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Frequency-domain analysis of the energy budget in an idealized coupled ocean–atmosphere model

Frequency-domain analysis of the energy budget in an idealized coupled ocean–atmosphere model
Frequency-domain analysis of the energy budget in an idealized coupled ocean–atmosphere model
Climate variability is investigated by identifying the energy sources and sinks in an idealized, coupled, ocean–atmosphere model, tuned to mimic the North Atlantic region. The spectral energy budget is calculated in the frequency domain to determine the processes that either deposit energy into or extract energy from each fluid, over time scales from one day up to 100 years. Nonlinear advection of kinetic energy is found to be the dominant source of low-frequency variability in both the ocean and the atmosphere, albeit in differing layers in each fluid. To understand the spatial patterns of the spectral energy budget, spatial maps of certain terms in the spectral energy budget are plotted, averaged over various frequency bands. These maps reveal three dynamically distinct regions: along the western boundary, the western boundary current separation, and the remainder of the domain. The western boundary current separation is found to be a preferred region to energize oceanic variability across a broad range of time scales (from monthly to decadal), while the western boundary itself acts as the dominant sink of energy in the domain at time scales longer than 50 days. This study paves the way for future work, using the same spectral methods, to address the question of forced versus intrinsic variability in a coupled climate system.
0894-8755
707-726
Martin, Paige E.
62969042-dc25-438f-bdf1-53b3a171310f
Arbic, Brian K.
297f49fc-6755-42f6-b6b2-6307bcd375a3
Mcc. Hogg, Andrew
ea62302d-8aca-43d7-894b-a7821182e4fd
Kiss, Andrew E.
27c1043a-e455-495b-a27a-17f67399de3d
Munroe, James R.
dfdd0d9e-da08-4ba1-8ca5-e5c3415e2337
Blundell, Jeffrey R.
88114f32-6b76-46b2-b2d8-d6ef64a82b0d
Martin, Paige E.
62969042-dc25-438f-bdf1-53b3a171310f
Arbic, Brian K.
297f49fc-6755-42f6-b6b2-6307bcd375a3
Mcc. Hogg, Andrew
ea62302d-8aca-43d7-894b-a7821182e4fd
Kiss, Andrew E.
27c1043a-e455-495b-a27a-17f67399de3d
Munroe, James R.
dfdd0d9e-da08-4ba1-8ca5-e5c3415e2337
Blundell, Jeffrey R.
88114f32-6b76-46b2-b2d8-d6ef64a82b0d

Martin, Paige E., Arbic, Brian K., Mcc. Hogg, Andrew, Kiss, Andrew E., Munroe, James R. and Blundell, Jeffrey R. (2020) Frequency-domain analysis of the energy budget in an idealized coupled ocean–atmosphere model. Journal of Climate, 33 (2), 707-726. (doi:10.1175/JCLI-D-19-0118.1).

Record type: Article

Abstract

Climate variability is investigated by identifying the energy sources and sinks in an idealized, coupled, ocean–atmosphere model, tuned to mimic the North Atlantic region. The spectral energy budget is calculated in the frequency domain to determine the processes that either deposit energy into or extract energy from each fluid, over time scales from one day up to 100 years. Nonlinear advection of kinetic energy is found to be the dominant source of low-frequency variability in both the ocean and the atmosphere, albeit in differing layers in each fluid. To understand the spatial patterns of the spectral energy budget, spatial maps of certain terms in the spectral energy budget are plotted, averaged over various frequency bands. These maps reveal three dynamically distinct regions: along the western boundary, the western boundary current separation, and the remainder of the domain. The western boundary current separation is found to be a preferred region to energize oceanic variability across a broad range of time scales (from monthly to decadal), while the western boundary itself acts as the dominant sink of energy in the domain at time scales longer than 50 days. This study paves the way for future work, using the same spectral methods, to address the question of forced versus intrinsic variability in a coupled climate system.

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Accepted/In Press date: 7 October 2019
e-pub ahead of print date: 26 December 2019
Published date: 15 January 2020
Additional Information: Funding Information: Acknowledgments. The authors thank the following individuals for their help and insight: Amanda O’Rourke, Aidan Heerdegen, and Bruno Deremble. Special thanks are due to William Dewar for many useful discussions over the course of this project. The authors also wish to recognize the reviewers whose comments significantly improved this manuscript. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant DGE 1256260. PEM also acknowledges the associated Graduate Research Opportunities World-wide fellowship to conduct research at the Australian National University. Q-GCM and the analysis codes were run on the National Computational Infrastructure (NCI), which is supported by the Australian Government. The codes are written in Python with the Pangeo environment. PEM and BKA acknowledge support from NSF Grants OCE-0960820 and OCE-1351837, and the University of Michigan African Studies Center and M-Cubed program, the latter supported by the Office of the Provost and the College of Literature, Science, and the Arts. Publisher Copyright: © 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

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Local EPrints ID: 439759
URI: http://eprints.soton.ac.uk/id/eprint/439759
ISSN: 0894-8755
PURE UUID: d748fc08-6349-4193-ba1a-d28c12310a16

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Date deposited: 01 May 2020 16:39
Last modified: 17 Mar 2024 05:16

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Contributors

Author: Paige E. Martin
Author: Brian K. Arbic
Author: Andrew Mcc. Hogg
Author: Andrew E. Kiss
Author: James R. Munroe

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