{"id":233371,"date":"2026-04-30T10:15:21","date_gmt":"2026-04-30T20:15:21","guid":{"rendered":"https:\/\/www.hawaii.edu\/news\/?p=233371"},"modified":"2026-04-30T10:15:21","modified_gmt":"2026-04-30T20:15:21","slug":"el-nino-15-months","status":"publish","type":"post","link":"https:\/\/www.hawaii.edu\/news\/2026\/04\/30\/el-nino-15-months\/","title":{"rendered":"Simple ocean model predicts El Niño 15 months in advance"},"content":{"rendered":"Reading time: <\/span> 2<\/span> minutes<\/span><\/span>
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Heavy rainfall pours over a steep tropical landscape in Â鶹´«Ã½.<\/span><\/figcaption><\/figure>\n

For decades, scientists have worked to improve predictions of El Niño-Southern Oscillation (ENSO<\/abbr>), a climate powerhouse that can cause droughts, flooding, marine heatwaves and more around the world. Researchers from the University of Â鶹´«Ã½<\/span> at Mānoa<\/span> published<\/a> a study showing that they can skillfully predict El Niño and La Niña 15 months ahead of time using only observations of the ocean surface temperature and height—no complex climate model needed.<\/p>\n

“We found that it can predict El Niño and La Niña surprisingly well, with useful skill up to about 15 months ahead,” said Yuxin Wang, lead author of the study and postdoctoral researcher with the UH<\/abbr> Sea Level Center<\/a> in the UH<\/abbr> Mānoa<\/span> School of Ocean and Earth Science and Technology<\/a> (SOEST<\/abbr>). “Accurately predicting ENSO<\/abbr> more than a year in advance is important because it can provide early warning, allowing communities, governments and resource managers to take actions and make adaptations to reduce the potential impacts from El Niño and La Niña.”<\/p>\n

“Our simpler, data-driven empirical climate model, built only from ocean observations related to two core climate memories known for over 50 years, achieves ENSO<\/abbr> forecast skill comparable to, and in some cases better than, many of today\u2019s more complex climate models and leading AI-based approaches,” added Wang.<\/p>\n

Building on past discoveries<\/h2>\n

Klaus Wyrtki, a pioneering oceanographer at SOEST<\/abbr> in the 1960s through 1990s, was the first to show that sea level changes can reveal heat build-up in the tropical Pacific, which led him to propose using tide gauge observations to predict El Niño. Klaus Hasselmann, a German oceanographer and Nobel laureate, showed that the ocean can retain a memory of past climate conditions through large-scale temperature patterns, including sea surface temperature patterns outside the tropical Pacific that can still influence ENSO<\/abbr>.<\/p>\n

Building on these two principles, the SOEST<\/abbr> team developed the “Wyrtki-CSLIM<\/abbr>,” short for Wyrtki CycloStationary Linear Inverse Model, a computer model to predict ENSO<\/abbr>.<\/p>\n

Predicting future ENSO<\/h2>\n

The Wyrtki-CSLIM<\/abbr> currently predicts the development of a strong El Niño, more than 2°C warmer than normal over the equatorial eastern Pacific, toward the end of this year. This up-to-date ENSO<\/abbr> forecast<\/a> is available online at the UH<\/abbr> Sea Level Center.<\/p>\n

“Our Wyrtki model is predicting a stronger El Niño than most of the other statistical models, and it is in line with the much more sophisticated dynamical models,” said Matthew Widlansky, study co-author and associate director of the UH<\/abbr> Sea Level Center. “However, it is important to note that all models have uncertainties, and the climate impacts of each El Niño event are different.”<\/p>\n

This new research also offers a clear direction for other ENSO<\/abbr> forecasting systems.<\/p>\n

For more information, see SOEST<\/abbr>\u2019s website<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

Researchers can now skillfully predict El Niño and La Niña 15 months ahead of time using observations of the ocean surface temperature and height.<\/p>\n","protected":false},"author":16,"featured_media":233385,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[30],"tags":[93,1363,1314,107,158,92,806,73,9],"class_list":["post-233371","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research","tag-climate-change","tag-manoa-research","tag-manoa-sustainability","tag-oceanography","tag-publication","tag-school-of-ocean-and-earth-science-and-technology","tag-sea-level-center","tag-sustainability","tag-uh-manoa","entry","has-media"],"aioseo_notices":[],"jetpack_featured_media_url":"https:\/\/www.hawaii.edu\/news\/wp-content\/uploads\/2026\/04\/manoa-soest-el-nino-output.jpg","_links":{"self":[{"href":"https:\/\/www.hawaii.edu\/news\/wp-json\/wp\/v2\/posts\/233371","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.hawaii.edu\/news\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.hawaii.edu\/news\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.hawaii.edu\/news\/wp-json\/wp\/v2\/users\/16"}],"replies":[{"embeddable":true,"href":"https:\/\/www.hawaii.edu\/news\/wp-json\/wp\/v2\/comments?post=233371"}],"version-history":[{"count":7,"href":"https:\/\/www.hawaii.edu\/news\/wp-json\/wp\/v2\/posts\/233371\/revisions"}],"predecessor-version":[{"id":233388,"href":"https:\/\/www.hawaii.edu\/news\/wp-json\/wp\/v2\/posts\/233371\/revisions\/233388"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.hawaii.edu\/news\/wp-json\/wp\/v2\/media\/233385"}],"wp:attachment":[{"href":"https:\/\/www.hawaii.edu\/news\/wp-json\/wp\/v2\/media?parent=233371"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.hawaii.edu\/news\/wp-json\/wp\/v2\/categories?post=233371"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.hawaii.edu\/news\/wp-json\/wp\/v2\/tags?post=233371"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}