Long-range forecasts are a vital tool for understanding and adapting to climate variability and change.
Unlike short-term weather forecasts, which predict conditions over the next few days, long-range forecasts look ahead from one month to a decade ahead, bridging the gap between daily weather prediction and long-term climate projections.
These forecasts are increasingly important for governments, businesses, and individuals planning for the future in a world where climate extremes are becoming more common.
The science behind long-range forecasting
There is a fundamental difference between long-range forecasts and the forecast you might get for tomorrow’s weather. The atmosphere is a complex system, sensitive to small initial changes that can grow into significant events, a concept often illustrated by the idea that a butterfly flapping its wings in Brazil could eventually influence weather halfway across the world.
Runs of computer models with similar weather forecasts for the next day will have entirely different predictions looking weeks or months ahead. Long-range forecasts do not try to predict the exact weather this far ahead, therefore. Instead, they aim to identify the more likely weather trends in the period of interest.
For forecasts on monthly to decadal timescales, it’s not enough to consider just the atmosphere. The models must also include the role of the ocean, land surface changes, and increasing greenhouse gases, factors typically associated with climate prediction. By integrating these elements, forecasters can simulate how today’s climate might evolve over months and years, providing valuable insights into future conditions.
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The value of long-range forecasts
Long-range forecasts are valuable for planning and risk management across many sectors. For example, predicting the intensity of the Atlantic hurricane season months in advance could help the reinsurance industry prepare for potential losses. Agricultural users, governments, and individual decision-makers also benefit from information about risks of climate extremes, enabling them to make informed choices about resource allocation, infrastructure, and safety.
Ensemble prediction: embracing uncertainty
Given the challenges outlined above, long-range forecasts need to rely on ensemble prediction systems. This means running many simulations with slightly different starting conditions, then analysing the range of behaviour across all these forecasts. The result is not a single prediction, but a range of possible outcomes The more likely types of weather conditions are highlighted when more of the members of the ensemble have similar outcomes. To further strengthen these forecasts, the Met Office participates in international collaborations, sharing its seasonal forecasts with other national meteorological services. By comparing forecasts from around the world, experts can make more robust and informed judgments about future climate risks.
How to use long-range predictions
Long-range predictions are best used to assess the likelihood and risk of different outcomes, rather than to warn of specific events. For example, while it’s not possible to predict the exact weather on a particular day months ahead, forecasters can estimate the probability of certain conditions, such as a wetter-than-average season or an increased risk of heatwaves.
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Accuracy in long-range forecasting is assessed differently from short-term weather prediction. Rather than focusing on individual forecasts, performance is evaluated over many cases, looking at how often the most likely outcomes occur. This approach recognises that less likely scenarios than those preferred by the forecast can and do occur. The greatest value of long-range forecasts is to guide planning and risk management over, helping organizations and individuals make more resilient choices over the long term.
It’s also important to remember that long-range forecasts describe average conditions over a specified period and region. They do not guarantee that these conditions will prevail continuously, nor do they account for local variations, especially in areas with complex terrain.
Decadal prediction: looking further ahead
Decadal prediction systems are at the forefront of research in long-range forecasting. Over the next decade, climate changes will result from a combination of human-driven changes in greenhouse gases and aerosols, natural variations in volcanic and solar activity, and variability intrinsic to the climate system. To predict regional changes on these timescales, models must include all these influences.
The Met Office’s decadal prediction system, DePreSys, starts its forecasts from observed atmospheric and oceanic conditions and incorporates projected emissions and natural climate forcings. Retrospective tests show that DePreSys improves predictions of global average temperature and Atlantic hurricane frequency compared to models that don’t use current observations.
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Decadal prediction allows us to look into the new world that is emerging as a result of climate change. Rather than something that will occur in distant decades, climate change is making itself felt now, and over the next decade more extreme weather events than have hitherto been observed will occur. These predictions permit changes to be anticipated, giving time to plan and prepare.
Decadal prediction research includes improving understanding of decadal variability mechanisms, enhancing predictive capability, and developing operational products. Current projects focus on assessing the skill of predictions for phenomena such as the Atlantic overturning circulation and extreme events, as well as re-analysing historical ocean data and supporting international climate assessments.
Monthly to decadal operational systems
For seasonal timescales, the Met Office uses the Global Seasonal Forecast System (GloSea6), an ensemble system that integrates influences from atmosphere, land, ocean, and sea ice models. GloSea6 generates probabilistic forecasts up to six months ahead, accounting for uncertainties in initial conditions.
Outputs from GloSea6 are used to produce monthly and seasonal forecast products, support research into climate variability impacts, and fulfil requirements for the World Meteorological Organization’s global producing centres of long-range forecasts.
As research and operational systems continue to advance, long-range forecasts will become even more skilful and useful, supporting adaptation to a changing climate and helping society prepare for the challenges ahead.
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