season forecast?
The 2026 Atlantic hurricane season officially begins June 1, 2026. NOAA has forecast a below-average season with 8 to 14 named storms, 3 to 6 hurricanes, and 1 to 3 major hurricanes. Colorado State University forecasts 13 named storms and 6 hurricanes. Despite the below-average forecast, Colorado State estimates a 35 percent chance that the Caribbean will see a major hurricane landfall. Below-average is not the same as safe. Hurricane Melissa struck in a year that was not considered an exceptionally active season.
Did AI models help forecast Hurricane Melissa?
Yes. According to the National Hurricane Center's review of the 2025 Atlantic hurricane season, AI models including Google DeepMind's GDMI suite provided very valuable guidance early on for Hurricane Melissa's likely track and intensity, even though the storm was described as very difficult to forecast. The AI models outperformed or matched traditional numerical weather prediction for key forecast parameters. This early guidance gave Jamaica additional preparation time. The lesson: more AI, deployed faster, directly saves Caribbean lives.
What AI tools exist for hurricane forecasting in the Caribbean?
Several AI tools are now available for hurricane forecasting. Google DeepMind's GDMI suite, introduced in June 2025, is used operationally by the National Hurricane Center. The University of Miami deployed a new AI tool in 2025 that is the first automated system to track tropical easterly waves in the Caribbean basin. NVIDIA's FourCastNet provides high-resolution global weather forecasts. Huawei's Pangu-Weather offers strong track and intensity guidance. The critical next step is adapting and integrating these tools into Caribbean national meteorological services with Caribbean-specific training data.
How can AI speed up disaster recovery in the Caribbean?
AI can dramatically accelerate post-hurricane recovery through automated damage assessment using satellite and drone imagery, mapping destruction across an entire island within hours. AI logistics optimization routes relief supplies through damaged road networks more efficiently than manual coordination. Infrastructure triage AI identifies which repairs restore the most services fastest. Case management AI helps displaced families access government assistance programs more quickly. Disease surveillance AI can identify communities at risk of outbreak before it spreads, allowing preventive medical deployment.
What would a CARICOM AI disaster network look like?
A CARICOM AI disaster network would be a shared regional platform integrating weather data, sensor feeds, satellite imagery, and historical storm records from across all member states. It would power a common hurricane forecasting system tuned for Caribbean conditions, automated early warning alerts in multiple languages including Caribbean creoles, cross-border resource optimization for sharing emergency supplies, and joint damage assessment capabilities that activate immediately after landfall. Sharing costs across the region makes a world-class AI disaster system affordable for even the smallest islands.
How can AI help Caribbean farmers recover from hurricane damage?
AI can support Caribbean agricultural recovery through rapid crop damage assessment using drone and satellite imagery, helping farmers document losses for insurance claims within days. AI can optimize replanting decisions by analyzing soil conditions, projected weather patterns, and market demand to recommend the most resilient crops for each farmer. Supply chain AI can reconnect disrupted agricultural markets by matching available produce with buyers. Long-term, AI climate models help Caribbean farmers adapt by identifying which crops will thrive under future conditions as weather patterns shift.
What should Caribbean governments do right now to use AI for hurricane protection?
Caribbean governments should take four immediate actions. First, integrate AI weather models from Google DeepMind and the University of Miami into national meteorological services today. Second, commission national AI flood mapping for coastlines and river basins before June 1. Third, deploy AI-powered SMS and WhatsApp early warning systems that reach every resident in high-risk zones with targeted, actionable alerts. Fourth, begin negotiations through CARICOM for a shared regional AI disaster management platform to distribute costs and dramatically increase capabilities across all member states.