IAMElNino.com is an independent, hobbyist-built dashboard that tracks the El Niño–Southern Oscillation (ENSO) cycle in near real time, pulling directly from NOAA's Climate Prediction Center and other public data sources, rather than summarizing other people's reporting.
I built and maintain IAMElNino.com as a personal project. I hold a degree in meteorology, which is why this site is built around primary NOAA/NASA source data rather than secondhand interpretation, and why accuracy takes priority over speed.
Blog posts on this site are drafted with AI research assistance and reviewed before publishing. Live dashboard data is pulled directly and automatically from NOAA CPC, NASA, and partner agency feeds with no manual editing of the underlying figures. Analysis and commentary in blog posts are clearly separated from the raw data panels and represent informed interpretation, not official forecasts.
If you spot an error or an outdated figure, please use the contact page, corrections are made promptly and we'd rather hear about a mistake than have it sit uncorrected.
This started as a personal project to better understand ENSO methodology, particularly the February 2026 shift from the legacy Oceanic Niño Index (ONI) to the Relative Oceanic Niño Index (RONI), which better accounts for long-term ocean warming trends. Most public dashboards hadn't caught up to that change, so this site was built to track the new standard directly, alongside the older index for comparison.
It's run independently, isn't affiliated with NOAA or any government agency, and exists to make publicly available climate data easier to read at a glance, for weather enthusiasts, students, and anyone trying to understand what's actually happening in the Pacific without wading through raw data files.
All figures on this site are pulled directly from public NOAA, NASA, and partner agency data feeds and refreshed automatically. We do not editorialize the underlying numbers, interpretation and context in blog posts are clearly written as analysis, separate from the live data panels.