Editing IPCC:AR6/SROCC/Chapter-5 (section)

===== 5.2.2.2.4 5.2.2.2.4 Systematic sources of uncertainty in projections of ocean physical changes =====

ESMs are able to capture the dynamics of the climate system, but all numerical models have approximations and biases. The most commonly used type of ocean component in ESMs is known to exhibit numerically induced vertical mixing that can be a significant fraction of the physical mixing (Ilıcak et al., 2012 <sup>[[#fn:r159|159]]</sup> ; Megann, 2018 <sup>[[#fn:r160|160]]</sup> ). Because so many ocean models exhibit the same sign of bias, there is a systematic warming of the lower-main thermocline that is not cancelled out when taking the average over the ensemble of all the models in CMIP5. These biases are widely known within the ocean modelling community, and various groups are working to reduce these biases in future ESMs with better ocean model numerics and parameterisations. To correct for model biases, ESM projections are always taken as the difference from a control run without the anomalous forcing. However, some aspects of the ocean response to climate change are nonlinear, and model biases can introduce uncertainties into climate projections. In the case of heat uptake, this is of the order of 10% uncertainty, while for the rate of steric SLR (which depends on the nonlinear equation of state of seawater) the uncertainty in CMIP5 models is of the order of 20% (Hallberg et al., 2012 <sup>[[#fn:r161|161]]</sup> ).

Mesoscale eddies (geostrophic rotating vortices with spatial scales of 10–100 km that penetrate deeply into the water column, and are often described as the ocean’s weather) play an important role in regulating the changes to the larger scale ocean circulation, especially in the Antarctic Circumpolar current, as is discussed in Cross Chapter Box 7. In addition, sub-mesoscale eddies (rotationally influenced motions with smaller horizontal scales of hundreds of metres to about 10 km and intrinsic timescales of a few days that especially arise in association with fronts in the ocean’s surface properties) are known to be particularly important in the dynamics of the near-surface ocean boundary layer (see the review by Mahadevan (2016)). Sub-mesoscale instabilities are associated with re-stratifying overturning circulations that can limit the thickness of the well-mixed ocean surface boundary layer near fronts (Bachman et al., 2017 <sup>[[#fn:r162|162]]</sup> ). Moreover, sub-mesoscale motions generate strong vertical velocities that drive fluxes of nutrients from the interior ocean into the euphotic zone or create pockets of reduced mixing with increased phytoplankton residency time within the euphotic zone (Lévy et al., 2012 <sup>[[#fn:r163|163]]</sup> ). Intense mesoscale eddies are known to create favourable conditions for sub-mesoscale instabilities as shown in both observational (Bachman et al., 2017 <sup>[[#fn:r164|164]]</sup> ) and numerical studies (Brannigan et al., 2017 <sup>[[#fn:r165|165]]</sup> ). Intensifying Southern Ocean eddy fields will have a significant local impact on biological productivity, ecosystem structure, and carbon uptake, both directly and via sub-mesoscale processes. At typical CMIP5 ESM resolutions, it is only in the tropics that mesoscale eddies are adequately resolved to explicitly model their effects (Hallberg, 2013 <sup>[[#fn:r166|166]]</sup> ), while sub-mesoscale eddies are not resolved anywhere, so eddy effects need to be parameterised in ESMs. Despite great progress over the past 30 years in parameterising eddy effects, uncertainties in these parameterisations and how eddies will respond to novel conditions continue to contribute to uncertainties in projections of oceanic climate change ( ''medium confidence'' ).

Ocean turbulent mixing is a key process regulating the ocean circulation and climate. Turbulent mixing is important for the uptake and redistribution of heat, carbon, nutrients, oxygen and other tracers (properties that are carried along with the flow of water) in the ocean (Schmittner et al., 2009 <sup>[[#fn:r167|167]]</sup> ; MacKinnon et al., 2017 <sup>[[#fn:r168|168]]</sup> ). Both observations and theory indicate that turbulent mixing in the ocean is not constant in space or time. Global estimates of both the turbulent kinetic energy dissipation rate and the vertical diffusivity, two measures of ocean turbulence, vary over several orders of magnitude throughout the ocean (Figure 5.6) (Polzin et al., 1997 <sup>[[#fn:r170|170]]</sup> ; Waterman et al., 2012 <sup>[[#fn:r171|171]]</sup> ; Whalen et al., 2012 <sup>[[#fn:r172|172]]</sup> ; Alford et al., 2013 <sup>[[#fn:r173|173]]</sup> ; Hummels et al., 2013 <sup>[[#fn:r174|174]]</sup> ; Sheen et al., 2013 <sup>[[#fn:r175|175]]</sup> ; Waterhouse et al., 2014 <sup>[[#fn:r176|176]]</sup> ; Kunze, 2017 <sup>[[#fn:r177|177]]</sup> ). For a given energy dissipation rate, the turbulent diffusivities of heat, salinity, nutrients and other tracers tend to be smaller with stronger stratification. This dependency on stratification helps explain why the observationally inferred diffusivity in the heavily stratified main thermocline (250–1000 m depth) is of similar magnitude to those deeper in the water column, while the turbulent energy density and dissipation rate are much stronger at the shallower depths (Whalen et al., 2012 <sup>[[#fn:r178|178]]</sup> ). Oceanic turbulence also fluctuates in time, is modulated by tidal cycles (Klymak et al., 2008 <sup>[[#fn:r179|179]]</sup> ), the mesoscale eddy field and seasonal changes (Whalen et al., 2018 <sup>[[#fn:r180|180]]</sup> ). In the mixed layer and directly below, turbulence changes according to local conditions, such as the winds, heating rates and local stratification (Sloyan et al., 2010 <sup>[[#fn:r181|181]]</sup> ; Moum et al., 2013 <sup>[[#fn:r182|182]]</sup> ; D’Asaro, 2014 <sup>[[#fn:r183|183]]</sup> ; Tanaka et al., 2015 <sup>[[#fn:r184|184]]</sup> ) at diurnal to seasonal and longer timescales. These variations in near-surface turbulence need to be taken into account for ESMs to reproduce more accurately the observed seasonal cycle of surface properties and spatial structure of the depth of the thermally well-mixed near surface layer of the ocean. The spatial and temporal patterns of ocean turbulence help shape ocean tracer distributions (heat, dissolved greenhouse gases and nutrients) and how they will evolve in a changing climate ( ''high confidence'' ).

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'''Figure 5.6'''

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'''Figure 5.6 | Estimate of the average vertical turbulent diffusivity between 250–1000 m calculated by applying fine structure techniques to Argo float data from below the well-mixed near-surface boundary layer. Only bins with at least three estimates are plotted and regions with insufficient data are coloured grey. This figure was created using updated data through […]'''
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Figure 5.6 | Estimate of the average vertical turbulent diffusivity between 250–1000 m calculated by applying fine structure techniques to Argo float data from below the well-mixed near-surface boundary layer. Only bins with at least three estimates are plotted and regions with insufficient data are coloured grey. This figure was created using updated data through April, 2018 with the techniques from Whalen et al. (2012).

Ocean turbulent mixing requires energy sources, many of which are expected to change with a changing climate. Surface wind and buoyancy forcing, the mean and eddying larger-scale ocean circulation itself, and the barotropic tides are all thought to be significant sources of the energy that drives mixing (Wunsch and Ferrari, 2004 <sup>[[#fn:r185|185]]</sup> ). Often this energy first passes through the ocean’s pervasive field of internal gravity waves that propagate and refract through the varying ocean circulation, often breaking into turbulent mixing far from their sources (Eden and Olbers, 2014 <sup>[[#fn:r186|186]]</sup> ; Alford et al., 2016 <sup>[[#fn:r187|187]]</sup> ; Melet et al., 2016 <sup>[[#fn:r188|188]]</sup> ; Meyer et al., 2016 <sup>[[#fn:r189|189]]</sup> ; Zhao et al., 2016b <sup>[[#fn:r190|190]]</sup> ). The energy contributing to the internal waves from the winds and the subsequent turbulence will be altered by changes in tropical storm activity or sea ice coverage. For example, the increasing extent of ice-free Arctic Ocean has already been observed to lead to increased wind-driven internal waves (Dosser and Rainville, 2016 <sup>[[#fn:r191|191]]</sup> ). The Southern Annular Mode is expected to intensify as a result of climate change (Young et al., 2011 <sup>[[#fn:r192|192]]</sup> ; Jones et al., 2016b <sup>[[#fn:r193|193]]</sup> ), bringing with it stronger winds, and more wind-energy input over most of the Southern Ocean and a more intense mesoscale eddy field (Hogg et al., 2015 <sup>[[#fn:r194|194]]</sup> ). Changes in the near-bottom stratification will alter the rate that the barotropic tides generate internal waves, thereby altering the strength and distribution of the tidally generated mixing. Some of the parameterisations of interior ocean mixing used in CMIP5 ESMs take some changing turbulent energy sources into account (Jayne and St. Laurent, 2001 <sup>[[#fn:r195|195]]</sup> ) , and more comprehensive mixing treatments are being developed for use in future generations of ESMs (Eden and Olbers, 2014 <sup>[[#fn:r196|196]]</sup> ). However, not all of the physical processes leading to the rich structure of mixing shown in Figure 5.6 are well understood or included in ESMs; the prospect of significant changes in the patterns and intensity of ocean turbulent mixing is a potential source of uncertainty (probably at the 10% level) in projections of physical and ecological changes in the ocean, including heat uptake, stratification changes, steric SLR, deoxygenisation and nutrient fluxes ( ''medium confidence'' ).

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