Chaotic Variability of Ocean Heat Content: Climate-Relevant Features and Observational Implications

• Main Authors: Thierry Penduff, Guillaume Sérazin, Stéphanie Leroux, Sally Close, Jean-Marc Molines, Bernard Barnier, Laurent Bessières, Laurent Terray, Guillaume Maze
• Format: Article
• Language: English
• Published: The Oceanography Society 2018-06-01
• Series: Oceanography
• Subjects: ocean models; mesoscale turbulence; ocean heat
• Online Access: https://doi.org/10.5670/oceanog.2018.210

Global ocean models that admit mesoscale turbulence spontaneously generate interannual-to-multidecadal chaotic intrinsic variability in the absence of atmospheric forcing variability at these timescales. This phenomenon is substantially weaker in non-turbulent ocean models but provides a marked stochastic flavor to the low-frequency variability in eddying ocean models, which are being coupled to the atmosphere for next-generation climate projections. In order to disentangle the atmospherically forced and intrinsic ocean variabilities, the OCCIPUT (Oceanic Chaos – Impacts, Structures, Predictability) project performed a long (1960–2015), large ensemble (50 members) of global ocean/sea ice 1/4° simulations driven by the same atmospheric reanalysis, but with perturbed initial conditions. Subsequent ensemble statistics show that the ocean variability can be seen as a broadband "noise," with characteristic scales reaching multiple decades and basin sizes, locally modulated by the atmospheric variability. In several mid-latitude regions, chaotic processes have more impact than atmospheric variability on both the low-frequency variability and the long-term trends of regional ocean heat content. Consequently, certain climate-relevant oceanic signals cannot be unambiguously attributed to atmospheric variability, raising new issues for the detection, attribution, and interpretation of oceanic heat variability and trends in the presence of mesoscale turbulence.