Sub-seasonal forecasts, which predict weather conditions from ten days to two months ahead, are emerging as a powerful tool in the fight against climate-related risks.

The forecast are able to strike a balance between short-term precision and long-term planning, creating a “sweet spot” for actionable, science-based decision-making.

While traditional weather forecasts focus on the next few days, and seasonal outlooks stretch over several months, sub-seasonal predictions offer a timely middle ground – and one that could be transformative for both governments and industries, if communicated effectively according to a team form the Institute of Atmospheric Physics, Chinese Academy of Sciences.

The review presents how scientists can bridge the gap between complex forecast data and real-world decisions to turn raw climate intelligence into lifesaving, economy-boosting action.

“Sub-seasonal forecasting better balances accuracy and timeliness. It provides sufficiently detailed predictive information while allowing ample time for early warnings and effective decision-making,” said Jing Yang, first author of the study and a professor at Beijing Normal University in Beijing, China.

He added the advantages are clear: businesses can optimize operations and reduce losses, while governments can better prepare for climate disasters, safeguarding lives and infrastructure. Yet despite its game-changing potential, sub-seasonal data often remains underutilized. Both the private and public sector may hesitate to make potentially costly decisions based on complex and uncertain forecasts.

“The core challenge is transforming professional meteorological forecast data into tailored, actionable decision-making information for different industries,” said Mengqian Lu, corresponding author of the study and a professor at the Hong Kong University of Science and Technology in Hong Kong. “Establishing a standardised and transferrable ‘supply-demand interaction framework’ for climate services is vital, and it must be scalable across industries, avoid redundancy, and bring science directly into decision-making process”.

The team cautioned the accuracy of sub-seasonal predictions depends on many variables. For dangerous weather patterns, heatwaves and wildfires can be predicted up to four weeks out, tropical cyclones two to three weeks out, and floods one to two weeks out. For sustainability efforts, sub-seasonal forecasts can be used to help manage crop yield, conserve water resources, predict wind and solar energy, and predict sea ice impacts on shipping. All of these different forecasts will include unique complexities that the end user may need help interpreting.

The study recommends new forms of “actionable outputs” – such as risk maps that combine forecast data with local infrastructure, population vulnerability, and resilience metrics. For instance: Wildfire risk maps could show not just the likelihood of fire, but the severity and confidence level of the forecast. Extreme rainfall maps could integrate rainfall intensity, frequency, and probability with flood-prone infrastructure and population density.

Looking ahead, researchers hope to continue to develop this framework for the real world.

“The ultimate goal is to achieve the real-world application of atmospheric science, transforming scientific and technological advancements into economic and social value. Against the backdrop of climate change, we aim to effectively enhance disaster prevention and mitigation efforts as well as optimize resource utilization, thereby developing actionable pathways to genuinely achieve sustainable development goals,” said Lu.