From forecasting to real-time alerting to post-disaster response, here’s how we work with the UN, governments and international organizations on global crisis resilience.
Hazard prediction and preparation
Timely nucasts and forecasts enable governments, humanitarian organizations and communities to intervene before disasters strike. During the 2025 hurricane season, the US National Hurricane Center used Google’s WeatherNext model. It predicted Hurricane Melissa’s historic landfall in Jamaica five days in advance, allowing the Met Service in Jamaica to notify the public. In Nigeria’s Adamawa state, UN OCHA launched a flood prevention action program using Google’s river flood forecasts. When forecasts indicate a high risk of significant flooding, it activates a set of early interventions, such as shelter preparation. The NGO GiveDirectly used a similar approach in Nigeria’s Kogi state, using Google forecasts to deliver cash transfers before floods. This allowed families to evacuate safely and purchase equipment such as sandbags to protect their property.
Our forecasts are available on the Flood Hub, covering 2 billion people in more than 150 countries, in areas at risk of significant flooding. We are continuously improving forecasting capabilities together with our partners. The World Meteorological Organization (WMO) and national hydrological agencies in the Czech Republic, Nigeria, Uruguay and Vietnam launched a pilot with Google to evaluate how local data affects AI forecasts in regional river basins. We found that incorporating local streamflow data into global AI models significantly improves forecasts in unmanageable areas. The results of the study, which will be published in the coming weeks, highlight the value of combining global AI models with localized expertise, providing a blueprint for how AI can better support national forecasting efforts.
To further advance research, we recently open-sourced our Groundsource urban stormwater dataset and our hydrology modeling framework, helping experts build new approaches while maintaining full control over their own local data. We tested the hydrology framework with the Czech Hydrometeorological Institute (CHMI), which developed an adapter that enables them and other hydrological services worldwide to use the model in their standard workflows.
For wildfires, we utilize satellite images to track fire boundaries in Search and Maps, with coverage in 34 countries. In collaboration with the Earth Fire Alliance and Muon Space, we developed the purpose-built FireSat constellation, which aims to provide an unprecedented wildfire data set and help fire authorities detect wildfires faster before they spread, anywhere on Earth. Earlier today, three new FireSat satellites were launched from Vandenberg Space Force Base in California.
Provides life-saving alarms in times of crisis
In times of crisis, access to reliable, authoritative information is essential for those affected. In 2025 alone, Google helped connect people with crisis information more than 10 million times a day on average.
Among the alerts we distribute are Public Alerts – displaying content from alerting authorities through Common Alerting Protocol (CAP) feeds. These public alerts include data from authorities in over 90 countries so far, from partners such as the US National Weather Service, the UK’s Met Office and Brazil’s Centro Nacional de Gerenciamento de Riscos e Desastres (CENAD). We encourage more nations to publish CAP warning feeds.
When authorities issue these notifications, they can appear across Search, Maps and as Android notifications. This ensures that public safety information, such as severe weather warnings and flood updates, and the practical information people need to stay safe, reach people quickly and directly.
Although warning people about earthquakes remains a critical challenge, we have made progress in warning those outside the epicenter. When devastating earthquakes struck Venezuela last month, Google’s Android Earthquake alert system, which leveraged a network of Android phones as mini-seismometers, alerted millions of users outside the epicenter, allowing them to take cover seconds before the shaking began.
Using satellite imagery to accelerate disaster response
After a disaster, the core challenge is to get life-saving help to the people who need it as quickly as possible. AI-powered insights can help governments and organizations respond more effectively.
Data Insights for Social and Humanitarian Action (DISHA) developed in collaboration with Google a damage assessment workflow, implemented in collaboration with the UN Satellite Center (UNOSAT). It uses open buildings and building damage assessment models to analyze satellite imagery, and was recently enhanced with a new interface that marks a new phase of operational impact. To date, it has been deployed 11 times, supporting the response to disasters such as earthquakes, floods and cyclones. It enables high-precision analysis of hundreds of thousands of buildings in very short time frames, saving UNOSAT specialists weeks of work per activation.
When Hurricane Melissa devastated Jamaica in October 2025, this AI-based analysis assigned preliminary damage scores to over 385,000 buildings to inform recovery efforts. More recently, following the February 2026 floods in Colombia, UNOSAT rapidly assessed damaged infrastructure by cross-referencing AI-derived building maps with radar images of the flood. The analysis informed the response planning of UN humanitarian agencies and the national government.