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- Title
Probabilistic Prediction of ENSO Over the Past 137 Years Using the CESM Model.
- Authors
Liu, Ting; Tang, Youmin; Wang, Chunzai; Song, Xunshu
- Abstract
In this study, we investigate probabilistic predictability for the El Niño‐Southern Oscillation (ENSO) by assessing both actual prediction skill and potential predictability using a long‐term retrospective forecast from a complicated coupled general circulation model (CGCM). Our results indicate that above and below normal events are more predictable than neutral events. The probabilistic prediction skill suffers prominent "Spring Predictability Barrier" and undergoes notable interdecadal variation. For the above and below normal events, the lowest probabilistic prediction skills appear during 1920–1940 and the higher prediction skills occur after the 1960s. The seasonal and interdecadal variability of the probabilistic prediction skill stems mainly from the variability of the ENSO signal intensity. There is much room for improvement for the predictability of all three categories of ENSO events. At least an additional 1 or 2 months of skillful probabilistic predictions can be expected to progress in the future. To our knowledge, this is the first study to use a CGCM to evaluate probabilistic predictability for ENSO at various time scales. Plain Language Summary: The predictability of El Niño‐Southern Oscillation (ENSO) has important implications for seasonal climate predictions. The chaotic nature of ENSO means that probabilistic prediction is required to quantitatively capture forecast uncertainty. Most current studies of probabilistic ENSO prediction are based on hindcasts from complicated coupled general circulation models (CGCMs) that cover the past three or four decades. It is difficult to fully understand the variability of probabilistic ENSO predictability on inter‐decadal (or longer) timescales. In this study, we firstly assess probabilistic predictability for the ENSO by assessing both actual and potential probabilistic prediction skills using a long‐term retrospective forecast from a CGCM. Robust conclusions are derived and deepen the understanding of probabilistic predictability for the ENSO. Key Points: A study to evaluate the probabilistic El Niño‐Southern Oscillation (ENSO) predictability on various time scales with long‐term ensemble hindcast based on complicated coupled general circulation modelENSO probabilistic predictability from both actual and potential perspectivesThere is plenty of room for improvement of all three categories of ENSO events
- Subjects
EL Nino; GENERAL circulation model; LONG-range weather forecasting
- Publication
Journal of Geophysical Research. Oceans, 2022, Vol 127, Issue 12, p1
- ISSN
2169-9275
- Publication type
Article
- DOI
10.1029/2022JC019127