Robust skill of decadal climate predictions

By D. Smith, R. Eade, Adam A. Scaife, L. Caron, Gokhan Danabasoglu, T. Delsole, T. Delworth, Francisco J. Doblas-Reyes, N. Dunstone, L. Hermanson and 8 more. npj Climate and Atmospheric Science, 2019

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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.Forecasting: Large ensemble improves decadal climate predictionsThere is increasing demand for near-time climate predictions to provide guidance for adaptation planning at policy-relevant timescales. Although previous work has shown some skill in forecasting decadal surface temperature, it has proven more difficult to make predictions for precipitation and atmospheric circulation. By using a large, multi-model ensemble of climate models, a multi-institution team lead by Doug Smith of the Met Office Hadley Centre, UK were able to make skillful decadal predictions for near surface temperature, precipitation for the Sahel and broad swathes of Europe and Eurasia, and mean sea level pressure for many regions, with some exceptions being predictions for the South Atlantic and Southern Ocean. Further work is needed to understand whether the instances in which forecasts and observations differ are due to internal variability or external factors such as solar variability, volcanoes and anthropogenic aerosols.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/d1e51488da778c1b143e61c4bc23f578cb2d0e1e