AI can help to predict, manage the impacts of climate

Earlier this month, Argentina's Esperanza research station on the Antarctic Peninsula recorded an unprecedented temperature of 15.4 C, more than 20 degrees above the seasonal norm and the highest June reading ever observed at the station. The anomaly, which has contributed to unusual ice melt and raised concerns about polar ecosystems, serves as a stark reminder that climate change is no longer a distant threat but an accelerating reality reshaping economies, ecosystems and societies worldwide.

According to the World Meteorological Organization, there is an 86 percent likelihood that between 2026 and 2030, at least one year will surpass 2024 as the hottest year on record, underscoring the accelerating pace of global warming.

Scientists also project a 91 percent likelihood that average global temperatures will exceed 1.5 C above pre-industrial levels during at least one of the next five years, increasing the likelihood of more frequent heat waves, floods, droughts and wildfires.

Yet amid these alarming projections lies an opportunity. The next five years could mark a turning point in humanity's response to climate change if governments, businesses and communities fully harness the power of artificial intelligence and green technologies. The challenge before us is not simply to understand climate risks, but to predict, manage and reduce them more effectively than ever before.

Every day, satellites, weather stations and sensors generate enormous volumes of information about the Earth's atmosphere, oceans and land systems. But turning that data into actionable intelligence is difficult, and this is where AI becomes indispensable.

AI is already revolutionizing weather and climate forecasting, allowing communities to prepare for severe storms and flooding days earlier than previously possible. Google's FloodHub is one such tool that uses AI models and satellite data to provide flood forecasts up to seven days in advance.

AI is also helping farmers receive highly localized forecasts to guide planting decisions and water use. In Kenya, for example, smallholder farmers are using AI-powered early warning systems to predict crop yields and monitor agricultural conditions. AI-driven remote sensing techniques are also being applied in the Amazon region, as well as in countries such as Vietnam, Madagascar and Mexico, to improve the detection of forest cover changes and inform where urgent interventions are required.

However, forecasting alone will not solve the climate crisis. The ultimate objective must be to reduce emissions while building resilience, which requires radical systemic and structural changes across all key complex systems, including cities, transportation, industry and energy. Redesigning and transforming such systems and running them effectively and efficiently can be greatly facilitated by AI.

In the energy sector, for example, AI can enhance the stability and efficiency of renewable energy integration into power grids. The intermittency of solar and wind energy presents a significant challenge, as fluctuating supply must be balanced with real-time demand. AI can optimize grid management by forecasting supply and demand more accurately and by managing distributed energy resources, such as electric vehicles and energy storage systems.

China offers one of the clearest examples of how AI can accelerate climate action at scale. As China is the world's largest producer of renewable energy, its grid operators are deploying AI-powered smart grid technologies that analyze massive volumes of real-time data from power plants, weather systems, transmission networks and electricity consumers. Machine-learning algorithms can forecast electricity demand, predict renewable energy output and optimize the dispatch of power across regions.

AI can also improve power grid reliability by rapidly identifying maintenance needs. In Barbados, Mauritius and Seychelles, AI already plays a role in managing microgrids that distribute energy efficiently across local networks. Embedding AI in these systems enables these countries to optimize energy flows, reducing the need for fossil fuel-based energy.

Beyond optimizing grids, AI can help urban planners map patterns of urbanization and identify energy and infrastructure needs for local communities. For example, the Open Building Insights Tool, which Sustainable Energy for All developed in collaboration with IBM, helps energy planners overcome critical data gaps to inform energy access and energy transition interventions and better deliver results for those most in need. This publicly available AI-powered solution is already providing valuable insights to decision-makers and policymakers in India and Kenya.

The question over the next five years is whether governments, businesses and societies can scale these innovations quickly enough to stay ahead of rising climate risks.

If we succeed, AI and green technologies may prove to be among humanity's most powerful allies in the fight against climate change.

The author is CEO and special representative of the UN Secretary-General for Sustainable Energy for All, and co-chair of UN-Energy. The views do not necessarily reflect those of China Daily.