[DSRP Evidence](https://dsrpevidence.org/)

# Tropical–Extratropical Teleconnection of the Winter Atlantic Niño in a Climate Model

Gil-Reyes et al., 2026, Journal of Climate — Climatology

Patterns: [Relationships](https://dsrpevidence.org/pattern/relationships)

## In short

A teleconnection is action and reaction across distance: a change in one place produces a specific change in another, with the direction of the effect established.

## What they found (results)

Climate model simulations show winter Atlantic Niño sea-surface warming drives an extratropical wave train — cyclonic anomalies at midlatitudes, anticyclonic at higher latitudes — with North Atlantic-European precipitation anomalies that intensify from November–December into January–February.

## Abstract

Tropical Atlantic variability (TAV) in sea surface temperature (SST) exerts a significant influence on the climate of surrounding regions. The Atlantic Niño (ATLN) is one of the leading modes of TAV, with a primary peak in summer (June–July) and a secondary peak in early winter (November–December). This study aims at exploring the atmospheric response to winter ATLN, as it has been much less documented than the summer ATLN. Coupled and atmosphere-only simulations with the climate model European Consortium Earth System Model (EC-EARTH) have been performed and analyzed to investigate the extratropical teleconnection of the winter ATLN in the North Atlantic–European (NAE) sector. Results show a tropical Gill-type structure, baroclinic and symmetrically straddling the equator, whose amplitude increases from November–December to January–February. In the extratropics, the atmospheric circulation displays a wave-like dipolar structure with cyclonic anomalies at midlatitudes and anticyclonic anomalies at subpolar latitudes, which is different from the North Atlantic Oscillation. This wave train response includes the feedback from both stationary and transient eddy activity. The associated precipitation anomalies show a robust signal over NAE. Differences in statistical significance are found when comparing observational data with model results, although the spatial patterns are similar, particularly in early winter. These findings enhance our understanding of the potential impact of the winter ATLN and suggest it could represent an untapped source of predictability.

These researchers were not testing DSRP. The finding is theirs; the correspondence to DSRP is drawn by this site.

[Source](https://doi.org/10.1175/jcli-d-25-0164.1)