Strong El Niño Events Lead to Robust Multi-Year ENSO Predictability

The El Niño-Southern Oscillation (ENSO) phenomenon—the dominant source of climate variability on seasonal to multi-year timescales—is predictable a few seasons in advance. Forecast skill at longer multi-year timescales has been found in a few models and forecast systems, but the robustness of this predictability across models has not been firmly established owing to the cost of running dynamical model predictions at longer lead times. In this study, we use a massive collection of multi-model hindcasts performed using model analogs to show that multi-year ENSO predictability is robust across models and arises predominantly due to skillful prediction of multi-year La Nina events following strong El Niño events.

See also the associated paper in Geophysical Research Letters:
Lenssen, N., P. DiNezio, L. Goddard, C. Deser, Y. Kushnir, S. Mason, M. Newman and Y. Okumura, 2024: Strong El Niño Events Lead to Robust Multi-Year ENSO Predictability. Geophysical Research Letters, 51, 12, e2023GL106988, doi:10.1029/2023GL106988.

Bio:

Dr. Nathan Lenssen is a Teaching Assistant Professor in Applied Mathematics at the Colorado School of Mines. His research sits at the intersection between atmospheric and ocean physics, and applied statistics. He is currently a Project Scientists at the National Center for Atmospheric Research, an associate editor of the Journal of Climate, and a member of the National Aeronautics and Space Administration's Goddard Institute for Space Studies Surface Temperature Analysis science team. At the Colorado School of Mines, he teaches statistics with an emphasis on how statistics can be used to answer questions about the world.

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