4.7 Article

Imprints of Ocean Chaotic Intrinsic Variability on Bottom Pressure and Implications for Data and Model Analyses

Journal

GEOPHYSICAL RESEARCH LETTERS
Volume 48, Issue 24, Pages -

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2021GL096341

Keywords

ocean bottom pressure; chaotic intrinsic variability; large ensemble simulations; eddies; GRACE; energy inverse cascade

Funding

  1. NASA through GRACE Follow-On Science Team [80NSSC20K0728]
  2. ANR [ANR-13-BS06-0007-01]
  3. CNES through the Ocean Surface Topography Science Team (OST/ST)
  4. French National Programme LEFE (Les Enveloppes Fluides de l'Environnement)-GMMC (Groupe Mission Mercator-Coriolis) by the CRATERE project

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The study reveals that intrinsic variability generated by nonlinear oceanic processes is larger than atmospherically driven variability in the ocean, especially in the intra-annual range. Intrinsic variability is significant at various spatiotemporal scales, supporting the process of energy inverse cascade.
Variations in ocean bottom pressure are important for understanding ocean circulation and climate. While most studies have focused on atmospherically driven variability, here we use eddy-permitting large ensemble simulation output from the OceaniC Chaos-ImPacts, strUcture, predicTability (OCCIPUT) project to isolate chaotic intrinsic variability generated by nonlinear oceanic processes. Analyzing separately the mean seasonal cycle and remainder variability in intra-annual (60-365 days) and subseasonal (2-60 days) bands, we find intrinsic variations larger than atmospherically driven ones over eddy-active regions across all timescales, particularly in the intra-annual range, where intrinsic variations dominate in almost 25% of the oceans. At scales larger than mesoscale, intrinsic variability is still considerable, supporting the process of energy inverse cascade toward lower frequency and larger scales. Results highlight the importance of intrinsic variability over a range of spatiotemporal scales and provide new insights on the interpretation of GRACE-like observations and their de-aliasing procedures.

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