Cargando…
Surface Current in “Hotspot” Serves as a New and Effective Precursor for El Niño Prediction
The El Niño and Southern Oscillation (ENSO) is the most prominent sources of inter-annual climate variability. Related to the seasonal phase-locking, ENSO’s prediction across the low-persistence barrier in the boreal spring remains a challenge. Here we identify regions where surface current variabil...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5427969/ https://www.ncbi.nlm.nih.gov/pubmed/28279021 http://dx.doi.org/10.1038/s41598-017-00244-2 |
_version_ | 1783235731325452288 |
---|---|
author | Wang, Jianing Lu, Youyu Wang, Fan Zhang, Rong-Hua |
author_facet | Wang, Jianing Lu, Youyu Wang, Fan Zhang, Rong-Hua |
author_sort | Wang, Jianing |
collection | PubMed |
description | The El Niño and Southern Oscillation (ENSO) is the most prominent sources of inter-annual climate variability. Related to the seasonal phase-locking, ENSO’s prediction across the low-persistence barrier in the boreal spring remains a challenge. Here we identify regions where surface current variability influences the short-lead time predictions of the July Niño 3.4 index by applying a regression analysis. A highly influential region, related to the distribution of wind-stress curl and sea surface temperature, is located near the dateline and the southern edge of the South Equatorial Current. During El Niño years, a westward current anomaly in the identified high-influence region favours the accumulation of warm water in the western Pacific. The opposite occurs during La Niña years. This process is seen to serve as the “goal shot” for ENSO development, which provides an effective precursor for the prediction of the July Niño 3.4 index with a lead time of 2–4 months. The prediction skill based on surface current precursor beats that based on the warm water volume and persistence in the subsequent months after July. In particular, prediction based on surface current precursor shows skill in all years, while predictions based on other precursors show reduced skill after 2002. |
format | Online Article Text |
id | pubmed-5427969 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54279692017-05-15 Surface Current in “Hotspot” Serves as a New and Effective Precursor for El Niño Prediction Wang, Jianing Lu, Youyu Wang, Fan Zhang, Rong-Hua Sci Rep Article The El Niño and Southern Oscillation (ENSO) is the most prominent sources of inter-annual climate variability. Related to the seasonal phase-locking, ENSO’s prediction across the low-persistence barrier in the boreal spring remains a challenge. Here we identify regions where surface current variability influences the short-lead time predictions of the July Niño 3.4 index by applying a regression analysis. A highly influential region, related to the distribution of wind-stress curl and sea surface temperature, is located near the dateline and the southern edge of the South Equatorial Current. During El Niño years, a westward current anomaly in the identified high-influence region favours the accumulation of warm water in the western Pacific. The opposite occurs during La Niña years. This process is seen to serve as the “goal shot” for ENSO development, which provides an effective precursor for the prediction of the July Niño 3.4 index with a lead time of 2–4 months. The prediction skill based on surface current precursor beats that based on the warm water volume and persistence in the subsequent months after July. In particular, prediction based on surface current precursor shows skill in all years, while predictions based on other precursors show reduced skill after 2002. Nature Publishing Group UK 2017-03-13 /pmc/articles/PMC5427969/ /pubmed/28279021 http://dx.doi.org/10.1038/s41598-017-00244-2 Text en © The Author(s) 2017 This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Wang, Jianing Lu, Youyu Wang, Fan Zhang, Rong-Hua Surface Current in “Hotspot” Serves as a New and Effective Precursor for El Niño Prediction |
title | Surface Current in “Hotspot” Serves as a New and Effective Precursor for El Niño Prediction |
title_full | Surface Current in “Hotspot” Serves as a New and Effective Precursor for El Niño Prediction |
title_fullStr | Surface Current in “Hotspot” Serves as a New and Effective Precursor for El Niño Prediction |
title_full_unstemmed | Surface Current in “Hotspot” Serves as a New and Effective Precursor for El Niño Prediction |
title_short | Surface Current in “Hotspot” Serves as a New and Effective Precursor for El Niño Prediction |
title_sort | surface current in “hotspot” serves as a new and effective precursor for el niño prediction |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5427969/ https://www.ncbi.nlm.nih.gov/pubmed/28279021 http://dx.doi.org/10.1038/s41598-017-00244-2 |
work_keys_str_mv | AT wangjianing surfacecurrentinhotspotservesasanewandeffectiveprecursorforelninoprediction AT luyouyu surfacecurrentinhotspotservesasanewandeffectiveprecursorforelninoprediction AT wangfan surfacecurrentinhotspotservesasanewandeffectiveprecursorforelninoprediction AT zhangronghua surfacecurrentinhotspotservesasanewandeffectiveprecursorforelninoprediction |