New research links global climate patterns to wildfires in Los Angeles

As wildfires continue to ravage regions from Los Angeles to South Korea, a new study featured on the cover of the Issue 7, 2025 of Advances in Atmospheric Sciences sheds light on the large-scale climate patterns influencing these devastating global extreme events. The research, led by Professor Young-Min Yang from Jeonbuk National University, reveals how tropical climate phenomena like the Madden-Julian Oscillation (MJO) can trigger dry, windy conditions that exacerbate wildfires in mid-latitude regions, including the western U.S. and East Asia.

Wildfire prediction remains a major challenge due to rapidly changing weather conditions and complex environmental factors. The study highlights the MJO—a large-scale tropical weather pattern—as a key driver of atmospheric waves that can lead to fire-favorable conditions thousands of miles away.

"Our findings show that strong MJO activity in the eastern Indian Ocean can trigger atmospheric teleconnections, leading to dry and windy weather in wildfire-prone areas like Los Angeles within days to a week," said Professor Yang. "This provides a crucial prediction window that could improve wildfire forecasting and risk management."

The research also suggests that the Arctic Oscillation (AO) may contribute by bringing colder, drier air to regions like North America, further increasing fire risk. These insights could help explain why recent wildfires in Los Angeles have been severe even in years with less extreme drought conditions.

The study’s release follows South Korea’s worst-ever wildfire outbreak, which has now been contained after killing 28 people and razing vast swaths of land. As the lead author’s home country recovers from this disaster, the research underscores how large-scale climate patterns like the MJO may contribute to extreme fire weather in the region.

To enhance wildfire prediction, the research team plans to integrate additional climate signals—such as warming in the tropical Indian Ocean and Siberia—into advanced AI-based weather models. These tools could extend forecast accuracy to several weeks, aiding preparedness efforts.

"Our ultimate goal is to develop more reliable wildfire prediction models by incorporating MJO and AO influences," said Professor Yang. "With better forecasting, communities can implement earlier mitigation strategies, reducing the damage from these disasters."

The study underscores the growing need to consider global climate dynamics in regional wildfire management, particularly as climate change intensifies weather extremes.

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