📄 earth_science

North Atlantic SST Drives Sub-seasonal Variability and Predictability of the Large-Scale Circulation

This study demonstrates that North Atlantic sea surface temperature patterns actively drive sub-seasonal atmospheric circulation, with specific regimes—particularly one favoring atmospheric blocking—significantly extending weather predictability beyond the typical two-week limit.

Original authors: Victor Murphy, Roy Yaniv, Valerio Lembo, Simona Bordoni, Assaf Hochman

Published 2026-08-10

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Victor Murphy, Roy Yaniv, Valerio Lembo, Simona Bordoni, Assaf Hochman

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

The Ocean's Hidden Hand

Imagine the Earth's atmosphere as a giant, chaotic dance floor where air masses swirl, collide, and spin in unpredictable patterns. For decades, scientists have watched this dance, trying to figure out who is leading. Is the atmosphere the DJ, spinning the music and forcing the ocean to move? Or is the ocean the steady bassline, setting the rhythm that the atmosphere must follow? This question sits at the heart of climate science, specifically in the North Atlantic, a vast stretch of water that acts like a giant thermostat for Europe and the Mediterranean.

To understand the stakes, think of "Sea Surface Temperature" (SST) as the temperature of the ocean's skin. When this skin gets warmer or cooler than usual, it creates "anomalies"—spots of heat or cold that stick around. These spots can act like invisible walls or ramps for the wind. If the ocean can actually push the atmosphere into a specific pattern, it changes everything. It means we might be able to look at the ocean today and predict the weather weeks or even months from now, giving us a "window of opportunity" to prepare for storms, heatwaves, or droughts. But for a long time, scientists weren't sure if the ocean was just a passenger or the actual driver.

The Ocean Takes the Wheel

In this study, a team of researchers decided to settle the debate: Does the North Atlantic ocean actively drive the weather, or is it just along for the ride? They used a clever mathematical tool called Convergent Cross Mapping (CCM). You can think of CCM as a detective's magnifying glass that looks at the history of two variables to see if one contains the "memory" of the other. If the ocean is truly driving the atmosphere, then knowing the ocean's past should help you predict the atmosphere's future better than the other way around.

The results were clear: The ocean is the driver. The study found that North Atlantic sea surface temperatures actively shape atmospheric circulation on timescales of days to weeks. It's not just a two-way conversation where they influence each other equally; the ocean sends a strong signal that the atmosphere listens to. This relationship holds true from daily changes all the way up to sub-seasonal periods (about a month). The researchers showed that the ocean's temperature patterns contain predictive information about the wind and pressure systems that the atmosphere doesn't contain about the ocean. This suggests that the ocean isn't just a passive sponge soaking up heat from the air; it's an active puppeteer pulling the strings of the weather.

Four Distinct "Ocean Moods"

To understand how the ocean pulls these strings, the researchers used machine learning to sort 75 years of winter ocean data into four distinct "moods" or patterns. Imagine the ocean wearing four different outfits, each causing a completely different reaction in the atmosphere:

The "Zonal Flow" Outfit (Regime 1): This pattern features a long, warm strip of water stretching across the middle of the Atlantic. When the ocean wears this, it encourages the atmosphere to flow smoothly from west to east, like a fast-moving river. It boosts storm activity and pushes rain and wind toward northern Europe.
The "Cool Down" Outfit (Regime 2): Here, the whole ocean basin gets a bit chilly. The atmosphere's reaction to this is surprisingly mild. It's like the ocean whispered a secret, and the atmosphere just shrugged. While there are some changes, they aren't as dramatic as the other patterns.
The "Traffic Jam" Outfit (Regime 3): This is the most interesting one. It looks like a "tripole"—warm water near the equator, cold water in the middle, and warm water near the poles. When the ocean wears this outfit, it acts like a giant brake on the weather. It suppresses the usual swirling waves of air and causes the atmosphere to get stuck in one place. This leads to "blocking" events, where high-pressure systems sit still for weeks, causing persistent weather (like long heatwaves or cold snaps).
The "Unprecedented" Outfit (Regime 4): Since 2021, a brand new, super-warm pattern has appeared that the ocean has never shown before in the last 71 years. It's a massive, intense warm strip running diagonally across the Atlantic. Because it's so new and rare, the researchers set it aside for future study, but it hints that the ocean might be entering a new, uncharted territory.

The "Window of Opportunity" for Forecasts

The most exciting discovery lies in Regime 3, the "Traffic Jam" outfit. The researchers used advanced math to measure how "sticky" the weather is when this ocean pattern is present. They found that when the ocean is in this specific mood, the atmosphere becomes incredibly persistent. The weather patterns stop changing as quickly as usual.

Normally, weather forecasts become unreliable after about 14 days because the atmosphere is too chaotic. However, when Regime 3 is active, the atmosphere gets "stuck" in a predictable state for 3 to 4 weeks. This creates a "window of opportunity" for forecasters. If they can spot this specific ocean pattern early, they might be able to predict weather extremes (like blocking events) a full month in advance, a timeframe that was previously thought impossible.

Why This Matters

This study doesn't just tell us that the ocean and atmosphere are friends; it proves the ocean is the one giving the orders. By identifying these specific ocean patterns, scientists have found a new way to look at the future. The ocean isn't just reacting to the weather; it's setting the stage. If we can learn to recognize these "outfits" the ocean is wearing, we might finally be able to see the weather coming long before it arrives, turning the chaotic dance of the atmosphere into something we can anticipate with much greater confidence.

Technical Summary: North Atlantic SST Drives Sub-seasonal Variability and Predictability of the Large-Scale Circulation

Problem Statement
While North Atlantic sea surface temperature (SST) variability is widely recognized as a modulator of European and Mediterranean weather patterns, the causal directionality of this relationship remains debated. The prevailing interpretation posits that SST anomalies are primarily passive responses to atmospheric forcing via surface heat fluxes and wind-driven Ekman transport. However, correlation-based analyses cannot distinguish between direct atmospheric forcing, oceanic forcing of the atmosphere, or bidirectional coupling within a shared dynamical system. Consequently, it remains an open question whether North Atlantic SST anomalies contain independent predictive information for atmospheric circulation, particularly at daily-to-subseasonal timescales relevant for extended-range forecasting. Furthermore, discrete SST regime structures that systematically modulate atmospheric responses and their associated intrinsic predictability have not been fully characterized.

Methodology
The study employs a unified framework integrating nonlinear causal inference, regime identification, and dynamical diagnostics using observational data from 1950 to 2024.

Causal Inference (Convergent Cross Mapping - CCM): To resolve causal directionality, the authors apply CCM, a method derived from dynamical systems theory. Unlike traditional Granger causality, CCM reconstructs attractor manifolds from time-delayed observations to test whether the time series of one variable can be reliably reconstructed from the manifold of another. This allows for the detection of directional coupling even in the presence of bidirectional interactions. The analysis computes cross-map skill ( $\rho$ ) across varying library sizes ( $L$ ) and embedding parameters ( $E, \tau$ ) to establish convergence and asymmetry between SST and 500 hPa geopotential height (Z500).
Regime Identification (SOM and K-means): To identify discrete SST structures, the authors utilize Self-Organizing Maps (SOM) with 28 nodes to classify 75 years of winter (DJF) North Atlantic SST anomalies. These patterns are subsequently grouped into four physically coherent regimes using k-means clustering.
Dynamical and Process-Based Diagnostics: The atmospheric response to each regime is quantified using:
- Circulation Metrics: Composite Z500 anomalies and spatial correlations.
- Wave Activity: Finite-amplitude Local Wave Activity (LWA) and Wave Activity Flux (WAF) to diagnose Rossby wave amplitude and propagation pathways.
- Storm Track Dynamics: Eddy Kinetic Energy (EKE) at 850 hPa and upper-tropospheric eddy momentum flux ( $u'v'$ ) at 250 hPa.
- Hydrological Impact: Atmospheric River (AR) frequency based on Integrated Water Vapour Transport (IVT).
- Intrinsic Predictability: Dynamical systems metrics, specifically local dimension ( $d$ ) and inverse persistence ( $\theta$ ), to quantify the geometry of the atmospheric attractor and the rate of state transitions.

Key Contributions and Results

Evidence of Directional Ocean-to-Atmosphere Forcing: CCM analysis reveals a persistent directional asymmetry where SST predicts Z500 more effectively than Z500 predicts SST. This asymmetry emerges as library sizes increase (converging at $L \approx 7,500$ days) and remains robust across daily-to-subseasonal lags (0–30 days). The SST $\to$ Z500 skill ( $\rho \approx 0.88$ ) significantly exceeds the reverse direction ( $\rho \approx 0.78$ ), indicating that the ocean actively shapes atmospheric states rather than merely integrating atmospheric variability.
Identification of Four Recurrent SST Regimes: The study identifies four distinct winter SST patterns:
- Regime 1: An elongated warm anomaly from $\sim25^\circ$ N to $45^\circ$ N.
- Regime 2: A coherent basin-wide cooling, strongest in the subtropics.
- Regime 3: A tripole-like structure with low-latitude warming and sub-polar warming separated by mid-latitude cooling.
- Regime 4: An unprecedented, exceptionally warm anomaly extending from $\sim10^\circ$ N to $40^\circ$ N, appearing only since 2021. This regime is excluded from comparative analysis due to its limited sample size.
Mechanistically Distinct Atmospheric Responses:
- Regime 1 promotes enhanced zonal (west-to-east) flow, characterized by a southwestward shift of the stationary wave ridge, intensified Rossby wave activity over the North Atlantic, and an extended storm track toward northwestern Europe.
- Regime 2 elicits a comparatively weak response, with modest changes in wave activity and storm tracks, though it does produce anomalous ridging over the Mediterranean.
- Regime 3 induces a suppression of Rossby wave activity across the North Atlantic, a poleward displacement of the European ridge, and enhanced high-latitude blocking (Greenland and Scandinavian Blocking). It is associated with an equatorward-displaced storm track and increased atmospheric river activity over Iberia and the western Mediterranean.
Sub-seasonal Predictability Windows: Dynamical systems metrics reveal that Regime 3 exhibits enhanced atmospheric persistence (negative inverse persistence, $\theta$ ) and reduced state-transition frequency. This suggests that when this SST regime is active, the atmospheric circulation enters a state of higher intrinsic predictability, potentially offering "windows of opportunity" for forecasts at 3- to 4-week lead times, beyond the typical 14-day deterministic limit.

Significance and Claims
The paper claims to provide direct evidence that North Atlantic SST actively forces atmospheric circulation on subseasonal timescales, challenging the traditional view of SST as a passive integrator. By combining causal inference with regime analysis, the study demonstrates that specific, recurrent SST configurations (particularly the tripole-like Regime 3) organize large-scale circulation through distinct dynamical pathways involving Rossby wave suppression and storm-track displacement.

The authors assert that these findings highlight an actionable pathway for extending the predictability of weather and climate extremes. Specifically, the identification of SST regimes with high dynamical persistence (like Regime 3) offers a physical basis for improving subseasonal-to-seasonal (S2S) forecasts. The study suggests that operational implementation could involve near-real-time SST regime classification to identify periods where atmospheric states are more constrained by external forcing, thereby enhancing forecast skill for circulation anomalies and extremes over Europe and the Mediterranean. The framework is presented as potentially portable to other ocean basins where SST gradients drive atmospheric responses.