Abstract
There is a growing need for skilful predictions of climate up to a decade ahead. Decadal climate predictions show high skill for surface temperature, but confidence in forecasts of precipitation and atmospheric circulation is much lower. Recent advances in seasonal and annual prediction show that the signal-to-noise ratio can be too small in climate models, requiring a very large ensemble to extract the predictable signal. Here, we reassess decadal prediction skill using a much larger ensemble than previously available, and reveal significant skill for precipitation over land and atmospheric circulation, in addition to surface temperature. We further propose a more powerful approach than used previously to evaluate the benefit of initialisation with observations, improving our understanding of the sources of skill. Our results show that decadal climate is more predictable than previously thought and will aid society to prepare for, and adapt to, ongoing climate variability and change.
Highlights
Human society and natural ecosystems are vulnerable to climate variability and change,[1] which impacts food security, freshwater availability, spread of pests and diseases, heat waves, droughts, floods, cyclones, wildfires, energy supply and demand, transport, migration and conflict
Some aspects of climate, for example, multi-year atmospheric circulation changes,[24,25] the frequency of extreme weather events[26] and total amounts of rainfall,[27] are potentially predictable over the coming decade. Such forecasts will not be perfectly deterministic because uncertainties are inevitable due to the chaotic nature of the atmosphere, and errors will be introduced by imperfect climate models and imperfect knowledge of the initial state of the climate system
Our results show that the signal-to-noise paradox, in which the small predictable signal in climate model ensembles is inconsistent with their high level of agreement with observations, is widespread in multi-model decadal predictions, especially for precipitation and mean sea level pressure
Summary
Human society and natural ecosystems are vulnerable to climate variability and change,[1] which impacts food security, freshwater availability, spread of pests and diseases, heat waves, droughts, floods, cyclones, wildfires, energy supply and demand, transport, migration and conflict. Previous assessments have shown high skill in decadal forecasts of surface temperature, confidence in predictions of precipitation and atmospheric circulation, which are vital for many climate impacts, is much lower.[4,12,13,14,15,16,17] recent developments in seasonal forecasting have highlighted the need for very large ensembles to achieve skilful predictions especially for precipitation and atmospheric circulation.[18,19,20,21,22,23] Here we take advantage of these developments to reassess decadal prediction skill using a larger multi-model ensemble than was previously available. We propose a new approach for identifying the sources of skill in order to gain further confidence in forecasts
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