Zhao et al. (2026) Ocean mixed-layer damping and air–sea coupling modulate multidecadal spectral selectivity in the North Atlantic

Identification

• Journal: Climate Dynamics
• Year: 2026
• Date: 2026-01-14
• Authors: Hongyuan Zhao, Jianping Li
• DOI: 10.1007/s00382-025-08029-4

Research Groups

• Frontiers Science Center for Deep Ocean Multi-Spheres and Earth System (DOMES)/Key Laboratory of Physical Oceanography/Academy of Future Ocean/College of Oceanic and Atmospheric Sciences/Center for Ocean Carbon Neutrality, Ocean University of China, Qingdao, China
• Laboratory for Ocean Dynamics and Climate, Qingdao Marine Science and Technology Center, Qingdao, China

Short Summary

This study reveals how ocean mixed-layer damping and air-sea coupling drive multidecadal spectral selectivity in the North Atlantic. It demonstrates that oceanic damping acts as a frequency filter for stochastic atmospheric forcings, and a coupled ocean-atmosphere model with stochastic forcing explains the quasi-periodic multidecadal oscillations of the Atlantic Multidecadal Oscillation (AMO) and North Atlantic Oscillation (NAO).

Objective

• To reveal the mechanism of frequency-selective amplification driven by stochastic forcings in the North Atlantic air-sea system.
• To explain the origins of climatic quasi-periodicity, specifically the multidecadal timescale preference in the North Atlantic and NAO-AMO transitions, through ocean damping effects and stochastically forced oscillation.

Study Configuration

• Spatial Scale: North Atlantic (75°–7.5°W, 0°–60°N for AMO index calculation), global ocean for damping coefficient analysis.
• Temporal Scale: Multidecadal variability (e.g., 60–80 years for AMO), 1900–2015 for decadal variance analysis, 1980–2015 for climatological calculations, 1854–2019 for model optimization, and centennial to millennial (up to 5000 years) for simulations.

Methodology and Data

• Models used:
  • Linear feedback model (stochastic climate model) to analyze frequency response.
  • Two-component coupled model with stochastic forcing (ocean-atmosphere oscillator) to simulate coupled oscillations.
  • Numerical integration of stochastic differential equations using the Euler–Maruyama scheme.
  • Numerical least-squares optimization method for parameter estimation in the coupled model.
• Data sources:
  • Sea level pressure (SLP): HadSLP2 dataset.
  • Sea surface temperature (SST): Extended Reconstructed SST Version 5 (ERSSTv5) dataset.
  • Mixed layer depth: NCEP Global Ocean Data Assimilation System (GODAS) dataset.
  • 10 m wind data: NCEP-NCAR Reanalysis 1 dataset.
  • AMO index (AMOI): Area-weighted average of detrended SST anomaly in the North Atlantic (75°–7.5°W, 0°–60°N).
  • NAO index (NAOI): Difference between normalized SLP zonally averaged from 80°W to 30°E at 35°N and 65°N.

Main Results

• The oceanic damping effect, influenced by mixed layer depth, wind speed, and latent heat sensitivity, acts as a low-pass frequency filter, converting broadband stochastic atmospheric forcings into low-frequency oceanic responses.
• In the subpolar North Atlantic, lower damping coefficients (e.g., corresponding to a cutoff period of approximately 50 years) are attributed to deeper mixed layers, lower wind speeds, and weaker latent heat damping, favoring multidecadal variability.
• A two-component coupled model with stochastic forcing successfully simulates quasi-periodic oscillations, exhibiting power spectrum peaks at specific low frequencies (e.g., a model period of approximately 85.6 years for the AMO-NAO system).
• The optimized coupled model reproduces observed AMO and NAO indices (1854–2019) with an RMSE of 0.1443 K for AMOI and 0.1508 (dimensionless) for NAOI, capturing their dominant multidecadal periods and a phase-locked relationship where NAO leads AMO by approximately 15-20 years (model result: 18.9 years).
• Analytical solutions derived from the coupled model link the spectral peak to the system's dynamical parameters, including coupling coefficients and damping rates.
• The framework explains the multidecadal timescale preference in the North Atlantic via the ocean damping effect and the transitions between NAO and AMO through stochastically forced oscillation.

Contributions

• Advances the understanding of low-frequency climate variability by providing a mechanistic framework that explains spectral selectivity in the North Atlantic air-sea system, resolving the dynamics between stochastic forcing and deterministic responses.
• Identifies ocean mixed-layer thermal inertia and surface heat damping as a local-scale mechanism actively shaping multidecadal spectral selectivity, offering an alternative perspective to AMOC's advective timescales.
• Provides a process-oriented analytical tool for evaluating General Circulation Models (GCMs) by deriving and comparing key parameters (e.g., ocean-atmosphere coupling strength, damping timescales) from observational data against model simulations, aiding in the diagnosis of biases and refinement of parameterizations.
• Offers insights into the mechanisms behind oscillatory modes like the AMO and NAO, with implications for assessing future AMO changes under evolving ocean stratification and for analyzing coupled variability in other ocean-atmosphere systems.

Funding

• National Natural Science Foundation of China (NSFC) Project (42130607)
• Laoshan Laboratory (No.LSKJ202202600)
• Shandong Natural Science Foundation Project (ZR2019ZD12)
• Fundamental Research Funds for the Central Universities (202242001)

Citation

@article{Zhao2026Ocean,
  author = {Zhao, Hongyuan and Li, Jianping},
  title = {Ocean mixed-layer damping and air–sea coupling modulate multidecadal spectral selectivity in the North Atlantic},
  journal = {Climate Dynamics},
  year = {2026},
  doi = {10.1007/s00382-025-08029-4},
  url = {https://doi.org/10.1007/s00382-025-08029-4}
}