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

===== 5.2.1.4.2 Interannual variability in land–atmosphere CO <sub>2</sub> exchange =====

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The AR5 stated that the interannual variability of the atmospheric CO <sub>2</sub> growth rate is dominated by tropical land ecosystems. A set of new satellite measurements applied to assess the variability of the tropical land carbon balance since AR5 ( [[#Ciais--2013|Ciais et al., 2013]] ) confirm this statement, including satellite column CO <sub>2</sub> measurements, estimating the recent anomalous land–atmosphere CO <sub>2</sub> exchange induced by El Niño at continental scale (e.g., J. [[#Liu--2017|]] [[#Liu--2017|Liu et al., 2017]] ; [[#Palmer--2019|Palmer et al., 2019]] ), and L-band vegetation optical depth, estimating tropical above-ground biomass carbon stock changes ( [[#Fan--2019|Fan et al., 2019]] ). In addition, based on ''medium evidence'' and ''medium agreement'' between studies with DGVMs and atmospheric inversions, semi-arid ecosystems over the tropical zones have a larger contribution to interannual variability in global land–atmosphere CO <sub>2</sub> exchange than moist tropical forest ecosystems ( ''low'' to ''medium confidence'' ) ( [[#Poulter--2014|Poulter et al., 2014]] ; [[#Ahlstrom--2015|Ahlstrom et al., 2015]] ; [[#Piao--2020|Piao et al., 2020]] ).

Understanding the mechanisms driving interannual variability in the carbon cycle has the potential to provide insights into whether and to what extent the carbon cycle can affect the climate (carbon–climate feedback), with particular interests over the highly climate-sensitive tropical carbon cycle (e.g., [[#Cox--2013|Cox et al., 2013]] ; [[#Wang--2014|X. Wang et al., 2014]] ; [[#Fang--2017|Fang et al., 2017]] ; [[#Jung--2017|Jung et al., 2017]] ; [[#Humphrey--2018|Humphrey et al., 2018]] ; [[#Malhi--2018|Malhi et al., 2018]] ; see [[#5.4|Section 5.4]] ). Consistent findings from studies with atmospheric inversions, satellite observations and DGVMs (e.g., [[#Malhi--2018|Malhi et al., 2018]] ; [[#Rödenbeck--2018|Rödenbeck et al., 2018]] ) lead to ''high confidence'' that the tropical net land CO <sub>2</sub> sink is reduced under warmer and drier conditions, particularly during El Niño events. Interannual variations in tropical land-atmosphere CO <sub>2</sub> exchange are significantly correlated with anomalies of tropical temperature, water availability and terrestrial water storage (X. [[#Wang--2014|]] [[#Wang--2014|Wang et al., 2014]] ; [[#Jung--2017|Jung et al., 2017]] ; [[#Humphrey--2018|Humphrey et al., 2018]] ; [[#Piao--2020|Piao et al., 2020]] ), whose relative contribution are difficult to separate due to covariations between these climatic factors. At continental scale, the dominant climatic driver of interannual variations of tropical land-atmosphere CO <sub>2</sub> exchange was temperature variations (Figure 5.11; [[#Piao--2020|Piao et al., 2020]] ), which could partly result from the spatial compensation of the water availability effects on land-atmospheric CO <sub>2</sub> exchange ( [[#Jung--2017|Jung et al., 2017]] ).

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[[File:067816dc3276215cf4b949a44f046544 IPCC_AR6_WGI_Figure_5_11.png]]

'''Figure 5.11 |''' '''Interannual variation in detrended anomalies of the net land CO''' <sub>2</sub> '''sink and land surface air temperature during 1980–2019.''' Correlation coefficients between the net land CO <sub>2</sub> sink anomalies and temperature anomalies are show on the right bar plots. The net land CO <sub>2</sub> sink is estimated by four atmospheric inversions (blue) and 15 Dynamic Global Vegetation Models (DGVMs) (green), respectively ( [[#Friedlingstein--2020|Friedlingstein et al., 2020]] ). Solid blue and green lines show model mean detrended anomalies of the net land CO <sub>2</sub> sink. The ensemble mean of DGVMs is bounded by the 1– σ inter-model spread in each large latitude band (North 30°N–90°N, Tropics 30°S–30°N, South 90°S–30°S) and the globe. The ensemble mean of atmospheric inversions is bounded by model spread. For each latitudinal band, the anomalies of the net land CO <sub>2</sub> sink and temperature (orange) were obtained by removing the long-term trend and seasonal cycle. A 12-month running mean was taken to reduce high-frequency noise. The bars in the right panels show correlation coefficients between the net land CO <sub>2</sub> sink anomalies and temperature anomalies for each region. ** indicates P&lt;0.01; * indicates P&lt;0.05. The grey shaded area shows the intensity of El Niño–Southern Oscillation (ENSO) as defined by the Niño 3.4 index. Two volcanic eruptions (El Chichón and Mount Pinatubo) are indicated with light blue dashed lines. Temperature data are from the Climatic Research Unit (CRU), University of East Anglia ( [[#Harris--2014|Harris et al., 2014]] ). Anomalies were calculated following [[#Patra--2005|Patra et al. (2005)]] , but using a 12-month low-pass filter and detrended to obtain interannual variations. Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

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'''Cross-Chapter Box 5.1 | Interactions Between the Carbon and Water Cycles, Particularly Under Dro''' '''ught Conditions'''

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'''Contributors:''' Josep G. Canadell (Australia), Philippe Ciais (France), Hervé Douville (France), Sabine Fuss (Germany), Robert Jackson (United States of America), Annalea Lohila (Finland), Shilong Piao (China), Sonia I. Seneviratne (Switzerland), Sergio M. Vicente-Serrano (Spain), Sönke Zaehle (Germany)

This box presents an assessment of interactions between the carbon and water cycles that influence the dynamics of the biosphere and its interaction with the climate system. It also highlights carbon–water trade-offs arising from the use of land-based climate change mitigation options. Individual aspects of the interactions between the carbon and water cycles are addressed in separate chapters (Sections 5.2.1, 5.4.1, 8.2.3, 8.3.1, 8.4.1 and 11.6). The influence of wetlands and dams on methane emissions is assessed elsewhere (Sections 5.2.2, 5.4.7 and 8.3.1), as well as the consequences of permafrost thawing ( [[IPCC:Wg1:Chapter:Chapter-9#9.5.2|Section 9.5.2]] and Box 5.1) and/or increased flooding (Sections 8.4.1, 11.5 and 12.4) on wetland extent in the northern high latitudes and wet tropics.

'''Does elevated CO <sub>2</sub> alleviate the impacts of drought?'''

Increasing atmospheric CO <sub>2</sub> concentration enhances leaf photosynthesis and drives a partial closure of leaf stomata, leading to higher water-use efficiency (WUE) at the leaf canopy and ecosystem scales ( [[#Norby--2011|Norby and Zak, 2011]] ; [[#De%20Kauwe--2013|De Kauwe et al., 2013]] ; [[#Fatichi--2016|Fatichi et al., 2016]] ; [[#Knauer--2017|Knauer et al., 2017]] ; [[#Mastrotheodoros--2017|Mastrotheodoros et al., 2017]] ). Since AR5 (Box 6.3), a growing body of evidence from tree-ring and carbon isotopes further confirms an increase of plant water-use efficiency over decadal to centennial time scales, with some evidence for a stronger enhancement of photosynthesis compared to stomatal reductions ( [[#Frank--2015|Frank et al., 2015]] ; [[#Guerrieri--2019|Guerrieri et al., 2019]] ; [[#Adams--2020|Adams et al., 2020]] ).

Multiple lines of evidence suggest that WUE has increased in near proportionality to atmospheric CO <sub>2</sub> ( ''high confidence'' ) at a rate generally consistent with Earth system models (ESMs), despite variation in the WUE response to CO <sub>2</sub> ( [[#De%20Kauwe--2013|De Kauwe et al., 2013]] ; [[#Frank--2015|Frank et al., 2015]] ; [[#Keeling--2017|Keeling et al., 2017]] ; [[#Lavergne--2019|Lavergne et al., 2019]] ; [[#Walker--2021|Walker et al., 2021]] ). Both field-scale CO <sub>2</sub> enrichment experiments and process models show the effect of physiologically induced water savings, particularly under water-limiting conditions ( [[#De%20Kauwe--2013|De Kauwe et al., 2013]] ; [[#Farrior--2015|Farrior et al., 2015]] ; [[#Lu--2016|Lu et al., 2016]] ; [[#Roy--2016|Roy et al., 2016]] ). Plants can also benefit from reduced drought stress due to enhanced CO <sub>2</sub> without ecosystem-scale water savings ( [[#Jiang--2021|Jiang et al., 2021]] ). To some extent, this increased WUE offsets the effects of enhanced vapour pressure deficit (VPD) on plant transpiration ( [[#Bobich--2010|Bobich et al., 2010]] ; [[#Creese--2014|Creese et al., 2014]] ; [[#Jiao--2019|Jiao et al., 2019]] ), but will have limited effect on ameliorating plant water stress during extreme drought events ( [[#Xu--2016|Xu et al., 2016]] ; [[#Menezes-Silva--2019|Menezes-Silva et al., 2019]] ; L. [[#Liu--2020|]] [[#Liu--2020|]] [[#Liu--2020|Liu et al., 2020]] ), when leaf stomata are governed primarily by soil moisture ( [[#Roy--2016|Roy et al., 2016]] ).

Leaf stomata closure can have large effects on land freshwater availability because of reduced plant transpiration, leading in some regions to higher soil moisture and runoff ( [[#Roderick--2015|Roderick et al., 2015]] ; [[#Milly--2016|Milly and Dunne, 2016]] ; Y. [[#Yang--2019|Yang et al., 2019]] ). However, increased water availability is often not realized because other CO <sub>2</sub> physiological effects that enhance ecosystem evapotranspiration might offset the gains. These effects include plant growth and leaf area expansion ( [[#Ainsworth--2005|Ainsworth and Long, 2005]] ; [[#Ukkola--2016|Ukkola et al., 2016]] ; [[#McDermid--2021|McDermid et al., 2021]] ), lengthening of the vegetative growing season ( [[#Frank--2015|Frank et al., 2015]] ; [[#Lian--2021|Lian et al., 2021]] ), and the effects of stomatal closure on near-surface atmosphere that leads to increased air temperature and VPDs ( [[#Berg--2016|Berg et al., 2016]] ; [[#Vogel--2018|Vogel et al., 2018]] ; [[#Zhou--2019|Zhou et al., 2019]] ; [[#Grossiord--2020|Grossiord et al., 2020]] ).

ESMs show no consensus about the net hydrological response to physiological CO <sub>2</sub> effects. Some studies show water savings as a consequence of the CO <sub>2</sub> effects on leaf stomata closure ( [[#Swann--2016|Swann et al., 2016]] ; [[#Lemordant--2018|Lemordant et al., 2018]] ), while other studies show that increased leaf area offsets the gains from increased WUE ( [[#Mankin--2019|Mankin et al., 2019]] ). However, these projections are subject to ESM uncertainties to quantify transpiration ( [[#Lian--2021|Lian et al., 2021]] ), among them the correct representations of plant hydraulic architecture such as changes in xylem anatomical properties and deep rooting ( [[#Nie--2013|Nie et al., 2013]] ; L. [[#Liu--2020|]] [[#Liu--2020|]] [[#Liu--2020|Liu et al., 2020]] ).

In conclusion, it is ''very likely'' that elevated CO <sub>2</sub> leads to increased WUE at the leaf level, concurrent with enhanced photosynthesis. Increased CO <sub>2</sub> concentrations alleviate the effects of water deficits on plant productivity ( ''medium confidence'' ) but there is ''low confidence'' for its role under extreme drought conditions. There is ''low confidence'' that increased WUE by vegetation will substantially reduce global plant transpiration and diminish the frequency and severity of soil moisture and streamflow deficits associated with the radiative effect of higher CO <sub>2</sub> concentrations.

'''How does drought affect the terrestrial CO <sub>2</sub> sink?'''

Water availability controls the spatial distribution of photosynthesis – gross primary productivity (GPP) – over a larger part of the globe ( [[#Beer--2010|Beer et al., 2010]] ) and, at local scale, drought decreases GPP more than respiration ( [[#Schwalm--2012|Schwalm et al., 2012]] ) over most ecosystem types. This makes water availability a major climatic driver of variability in net ecosystem exchange ( [[#Jung--2017|Jung et al., 2017]] ; [[#Humphrey--2018|Humphrey et al., 2018]] ). In addition to suppressing photosynthesis, field evidence suggests that droughts reduce the land CO <sub>2</sub> sink, also through increasing forest mortality and promoting wildfire ( [[#Allen--2015|Allen et al., 2015]] ; [[#Brando--2019|Brando et al., 2019]] ; [[#Abram--2021|Abram et al., 2021]] ).

At the global scale, interannual variability in the atmospheric CO <sub>2</sub> growth rate and global-scale terrestrial water storage from satellite show that a lower global net land CO <sub>2</sub> sink is associated with below-average terrestrial water storage ( [[#Humphrey--2018|Humphrey et al., 2018]] ). Atmospheric inversions based on surface and satellite column CO <sub>2</sub> measurements show significant carbon release during drought events in pan-tropic areas ( [[#Phillips--2009|Phillips et al., 2009]] ; [[#Gatti--2014|Gatti et al., 2014]] ; J. [[#Liu--2017|]] [[#Liu--2017|Liu et al., 2017]] ; [[#Palmer--2019|Palmer et al., 2019]] ). Regional extreme droughts in the mid-latitudes also decrease GPP and land CO <sub>2</sub> sink ( [[#Ciais--2005|Ciais et al., 2005]] ; [[#Wolf--2016|Wolf et al., 2016]] ; W. [[#Peters--2020|]] [[#Peters--2020|Peters et al., 2020]] ; [[#Flach--2021|Flach et al., 2021]] ). Droughts are not compensated by equivalent wet anomalies because of the non-linear response of the terrestrial carbon uptake to soil moisture ( [[#Green--2019|Green et al., 2019]] ).

Uncertainties remain on the magnitude of sensitivity of the land carbon fluxes to droughts. Global studies indicate stronger control of soil moisture to variations in satellite proxies of GPP than VPD ( [[#Stocker--2019|Stocker et al., 2019]] ; L. [[#Liu--2020|]] [[#Liu--2020|]] [[#Liu--2020|Liu et al., 2020]] ). However, given that VPD increases exponentially with atmospheric warming, some studies suggest that VPD in stomatal regulation will become increasingly more important under a warmer climate ( [[#Novick--2016|Novick et al., 2016]] ; [[#Grossiord--2020|Grossiord et al., 2020]] ). It is difficult to isolate the relative contributions of warmer temperature, higher VPD and lower soil moisture. This is because land-atmosphere feedbacks cause a simultaneous increase of plant evaporative demand and of root zone water deficit impairing plant root uptake ( [[#Berg--2016|Berg et al., 2016]] ). These physiological responses can be further compounded by drought legacies ( [[#Anderegg--2015|Anderegg et al., 2015]] ), changes in structure and population dynamics due to forest mortality (McDowell et al., 2020), disturbances associated with drought (fire, insects damage; [[#Anderegg--2020|Anderegg et al., 2020]] ) and possible trade-offs between resistance and resilience (X. [[#Li--2020|]] [[#Li--2020|Li et al., 2020]] ). Nonetheless, ESMs suggest that increased drought effects under very high levels of global warming (about 4°C at the end of the 21st century) contribute to the reduced efficiency of the land sink ( [[#Green--2019|Green et al., 2019]] ).

In conclusion, there is ''high confidence'' that the global net land CO <sub>2</sub> sink is reduced on interannual scale when regional-scale reductions in water availability associated with droughts occur, particularly in tropical regions. There is also ''high confidence'' that the global land sink will become less efficient due to soil moisture limitations and associated drought conditions in some regions for high-emissions scenarios, specially under global warming above 4°C. However, there is ''low confidence'' on how these water cycle feedbacks will play out in lower emissions scenarios (at 2°C global warming or lower) due to uncertainties in regional rainfall changes and the balance between the CO <sub>2</sub> fertilization effect, through WUE, and the radiative impacts of greenhouse gases.

'''What are the limits of carbon dioxide removal from a water cycle perspective?'''

Carbon dioxide removal (CDR) options based on terrestrial carbon sinks will require the appropriation of significant amounts of water at the landscape level. Most mitigation pathways that seek to limit global warming to 1.5°C or less than 2°C require the removal of about 30 to 300 GtC from the atmosphere by 2100 ( [[#Rogelj--2018b|Rogelj et al., 2018b]] ). Bioenergy with carbon capture and storage (BECCS), and afforestation/reforestation are the dominant CDR options used in climate stabilization scenarios, implying large requirements for land and water ( [[#5.6|Section 5.6]] ; [[#Beringer--2011|Beringer et al., 2011]] ; [[#Boysen--2017b|Boysen et al., 2017b]] ; [[#Fajardy--2017|Fajardy and Mac Dowell, 2017]] ; [[#Jans--2018|Jans et al., 2018]] ; [[#Séférian--2018b|Séférian et al., 2018b]] ; [[#Yamagata--2018|Yamagata et al., 2018]] ; [[#Stenzel--2019|Stenzel et al., 2019]] ). A review of freshwater requirements for irrigating biomass plantations shows a range between 15 and 1250 km <sup>3</sup> per GtC of biomass harvest. This is equivalent to a water requirement of 99–8250 km <sup>3</sup> for the median BECCS deployment of around 3.3 GtC yr <sup>−1</sup> ( [[#Smith--2016|Smith et al., 2016]] ) in &lt;2°C-scenarios ( [[#Stenzel--2021|Stenzel et al., 2021]] ), assuming that biomass is converted to electricity, which is substantially less efficient than converting biomass to heat. These large ranges are the result of different assumptions about the type of biomass and yield improvements, management, and land availability. The use of alternative feedstocks, such as wastes, residues and algae, would lead to smaller water requirements ( [[#Smith--2019|Smith et al., 2019]] ).

Most of the water consumed in BECCS is used to grow the feedstock, with carbon capture and storage constituting a smaller portion across all crops ( [[#Rosa--2020|Rosa et al., 2020]] ), with an estimated evaporative loss of 260 km <sup>3</sup> yr <sup>−1</sup> for 3.3 GtC yr <sup>−1</sup> ( [[#Smith--2016|Smith et al., 2016]] ). The same authors also estimate water use for CDR through afforestation at 1040 km <sup>3</sup> yr <sup>−1</sup> for 3.3 GtC yr <sup>−1</sup> , including interception and transpiration, adjusted for the original land cover’s water use.

The impacts of different CDR options on the water cycle depend crucially on regional climate, prior land cover, and scale of deployment ( [[#Trabucco--2008|Trabucco et al., 2008]] ). Extensive irrigation for afforestation in drier areas will have larger downstream impacts than in wetter regions, with the difference in water use between the afforested landscapes and its previous vegetation determining the level of potential impacts on evapotranspiration and runoff ( [[#Jackson--2005|Jackson et al., 2005]] ; [[#Teuling--2017|Teuling et al., 2017]] ). Afforestation and reforestation sometimes enhances precipitation through atmospheric feedbacks such as increased convection, at least in the tropics ( [[#Ellison--2017|Ellison et al., 2017]] ) and the increase in precipitation can, in some regions, even cancel out the increased evapotranspiration ( [[#Li--2018|Li et al., 2018]] ).

In conclusion, extensive deployment of BECCS and afforestation/reforestation will require larger amounts of freshwater resources than used by the previous vegetation, altering the water cycle at regional scales ( ''high confidence'' ). Consequences of high water consumption on downstream uses, biodiversity, and regional climate depend on prior land cover, background climate conditions, and scale of deployment ( ''high confidence'' ). Therefore, a regional approach is required to determine the efficacy and sustainability of CDR projects.

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