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

===== 4.2.3.1.1 Greenland =====

The GIS is currently losing mass at roughly twice the pace of the AIS (see Chapter 3 and Table 4.1). About 60% of the mass loss between 1991 and 2015 has been attributed to increasingly negative SMB from surface melt and runoff on the lower elevations of the ice sheet margin. Ice dynamical changes and increased discharge of marine-terminating glaciers account for the remaining 40% of mass loss (Csatho et al., 2014 <sup>[[#fn:r376|376]]</sup> ; Enderlin, 2014 <sup>[[#fn:r377|377]]</sup> ; van den Broeke et al., 2016 <sup>[[#fn:r378|378]]</sup> ). The ability of firn on Greenland to retain meltwater until it refreezes has diminished markedly since the late 1990s, especially in lower elevations and on peripheral ice caps (Noël et al., 2017 <sup>[[#fn:r379|379]]</sup> ). Patterns of surface melt on Greenland are highly dependent on regional atmospheric patterns (Bevis et al., 2019 <sup>[[#fn:r380|380]]</sup> ), adding uncertainty to future projections of SMB. Melt-albedo feedbacks associated with darkening of the ice surface from ponded water, changes in snow and firn properties, and accumulation of impurities are also important, because they can strongly enhance surface melt (Tedesco et al., 2016 <sup>[[#fn:r381|381]]</sup> ; Ryan et al., 2018 <sup>[[#fn:r382|382]]</sup> ; Trusel et al., 2018 <sup>[[#fn:r383|383]]</sup> ; Ryan et al., 2019 <sup>[[#fn:r384|384]]</sup> ). These processes are not fully captured by most Greenland-scale models which is an important deficiency, because surface processes tend to dominate uncertainty in future GIS model projections (e.g., Edwards et al., 2014; Aschwanden et al., 2019 <sup>[[#fn:r385|385]]</sup> ). Increases in meltwater and changes in the basal hydrologic regime, once thought to have a possible destabilising effect on the ice sheet (Zwally et al., 2002 <sup>[[#fn:r386|386]]</sup> ), have been linked with recent reductions in ice velocity in western Greenland. On decadal time scales the effect of meltwater on ice dynamics are now assessed to be small (van de Wal et al., 2015 <sup>[[#fn:r387|387]]</sup> ; Flowers, 2018 <sup>[[#fn:r388|388]]</sup> ), which is supported by ice sheet model experiments (Shannon et al., 2013 <sup>[[#fn:r389|389]]</sup> ). In sum, uncertain climate projections (Edwards et al., 2014 <sup>[[#fn:r390|390]]</sup> ), albedo evolution, uncertainties around meltwater buffering by firn, complex processes linking surface, englacial and basal hydrology with ice dynamics (Goelzer et al., 2013 <sup>[[#fn:r391|391]]</sup> ; Stevens et al., 2016 <sup>[[#fn:r392|392]]</sup> ; Noël et al., 2017 <sup>[[#fn:r393|393]]</sup> ; Hempelmann et al., 2018 <sup>[[#fn:r394|394]]</sup> ) and meltwater induced melting at marine-terminating ice fronts (Chauché et al., 2014 <sup>[[#fn:r395|395]]</sup> ), and coarse spatial model resolution (Pattyn et al., 2018 <sup>[[#fn:r396|396]]</sup> ), all continue to provide substantial challenges for ice sheet and SMB models.

Greenland-scale ice sheet modelling since AR5 (Edwards et al., 2014 <sup>[[#fn:r397|397]]</sup> ; Fürst et al., 2015 <sup>[[#fn:r398|398]]</sup> ; Vizcaino et al., 2015 <sup>[[#fn:r399|399]]</sup> ; Calov et al., 2018 <sup>[[#fn:r400|400]]</sup> ; Golledge et al., 2019 <sup>[[#fn:r401|401]]</sup> ; Aschwanden et al., 2019 <sup>[[#fn:r402|402]]</sup> ) has built upon earlier work by coupling the ice models with regional climate models and using multiple climate and ice sheet models within single studies (Edwards et al., 2014 <sup>[[#fn:r403|403]]</sup> ). Recent modelling studies use higher-order representations of ice flow (Fürst et al., 2015 <sup>[[#fn:r404|404]]</sup> ), include more explicit representations of ice sheet processes including subglacial hydrology (Calov et al., 2018 <sup>[[#fn:r405|405]]</sup> ), run the models at higher resolution and with updated boundary conditions (Aschwanden et al., 2019 <sup>[[#fn:r406|406]]</sup> ), and account for two-way coupling between the ice sheet and the global ocean (Vizcaino et al., 2015 <sup>[[#fn:r407|407]]</sup> ; Golledge et al., 2019 <sup>[[#fn:r408|408]]</sup> ). Among these studies, Fürst et al. (2015), Vizcaino et al. (2015) <sup>[[#fn:r409|409]]</sup> , and Aschwanden et al. (2019) provide projections following RCP2.6, RCP4.5, and RCP8.5 emissions scenarios. Calov et al. (2018) <sup>[[#fn:r412|412]]</sup> and Golledge et al. (2019) <sup>[[#fn:r413|413]]</sup> did not consider RCP2.6. Edwards et al. (2014) <sup>[[#fn:r414|414]]</sup> used the Special Report on Emissions Scenarios (SRES) A1B scenario which isn’t directly comparable to the other studies assessed here, but they do provide a rigorous analysis of uncertainty contributed by different climate forcings, varying simplifications of ice flow equations and height-SMB feedbacks.

Fürst et al. (2015) <sup>[[#fn:r415|415]]</sup> used ten different CMIP5 Atmosphere-Ocean General Circulation Model (AOGCM) simulations to provide offline SMB and ocean forcing for their Greenland-wide ice sheet model, accounting for influences of warming subsurface ocean temperatures and basal lubrication on ice dynamics. In their RCP8.5 ensemble, they found a GIS contribution to GMSL in 2100 of 10.15 cm ± 3.24 cm. Similarly, Calov et al. (2018) <sup>[[#fn:r417|417]]</sup> found a range of GMSL contributions between 4.6 – 13 cm, depending on which CMIP5 GCM is used to force their regional climate model to produce SMB forcing. The wide range of RCP8.5 results in these studies highlights the substantial climate-driven uncertainty in 21st century projections of the GIS as emphasised by Edwards et al. (2014). It was found that central estimates and ranges for RCP8.5 simulated by Fürst et al. (2015), Calov et al. (2018), and Golledge et al. (2019) are in reasonable agreement with previous multi-model results (Bindschadler et al., 2013) and the assessment of AR5 (Church et al., 2013 <sup>[[#fn:r419|419]]</sup> ), which reported a ''likely'' RCP8.5 range of Greenland’s contribution to GMSL between 7 – 21 cm by 2100 (Table 4.2.). The GIS simulations provided by Vizcaino et al. (2015) <sup>[[#fn:r420|420]]</sup> , using a relatively course-resolution ice model (10 km) with SMB forcing provided by a single GCM, estimate much less ice loss than other recent studies. Their GMSL projections (Vizcaino et al., 2015 <sup>[[#fn:r421|421]]</sup> ) also fall below the ''likely'' range of AR5 estimates. In contrast, the study by Aschwanden et al. (2019) <sup>[[#fn:r422|422]]</sup> shows a significantly higher contribution to GMSL than the other studies, especially under RCP8.5 and beyond 2100 (see 4.2.3.5). This may be due to their SMB forcing, which is based on spatially uniform warming derived from future CMIP5 GCM climatologies averaged over the entire Greenland region. As noted by earlier work (e.g., Van de Wal and Wild, 2001; Gregory and Huybrechts, 2006 <sup>[[#fn:r423|423]]</sup> ), this approach can overestimate melt rates in the ablation zone, which could account for their higher projected ice loss. It is noted that the process-based estimates of future GMSL rise from Greenland found in Aschwanden et al. (2019) <sup>[[#fn:r424|424]]</sup> are closest to those from an updated, structured judgement of glaciological and modelling experts (Bamber et al., 2019 <sup>[[#fn:r425|425]]</sup> ). Calculations from the expert elicitation (Bamber et al., 2019 <sup>[[#fn:r426|426]]</sup> ) result in higher estimates of Greenland ice loss than any of the process-based studies, with a mean and standard deviation of 33 ± 30 cm and a 17 – 83% range of 10 – 60 cm by 2100, following a climate scenario comparable to RCP8.5. The combination of the new process-based studies produces central estimates (Table 4.2) consistent with the ''likely'' ranges for Greenland’s contribution to GMSL in 2100 assessed by AR5.

<span id="table-4.2"></span>
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'''Table 4.2'''
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Estimates of the Greenland Ice Sheet (GIS) contribution to Global Mean Sea Level (GMSL; cm) in 2100 reported by process-based modelling studies including the effects of both surface mass balance (SMB) and ice dynamics published since the IPCC 5th Assessment Report (AR5). Only model results including elevation-SMB feedback are shown. All values are reported as the contribution to GMSL in 2100 relative to 2000, with the exception of Aschwanden et al. (2019) <sup>[[#fn:r428|428]]</sup> who report values relative to 2008. The median estimate for comparison with AR5 is based on the average of the three simulations in Calov et al. (2018) <sup>[[#fn:r429|429]]</sup> using different General Climate Models (GCMs), combined with the central estimates from the other studies. RMSD (Fürst et al., 2015 <sup>[[#fn:r430|430]]</sup> ) is the Root Mean Squared Deviation from their ensemble median. The range reported by Aschwanden et al. (2019) <sup>[[#fn:r431|431]]</sup> refers to the 16–84% interval of a 500 member ensemble with varying model physical parameters. RCP is Representative Concentration Pathway.
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[[File:0867c405058758b3a0714c022b257a62 table4.2.png]]

Complimentary to the ice sheet scale simulations discussed above, Nick et al. (2013) <sup>[[#fn:r427|427]]</sup> used detailed flowline models of four Greenland outlet glaciers (Petermann, Kangerdlugssuaq, Jakobshavn Isbræ, and Helheim) to estimate a dynamical contribution to sea level in an RCP8.5 scenario of 11.3–17.5 mm by 2100, and 29–49 mm, by 2200. This demonstrates the limited potential of Greenland outlet glaciers alone to drive GMSL rise. Greenland-wide modelling studies (Table 4.2) consistently find a dominant role of runoff relative to dynamic discharge of ice loss, and a long-term reduction in the rate of dynamic ice discharge to the ocean as the ice sheet margin thins and the termini of outlet glaciers retreat from the coast (Goelzer et al., 2013 <sup>[[#fn:r438|438]]</sup> ; Lipscomb et al., 2013 <sup>[[#fn:r439|439]]</sup> ). Greenland’s bedrock geography and the limited, direct access of thick interior ice to the ocean ultimately limits the potential pace of GMSL rise from the GIS. Figure 4.7 illustrates a fundamental difference between Greenland and Antarctica. In Greenland, most of the bedrock at the ice sheet margin is above sea level (land terminating), with relatively narrow (generally &lt;10 km wide) outlet glaciers reaching the ocean. In contrast, Antarctica has extensive areas with subglacial bedrock below sea level, and thick marine-terminating ice in direct contact with the open ocean. Recent subglacial mapping and mass conservation calculations since AR5 (Morlighem et al., 2014 <sup>[[#fn:r440|440]]</sup> ; Morlighem et al., 2017 <sup>[[#fn:r441|441]]</sup> ) revise earlier bathymetric maps under and around the ice sheet, and reveal deeper and more extensive valley networks extending into the GIS interior than previously known. Accurate subglacial topography is important for modelling individual Greenland outlet glaciers (Aschwanden et al., 2016 <sup>[[#fn:r442|442]]</sup> ; Morlighem et al., 2016 <sup>[[#fn:r443|443]]</sup> ); however, the importance of these revised bedrock boundary conditions for the broader ice sheet has yet to be fully tested. Based on the limited cross sectional area of subglacial valleys and outlet glaciers on Greenland (Figure 4.7) and the results of Nick et al. (2013) <sup>[[#fn:r444|444]]</sup> , the effects of uncertain bathymetric boundary conditions are assessed to be small relative to the uncertainties in future SMB forcing ( ''medium confidence'' ).

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<span id="figure-4.7"></span>
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'''Figure 4.7'''

<span id="figure-4.7-bedrock-topography-below-the-existing-ice-sheets-in-greenland-morlighem-et-al.-2017-and-antarctica-right-fretwell-et-al.-2013.-horizontal-scales-are-not-the-same-in-both-panels.-note-the-deep-subglacial-basins-in-west-antarctica-and-the-east-antarctic-margin.-the-ice-above-floatation-in-these-areas-is-equivalent-to"></span>
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'''Figure 4.7 | Bedrock topography below the existing ice sheets in Greenland (Morlighem et al., 2017) and Antarctica (right) (Fretwell et al., 2013). Horizontal scales are not the same in both panels. Note the deep subglacial basins in West Antarctica and the East Antarctic margin. The ice above floatation in these areas is equivalent to […]'''
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[[File:7c5a735653ef82fd11e92c7c390ed2d9 IPCC-SROCC-CH_4_7-3000x1355.jpg]]

Figure 4.7 | Bedrock topography below the existing ice sheets in Greenland (Morlighem et al., 2017) and Antarctica (right) (Fretwell et al., 2013). Horizontal scales are not the same in both panels. Note the deep subglacial basins in West Antarctica and the East Antarctic margin. The ice above floatation in these areas is equivalent to &gt;20 m of Global Mean Sea Level (GMSL).

In summary, new modelling since AR5 is consistent with previous studies suggesting future Greenland ice loss over the 21st century will be dominated by surface processes, rather than dynamic ice discharge to the ocean, regardless of which emissions scenario is followed ( ''high confidence'' ). Based on these modelling studies, the GIS is not expected to contribute more than 20 cm of GMSL rise by 2100 in a RCP8.5 scenario, similar to the upper end of the ''likely'' range reported by AR5 (Church et al., 2013 <sup>[[#fn:r445|445]]</sup> ). GIS simulations are most sensitive to uncertainties in the applied climate forcing, especially over this century (Edwards et al., 2014 <sup>[[#fn:r446|446]]</sup> ), but updated climate projections since AR5 are not yet available. Because of the consistency of recent modelling with the assessment of Church et al. (2013 <sup>[[#fn:r447|447]]</sup> ), Greenland’s contribution to future sea level reported in AR5 was used in our projections of GMSL.

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