Editing IPCC:AR6/WGI/Chapter-1 (section)

===== 1.5.3.1.3 Representation of biogeochemistry, including the carbon cycle =====

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Since AR5, more sophisticated land-use and land-cover change representations in ESMs have been developed to simulate the effects of land management on surface fluxes of carbon, water and energy ( [[#Lawrence--2016|Lawrence et al., 2016]] ), although the integration of many processes (e.g., wetland drainage, fire as a management tool) remains a challenge ( [[#Pongratz--2018|Pongratz et al., 2018]] ). The importance of nitrogen availability to limit the terrestrial carbon sequestration has been recognized (Section 5.4; [[#Zaehle--2014|Zaehle et al., 2014]] ) and so an increasing number of models now include a prognostic representation of the terrestrial nitrogen cycle and its coupling to the land carbon cycle ( [[#Jones--2016|Jones et al., 2016]] ; [[#Arora--2020|Arora et al., 2020]] ), leading to a reduction in uncertainty for carbon budgets (Section 5.1; [[#Jones--2020|Jones and Friedlingstein, 2020]] ). As was the case in CMIP5 ( [[#Ciais--2013|Ciais et al., 2013]] ), the land surface processes represented vary across CMIP6 models, with at least some key processes (fire, permafrost carbon, microbes, nutrients, vegetation dynamics, plant demography) absent from any particular ESM land model (Table 5.4). Ocean biogeochemical models have evolved to enhance the consistency of the exchanges between ocean, atmosphere and land, through riverine input and dust deposition ( [[#Stock--2014|Stock et al., 2014]] ; [[#Aumont--2015|Aumont et al., 2015]] ). Other developments include flexible plankton stoichiometric ratios ( [[#Galbraith--2015|Galbraith and Martiny, 2015]] ), improvements in the representation of nitrogen fixation ( [[#Paulsen--2017|Paulsen et al., 2017]] ), and the limitation of plankton growth by iron ( [[#Aumont--2015|Aumont et al., 2015]] ). Due to the long time scale of biogeochemical processes, how the models are initialized (spun up) strategies has been shown to affect their performance in AR5 ( [[#Séférian--2016|Séférian et al., 2016]] ).

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