AI aims to become farmers’ weather forecaster

of public policy at the University of Chicago, wrote about the implementation of AI in agrometeorology in an article for Reuters Connect. For farmers, every planting decision carries risks, which are increasing due to climate change. One of the most serious consequences is weather, which can negatively affect crop yields and livelihoods. For example, a delayed monsoon can force a rice farmer in South Asia to replant or switch crops entirely, resulting in lost time and income. Access to reliable and timely weather forecasts helps farmers plan sowing, determine the best time for fertilization, and increase yields while reducing costs. However, in many low- and middle-income countries, accurate forecasts remain inaccessible due to the high costs of technology and the infrastructure demands of traditional forecasting models. A new wave of AI-based weather models promises to change that. These models can provide accurate, localized forecasts while requiring only a fraction of the ...