Editing IPCC:AR6/SROCC/Chapter-4 (section)

===== 4.2.3.1.2 Antarctica =====

Unlike Greenland, most of the AIS margin terminates in the ocean. The AIS also contains almost eight times more glacial ice above flotation than Greenland, and nearly half of this ice is marine-based, that is, grounded on bedrock hundreds of metres (or more) below sea level (Figure 4.7; Fretwell et al., 2013 <sup>[[#fn:r448|448]]</sup> ). In places where the subglacial bedrock slopes downward away from the coast (reverse-sloped), the marine-based glacial ice is susceptible to dynamical instabilities (Weertman, 1974 <sup>[[#fn:r449|449]]</sup> ; Schoof, 2007b <sup>[[#fn:r450|450]]</sup> ; Pollard et al., 2015 <sup>[[#fn:r451|451]]</sup> ) that can contribute rapid ice loss (Cross-Chapter Box 8 in Chapter 3). The instabilities can be triggered by the loss or thinning of ice shelves through changes in the surrounding ocean and increased sub-ice melt rates and changes in the overlying atmosphere affecting SMB and surface meltwater production. Much progress has been made since AR5 in the understanding of these processes, but their representation in continental-scale models continue to be heavily parameterised in most cases. Complex interactions between the ice sheet, ocean, atmosphere and underlying bedrock also remain difficult to simulate collectively.

In contrast to Greenland, Antarctica’s recent contribution to SLR has been dominated by ice-dynamical processes rather than changes in SMB (Mouginot et al., 2014 <sup>[[#fn:r452|452]]</sup> ; Rignot et al., 2014 <sup>[[#fn:r453|453]]</sup> ; Scheuchl et al., 2016 <sup>[[#fn:r454|454]]</sup> ; Shen et al., 2018 <sup>[[#fn:r455|455]]</sup> ; The IMBIE team, 2018). Since AR5, it has become increasingly evident that this ice loss is being driven by sub-ice oceanic melt (thinning) of ice shelves (Paolo et al., 2015 <sup>[[#fn:r456|456]]</sup> ; Wouters et al., 2015) and the resulting loss of back stress (buttressing) that impedes the seaward flow of grounded ice upstream. Elevated melt rates are generally associated with the increased presence of warm Circumpolar Deep Water (CDW) on the continental shelf (Khazendar et al., 2016 <sup>[[#fn:r457|457]]</sup> ). Dynamic ice loss driven by ocean changes have also been observed on the East Antarctic margin (Li et al., 2016 <sup>[[#fn:r458|458]]</sup> ; Shen et al., 2018 <sup>[[#fn:r459|459]]</sup> ). This is an important development, because East Antarctica contains much more ice than West Antarctica, so even minor changes there could make major contributions to sea level in the future.

Several of West Antarctica’s major outlet glaciers, including Pine Island Glacier, and Thwaites Glacier in the Amundsen Sea (Figure 4.8) have grounding lines currently retreating on retrograde bedrock (Rignot et al., 2014 <sup>[[#fn:r460|460]]</sup> ). Thwaites Glacier is particularly important (Figure 4.8), because it extends into the interior of the WAIS, where the bed is &gt;2000 m below sea level in places. By itself, the Thwaites drainage area contains the equivalent of ~0.4 m GMSL (Holt et al., 2006 <sup>[[#fn:r461|461]]</sup> ; Millan et al., 2017 <sup>[[#fn:r462|462]]</sup> ), but loss of the glacier could have a destabilising impact on the entire WAIS (Feldmann and Levermann, 2015 <sup>[[#fn:r463|463]]</sup> ). The WAIS contains enough ice to raise GMSL by ~3.4 m (Fretwell et al., 2013 <sup>[[#fn:r464|464]]</sup> ). Since AR5, a number of ice sheet modelling studies have focussed on limited fractions of Antarctica and so are not included in estimating the SROCC Antarctic contribution to GMSL (see Section 4.2.3.2). However, these studies do allow an assessment of the potential for persistent and increasing ice loss, and the role of the marine ice sheet instability (MISI, see Cross-Chapter Box 8 in Chapter 3).

Joughin et al. (2014) <sup>[[#fn:r466|466]]</sup> modelled the response of the Thwaites Glacier to a combination of elevated sub-ice melt rates and increased precipitation and found persistent future retreat, despite either the partial compensation of increased accumulation or a future reduction in melt. Sub-ice melt rates sustained at current levels were found to generate &gt;1 mm yr –1 equivalent GMSL rise within a millennium. Higher melt rates and an assumed weak ice shelf triggered rapid retreat within a few centuries. Similarly, Waibel et al. (2018) used the BISICLES ice sheet model (Cornford et al., 2015 <sup>[[#fn:r465|465]]</sup> ) to investigate the potential for self-sustained retreat of Thwaites Glacier, by incrementally increasing sub-ice melt rates until retreat is triggered, and then returning to pre-retreat melt rates. Consistent with Joughin et al. (2014) <sup>[[#fn:r466|466]]</sup> , they found self-sustained retreat of Thwaites Glacier through MISI. Most uncertainty in their future WAIS simulations arises from uncertainties in the long-term response of Thwaites Glacier (Figure 4.8). Nias et al. (2016) demonstrated model sensitivity of Thwaites Glacier to poorly resolved bedrock boundary conditions (small scale topography), pointing to the need for better geophysical information to reduce model uncertainty (Schlegel et al., 2018 <sup>[[#fn:r468|468]]</sup> ). Arthern and Williams (2017) <sup>[[#fn:r469|469]]</sup> used adaptive mesh techniques, but with a different formulation than Cornford et al., (2015) <sup>[[#fn:r470|470]]</sup> , to simulate the future response of Amundsen Sea outlet glaciers. They demonstrate a sustained, but slow future retreat when sub-ice melt is maintained at current rates, and a direct relationship between the strength of ocean forcing and the pace of MISI-driven ice loss. Yu et al. (2018) simulate future Thwaites retreat using a range of model formulations with varying approximations of ice stress balance, different ocean melt schemes, and different basal friction laws. Like Arthern and Williams (2017) they find model-specific dependencies in the rate of ice loss, but all of their simulations demonstrate sustained ice loss and a bathymetrically controlled future acceleration.

Like Thwaites, the neighbouring Pine Island Glacier (PIG) has also been thinning and retreating at an accelerating rate in recent decades, in response to incursions of warm CDW in the waters underlying the glacier’s ice shelf. These incursions of CDW are controlled in part by sea floor bathymetry and climatic variability (Dutrieux et al., 2014 <sup>[[#fn:r471|471]]</sup> ). Favier et al. (2014) used three models with differing formulations to simulate PIG’s response to elevated sub-ice melt. Consistent with modelling of Thwaites Glacier (Joughin et al., 2014 <sup>[[#fn:r473|473]]</sup> ), all three models demonstrate sustained future retreat at an increasing rate, as the glacier backs onto its retrograde bed. Only one of the three models used by Favier et al. (2014) demonstrates the possibility that the glacier can recover if sub-ice melt rates are reduced enough to allow the ice shelf to thicken and pin on bathymetric features to provide buttressing. These results highlight the long-term commitment to marine-based ice loss.

While limited to 50 year simulations, Seroussi et al. (2017) <sup>[[#fn:r474|474]]</sup> provide the first interactively coupled ice-ocean model simulations of Thwaites Glacier at a high spatial resolution. Their model demonstrates MISI-like grounding line retreat at a rate of ~1 km yr –1 , comparable to observations between 1992 and 2011 (Rignot et al., 2014). The retreat is interrupted when the main trunk of the glacier stabilises on a bathymetric ridge, ~20 km upstream of the present-day grounding line (Figure 4.8), but due to the short duration of the simulation, the long-term potential for additional retreat into the interior of the ice sheet is not captured.

Despite the use of independent model formulations, forcings, and different geographic settings, the overall agreement among these highly-resolved regional modelling studies and their ability to capture current rates of retreat, increases confidence since AR5 that observed retreat of Amundsen Sea outlet glaciers is driven by processes consistent with MISI theory ( ''medium confidence'' ), will continue ( ''medium confidence'' ), and could accelerate ( ''medium confidence'' ).

Observations of rapid bedrock uplift in the Amundsen Sea, low viscosity of the underlying mantle, and short GIA response times to glacial unloading suggest ice-Earth interactions could be important there (Barletta et al., 2018 <sup>[[#fn:r475|475]]</sup> ). Bedrock uplift and reduced gravitational attraction between the ice sheet and ocean as an ice margin loses mass reduces RSL at the grounding line, promoting stability and providing a negative feedback on retreat (Adhikari et al., 2014 <sup>[[#fn:r476|476]]</sup> ; Gomez et al., 2015 <sup>[[#fn:r477|477]]</sup> ). Using a high-resolution ice sheet-Earth model, Larour et al. (2019) showed that long-term future retreat of Amundsen Sea grounding lines are slowed by these processes, but the effect is found to be minimal until after ~2250. This agrees with other recent modelling accounting for ice-Earth interactions, including the viscoelastic Earth response to changing ice loads and self-gravitation (Gomez et al., 2015 <sup>[[#fn:r478|478]]</sup> ; Konrad et al., 2015 <sup>[[#fn:r479|479]]</sup> ; Pollard et al., 2017 <sup>[[#fn:r480|480]]</sup> ). These studies also showed a small negative feedback on future retreat over the next several centuries, particularly under strong climate forcing. However, the viscosity structure of the Earth under the AIS is not well resolved, and lateral variations in Earth structure could impact these results (Hay et al., 2017 <sup>[[#fn:r481|481]]</sup> ). Based on these consistent model results, and new observational evidence that PIG has been retreating on reverse-sloped bedrock for a half-century or more (Smith et al., 2017), ice-Earth interactions are not expected to substantially slow GMSL rise from marine-based ice in Antarctica over the 21st century ( ''medium confidence'' ). However, these processes could become important for GMSL rise on multi-century and longer time scales.

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'''Figure 4.8'''

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'''Figure 4.8 | Processes affecting the Thwaites Glacier in the Amundsen Sea sector of Antarctica (adapted from Scambos et al., 2017). The grounding line is currently retreating on reverse-sloped bedrock at a water depth of ~600 m (Joughin et al., 2014; Mouginot et al., 2014). The glacier terminus is ~120 km wide, widens upstream, and […]'''
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[[File:ce6dc95edf37fa50cc08aa9551b90b2d IPCC-SROCC-CH_4_8-3000x1028.jpg]]

Figure 4.8 | Processes affecting the Thwaites Glacier in the Amundsen Sea sector of Antarctica (adapted from Scambos et al., 2017). The grounding line is currently retreating on reverse-sloped bedrock at a water depth of ~600 m (Joughin et al., 2014 <sup>[[#fn:r483|483]]</sup> ; Mouginot et al., 2014 <sup>[[#fn:r484|484]]</sup> ). The glacier terminus is ~120 km wide, widens upstream, and is minimally buttressed by a laterally discontinuous ~40 km long ice shelf. The remaining shelf is thinning in response to warm, sub-shelf incursions of circumpolar deep water (CDW), with melt rates up 200 m yr–1 near the groundling line in some places (Milillo et al., 2019 <sup>[[#fn:r485|485]]</sup> ). The bathymetry upstream of the grounding zone is complex, but it generally slopes downward into a deep basin, up to 2000 m below sea level under the centre of the West Antarctic Ice Sheet (WAIS) (far left), making the glacier vulnerable to marine ice sheet instabilities (Cross-Chapter Box 8 in Chapter 3).

Atmospheric forcing is also becoming increasingly recognised to be an important factor for the future of the AIS. A sustained (15 days) melt event over the Ross Sea sector of the WAIS in 2016 illustrated both the connectivity of Antarctica to the tropics and El Niño, and the possibility that future meltwater production on ice shelf surfaces could change in the near future (Nicolas et al., 2017 <sup>[[#fn:r487|487]]</sup> ). This was highlighted by Trusel et al. (2015) <sup>[[#fn:r488|488]]</sup> , who evaluated the future expansion of surface meltwater using the snow component in the RACMO2 regional atmospheric model (Kuipers Munneke et al., 2012 <sup>[[#fn:r489|489]]</sup> ) and output from CMIP5 GCMs. Under RCP8.5, they found a substantial expansion of surface meltwater production on ice shelves late in the 21st century that exceed melt rates observed before the 2002 collapse of the Larsen B Ice Shelf. Surface meltwater is important for both ice dynamics and SMB due to its potential to reduce albedo, saturate the firn layer, deepen surface crevasses, and to cause flexural stresses that can contribute to ice shelf break-up (hydrofracturing) (Banwell et al., 2013 <sup>[[#fn:r490|490]]</sup> ; Kuipers Munneke et al., 2014 <sup>[[#fn:r491|491]]</sup> ). The presence of surface meltwater does not necessarily lead to immediate ice shelf collapse (Bell et al., 2017b <sup>[[#fn:r492|492]]</sup> ; Kingslake et al., 2017 <sup>[[#fn:r493|493]]</sup> ), although surface meltwater was a precursor on ice shelves which have collapsed (Scambos et al., 2004 <sup>[[#fn:r494|494]]</sup> ; Banwell et al., 2013 <sup>[[#fn:r495|495]]</sup> ). This dichotomy illustrates the uncertain role of meltwater and the need for additional study. When and if melt rates will be sufficiently high in future warming scenarios to trigger widespread hydrofracturing is a key question, because the loss of ice shelves is associated with the onset of marine ice sheet instabilities (Cross-chapter Box 8 in Chapter 3). Based on the single modelling study by Trusel et al. (2015) <sup>[[#fn:r496|496]]</sup> , it is not expected that widespread ice shelf loss will occur before the end of the 21st century, but due to limited observations and modelling to date, there is ''low confidence'' in this assessment.

Continental-scale ice sheet simulations are ultimately required to provide projections of future GMSL rise from Antarctica. At this spatial scale, most models rely on simplifying approximations of the equations representing three-dimensional ice flow, and in some cases they parameterise ice flow at the grounding line (Schoof, 2007b <sup>[[#fn:r497|497]]</sup> ) to improve computational efficiency. Such simplifications are necessary to allow long simulations that can be validated against geological information, in addition to modern observations (Briggs et al., 2013 <sup>[[#fn:r498|498]]</sup> ; Pollard et al., 2016), however processes related to MISI are best represented at high spatial resolution and without simplifications of the underlying physics (Pattyn et al., 2013 <sup>[[#fn:r499|499]]</sup> ; Reese et al., 2018c <sup>[[#fn:r500|500]]</sup> ).

Various ice sheet model formulations, including the choice of grounding line parameterisations and basal sliding schemes can strongly affect model response to a given forcing (Brondex et al., 2017 <sup>[[#fn:r501|501]]</sup> ; Pattyn, 2017 <sup>[[#fn:r502|502]]</sup> ), although sophisticated statistical methodologies have been increasingly used since AR5 to quantitatively gauge model uncertainty (Bulthuis et al., 2019 <sup>[[#fn:r503|503]]</sup> ; Edwards et al., 2019 <sup>[[#fn:r504|504]]</sup> ). Accurate atmospheric forcing (SMB) and sub-ice melt are also prerequisite to resolving the time-evolving dynamics of the system, with sub-ice melt rates being particularly important (Schlegel et al., 2018 <sup>[[#fn:r505|505]]</sup> ). An important ongoing deficiency is the lack of ice-ocean coupling in most continental-scale studies, which remains too computationally expensive to simulate the ocean at the spatial scales necessary to capture circulation in ice shelf cavities and time-evolving ice-ocean interactions (Donat-Magnin et al., 2017 <sup>[[#fn:r506|506]]</sup> ; Hellmer et al., 2017 <sup>[[#fn:r507|507]]</sup> ). Instead, melt rates are often parameterised as a depth dependent function of nearby ocean temperature derived from offline ocean models, but the lack of ice-ocean interaction can seriously overestimate melt rates in some settings (de Rydt et al., 2015; Seroussi et al., 2017 <sup>[[#fn:r508|508]]</sup> ). Approaches that link offline ocean temperatures with efficient box models of the circulation in ice shelf cavities have been developed (Lazeroms et al., 2018 <sup>[[#fn:r509|509]]</sup> ; Reese et al., 2018a <sup>[[#fn:r510|510]]</sup> ) and used in long-term future simulations (Bulthuis et al., 2019 <sup>[[#fn:r511|511]]</sup> ), although they still require uncoupled ocean models to provide time-evolving ocean conditions outside the cavities.

Ritz et al. (2015) <sup>[[#fn:r512|512]]</sup> used a hybrid physical-statistical modelling approach, whereby the timing of MISI onset is determined statistically rather than physically. They estimated probabilities of MISI onset in eleven different sectors around the ice sheet margin based on observations of continent-wide retreat and thinning over the last few decades, and expected future climate change following an IPCC SRES A1B emission scenario only. In places where MISI is projected to begin, the persistence and rate of grounding-line retreat is parameterised as a function of the local bedrock topography (slope), ice thickness at grounding lines following Schoof (2007b), and basal friction. This study represents a statistically rigorous approach in which model parameters are based on a synthesis of observations and projected surface and sub-shelf forcing, rather than coming directly from climate and ocean models. However, the model calibrations rely on recent observations, which may not provide adequate guidance under warmer future conditions.

Levermann et al. (2014) <sup>[[#fn:r513|513]]</sup> use simplified emulations of temperature increase in order to estimate both SMB and sub-ice melt (including a parameterised delay for ocean warming) to determine the linearised response of five ice sheet models calibrated against recent rates of retreat. Substantial uncertainty arises from the different model treatments of grounding line dynamics and ice shelves. However, they conclude that the single greatest source of uncertainty stems from the external forcing. Golledge et al. (2015) <sup>[[#fn:r514|514]]</sup> used PISM (Parallel Ice Sheet Model; Winkelmann et al., 2011 <sup>[[#fn:r515|515]]</sup> ) to simulate the future response of the AIS to RCP emission scenarios. PISM links grounded, streaming, and shelf flow, and has freely evolving grounding lines required to capture MISI. PISM’s parameterised treatment of sub-ice melt applies melt under partially grounded grid cells (Feldmann and Levermann, 2015 <sup>[[#fn:r516|516]]</sup> ), making the model sensitive to subsurface ocean warming, although the validity of this approach is contested (Arthern and Williams, 2017 <sup>[[#fn:r517|517]]</sup> ; Seroussi and Morlighem, 2018 <sup>[[#fn:r518|518]]</sup> ; Yu et al., 2018 <sup>[[#fn:r519|519]]</sup> ). While providing alternative outcomes with the two basal melt rate parameterisations, the model is not calibrated to observations and doesn’t provide a probability distribution. In a subsequent study Golledge et al. (2019) <sup>[[#fn:r520|520]]</sup> used PISM, but with updated RCP climate forcing based on CMIP5 GCMs, and with sub-ice ocean melt calibrated to observations. An offline, intermediate-complexity climate model was used to capture global ice-climate feedbacks ignored in most other studies, but the simulations only include RCP4.5 and RCP8.5 and do not extend beyond 2100. Accounting for the climatic effects of meltwater input from Greenland and Antarctica nearly doubled their estimates of Antarctic’s contribution to GMSL in 2100 from 2.4 cm to 4.6 cm in RCP4.5, and from 7.7 cm to 14 cm in RCP8.5. The increase is caused by a combination of SMB decrease over the WAIS, combined with subsurface ocean warming that increases sub-ice melt. However, the climate model used to diagnose the spatial patterns of the atmospheric and oceanic response to the meltwater input is simplistic. Bronselaer et al. (2018) <sup>[[#fn:r521|521]]</sup> tested the global climatic response to future meltwater input from Antarctica using an ensemble of GCM simulations, but without an interactive ice sheet. They simulated an RCP8.5 scenario with and without a massive input of meltwater into the Southern Ocean and demonstrate that the addition of Antarctic meltwater expands sea ice in the Southern Ocean, delays the trajectory of global warming, and moderates atmospheric warming around the Antarctic coastline. Consistent with Golledge et al. (2019) <sup>[[#fn:r522|522]]</sup> , they found meltwater-induced stratification around Antarctica warms subsurface ocean temperatures, indicating the potential for a positive meltwater feedback on ice shelf melt. These studies reinforce the need for continental-scale studies to consider two-way ice-climate coupling, but with limited published studies to draw from and no simulations run beyond 2100, firm conclusions regarding the net importance of atmospheric versus ocean melt feedbacks on the long-term future of Antarctica can not be made.

Bulthuis et al. (2019) <sup>[[#fn:r526|526]]</sup> used a different continental-scale ice sheet model (Pattyn, 2017 <sup>[[#fn:r525|525]]</sup> ) with the same simplified atmospheric and ocean forcing used by Golledge et al. (2015) <sup>[[#fn:r528|528]]</sup> to simulate RCP2.6, RCP4.5, and RCP8.5 scenarios. Simulations with varying model parameters were used to quantify uncertainties related to the atmospheric forcing, various ice-model physics, and bedrock response to changing ice loads. A key finding was that irrespective of model parametric uncertainty, the strongly mitigated RCP2.6 scenario prevents catastrophic WAIS collapse over the coming centuries. The probabilistic projections of Antarctic GMSL contributions (Bulthuis et al., 2019 <sup>[[#fn:r531|531]]</sup> ) represent a rigorous blending of physical ice sheet modelling and uncertainty quantification (UQ) techniques, albeit with a simplistic representation of future climate and using a relatively coarse-resolution ice sheet model. These results are well-supported by Schlegel et al. (2018), who blend UQ with a higher resolution ice sheet model than used by Bulthuis et al. (2019), but using an idealised climate forcing scheme not directly linked to time-evolving future climate trajectories. Their 800 simulations, run to 2100, provide not only probabilistic constraints on future GMSL-rise from Antarctica, but an assessment of key drivers of uncertainty, including uniform and regional dependencies on model physical parameters, climate forcing, and boundary conditions. Sub-ice shelf melt rates provide the greatest source of uncertainty in their projections, although the source region dominating the GMSL contribution is found to be dependent on the climate forcing applied, and different from those found by Golledge et al. (2015) <sup>[[#fn:r530|530]]</sup> .

DeConto and Pollard (2016) <sup>[[#fn:r529|529]]</sup> used an ice sheet model with a formulation similar to that used by Golledge et al. (2015) and Bulthuis et al. (2019) but they include glaciological processes not accounted for in other continental-scale models: 1) surface melt and rain water influence on hydrofracturing of ice shelves; and 2) brittle failure of thick, marine-terminating ice fronts that have lost their buttressing ice shelves. Where the ice fronts are thick enough to form tall ice cliffs above the waterline, they can produce stresses exceeding the strength of the ice, causing calving (Bassis and Walker, 2012 <sup>[[#fn:r532|532]]</sup> ). Once initiated, ice-cliff calving has been hypothesised to produce a self-sustaining Marine Ice Cliff Instability (MICI; Cross-chapter Box 8, Chapter 3). The validity of MICI remains unproven (Edwards et al., 2019 <sup>[[#fn:r533|533]]</sup> ) and is considered to be characterised by ‘deep uncertainty’, but it has the potential to raise GMSL faster than MISI. DeConto and Pollard (2016) represent hydrofracturing and ice-cliff calving with simple parameterisations, but the glaciological processes themselves are supported by more detailed modelling and observations (Scambos et al., 2009 <sup>[[#fn:r534|534]]</sup> ; Banwell et al., 2013 <sup>[[#fn:r535|535]]</sup> ; Ma et al., 2017 <sup>[[#fn:r536|536]]</sup> ; Wise et al., 2017 <sup>[[#fn:r537|537]]</sup> ; Parizek et al., 2019 <sup>[[#fn:r538|538]]</sup> ). DeConto and Pollard (2016) <sup>[[#fn:r539|539]]</sup> provide four ensembles for RCP2.6, RCP4.5, and RCP8.5 scenarios, representing two alternative ocean model treatments and two alternative palaeo sea level targets used to tune their model physical parameters. However, their ensembles do not explore the full range of model parameter space or provide a probabilistic assessment (Kopp et al., 2017 <sup>[[#fn:r540|540]]</sup> ; Edwards et al., 2019 <sup>[[#fn:r541|541]]</sup> ). Under RCP2.6, DeConto and Pollard (2016) find very little GMSL rise from Antarctica by 2100 (0.02–0.16 m), consistent with the findings of Golledge et al. (2015) <sup>[[#fn:r542|542]]</sup> and Bulthuis et al. (2019) <sup>[[#fn:r543|543]]</sup> . In contrast, their four ensemble means range between 0.26–0.58 m for RCP4.5, and 0.64–1.14 m for RCP8.5. In RCP8.5, rates of GMSL rise from Antarctica exceed 5 cm yr -1 in the 22nd century and contribute as much as 15 m of GMSL rise by 2500, largely due to the ice cliff calving process. The climate forcing used by DeConto and Pollard (2016) <sup>[[#fn:r544|544]]</sup> simulates the appearance of extensive surface meltwater several decades earlier than indicated by other CMIP5 climate simulations (Trusel et al., 2015 <sup>[[#fn:r545|545]]</sup> ). Because their model physics are sensitive to melt water through hydrofracturing, this makes the timing and magnitude of their simulated ice loss too uncertain to include in SROCC sea level projections. However, their results do demonstrate the potential for brittle ice sheet processes not considered by AR5 to exert a strong influence on future rates of GMSL rise and the possibility that GMSL beyond 2100 could be considerably higher than the ''likely'' range projected by models that do not include these processes.

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