richter – Bjerknes Climate Prediction Unit

Richter, I., Ratnam, J.V., Martineau, P., Oettli, P., Doi, T., Ogata, T., Kataoka, T., Counillon, F. 2024: A simple statistical post-processing scheme for enhancing the skill of seasonal SST predictions in the tropics. Monthly Weather Review. https://doi.org/10.1175/MWR-D-23-0266.1

Summary: The prediction of year-to-year climate variability patterns, such as El Niño, offers potential benefits to society by aiding mitigation and adaptation efforts. Current prediction systems, however, may still have substantial room for improvement due to systematic model errors and due to imperfect initialization of the oceanic state at the start of predictions. Here we develop a statistical correction scheme to improve prediction skill after forecasts have been completed. The scheme shows some moderate success in improving the skill for predicting El Niño and similar climate patterns in seven prediction systems. Our results not only indicate a potential for improving prediction skill after the fact but also point to the importance of improving the way prediction systems are initialized.

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Crespo, L.R., Prigent, A., Keenlyside, N., Koseki, S., Svendsen, L., Richter, I., Sánchez-Gómez, E. 2022: Weakening of the Atlantic Niño variability under global warming. Nat. Clim. Chang. https://doi.org/10.1038/s41558-022-01453-y

Summary: The Atlantic Niño is one of the most important patterns of interannual tropical climate variability, but how climate change will influence this pattern is not well known due to large climate model biases. Here we show that state-of-the-art climate models robustly predict a weakening of Atlantic Niños in response to global warming, mainly due to a decoupling of subsurface and surface temperature variations as the upper equatorial Atlantic Ocean warms. This weakening is predicted by most (>80%) models in the Coupled Model Intercomparison Project Phases 5 and 6 under the highest emission scenarios. Our results indicate a reduction in variability by the end of the century by 14%, and as much as 24–48% when accounting for model errors using a simple emergent constraint analysis. Such a weakening of Atlantic Niño variability will potentially impact climate conditions and the skill of seasonal predictions in many regions.

Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.