Editing IPCC:AR6/WGI/Chapter-7 (section)

===== 7.4.2.5.2 Biogeophysical feedbacks =====

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Biogeophysical feedbacks are associated with changes in the spatial distribution and/or biophysical properties of vegetation, induced by surface temperature change and attendant hydrological cycle change. These vegetation changes can alter radiative fluxes directly via albedo changes, or via surface momentum or moisture flux changes and hence changes in cloud properties. However, the direct physiological response of vegetation to changes in CO <sub>2</sub> , including changes in stomatal conductance, is considered part of the CO <sub>2</sub> effective radiative forcing rather than a feedback ( [[#7.3.2.1|Section 7.3.2.1]] ). The time scale on which vegetation responds to climate change is relatively uncertain but can be from decades to hundreds of years ( [[#Willeit--2014|Willeit et al., 2014]] ), and could occur abruptly or as a tipping point (Sections 5.4.9.1.1, 8.6.2.1 and 8.6.2.2); equilibrium only occurs when the soil system and associated nutrient and carbon pools equilibrate, which can take millennia ( [[#Brantley--2008|Brantley, 2008]] ; [[#Sitch--2008|Sitch et al., 2008]] ). The overall effects of climate-induced vegetation changes may be comparable in magnitude to those from anthropogenic land-use and land-cover change ( [[#Davies-Barnard--2015|Davies-Barnard et al., 2015]] ). Climate models that include a dynamical representation of vegetation (e.g., [[#Reick--2013|Reick et al., 2013]] ; [[#Harper--2018|Harper et al., 2018]] ) are used to explore the importance of biogeophysical feedbacks ( [[#Notaro--2007|Notaro et al., 2007]] ; [[#Brovkin--2009|Brovkin et al., 2009]] ; [[#O’ishi--2009|O’ishi et al., 2009]] ; [[#Port--2012|Port et al., 2012]] ; [[#Willeit--2014|Willeit et al., 2014]] ; [[#Alo--2017|Alo and Anagnostou, 2017]] ; W. [[#Zhang--2018|]] [[#Zhang--2018|]] [[#Zhang--2018|Zhang et al., 2018]] ; [[#Armstrong--2019|Armstrong et al., 2019]] ). In AR5, it was discussed that such model experiments predicted that expansion of vegetation in the high latitudes of the Northern Hemisphere would enhance warming due to the associated surface-albedo change, and that reduction of tropical forests in response to climate change would lead to regional surface warming, due to reduced evapotranspiration (M. [[#Collins--2013|]] [[#Collins--2013|Collins et al., 2013]] ), but there was no assessment of the associated feedback parameter. The SRCCL stated that regional climate change can be dampened or enhanced by changes in local land cover, but that this depends on the location and the season; however, in general the focus was on anthropogenic land-cover change, and no assessment of the biogeophysical feedback parameter was carried out. There are also indications of a marine biogeophysical feedback associated with surface-albedo change due to changes in phytoplankton ( [[#Frouin--2002|Frouin and Iacobellis, 2002]] ; [[#Park--2015|Park et al., 2015]] ), but there is not currently enough evidence to quantitatively assess this feedback.

Since AR5, several studies have confirmed that a shift from tundra to boreal forests and the associated albedo change leads to increased warming in Northern Hemisphere high latitudes ( ''high confidence'' ) ( [[#Willeit--2014|Willeit et al., 2014]] ; W. [[#Zhang--2018|]] [[#Zhang--2018|]] [[#Zhang--2018|Zhang et al., 2018]] ; [[#Armstrong--2019|Armstrong et al., 2019]] ). However, regional modelling indicates that vegetation feedbacks may act to cool climate in the Mediterranean ( [[#Alo--2017|Alo and Anagnostou, 2017]] ), and in the tropics and subtropics the regional response is in general not consistent across models. On a global scale, several modelling studies have either carried out a feedback analysis ( [[#Stocker--2013|Stocker et al., 2013]] ; [[#Willeit--2014|Willeit et al., 2014]] ) or presented simulations that allow a feedback parameter to be estimated ( [[#O’ishi--2009|O’ishi et al., 2009]] ; [[#Armstrong--2019|Armstrong et al., 2019]] ), in such a way that the physiological response can be accounted for as a forcing rather than a feedback. The central estimates of the biogeophysical feedback parameter from these studies range from close to zero ( [[#Willeit--2014|Willeit et al., 2014]] ) to +0.13 W m <sup>–2</sup> °C <sup>–1</sup> ( [[#Stocker--2013|Stocker et al., 2013]] ). An additional line of evidence comes from the mid-Pliocene warm period (MPWP, Chapter 2, Cross-Chapter Box 2.1), for which paleoclimate proxies provide evidence of vegetation distribution and CO <sub>2</sub> concentrations. Model simulations that include various combinations of modern versus MPWP vegetation and CO <sub>2</sub> allow an associated feedback parameter to be estimated, as long as account is also taken of the orographic forcing ( [[#Lunt--2010|Lunt et al., 2010]] , 2012b). This approach has the advantage over pure modelling studies in that the reconstructed vegetation is based on (paleoclimate) observations, and is in equilibrium with the CO <sub>2</sub> forcing. However, there are uncertainties in the vegetation reconstruction in regions with little or no proxy data, and it is uncertain how much of the vegetation change is associated with the physiological response to CO <sub>2</sub> . This paleoclimate approach gives an estimate for the biogeophysical feedback parameter of +0.3 W m <sup>–2</sup> °C <sup>–1</sup> .

Given the limited number of studies, we take the full range of estimates discussed above for the biogeophysical feedback parameter, and assess the ''very likely'' range to be from 0.0 to +0.3 W m <sup>–2</sup> °C <sup>–1</sup> , with a central estimate of +0.15 W m <sup>–2</sup> °C <sup>–1</sup> ( ''low confidence'' ). Although this assessment is based on evidence from both models and paleoclimate proxies, and the studies above agree on the sign of the change, there is nonetheless ''limited evidence'' . Higher confidence could be obtained if there were more studies that allowed calculation of a biogeophysical feedback parameter (particularly from paleoclimates), and if the partitioning between biogeophysical feedbacks and physiological forcing were clearer for all lines of evidence.

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