Editing IPCC:AR6/WGI/Chapter-6 (section)

=== 6.4.5 Non-CO <sub>2</sub> biogeochemical Feedbacks ===

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Climate change-induced changes in atmospheric composition and forcing due to perturbations in natural processes constitute an Earth system feedback amplifying (positive feedback) or diminishing (negative feedback) the initial climate perturbation ( [[#Ciais--2013|Ciais et al., 2013]] ; [[#Heinze--2019|Heinze et al., 2019]] ). Quantification of these biogeochemical feedbacks is important to allow for a better estimate of the expected effects of emissions reduction policies for mitigating climate change and the effect on the allowable global carbon budget ( [[#Lowe--2018|Lowe and Bernie, 2018]] ). Biogeochemical feedbacks due to changes in the carbon cycle are assessed in [[IPCC:Wg1:Chapter:Chapter-5#5.4.5|Section 5.4.5]] , while physical and biogeophysical climate feedbacks are assessed in [[IPCC:Wg1:Chapter:Chapter-7#7.4.2|Section 7.4.2]] . Additionally, non-CO <sub>2</sub> biogeochemical feedbacks due to climate-driven changes in methane sources and N <sub>2</sub> O sources and sinks are assessed in [[IPCC:Wg1:Chapter:Chapter-5#5.4.7|Section 5.4.7]] . The goal of this section is to estimate the feedback parameter ( α as defined in section 7.4.1.1) from climate-induced changes in atmospheric abundances or lifetimes of SLCFs mediated by natural processes or atmospheric chemistry. These non-CO <sub>2</sub> biogeochemical feedbacks act on time scales of years to decades and have important implications for climate sensitivity and emissions-abatement policies. The feedback parameter is quantified entirely from ESMs that expand the complexity of CCMs by coupling the physical climate and atmospheric chemistry to land and ocean biogeochemistry. In AR5, α for non-CO <sub>2</sub> biogeochemical feedbacks was estimated from an extremely limited set of modelling studies with much less confidence associated with the estimate. Since AR5, ESMs have advanced to include more feedback processes, facilitating a relatively more robust assessment of α . CMIP6 ESMs participating in AerChemMIP performed coordinated sets of experiments ( [[#Collins--2017|Collins et al., 2017]] ) facilitating the consistent estimation of α ( [[#Thornhill--2021a|Thornhill et al., 2021a]] ) and we rely on this multi-model analysis for the best estimates (Table 6.8). Considering the consistent methodology, the assessed central values and 5–95% ranges for α are based on the AerChemMIP estimates. The full range of model uncertainty is not captured in AerChemMIP because of the relatively small ensemble size, therefore estimates from studies using other models or with different protocols are discussed to reinforce or critique these values.

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'''Table 6.8 |''' '''Assessed central estimates and the''' very likely '''ranges (5–95%) of non-CO''' <sub>2</sub> '''biogeochemical feedback parameter''' ( α <sub>x</sub> ''') based on the AerChemMIP ensemble estimates (Thornhill''' '''et al.''' ''', 2021a).''' As in [[IPCC:Wg1:Chapter:Chapter-7#7.4.1.1|Section 7.4.1.1]] , α <sub>x</sub> (W m <sup>−2</sup> °C <sup>−1</sup> ) for a feedback variable ''x'' is defined as   where   is the change in TOA energy balance in response to a change in ''x'' induced by a change in surface temperature ( ''T'' ). The 5–95% range is calculated as mean ± standard deviation × 1.645 for each feedback. The level of confidence in these estimates is ''low'' owing to the large intermodel spread. Published estimates of α <sub>x</sub> are also shown for comparison.

{| class="wikitable"
|-
| '''Non-CO''' <sub>2</sub> '''Biogeochemical Climate Feedback''' ( x ''')'''

| '''Number of AerChemMIP Models'''

| '''Assessed Central Estimate and Very Likely Range of Feedback Parameter''' ( α <sub>x</sub> ''')'''

'''W m''' <sup>−2</sup> '''°C''' <sup>−1</sup>

| '''Published Estimates of''' α <sub>x</sub>

'''W m''' <sup>−2</sup> '''°C''' <sup>−1</sup>

|-
| Sea salt

| 6

| –0.049 [–0.13 to +0.03]

| –0.08 ( [[#Paulot--2020|Paulot et al., 2020]] )

|-
| DMS

| 3

| 0.005 [0.0 to 0.01]

| –0.02 ( [[#Ciais--2013|Ciais et al., 2013]] )

|-
| Dust

| 6

| –0.004 [–0.02 to +0.01]

| –0.04 to +0.02 ( [[#Kok--2018|Kok et al., 2018]] )

|-
| Ozone

| 4

| –0.064 [–0.08 to -0.04]

| –0.015 ( [[#Dietmüller--2014|Dietmüller et al., 2014]] ), –0.06 ( [[#Muthers--2014|Muthers et al., 2014]] , stratospheric ozone changes only), –0.01 ( [[#Marsh--2016|Marsh et al., 2016]] , stratospheric ozone changes only), –0.13 ( [[#Nowack--2015|Nowack et al., 2015]] , stratospheric ozone and water vapour changes), –0.007 ± 0.009 ( [[#Heinze--2019|Heinze et al., 2019]] , tropospheric ozone changes only)

|-
| BVOC

| 4

| –0.05 [–0.22 to +0.12]

| –0.06 ( [[#Scott--2017|Scott et al., 2017]] , aerosol effects only), –0.01 ( [[#Paasonen--2013|Paasonen et al., 2013]] ; indirect aerosol effects only), 0–0.06 ( [[#Ciais--2013|Ciais et al., 2013]] )

|-
| Lightning

| 4

| –0.010 [–0.04 to +0.02]

|
|-
| Methane lifetime

| 4

| –0.030 [–0.12 to +0.06]

| –0.30 ± 0.01 ( [[#Heinze--2019|Heinze et al., 2019]] )

|-
| Total non-CO <sub>2</sub> Biogeochemical feedbacks assessed in this chapter

|
| –0.200 [–0.41 to +0.01]

| 0.0 ± 0.15 ( [[#Sherwood--2020|Sherwood et al., 2020]] )

|}

'''Climate–sea-spray feedback:''' Sea-spray emissions from ocean surfaces influence climate directly or indirectly through the formation of CCN as discused in Section 6.2.1.2. They are sensitive to SST and sea ice extent, as well as to wind speed, and are therefore expected to feedback on climate ( [[#Struthers--2013|Struthers et al., 2013]] ). However, there are large uncertainties in the strength of climate feedback from sea-spray aerosols because of the diversity in the model representation of emissions (many represent sea-salt emissions only) and their functional dependence on environmental factors noted above, in situ atmospheric chemical and physical processes affecting the sea-spray lifetime, and aerosol–cloud interactions ( [[#Struthers--2013|Struthers et al., 2013]] ; [[#Soares--2016|Soares et al., 2016]] ; [[#Nazarenko--2017|Nazarenko et al., 2017]] ). Additional work is needed to identify how sea-spray and POA emissions respond to shifts in ocean biology and chemistry in response to warming, ocean acidification and changes in circulation patterns (Cochran et al. , 2017) , and affect CCN and INP formation ( [[#DeMott--2016|DeMott et al., 2016]] ). AerChemMIP models, representing only the sea-salt emissions, agree that the sea-salt-climate feedback is negative, however there is a large range in the feedback parameter indicating large uncertainties (Table 6.8).

'''Climate–DMS feedback:''' Dimethyl sulphide (DMS) is produced by marine phytoplankton and is emitted to the atmosphere where it can lead to the subsequent formation of sulphate aerosol and CCN (Section 6.2.2.5). Changes in DMS emissions from ocean could feedback on climate through their response to changes in temperature, solar radiation, ocean mixed-layer depth, sea ice extent, wind speed, nutrient recycling or shifts in marine ecosystems due to ocean acidification and climate change, or atmospheric processing of DMS into CCN ( [[#Heinze--2019|Heinze et al., 2019]] ). Models with varying degrees of representation of the relevant biogeochemical processes and effects on DMS fluxes produce diverging estimates of changes in DMS emissions strength under climate change resulting in large uncertainties in the DMS–sulphate–cloud albedo feedback ( [[#Bopp--2004|Bopp et al., 2004]] ; [[#Kloster--2007|Kloster et al., 2007]] ; [[#Gabric--2013|Gabric et al., 2013]] ). In AR5, the climate-DMS feedback parameter was estimated to be –0.02 W m <sup>–2</sup> °C <sup>–1</sup> based on a single model. Since AR5, new modelling studies using empirical relationships between pH and total DMS production find that global DMS emissions decrease due to combined ocean acidification and climate change, leading to a strong positive climate feedback ( [[#Six--2013|Six et al., 2013]] ; [[#Schwinger--2017|Schwinger et al., 2017]] ). However, another study argues for a much weaker positive feedback globally due to complex and compensating regional changes in marine ecosystems (S. [[#Wang--2018|]] [[#Wang--2018|]] [[#Wang--2018|Wang et al., 2018]] ). The AerChemMIP multi-model analysis suggests small positive feedback (Table 6.8), consistent with these recent studies, but with large uncertainties in the magnitude of α .

'''Climate–dust feedback:''' Mineral dust is the most abundant aerosol type in the atmosphere, when considering aerosol mass, and affects the climate system by interacting with both longwave and shortwave radiation as well as contributing to the formation of CCN and INP. Because dust emissions are sensitive to climate variability (e.g., through changes in the extent of arid land; Section 6.2.2.4), it has been hypothesized that the climate-dust feedback could be an important feedback loop in the climate system. Since AR5, an improved understanding of the shortwave absorption properties of dust as well as a consensus that dust particles are larger than previously thought has led to a revised understanding that the magnitude of radiative forcing due to mineral dust is small ( [[#Kok--2017|Kok et al., 2017]] ; [[#Ryder--2018|Ryder et al., 2018]] ). A recent study notes that global models underestimate the amount of coarse dust in the atmosphere and accounting for this limitation raises the possibility that dust emissions warm the climate system ( [[#Adebiyi--2020|Adebiyi and Kok, 2020]] ). Model predictions of dust emissions in response to future climate change range from an increase ( [[#Woodward--2005|Woodward et al., 2005]] ) to a decrease ( [[#Mahowald--2003|Mahowald and Luo, 2003]] ), thus leading to high uncertainties on the sign of the climate-dust feedback. Since AR5, [[#Kok--2018|Kok et al. (2018)]] estimated the direct dust-climate feedback parameter, from changes in the dust direct radiative effect only, to be in the range –0.04 to +0.02 W m <sup>–2</sup> °C <sup>–1</sup> . The assessed central value and the 5–95% range of the climate-dust feedback parameter based on AerChemMIP ensemble (Table 6.8) is within the range of the published estimate, however both the magnitude and sign of α are model-dependent.

'''Climate–ozone feedback:''' Changes in ozone concentrations in response to projected climate change have been shown to lead to a potential climate-atmospheric chemistry feedback. Chemistry–climate models consistently project a decrease in lower tropical stratospheric ozone levels due to enhanced upwelling of ozone-poor tropospheric air associated with surface warming-driven strengthening of the Brewer-Dobson circulation ( [[#Bunzel--2013|Bunzel and Schmidt, 2013]] ). Further, models project an increase in middle and extratropical stratospheric ozone due to increased downwelling through the strengthened Brewer-Dobson circulation ( [[#Bekki--2013|Bekki et al., 2013]] ; [[#Dietmüller--2014|Dietmüller et al., 2014]] ). These stratospheric ozone changes induce a net-negative global mean ozone radiative feedback ( [[#Dietmüller--2014|Dietmüller et al., 2014]] ). Tropospheric ozone shows a range of responses to climate with models generally agreeing that warmer climate will lead to decreases in the tropical lower troposphere owing to increased water vapour, and increases in the subtropical to mid-latitude upper troposphere due to increases in lightning and stratosphere-to-troposphere transport ( [[#Stevenson--2013|Stevenson et al., 2013]] ). A small positive feedback is estimated from climate-induced changes in global mean tropospheric ozone ( [[#Dietmüller--2014|Dietmüller et al., 2014]] ) while a small negative feedback is estimated by [[#Heinze--2019|Heinze et al. (2019)]] based on the model results of [[#Stevenson--2013|Stevenson et al. (2013)]] . Additionally, these ozone feedbacks induce a change in stratospheric water vapour amplifying the feedback due to stratospheric ozone ( [[#Stuber--2001|Stuber et al., 2001]] ). Since AR5, several modelling studies have estimated the intensity of meteorology-driven ozone feedbacks on climate from either combined tropospheric and stratospheric ozone changes or separately with contrasting results. One study suggests no change ( [[#Marsh--2016|Marsh et al., 2016]] ), while other studies report reductions of ECS ranging from 7–8% ( [[#Dietmüller--2014|Dietmüller et al., 2014]] ; [[#Muthers--2014|Muthers et al., 2014]] ) to 20% ( [[#Nowack--2015|Nowack et al., 2015]] ). The estimate of this climate-ozone feedback parameter is very strongly model-dependent with values ranging from –0.13 to –0.01 W m <sup>–2</sup> °C <sup>–1</sup> though there is agreement that it is negative. The assessed central value and the 5–95% range of climate-ozone feedback parameter based on AerChemMIP ensemble is within the range of these published estimates, but closer to the lower bound. This climate-ozone feedback factor does not include the feedback on ozone from lightning changes which is discussed separately below.

'''Climate–BVOC feedback:''' BVOCs, such as isoprene and terpenes, are produced by land vegetation and marine plankton (Sections 6.2.2.3 and 6.2.2.5). Once in the atmosphere, BVOCs and their oxidation products lead to the formation of secondary organic aerosols (SOA) exerting a negative forcing, and increased ozone concentrations and methane lifetime exerting a positive forcing. BVOC emissions are suggested to lead to a climate feedback in part because of their strong temperature dependence observed under present-day conditions ( [[#Kulmala--2004|Kulmala et al., 2004]] ; [[#Arneth--2010a|Arneth et al., 2010a]] ). Their response to future changes in climate and CO <sub>2</sub> levels remains uncertain (Section 6.2.2.3). Estimates of the climate-BVOC feedback parameter are typically based on global models which vary in their level of complexity of emissions parametrization, BVOC speciation, the mechanism of SOA formation and the interaction with ozone chemistry ( [[#Thornhill--2021a|Thornhill et al., 2021a]] ). Since AR5, observational studies ( [[#Paasonen--2013|Paasonen et al., 2013]] ) and models ( [[#Scott--2018|Scott et al., 2018]] ) estimate the feedback due to biogenic SOA (via changes in BVOC emissions) to be in the range of about –0.06 to –0.01 W m <sup>–2</sup> °C <sup>–1</sup> . The assessed central estimate of the climate-BVOC feedback parameter based on the AerChemMIP ensemble suggests that climate-induced increases in SOA from BVOCs will lead to a strong cooling effect that will outweigh the warming from increased ozone and methane lifetime, however the uncertainty is large ( [[#Thornhill--2021a|Thornhill et al., 2021a]] ).

'''Climate–lightning NO''' <sub>x</sub> '''feedback:''' As discussed in Section 6.2.2.1, climate change influences lightning NO <sub>x</sub> emissions. Increases in lightning NO <sub>x</sub> emissions will not only increase tropospheric ozone and decrease methane lifetime but also increase the formation of sulphate and nitrate aerosols, via oxidant changes, offsetting the positive forcing from ozone. The response of lightning NO <sub>x</sub> to climate change remains uncertain and is highly dependent on the parametrization of lightning in ESMs (Section 6.2.1.2; [[#Finney--2016b|Finney et al., 2016b]] ; [[#Clark--2017|Clark et al., 2017]] ). AerChemMIP multi-model ensemble mean estimate a net-negative climate feedback from increases in lightning NO <sub>x</sub> in a warming world ( [[#Thornhill--2021a|Thornhill et al., 2021a]] ). All AerChemMIP models use a cloud-top height lightning parametrization that predicts increases in lightning with warming. However, a positive climate-lightning NO <sub>x</sub> feedback cannot be ruled out because of the dependence of the response to lightning parametrizations as discussed in Section 6.2.2.1.

'''Climate–methane lifetime feedback:''' Warmer and wetter climate will lead to increases in OH and oxidation rates leading to reduced atmospheric methane lifetime – a negative feedback ( [[#Naik--2013|Naik et al., 2013]] ; [[#Voulgarakis--2013|Voulgarakis et al., 2013]] ). Furthermore, since OH is in turn removed by methane, the climate-methane lifetime feedback will be amplified (Section 6.3.1; [[#Prather--1996|Prather, 1996]] ) . Based on the multi-model results of [[#Voulgarakis--2013|Voulgarakis et al. (2013)]] , α for climate-methane lifetime is estimated to be –0.030 ± 0.01 W m <sup>−2</sup> °C <sup>−1</sup> by [[#Heinze--2019|Heinze et al. (2019)]] . The assessed central value of α based on the AerChemMIP ensemble is within the range of this estimate but with greater uncertainty ( [[#Thornhill--2021a|Thornhill et al., 2021a]] ).

'''Climate–fire feedback:''' Wildfires are a major source of SLCF emissions (Section 6.2.2.6). Climate change has the potential to enhance fire activity (Sections 12.4 and 5.4.3.2) thereby enhancing SLCF emissions leading to feedbacks. Climate-driven increases in fire could potentially lead to offsetting feedback from increased ozone and decreased methane lifetime (due to increases in OH) leaving the feedback from aerosols to dominate with an uncertain net effect (e.g., [[#Landry--2015|Landry et al., 2015]] ). The AR5 assessment of climate-fire feedbacks included a value of α due to fire aerosols to be in the range of –0.03 to + 0.06 W m <sup>−2</sup> °C <sup>−1</sup> based on [[#Arneth--2010a|Arneth et al. (2010a)]] . A recent study estimates climate feedback due to fire aerosols to be greater than that due to BVOCs, with a value of α equal to –0.15 (–0.24 to –0.05) W m <sup>−2</sup> °C <sup>−1</sup> ( [[#Scott--2018|Scott et al., 2018]] ). Clearly, the assessment of fire-related non-CO <sub>2</sub> biogeochemical feedbacks is very uncertain because of limitations in the process understanding of the interactions between climate, vegetation and fire dynamics, and atmospheric chemistry and their representation in the current generation ESMs. Some AerChemMIP ESMs include the representation of fire dynamics but do not activate their interaction with atmospheric chemistry. Given the large uncertainty and lack of information from AerChemMIP ESMs, we do not include a quantitative assessment of climate-fire feedback for AR6.

In summary, climate-driven changes in emissions, atmospheric abundances or lifetimes of SLCFs are assessed to have an overall cooling effect, that is, a negative feedback parameter of –0.20 [–0.41 to + 0.01] W m <sup>−2</sup> °C <sup>−1</sup> , thereby reducing climate sensitivity ( [[IPCC:Wg1:Chapter:Chapter-7#7.4.2.5.1|Section 7.4.2.5.1]] ). This net feedback parameter is obtained by summing the assessed estimates for the individual feedback given in Table 6.8. ''confidence'' in the magnitude and the sign of most of the individual as well as the total non-CO <sub>2</sub> biogeochemical feedbacks remains ''low'' as evident from the large range in the value of α . This large uncertainty is attributed to the diversity in model representation of the relevant chemical and biogeochemical processes based on limited process-level understanding.

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