Researchers investigated a method to predict drought in South Korea using a combination of models. They found that the initial model had trouble predicting temperature and rainfall accurately, but the downscaled model improved these predictions. By using this downscaled model, they were able to make reasonably accurate forecasts of drought conditions six months in advance for the winter to spring period. This could help policymakers and stakeholders in water management plan for extreme weather events and adapt to climate change more effectively.