Grainswest - Fall 2026

Fall 2026 Grains West 28 types such as rain, snow and hail, said Separovic. It also more accurately predicts high-impact weather events such as thunderstorms, although researchers continue to improve these capabilities. “It’s not perfect, but it’s improving the predictability of our weather,” he added. Meaningful improvements to physics- based forecasting systems generally require years of development to improve the model itself and to better incorporate new weather observations. According to Separovic, the accuracy gains delivered by the development process of the hybrid system in less than two years is equivalent to a full decade of research and development with the previous system. To train the ECCC’s hybrid model, researchers used a historical reanalysis dataset compiled by the European Centre for Medium-Range Weather Forecasts (ECMWF) and ECCC forecast data collected between 2019 and 2023. “Because weather patterns evolve, and climate itself continues changing, the AI won’t simply learn once and stop,” said Separovic. “The model will need periodic retraining using newer Canadian data to maintain its performance.” Although training AI requires substantial computing resources, the financial cost of the hybrid system is not significantly greater than the old system, said Separovic. The Canadian government is not alone in exploration of AI for weather prediction. Corporations such as Google and Nvidia, as well as public weather services such as ECMWF have spent years developing AI forecasting systems that partially informed Canada’s approach. Many national weather agencies are experimenting with hybrid approaches, said Separovic, but Canada is the first to operate a hybrid system. “Integrating AI into forecasting is a huge step and a significant improvement for forecasting here in Canada,” he said. “We’re extremely proud of this achievement.” GREATER PREDICTABILITY The hybrid model has delivered its greatest improvements in five- to seven- day forecasts, said Separovic. “The new system extends the useful predictability of the weather forecast by roughly one day compared to conventional physics- based forecasting alone,” he said. Forecasters can more confidently rely on the new hybrid system to identify severe weather patterns sooner. For farmers deciding when to spray, seed or harvest ahead of heavy rain or strong winds, an extra day could influence logistics and profitability. Forecast accuracy in the 24- to 48-hour range, however, has changed little. Conventional forecasting performs well over short periods, noted Separovic. “But there is room for improvement with the hybrid approach.” Researchers now focus on the development of AI models that will improve these near-term forecasts. While farmers may not immediately notice dramatic differences in the forecasts they receive, meteorologists almost certainly will. Classen said he hasn’t used the hybrid model in his daily forecasting yet. He does expect it will become a valuable tool that will improve accuracy and predictability and deliver earlier warning for major weather events. “It’s our job as meteorologists to read and interpret the information we receive from various models,” said Classen. To produce a forecast requires comparison of multiple weather models as well as experience and local knowledge. “That’s why every forecast is different.” The hybrid system doesn’t disrupt weather prediction but is a natural evolution, said Classen. “This new system is 100 per cent a good thing. When you blend the two models, you get environmental science with speed.” He expects AI will deliver timely FEATURE “Because weather patterns evolve, and climate itself continues changing, the AI won’t simply learn once and stop. The model will need periodic retraining using newer Canadian data to maintain its performance.” —Leo Separovic