The Active and Passive Roles of the Ocean in Generating Basin‐Scale Heat Content Variability

Stephenson, Dafydd; Sévellec, Florian

doi:10.1029/2020gl091874

Cited by 3 publications

(1 citation statement)

References 56 publications

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“…The typical autocorrelation structure of flux principal components is roughly 1.5 days (not shown), substantially shorter than the interannual time scales of interest, so we compute Z following (9), consistent with a white noise assumption. We estimate seasonal nonstationarity in variance amplitudes (to specify the 𝑑 𝑖 in ( 9)) following Stephenson and Sévellec (2021a) (not shown).…”

Section: A Model Setupmentioning

confidence: 99%

A dynamics-weighted principal components analysis of dominant atmospheric drivers of ocean variability with an application to the North Atlantic subpolar gyre

Amrhein,

Stephenson,

Thompson

2024

Preprint

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This paper describes a framework for identifying dominant atmospheric drivers of ocean variability. The method combines statistics of atmosphere-ocean fluxes with physics from an ocean general circulation model to derive atmospheric patterns optimized to excite variability in a specified ocean quantity of interest. We first derive the method as a weighted principal components analysis and illustrate its capabilities in a toy problem. Next, we apply our analysis to the problem of interannual upper ocean heat content (HC) variability in the North Atlantic Subpolar Gyre (SPG) using the adjoint of the MITgcm and atmosphere-ocean fluxes from the ECCOv4-r4 state estimate. An unweighted principal components analysis reveals that North Atlantic heat and momentum fluxes in ECCOv4-r4 have a range of spatiotemporal patterns. By contrast, dynamicsweighted principal components analysis collapses the space of these patterns onto a small subset -principally associated with the North Atlantic Oscillation -that dominates interannual SPG HC variance. By perturbing the ECCOv4-r4 state estimate, we illustrate the pathways along which variability propagates from the atmosphere to the ocean in a nonlinear ocean model. This technique is applicable across a range of problems across Earth System components, including in the absence of a model adjoint. SIGNIFICANCE STATEMENT: While the oceans have absorbed 90% of the excess heat associated with human-forced climate change, the change in the ocean's heat content is not steady, with peaks and troughs superimposed upon a general increase. These fluctuations come from chaotic changes in the atmosphere and ocean, and can be hard to disentangle. We use this case of ocean heat content variability to introduce a new method for determining the patterns of weather and climate in the atmosphere that are most effective at generating fluctuations in the ocean. To do this, we combine the statistics of recent atmospheric activity with output from a state-of-the-art numerical ocean model that reveals physical processes driving changes in ocean quantities including ocean heat content. This approach suggests that the atmospheric patterns that stimulate the most energetic changes in ocean heat content in the northern North Atlantic are not the most energetic patterns present in the atmosphere. We test our findings by preventing these patterns from affecting the ocean in our numerical model, and measure a strong reduction in ocean heat content fluctuations.

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Section: A Model Setupmentioning

confidence: 99%

A dynamics-weighted principal components analysis of dominant atmospheric drivers of ocean variability with an application to the North Atlantic subpolar gyre

Amrhein,

Stephenson,

Thompson

2024

Preprint

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Simulated Impact of Time‐Varying River Runoff and Greenland Freshwater Discharge on Sea Level Variability in the Beaufort Gyre Over 2005–2018

Tajouri,

Llovel,

Sévellec

et al. 2024

JGR Oceans

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Global mean sea level has been rising at a rate of 3.25 ± 0.4 mm yr−1 over 1993–2018. Yet several regions are increasing at a much faster rate, such as the Beaufort Gyre in the Arctic Ocean at a rate of 9.3 ± 7.0 mm yr−1 over 2003–2014. At interannual to decadal time scales, the Beaufort Gyre sea level is controlled by salinity changes due to sea ice melt and wind‐driven lateral Ekman convergence–divergence of freshwater. This study uses recent Greenland discharge and river runoff estimates to isolate and quantify the sea level response to freshwater fluxes variability over the period 1980–2018. It relies on sensitivity experiments based on a global ocean model including sea‐ice and icebergs. These sensitivity experiments only differ by the freshwater fluxes temporal variability of Greenland and global rivers which are either seasonal climatologies or fully time varying, revealing the individual and combined impact of these freshwater sources fluctuations. Fully varying Greenland discharge and river runoff produce an opposite impact on sea level trends over 2005–2018 in the Beaufort Gyre region, the former driving an increase, while the latter, a decrease. Their combined impact leads to a fairly weak sea level trend. The sea level response is primarily driven by salinity variations in the upper 300 m, which are mainly caused by salinity advection involving complex compensations between passive, active, and nonlinear advection. This study shows that including the temporal variability of freshwater fluxes in forced global ocean models results in a better representation of regional sea level change.

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Dynamical attribution of North Atlantic interdecadal predictability to oceanic and atmospheric turbulence under diagnosed and optimal stochastic forcing

Stephenson

Sévellec

2021

Journal of Climate

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Unpredictable variations in the ocean originate from both external atmospheric forcing and chaotic processes internal to the ocean itself, and are a crucial sink of predictability on interdecadal timescales. In a global ocean model, we present i.) an optimization framework to compute the most efficient noise patterns to generate uncertainty and ii.) a computationally inexpensive, dynamical method for attributing sources of ocean uncertainty to internal (mesoscale eddy-driven) and external (atmospherically driven) origins, sidestepping the more typical ensemble approach. These two methods are then applied to a range of metrics (heat content, volume transport, and heat transport) and time averages (monthly, yearly, and decadal) in the subtropical and subpolar North Atlantic. The optimal noise patterns create variability in integrated quantities of interest through features of the underlying circulation such as the North Atlantic Current and deep water formation regions. Meanwhile, noise forcing diagnosed from model representations of the actual climate system stimulates these theoretical patterns with various degrees of efficiency, ultimately leading to the growth of error. We reaffirm that higher frequency variations in meridional transports are primarily wind driven, while surface buoyancy forcing is the ultimately dominant source of uncertainty at lower frequencies. For year-averaged quantities in the subtropics, it is mesoscale eddies which contribute the most to oceanic uncertainty, accounting for up to 60% after 60 years of growth for volume transport at 25°N. The impact of eddies is greatly reduced in the subpolar region, which we suggest may be explained by overall lower sensitivity to small-scale noise there.

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The Active and Passive Roles of the Ocean in Generating Basin‐Scale Heat Content Variability

Cited by 3 publications

References 56 publications

A dynamics-weighted principal components analysis of dominant atmospheric drivers of ocean variability with an application to the North Atlantic subpolar gyre

A dynamics-weighted principal components analysis of dominant atmospheric drivers of ocean variability with an application to the North Atlantic subpolar gyre

Simulated Impact of Time‐Varying River Runoff and Greenland Freshwater Discharge on Sea Level Variability in the Beaufort Gyre Over 2005–2018

Dynamical attribution of North Atlantic interdecadal predictability to oceanic and atmospheric turbulence under diagnosed and optimal stochastic forcing

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