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Probabilistic projections of El Niño Southern Oscillation properties accounting for model dependence and skill
The El Niño – Southern Oscillation (ENSO) is a dominant mode of global climate variability. Nevertheless, future multi-model probabilistic projections of ENSO properties have not yet been made. Main roadblocks that have been hindering making these projections are climate model dependence and difficu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780329/ https://www.ncbi.nlm.nih.gov/pubmed/36550170 http://dx.doi.org/10.1038/s41598-022-26513-3 |
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author | Olson, Roman Kim, Soong-Ki Fan, Yanan An, Soon-Il |
author_facet | Olson, Roman Kim, Soong-Ki Fan, Yanan An, Soon-Il |
author_sort | Olson, Roman |
collection | PubMed |
description | The El Niño – Southern Oscillation (ENSO) is a dominant mode of global climate variability. Nevertheless, future multi-model probabilistic projections of ENSO properties have not yet been made. Main roadblocks that have been hindering making these projections are climate model dependence and difficulty in quantifying historical model performance. Dependence is broadly defined as similarity between climate model output, assumptions, or physical parameterizations. Here, we propose a unifying metric of relative model performance, based on the probability density function (PDF) of ENSO paths. This metric is applied to assess the overall skill of Climate Model Intercomparison Project phase 6 (CMIP6) climate models at capturing ENSO. We then perform future multi-model probabilistic projections of changes in ENSO properties (from years 1850–1949 to 2040–2099) under the shared socioeconomic pathway scenario SSP585, accounting for model skill and dependence. We find that future ENSO will likely be more seasonally locked (89% chance), and have a longer period (67% chance). Yet, the jury is still out on future ENSO amplification. Our method reduces uncertainty by up to 37% compared to a simple approach ignoring model dependence and skill. |
format | Online Article Text |
id | pubmed-9780329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97803292022-12-24 Probabilistic projections of El Niño Southern Oscillation properties accounting for model dependence and skill Olson, Roman Kim, Soong-Ki Fan, Yanan An, Soon-Il Sci Rep Article The El Niño – Southern Oscillation (ENSO) is a dominant mode of global climate variability. Nevertheless, future multi-model probabilistic projections of ENSO properties have not yet been made. Main roadblocks that have been hindering making these projections are climate model dependence and difficulty in quantifying historical model performance. Dependence is broadly defined as similarity between climate model output, assumptions, or physical parameterizations. Here, we propose a unifying metric of relative model performance, based on the probability density function (PDF) of ENSO paths. This metric is applied to assess the overall skill of Climate Model Intercomparison Project phase 6 (CMIP6) climate models at capturing ENSO. We then perform future multi-model probabilistic projections of changes in ENSO properties (from years 1850–1949 to 2040–2099) under the shared socioeconomic pathway scenario SSP585, accounting for model skill and dependence. We find that future ENSO will likely be more seasonally locked (89% chance), and have a longer period (67% chance). Yet, the jury is still out on future ENSO amplification. Our method reduces uncertainty by up to 37% compared to a simple approach ignoring model dependence and skill. Nature Publishing Group UK 2022-12-22 /pmc/articles/PMC9780329/ /pubmed/36550170 http://dx.doi.org/10.1038/s41598-022-26513-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Olson, Roman Kim, Soong-Ki Fan, Yanan An, Soon-Il Probabilistic projections of El Niño Southern Oscillation properties accounting for model dependence and skill |
title | Probabilistic projections of El Niño Southern Oscillation properties accounting for model dependence and skill |
title_full | Probabilistic projections of El Niño Southern Oscillation properties accounting for model dependence and skill |
title_fullStr | Probabilistic projections of El Niño Southern Oscillation properties accounting for model dependence and skill |
title_full_unstemmed | Probabilistic projections of El Niño Southern Oscillation properties accounting for model dependence and skill |
title_short | Probabilistic projections of El Niño Southern Oscillation properties accounting for model dependence and skill |
title_sort | probabilistic projections of el niño southern oscillation properties accounting for model dependence and skill |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780329/ https://www.ncbi.nlm.nih.gov/pubmed/36550170 http://dx.doi.org/10.1038/s41598-022-26513-3 |
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