Editing IPCC:AR6/WGI/Chapter-9 (section)

==== 9.2.1.2 Air–Sea Fluxes ====

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Air–sea fluxes of energy, freshwater, and momentum (wind stresses) are difficult to observe directly ( [[#Cronin--2019|Cronin et al., 2019]] ), so estimates of the global mean net air–sea heat flux are inferred from observed ocean warming ( [[IPCC:Wg1:Chapter:Chapter-2#2.3.3.1|Section 2.3.3.1]] , Box 7.2, and Cross-Chapter Box 9.1). Air–sea heat fluxes resemble the warming patterns of CMIP3 ( [[#Domingues--2008|Domingues et al., 2008]] ; [[#Levitus--2012|Levitus et al., 2012]] ) and are consistent with the ensemble mean warming rate of CMIP5 ( [[#Cheng--2017|Cheng et al., 2017]] , 2019) and CMIP6 models ( [[IPCC:Wg1:Chapter:Chapter-3#3.5.1.3|Section 3.5.1.3]] ). Regional air–sea fluxes in models remain a key driver of uncertainty ( [[#Huber--2017|Huber and Zanna, 2017]] ; [[#Tsujino--2020|Tsujino et al., 2020]] ). A substantial part of the upper 700 m energy increase is ''very likely'' attributed to anthropogenic forcing via increasing radiative forcing (Sections 3.5.1.3, 7.2 and 7.3).

The SROCC ( [[#Abram--2019|Abram et al., 2019]] ) and AR5 ( [[#Rhein--2013|Rhein et al., 2013]] ) assessed that observations of air–sea fluxes had not yet reached the density or accuracy to directly detect trends beyond the noise. New evidence since SROCC confirms that direct heat and freshwater flux trends have not emerged yet as spatial (Figure 9.4), annual ( [[#Yu--2019|Yu, 2019]] ), and decadal ( [[#Zanna--2019|Zanna et al., 2019]] ) variability overwhelm detection. Since AR5, comprehensive comparisons ( [[#Bentamy--2017|Bentamy et al., 2017]] ; [[#Valdivieso--2017|Valdivieso et al., 2017]] ; [[#Yu--2017|Yu et al., 2017]] ) have used updated and new surface flux products to improve surface flux uncertainty estimates, and these comparisons note that implied global energy imbalances often exceed the observed ocean warming. Flux estimates using top of atmosphere observations and atmospheric fluxes from reanalysis have improved over past products ( [[#Trenberth--2018|Trenberth and Fasullo, 2018]] ) but require consistency adjustments ( [[#Trenberth--2019|Trenberth et al., 2019]] ) as the energy budget is not closed. Adjustments are needed for all flux products, and they remain less accurate than direct ocean heat content change measurements ( [[#Cheng--2017|Cheng et al., 2017]] ). Some regional changes are ''likely'' robust in both satellite observations and projections (Figure 9.4). Recent satellite-based surface flux products with improved retrieval algorithms and new satellites, for example, J-OFURO3 ( [[#Tomita--2019|Tomita et al., 2019]] ) and OAFlux-HR ( [[#Yu--2019|Yu, 2019]] ), provide a complete suite of turbulent fluxes including heat, moisture, and momentum. When combined with satellite-based surface radiation from Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF; [[#Kato--2018|Kato et al., 2018]] ) and precipitation from Global Precipitation Climatology Project (GPCP; [[#Adler--2003|Adler et al., 2003]] ), full ocean-surface forcing is available since 1987 (Figure 9.4). These products agree with sparse buoy and ship observations within 30 W m <sup>–2</sup> ( [[#Bentamy--2017|Bentamy et al., 2017]] ; [[#Cronin--2019|Cronin et al., 2019]] ) ''.'' While patterns agree between models and satellites in net fluxes (Figure 9.4), the trend magnitudes are substantially weaker in models. The fluxes tending to warm the North Atlantic and Southern Ocean are consistent with the largest changes observed in the surface properties and water masses (Sections 9.2.1.1, 9.2.2.1 and 9.2.2.3). The observed trend toward a saltier Atlantic Ocean and a fresher Indian Ocean, as well as trends in evaporation minus precipitation (E-P) patterns in the equatorial Pacific (see also [[IPCC:Wg1:Chapter:Chapter-8#8.3.1|Section 8.3.1]] ) enhance the present mean pattern of wetting and drying. Elsewhere patterns are less clear, with only partial, large-scale agreement with the ‘wet gets wetter’ simplification (Sections 3.3.2.3, 4.4.1 and 4.5.1). In summary, globally integrated and large-scale fluxes are more reliably inferred from heat content and salinity change, while regional trends are rarely robust in observations; where they are robust, they tend to be underestimated or in disagreement in models ( ''very high confidence'' ).

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[[File:171fa62ce903f21d239a4870f36f3f2a IPCC_AR6_WGI_Figure_9_4.png]]

'''Figure''' '''9.4 |''' '''Global maps of observed mean fluxes (a, d, g), the observed trends in these fluxes (b, e, h) and the projected rate of change in these fluxes from SSP5-8.5 (c, f, i).''' Shown are the freshwater flux '''(a–c)''' , net heat flux '''(d–f)''' , and momentum flux or wind stress magnitude '''(g–i)''' , with positive numbers indicating ocean freshening, warming, and accelerating respectively. The means and observed trends are calculated between 1995–2014 (freshwater and wind stress) or 2001–2014 (heat). The SSP5-8.5 projected rates are between 1995–2100 using 20-year averages at each end of the time period. Observations show objective interpolation from Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) v4 ( [[#Kato--2018|Kato et al., 2018]] ), Objectively Analyzed air–sea Fluxes-High Resolution (OAFlux-HR) ( [[#Yu--2019|Yu, 2019]] ), and Global Precipitation Climatology Project (GPCP) ( [[#Adler--2003|Adler et al., 2003]] ) of fluxes and flux trends (b, e, h). Observed trends with no overlay indicate regions where the trends are significant at p = 0.34 level. Crosses indicate regions where trends are not significant. For (c, f, i) projections, no overlay indicates regions with high model agreement, where ≥80% of models agree on the sign of change. Diagonal lines indicate regions with low model agreement, where &lt;80% of models agree on the sign of change (see Cross-Chapter Box Atlas.1 for more information). Further details on data sources and processing are available in the chapter data table (Table 9.SM.9).

There is ''low confidence'' in long-term wind stress trends in most regions, but a few locations have ''likely'' trends over the scatterometer era and in projections, as shown in Figure 9.4 ( [[#Desbiolles--2017|Desbiolles et al., 2017]] ; [[#Young--2019|Young and Ribal, 2019]] ; [[#Yu--2019|Yu, 2019]] ). The AR5 ( [[#Rhein--2013|Rhein et al., 2013]] ) assessed with ''medium confidence'' that zonal wind stress over the Southern Ocean increased from the early 1980s to the 1990s ( ''medium confidence'' ) (Figure 9.4). Over 1995–2014, the zonal wind stress over the Southern Ocean continued to increase, westerly winds in the North Pacific and North Atlantic weakened, while the easterly equatorial Pacific winds of the Walker circulation strengthened (Figure 9.4). In historical simulations, CMIP5 models projected annular modes (Annex IV) to move poleward and strengthen in both hemispheres ( [[#Yang--2016|Yang et al., 2016]] ), while in CMIP6 models westerlies only strengthen over the Southern Ocean, with a weaker trend than recently observed (Figure 9.4 and Sections 4.5.1 and 4.5.3). In the tropical Pacific Ocean, a weakening trend in easterly winds and Walker circulation in the 20th century has been inferred based on observed sea level pressure data ( [[#Vecchi--2006|Vecchi et al., 2006]] ; [[#Vecchi--2007|Vecchi and Soden, 2007]] ) and coral proxies ( [[#Carilli--2014|Carilli et al., 2014]] ) and is projected to continue by CMIP6 models (Figure 9.4). Yet, over 1995–2014 observed winds have strengthened (Figure 9.4). The observed strengthening may have been influenced by a combination of factors ( [[IPCC:Wg1:Chapter:Chapter-7#7.4.4.2.1|Section 7.4.4.2.1]] ), but there is ''low confidence'' in the attribution of this signal to anthropogenic warming ( [[IPCC:Wg1:Chapter:Chapter-3#3.3.3.1|Section 3.3.3.1]] ) and ''medium confidence'' that it reflects internal variability ( [[IPCC:Wg1:Chapter:Chapter-8#8.3.2.3|Section 8.3.2.3]] ). Near-term projected changes over the Southern Ocean result from ozone recovery and greenhouse gases (Sections 4.3.3 and 4.4.3). Overall, there is only ''low confidence'' in observed and projected wind stress trends in most regions because trends in oceanic wind stresses during the satellite era have not emerged or are inconsistent with historical simulated changes.

Air–sea flux biases result from common causes in most models, and many are the same as during AR5 ( [[#Rhein--2013|Rhein et al., 2013]] ). Important currents (e.g., Gulf Stream, Kuroshio, Antarctic Circum-polar Current patterns) are often found in erroneous locations in models, affecting SST and flux signatures ( [[#Bates--2012|Bates et al., 2012]] ; [[#Beadling--2020|Beadling et al., 2020]] ; J.-L.F. [[#Li--2020|]] [[#Li--2020|]] [[#Li--2020|Li et al., 2020]] ), but their locations are improved in high-resolution ocean models ( [[#Chassignet--2017|Chassignet et al., 2017]] , 2020; [[#Hewitt--2020|Hewitt et al., 2020]] ), and high-resolution coupled models reduce the mean air–sea flux biases ( [[#Delworth--2012|Delworth et al., 2012]] ; [[#Sakamoto--2012|Sakamoto et al., 2012]] ; [[#Small--2014|Small et al., 2014]] ; [[#Haarsma--2016|Haarsma et al., 2016]] ; [[#Caldwell--2019|Caldwell et al., 2019]] ; L.C [[#Jackson--2020|]] [[#Jackson--2020|Jackson et al., 2020]] ). Oceanic variability stems either from internal chaotic variability or atmospheric forcing ( [[#Hasselmann--1976|Hasselmann, 1976]] ; [[#Sérazin--2016|Sérazin et al., 2016]] , 2017). Large-scale variability in the ocean tends to follow atmospheric forcing in low-resolution models, while in high-resolution coupled models ocean variability drives atmospheric variability on small scales ( [[#Bishop--2017|Bishop et al., 2017]] ; [[#Small--2019|Small et al., 2019]] ), allowing these high-resolution models to mimic the coupling with clouds, precipitation, and atmospheric and oceanic boundary layers apparent in observations ( [[#Chelton--2010|Chelton and Xie, 2010]] ; [[#Frenger--2013|Frenger et al., 2013]] ). Even coarse-resolution models, such as the ocean and sea ice components used in CMIP6, show significant sensitivity in the mean and variability of SST and sea ice to modest changes in flux forcing ( [[#Tsujino--2020|Tsujino et al., 2020]] ). Finally, there is still considerable disagreement between different parametrizations of air–sea fluxes used in models and strong scatter in direct observations ( [[#Renault--2016|Renault et al., 2016]] ; [[#Brodeau--2017|Brodeau et al., 2017]] ). In summary, there is ''very high confidence'' that air–sea heat flux and stress biases are reduced in coupled models with high ocean resolution over coarse-resolution models, although the effect on trends remain unclear.

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