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

==== 9.4.1.4 Projections Beyond 2100 ====

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The AR5 ( [[#Church--2013b|Church et al., 2013b]] ) assessed the contribution from Greenland to sea level projections in 2300 as 0.15 m SLE in low-emissions scenarios (about RCP2.6) and 0.31–1.19 m in high scenarios (approximately RCP6.0/RCP8.5). The SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ) did not update AR5 estimates, given ''limited evidence'' and ''low agreement'' from three new studies ( [[#Vizcaino--2015|Vizcaino et al., 2015]] ; [[#Calov--2018|Calov et al., 2018]] ; [[#Aschwanden--2019|Aschwanden et al., 2019]] ). Since SROCC, a new study gives a sea level contribution of 0.11 to 0.20 m in low-emissions scenarios and 0.61 to 1.29 m in high-emissions scenarios ( [[#Van%20Breedam--2020|Van Breedam et al., 2020]] ). The low-emissions projections by [[#Van%20Breedam--2020|Van Breedam et al. (2020)]] encompass AR5’s assessed contribution, while the high emissions projections are higher than that from AR5. The ‘optimal’ ensemble member of [[#Aschwanden--2019|Aschwanden et al. (2019)]] (see also [[#9.4.1.3|Section 9.4.1.3]] ) indicates that Greenland could contribute 0.25 m under RCP2.6 and 1.74 m under RCP8.5. Structured expert judgement ( [[#Bamber--2019|Bamber et al., 2019]] ) projects Greenland losses of 0.54 (0.28–1.28) m under 2°C warming and 0.97 (0.4–2.23) m under 5°C warming. These studies therefore agree that the AR5 and SROCC assessments are at the low end of the range of projections. In addition, observations suggest that Greenland Ice Sheet losses are tracking the upper range of AR5 projections (T. [[#Slater--2020|]] [[#Slater--2020|Slater et al., 2020]] ). Therefore, we update the ''likely'' range for the contribution of the Greenland Ice Sheet to global mean sea level (GMSL) by 2300 to 0.11–0.25 m under RCP2.6/SSP1-2.6 and 0.31–1.74 m under RCP8.5/SSP5-8.5. However, given the uncertainty in climatic drivers used to project ice-sheet change over the 21st century ( [[#Goelzer--2020|Goelzer et al., 2020]] ; [[#Hofer--2020|Hofer et al., 2020]] ; [[#Noël--2021|Noël et al., 2021]] ) and the large range in simulations since AR5 extending beyond 2100, we only have ''low confidence'' in the contribution to GMSL by 2300 and beyond.

The role of the elevation–mass feedback for future projections of Greenland can be assessed from paleo simulations. Ice-sheet model simulations of the Laurentide ( [[#Gomez--2015|Gomez et al., 2015]] ; [[#Gregoire--2016|Gregoire et al., 2016]] ) and Eurasian ( [[#Alvarez-Solas--2019|Alvarez-Solas et al., 2019]] ) ice sheets invoke at least some contribution to last glacial termination mass loss from SMB reduction, as a consequence of an elevation–mass balance feedback ( [[#Levermann--2016|Levermann and Winkelmann, 2016]] ). In a model spanning Meltwater Pulse 1A, this mechanism increased mass loss by approximately 66% ( [[#Gregoire--2016|Gregoire et al., 2016]] ) but in Last Interglacial simulations, the effect of this feedback is shown to depend on the surface scheme of the climate model employed ( [[#Plach--2019|Plach et al., 2019]] ). Given the agreement between theoretical analyses and paleo-ice-sheet model experiments, there is ''high confidence'' that the elevation–mass balance feedback is most relevant at multi-centennial and millennial time scales, consistent with future-focused studies (Aschwanden et al. 2019, Le Clec’h et al., 2019, [[#Gregory--2020|Gregory et al., 2020]] ).

The SROCC adopted the AR5 assessment that complete loss of Greenland ice, contributing about 7 m to sea level, over a millennium or more would occur for a sustained global mean surface temperature (GMST) between 1°C ( ''low confidence'' ) and 4°C ( ''medium confidence'' ) above pre-industrial levels. New studies since SROCC ( [[#Gregory--2020|Gregory et al., 2020]] ; [[#Van%20Breedam--2020|Van Breedam et al., 2020]] ) confirm this assessment (see also Figure 9.30). [[#Clark--2016|Clark et al. (2016)]] estimate a complete loss to take about 8000 years at 5.5°C and about 3000 years at 8.6°C. Based on the agreement between new and previous studies, there is therefore ''high confidence'' that the rate at which Greenland Ice Sheet commitment is realized depends on the amount of warming.

Accounting for more detailed feedbacks between the atmosphere and the ice sheet ( [[#Gregory--2020|Gregory et al., 2020]] ) found a gradual relationship between sustained global mean warming and the corresponding near-equilibrium ice-sheet volume, in contrast to a sharp threshold as found by [[#Robinson--2012|Robinson et al. (2012)]] . Rather than a climatically controlled tipping point for irreversible loss of the Greenland Ice Sheet, [[#Gregory--2020|Gregory et al. (2020)]] found a threshold of irreversibility linked to ice-sheet size, similar to previous work ( [[#Ridley--2010|Ridley et al., 2010]] ). The results of [[#Gregory--2020|Gregory et al. (2020)]] show that, if the ice sheet loses mass equivalent to about 3–3.5 m of sea level rise, it would not regrow to its present state, and 2 m of the sea level rise would be irreversible. The point in time at which the current ice sheet might reach this critical volume depends on oceanic and atmospheric conditions, ice dynamics, and climate–ice sheet feedbacks ( [[#Gregory--2020|Gregory et al., 2020]] ; [[#Van%20Breedam--2020|Van Breedam et al., 2020]] ). Therefore, projections differ in the magnitude and rate of temperature change to cross the threshold for irreversible loss. Projections from a large ensemble indicate that the mass threshold may be reached in as early as 400 years under extended RCP8.5 if warming reaches 10°C or more above present levels ( [[#Aschwanden--2019|Aschwanden et al., 2019]] ). In summary, there is ''high confidence'' in the existence of threshold behaviour of the Greenland Ice Sheet in a warmer climate; however, there is ''low agreement'' on the nature of the thresholds and the associated tipping points.

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'''Box 9.3 | Insights into Land Ice Evolution From Model Intercomparison Projects'''

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Projections of ice sheets and glaciers in AR5 (Church et al., 2013b) and SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ) were assessed by collecting single model studies – with the exception of glaciers in SROCC ( [[#Hock--2019b|Hock et al., 2019b]] ). Community benchmark experiments (ISMIP-HOM; [[#Pattyn--2008|Pattyn et al., 2008]] ) or Marine Ice Sheet Model Intercomparison Projects (MISMIP; [[#Pattyn--2012|Pattyn et al., 2012]] ); MISMIP3d, ( [[#Pattyn--2013|Pattyn and Durand, 2013]] ); MISMIP+ ( [[#Asay-Davis--2016|Asay-Davis et al., 2016]] ; [[#Cornford--2020|Cornford et al., 2020]] ) have substantially advanced ice-sheet modelling since AR5. Model Intercomparison Projects (MIPs) now inform projections of both ice sheets and glaciers: the Ice Sheet MIP for CMIP6 (ISMIP6; Sections 9.4.1.3 and 9.4.2.5), the Linear Antarctic Response MIP (LARMIP-2; [[#9.4.2.5|Section 9.4.2.5]] ) and GlacierMIP ( [[#9.5.1.3|Section 9.5.1.3]] ).

'''Regional forcing for land ice intercomparison projects'''

Simulations of ice sheets and glaciers are dependent on forcing provided by atmosphere and ocean models. Despite progress in representing processes, reducing biases and increasing resolution, regional and global models still have difficulties reproducing observed regional air temperature, surface mass balance (SMB) and ocean changes (Sections 9.4.1.2 and 9.4.2.2, and Atlas.11). An assessment of CMIP5 and CMIP6 climate models, as forcing for land ice models, has been undertaken ( [[#Walsh--2018|Walsh et al., 2018]] ; [[#Barthel--2020|Barthel et al., 2020]] ; [[#Marzeion--2020|Marzeion et al., 2020]] ; [[#Nowicki--2020b|Nowicki et al., 2020b]] ) with the aim of selecting the best available historical forcings and sampling potential regional future climate changes. Despite improvement in simulation of atmospheric forcing, persistent biases remain in CMIP5 and CMIP6, which reduces the fidelity of historical and future simulations of land ice.

Box 9.3

'''ISMIP6 initial state intercomparison projects'''

The ISMIP6 initial state intercomparison projects (initMIP) for the Greenland ( [[#Goelzer--2018|Goelzer et al., 2018]] ) and Antarctic ( [[#Seroussi--2019|Seroussi et al., 2019]] ) ice sheets were designed to understand the uncertainty in sea level projections resulting from the choice of initialization procedures used for projections of sea level ( [[#Nowicki--2016|Nowicki et al., 2016]] ). Participating modelling groups (Annex II) were free to decide on the initialization method used to bring ice-sheet models to a present-day state, with the effect of these choices captured in a control simulation (starting from the present-day state, with no further climate forcing applied), which measures intrinsic model drift. Compared to the earlier SeaRISE intercomparison project ( [[#Bindschadler--2013|Bindschadler et al., 2013]] ; [[#Nowicki--2013|Nowicki et al., 2013]] ), the modelled present-day ice sheets are in closer agreement with observations, and the model drift has been reduced ( [[#Goelzer--2018|Goelzer et al., 2018]] ; [[#Seroussi--2019|Seroussi et al., 2019]] ). Nonetheless, historical simulations remain challenging for ice-sheet models, due to limited ice-sheet observations prior to the satellite era and biases in the historical atmospheric and oceanic forcings from climate models ( [[#Nowicki--2018|Nowicki and Seroussi, 2018]] ). ISMIP6 and LARMIP-2 therefore did not provide a protocol for the historical runs used to bring the ice sheets to present day, nor criteria for sub-selecting models from the multi-model ensemble based on the ability to reproduce historical changes ( [[#Levermann--2020|Levermann et al., 2020]] ; [[#Nowicki--2020a|Nowicki et al., 2020a]] ).

'''ISMIP6 projections for the Greenland and Antarctic ice sheets'''

The ISMIP6 projection protocol ( [[#Nowicki--2016|Nowicki et al., 2016]] , 2020a) was designed to sample the uncertainty in future sea level due to climate scenarios (via the use of high- and low-emissions scenarios and multiple climate models), ice–ocean interactions and inland response to ice-shelf collapse, and ice-sheet model diversity. The participating ice-sheet models are listed in Annex II. For each ice sheet, forcing was selected ( [[#Barthel--2020|Barthel et al., 2020]] ) from the CMIP5 ( [[#Taylor--2012|Taylor et al., 2012]] ) and CMIP6 ( [[#Eyring--2016|Eyring et al., 2016]] ) models. Atmospheric forcing fields consisted of anomalies in SMB and surface air temperatures; these were generated directly from the CMIP models for the Antarctic Ice Sheet and downscaled using the regional climate model (MAR) for the Greenland Ice Sheet ( [[#Hofer--2020|Hofer et al., 2020]] ). To sample the uncertainty due to ocean forcings, models used either a model-specific scheme with the ISMIP6-provided oceanic dataset or a standard ISMIP6 approach. For the Greenland Ice Sheet, the oceanic dataset consists of thermal forcing (temperature minus freezing temperature) extrapolated into fjords and subglacial runoff. The standard approach uses timelines of tidewater glacier retreat ( [[#Slater--2019|D.A. Slater et al., 2019]] , 2020). For the Antarctic Ice Sheet, the oceanic dataset consists of salinity, thermal forcing and temperature added to an observationally derived climatology and extrapolated under ice shelves. The standard approach is a basal melt rate that depends quadratically on thermal forcing, adapted from [[#Favier--2019|Favier et al. (2019)]] , with two different calibrations (Figure 9.19, [[#Jourdain--2020|Jourdain et al., 2020]] ) that reproduce observed basal melt rates across Antarctica or Pine Island Glacier, respectively (Sections 9.4.2.2, 9.4.2.3). Antarctic ice-shelf disintegration datasets ( [[#Nowicki--2020a|Nowicki et al., 2020a]] ) assume that ice shelves disintegrate when annual surface melt reaches a threshold ( [[#Trusel--2015|Trusel et al., 2015]] ).

The ISMIP6 projections (Goelzer et al.,2020; [[#Seroussi--2020|Seroussi et al., 2020]] ; [[#Payne--2021|Payne et al., 2021]] ) are reported as experiment minus control and represent the sea level resulting from future climate change only. The control simulation, which has constant climate conditions starting in 2015 from the historical run, captures drift associated with the choices made for the initialization method and historical run. Subtraction of this control removes any long-term dynamic response of the ice sheet to pre-2015 climate change. This response has been assessed using dynamic discharge derived from observations over the last 40 years ( [[#Mouginot--2019|Mouginot et al., 2019]] ; [[#Rignot--2019|Rignot et al., 2019]] ), under an assumption that it persists at the past rate until 2100, rather than diminishing. The dynamic response to historical forcing is estimated as 0.19 ± 0.10 mm yr <sup>–1</sup> for the Greenland Ice Sheet ( [[#9.4.1.3|Section 9.4.1.3]] ) and 0.33 ± 0.16 mm yr <sup>–1</sup> for the Antarctic Ice Sheet ( [[#9.4.2.5|Section 9.4.2.5]] ). Over the period 2015–2100, this leads to an additional sea level contribution of 1.7 cm for Greenland and 2.8 cm for Antarctica.

'''LARMIP-2 projections for the Antarctic Ice Sheet'''

LARMIP-2 is focused on the uncertainty in the ocean forcing and associated ice-shelf melting ( [[#Levermann--2014|Levermann et al., 2014]] , 2020) with the majority of the models also participating in ISMIP6 (Annex II). The experiments start from present day and impose an additional basal ice-shelf melting of 8 m yr <sup>–1</sup> at the beginning of the 100-year simulation. A control run is used to remove drift resulting from initialization. The time derivative of the ice-sheet response yields a linear response function, which is then convoluted with a forcing of basal shelf melt time series for five Antarctic regions. The forcing time series for RCP2.6, 4.5, 6.0 and 8.5 were obtained from a random combination of global mean temperature for each Representative Concentration Pathway (RCP) from MAGICC-6.0 ( [[#Meinshausen--2011|Meinshausen et al., 2011]] ), a scaling factor and time delay for the relationship between global surface air temperature and subsurface ocean warming in a given sector of the Southern Ocean from one of 19 CMIP5 models ( [[#Taylor--2012|Taylor et al., 2012]] ) and a basal melting sensitivity from the interval [7–16] m yr <sup>–1</sup> °C <sup>–1</sup> to convert the regional subsurface warming into basal ice-shelf melting. This process is repeated 20,000 times to obtain a probability distribution of the sea level contribution for five Antarctic sectors. The linear response framework captures complex temporal responses of the ice sheets resulting from an increase in basal ice-shelf melting, but neglects the response to SMB and any self-dampening or self-amplifying processes, such as marine ice shelf instability (MISI). The LARMIP-2 method is applied to temperature projections for the Shared Socio-economic Pathways (SSPs; Supplementary Material 7.SM.2) and an estimate of SMB change from the AR5 parametric Antarctic Ice Sheet SMB model ( [[#Church--2013b|Church et al., 2013b]] ) is added to the results (Sections 9.4.2.4, 9.4.2.5 and 9.6.3.2). It is not necessary to add a long-term dynamic response to the LARMIP-2 projections, as this is incorporated in the basal melt time series.

'''GlacierMIP projections'''

GlacierMIP ( [[#Marzeion--2020|Marzeion et al., 2020]] ) was designed to estimate the glacier contribution to sea level rise, including from peripheral glaciers in Greenland and Antarctica that can be considered to be dynamically decoupled, or entirely separate, from the ice sheets. Glacier models are described in Annex II. Initial conditions were based on Randolph Glacier Inventory Version 6 ( [[#RGI%20Consortium--2017|RGI Consortium, 2017]] ) and initial ice thickness and volume were provided from an update of [[#Huss--2012|Huss and Farinotti (2012)]] , although some glacier models used their own estimates. Forcings were taken from 10 different CMIP5 general circulation models, selected based on availability of multiple RCPs, the choice in a previous model intercomparison ( [[#Hock--2019a|Hock et al., 2019a]] ), and performance in glacier-covered regions according to [[#Walsh--2018|Walsh et al. (2018)]] . In addition, two global glacier models performed the same experiment with 13 CMIP6 models ( [[#9.5.1.3|Section 9.5.1.3]] ).

'''Use of an emulator with ISMIP6 and GlacierMIP projections'''

The ISMIP6 and GlacierMIP projections are primarily based on a limited number of CMIP5 RCPs and CMIP6 SSPs, and a limited sampling of ice–ocean interaction parameters and ice-shelf collapse simulations. Emulators provide a method for expanding these projections to a range of SSPs with more comprehensive sampling of climate, ice-sheet and glacier modelling uncertainties. Sections 9.4.1.3, 9.4.2.5 and 9.5.1.3 show estimates from the emulator of [[#Edwards--2021|Edwards et al. (2021)]] . This is a Gaussian Process, rather than a physically based (Cross-Chapter Box 7.1) model derived from the ISMIP6 and GlacierMIP simulations; projections use distributions of global surface air temperature (GSAT) from the two-layer emulator (Supplementary Material 7.SM.2) and ice-sheet parameters as inputs, and include estimates of the emulator uncertainty. Therefore, probability intervals are not inflated by a further factor, as is often the case for multi-model ensemble projections, to account for missing uncertainties ( [[#9.6.3.2|Section 9.6.3.2]] ). The emulator is used in [[#9.6.3|Section 9.6.3]] to provide projections of the land ice contribution to sea level that are fully consistent with each other, ocean heat content, and the assessed equilibrium climate sensitivity and projections of GSAT across the entire report.

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