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

=== 9.6.3 Future Sea Level Changes ===

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This section first assesses sea level projections since AR5 ( [[#Church--2013b|Church et al., 2013b]] ) and including SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ) based on Representative Concentration Pathways (RCPs; [[#9.6.3.1|Section 9.6.3.1]] ). Process-level assessments in sections 9.2.4, 9.4.1.3, 9.4.1.4, 9.4.2.5, 9.4.2.6 and 9.5.1.3 are synthesized ( [[#9.6.3.2|Section 9.6.3.2]] ) to produce new global mean and regional sea level projections based on the Shared Socio-economic Pathways up to 2150 ( [[#9.6.3.3|Section 9.6.3.3]] ) and on global warming levels up to 2100 ( [[#9.6.3.4|Section 9.6.3.4]] ). Long-term global mean sea level (GMSL) projections, both at 2300 and on multimillennial time scales, are also assessed ( [[#9.6.3.5|Section 9.6.3.5]] ).

Sections 9.6.3.3 and 9.6.3.4 present ''likely'' ranges of the new global mean sea levels, incorporating only processes in whose projections there is at least ''medium confidence'' , consistent with headline projections in AR5 and SROCC. As emphasized by SROCC, there is a substantial likelihood that sea level rise will be outside the ''likely'' range. As described in Box 1.1, since the definition of ‘ ''likely'' ’ refers to at least 66% probability, there may be as much as a 34% probability that the processes in which there is at least ''medium confidence'' will generate outcomes outside the ''likely'' range. Furthermore, additional processes in which there is ''low confidence'' [[#9.4.2.4|Section 9.4.2.4]] ; Box 9.4) may also contribute to sea level change. The presentation of ''likely'' sea level change (Tables 9.8–9.9 and in Figures 9.27, 9.29) is therefore accompanied by a ''low confidence'' range intended to reflect potential contributions from additional processes under high-emissions scenarios. The ''low confidence'' range incorporates ice-sheet projections based on Structured Expert Judgement (SEJ) – that is, a formal, calibrated method of combining quantified expert assessments that incorporates all potential processes – and projections from an AIS model that includes the marine ice cliff instability (a specific uncertain process not generally included in ice-sheet models; [[#9.4.2.4|Section 9.4.2.4]] ).

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<span id="global-mean-sea-level-projections-based-on-the-representative-concentration-pathways"></span>
==== 9.6.3.1 Global Mean Sea Level Projections Based on the Representative Concentration Pathways ====

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The AR5 ( [[#Church--2013b|Church et al., 2013b]] ) generated GMSL projections for the RCPs by combining information from CMIP5 climate models with glacier and ice-sheet surface mass balance (SMB) models and assessments of projected ice-sheet dynamic and land-water storage contributions ( [[#9.6.3.2|Section 9.6.3.2]] ). The SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ) updated AR5 projections based on a revised assessment of the AIS contribution to GMSL rise. The AR5 and SROCC employ a baseline period of 1986 to 2005, which is updated in this Report to a baseline period of 1995 to 2014 ( [[IPCC:Wg1:Chapter:Chapter-1#1.4.1|Section 1.4.1]] ). Between these two periods, GMSL rose by 3 cm, and this correction is applied to projections from previous reports to allow comparison (Table 9.8). Accounting for this shift, SROCC concludes that, with ''medium confidence,'' GMSL will rise between 0.40 (0.26–0.56, ''likely'' range) m (RCP2.6) and 0.81 (0.58–1.07 m, ''likely'' range) m (RCP8.5) by 2100 relative to 1995–2014. The AR5 and SROCC GMSL projections for the 2007–2018 period have been shown to be consistent with observed trends in GMSL and regional weighted mean tide gauges (J. [[#Wang--2021|]] [[#Wang--2021|Wang et al., 2021]] ).

Since AR5, a number of projections of GMSL rise have been published based on the RCPs ( [[#Kopp--2014|Kopp et al., 2014]] , 2017; [[#Slangen--2014b|Slangen et al., 2014b]] ; Grinsted et al., 2015; [[#Jackson--2016|Jackson et al., 2016]] ; [[#Mengel--2016|Mengel et al., 2016]] ; [[#Bakker--2017|Bakker et al., 2017]] ; [[#Bittermann--2017|Bittermann et al., 2017]] ; [[#Le%20Bars--2017|Le Bars et al., 2017]] ; [[#Nauels--2017|Nauels et al., 2017]] ; [[#Wong--2017|Wong et al., 2017]] ; [[#Goodwin--2018|Goodwin et al., 2018]] ; [[#Nicholls--2018|Nicholls et al., 2018]] ; [[#Le%20Cozannet--2019|Le Cozannet et al., 2019]] ; [[#Palmer--2020|Palmer et al., 2020]] ). See [[#Garner--2018|Garner et al. (2018)]] or a database (Tables 9.SM.5, 9.SM.6). Some studies also produced associated global sets of regional projections ( [[#Kopp--2014|Kopp et al., 2014]] , 2017; [[#Slangen--2014b|Slangen et al., 2014b]] ; [[#Le%20Cozannet--2019|Le Cozannet et al., 2019]] ; [[#Palmer--2020|Palmer et al., 2020]] ). Since SROCC ( [[#Le%20Cozannet--2019|Le Cozannet et al., 2019]] ) focused on the low end of the probability distribution of GMSL rise, [[#Palmer--2020|Palmer et al. (2020)]] extended projections beyond 2100 using a climate model emulator (Cross-Chapter Box 7.1), and [[#Horton--2020|Horton et al. (2020)]] conducted a survey of 106 sea level experts, providing additional context for interpreting sea level rise projections for 2100 and 2300.

As noted by SROCC, the largest differences between projections of GMSL in 2100 are due to the ice-sheet projection method, which generally fall into one of three categories: (i) projections from ice-sheet models that represent processes where there is at least ''medium confidence'' (Sections 9.4.1.2 and 9.4.2.2); (ii) projections from an Antarctic ice-sheet model that incorporates the marine ice cliff instability (MICI; [[#9.4.2.4|Section 9.4.2.4]] ; [[#DeConto--2016|DeConto and Pollard, 2016]] ); or (iii) projections based on SEJ (Sections 9.4.1.3, 9.4.1.4, 9.4.2.5 and 9.4.2.6; [[#Bamber--2013|Bamber and Aspinall, 2013]] ; [[#Bamber--2019|Bamber et al., 2019]] ). ''Low confidence'' is ascribed to projections incorporating MICI because there is ''low confidence'' in the current ability to quantify MICI ( [[#9.4.2.4|Section 9.4.2.4]] ). ''Low confidence'' is also ascribed to projections based on SEJ, because individual experts participating in the SEJ study may have incorporated processes in whose quantification there is ''low confidence'' , and the experts’ reasoning has not been examined in detail. In general, the range of GMSL projections based on ice-sheet models not incorporating MICI overlaps with, but is lower than, projections incorporating MICI or employing SEJ (Figure 9.25).

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[[File:98d08c28f372fd0e31a76d38b0573521 IPCC_AR6_WGI_Figure_9_25.png]]

'''Figure 9.25''' '''|''' '''Literature global mean sea level (GMSL) projections (m) for 2050 (left) and 2100 (right) since 199''' '''5–2''' '''014, for RCP8.5/SSP5-8.5 (top set), RCP4.5/SSP2-4.5 (middle set), and RCP2.6/SSP1-2.6 (bottom set).''' Projections are standardized to account for minor differences in time periods. Thick bars span from the 17th–83rd percentile projections, and thin bars span the 5th–95th percentile projections. The different assessments of ice-sheet contributions are indicated by ‘MED’ (ice-sheet projections include only processes in whose quantification there is ''medium confidence'' ), ‘MICI’ (ice-sheet projections which incorporate marine ice cliff instability), and ‘SEJ’ (structured expert judgement) to assess the central range of the ice-sheet projection distributions. ‘Survey’ indicates the results of a 2020 survey of sea level experts on global mean sea level (GMSL) rise from all sources ( [[#Horton--2020|Horton et al., 2020]] ). Projection categories incorporating processes in which there is ''low confidence'' (MICI and SEJ) are lightly shaded. Dispersion among the different projections represents ''deep uncertainty'' , which arises as a result of ''low agreement'' regarding appropriate conceptual models describing ice-sheet behaviour and ''low agreement'' regarding probability distributions used to represent key uncertainties. Individual studies are shown in Tables 9.SM.5 and 9.SM.6. Further details on data sources and processing are available in the chapter data table (Table 9.SM.9).

There is ''high'' ''agreement'' across published GMSL projections for 2050, and there is little sensitivity to emissions scenario (Figure 9.25, left panel). Up to 2050, projections are broadly consistent with extrapolation of the observed acceleration of GMSL rise (Sections 2.3.3.3, 9.6.1.1 and 9.6.1.2). Considering only projections incorporating ice-sheet processes in whose quantification there is at least ''medium confidence'' , the GMSL projections for 2050, across all emissions scenarios, fall between 0.1 and 0.4 m (5th–95th percentile range). Projections incorporating MICI or SEJ do not extend this range under RCP2.6 or RCP4.5 but do extend the upper part of the range to 0.6 m under RCP8.5. On the basis of these studies, we therefore have ''high confidence'' that GMSL in 2050 will be between 0.1 and 0.4 m higher than in 1995–2014 under low- and moderate-emissions scenarios, and between 0.1 and 0.6 m under high-emissions scenarios.

Conversely, there is ''low agreement'' across published GMSL projections for 2100, particularly for higher-emissions scenarios, as well as a higher degree of sensitivity to the choice of emissions scenario (Figure 9.25, right panel). Considering only projections representing processes in whose quantification there is at least ''medium'' ''confidence'' , the GMSL projections for 2100 fall between 0.2 and 1.0 m (5th–95th percentile range) under RCP2.6 and RCP4.5, and between 0.3 and 1.6 m under RCP8.5. Considering also projections incorporating MICI or SEJ ( ''low confidence'' ), the projections for 2100 fall between 0.2 and 1.0 m (5th–95th percentile range) under RCP2.6, 0.2, and 1.6 m under RCP4.5, and 0.4 and 2.4 m under RCP8.5. In summary, RCP-based projections published since AR5 show ''high agreement'' for 2050, but exhibit broad ranges and ''low agreement'' for 2100, particularly under RCP8.5.

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<span id="drivers-of-projected-sea-level-change"></span>
==== 9.6.3.2 Drivers of Projected Sea Level Change ====

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This section describes the choices made for the contributions to the updated global mean and regional sea level projections ( [[#9.6.3.3|Section 9.6.3.3]] ) based on assessments in this Report and compares the updated projections to AR5 ( [[#Church--2013b|Church et al., 2013b]] ) and SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ) (Tables 9.7 and 9.8). Since there is no single model that can directly compute all of the contributions to sea level change (Box 9.1), the contributions to sea level are computed separately and then combined (Tables 9.8 and 9.9). For consistency with global surface air temperature (GSAT) projections ( [[IPCC:Wg1:Chapter:Chapter-4#4.3.1.1|Section 4.3.1.1]] ), and assessment of equilibrium climate sensitivity (ECS) and transient climate response (TCR; [[IPCC:Wg1:Chapter:Chapter-7#7.5|Section 7.5]] ), temperature-dependent projections (thermal expansion, ice sheets, glaciers) are forced by GSAT projections from a two-layer energy budget emulator ( [[#Smith--2018|Smith et al., 2018]] ) that is calibrated to be consistent with the assessment of ECS and TCR (Box 7.1, Supplementary Material 7.SM.2). Throughout, ''likely'' ranges are assessed based on the combination of uncertainty in the GSAT distribution and uncertainty in the relationships between GSAT and changes to individual components. In general, 17th–83rd percentile results, incorporating both GSAT and sea level process uncertainty, are interpreted as ''likely'' ranges. This is distinct from the approach used by AR5, which interpreted the 5th–95th percentile range of CMIP5 projections, and therefore of GMSL projections driven by them, as ''likely'' ranges. The shift in interpretation is consistent with the use of the emulator for GSAT (Box 4.1, Cross-Chapter Box 7.1). ''Very likely'' ranges are not assessed because of the potential for processes in whose projections there is currently ''low confidence'' to substantially augment total projected GMSL change.

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'''Table''' '''9.7 |''' '''Methods used to project the drivers of global mean sea level (GMSL) and relative sea level (RSL) change in the Shared Socio-economic Pathway (SSP) and warming-level-based projections of GMSL, RSL and extreme sea level (ESL) change.''' Section numbers indicate location of primary assessment text.

{| class="wikitable"
|-
| '''Driver of Global Mean or Regional Sea Level change'''

| '''SROCC Projection Method'''

| '''AR6 Projection method'''

|-
| Thermal expansion ( [[#9.2.4.1|Section 9.2.4.1]] )

| CMIP5 ensemble drift-corrected ''zostoga'' , with surrogates derived from climate system heat content where not available

| Two-layer emulator with climate sensitivity calibrated to AR6 assessment (Supplementary Material 7.SM.2) and expansion coefficients calibrated to emulate CMIP6 models (Supplementary Material 9.SM.4.2 and 9.SM.4.3)

|-
| Greenland Ice Sheet (excluding peripheral glaciers) (Sections 9.4.1.3 and 9.4.1.4)

| ''Surface mass balance:''

scaled cubic polynomial fit to global mean surface temperature (GMST)

''Dynamics:''

Quadratic function of time, calibrated based on multi-model assessment

| ''Medium confidence'' processes up to 2100: Emulated Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) simulations (Box 9.3; [[#Edwards--2021|Edwards et al., 2021]] )

''Medium confidence'' processes after 2100: Parametric model fit to ISMIP6 simulations up to 2100, extrapolated based on either constant post-2100 rates or a quadratic interpolation to the multi-model assessed 2300 range (Supplementary Material 9.SM.4.4)

''Low confidence'' processes: Structured expert judgement ( [[#Bamber--2019|Bamber et al., 2019]] )

|-
| Antarctic Ice Sheet (excluding peripheral glaciers <sup>a</sup> ) (Sections 9.4.2.5 and 9.4.2.6)

| Multi-model assessment

| ''Medium confidence'' processes up to 2100: p-box including: (i) Emulated ISMIP6 simulations ( [[#Edwards--2021|Edwards et al., 2021]] ); and (ii) Linear Antarctic Response Model Intercomparison Project (LARMIP-2) simulations ( [[#Levermann--2020|Levermann et al., 2020]] ) augmented by AR5 surface mass balance model (Box 9.3)

''Medium confidence'' processes after 2100: p-box including: (i) AR5 parametric AIS model; and (ii) LARMIP-2 simulations augmented by AR5 surface mass balance model applied to CMIP6 models, with both methods extrapolated based on either constant post-2100 rates or a quadratic interpolation to the multi-model assessed 2300 range ( [[#9.6.3.2|Section 9.6.3.2]] )

''Low confidence'' processes: (i) Single-ice-sheet-model ensemble simulations incorporating marine ice cliff instability ( [[#DeConto--2021|DeConto et al., 2021]] ); and (ii) structured expert judgement ( [[#Bamber--2019|Bamber et al., 2019]] )

|-
| Glaciers (including peripheral glaciers) ( [[#9.5.1.3|Section 9.5.1.3]] )

| Power law function of integrated GMST fit to glacier models

| Up to 2100: Emulated GlacierMIP ( [[#Marzeion--2020|Marzeion et al., 2020]] ; [[#Edwards--2021|Edwards et al., 2021]] ) simulations (Box 9.3)

Beyond 2100: AR5 parametric model re-fit to GlacierMIP (Supplementary Material 9.SM.4.5; [[#Marzeion--2020|Marzeion et al., 2020]] )

|-
| Land-water storage ( [[#9.6.3.2|Section 9.6.3.2]] )

| ''Groundwater depletion:''

combination of: (i) continuation of early 21st-century trends; and (ii) land-surface hydrology models ( [[#Wada--2012|Wada et al., 2012]] )

''Water impoundment:''

combination of: (i) continuation of historical rate; and (ii) assumption of no net impoundment after 2010

| ''Groundwater depletion:''

Population/groundwater depletion relationship calibrated based on [[#Konikow--2011|Konikow (2011)]] and Wada et al. (2012, 2016)

''Water impoundment:''

Population/dam impoundment relationship calibrated based on [[#Chao--2008|Chao et al. (2008)]] , adjusted for new construction following [[#Hawley--2020|Hawley et al. (2020)]] for 2020 to 2040

|-
| Ocean dynamic sea level ( [[#9.2.4.2|Section 9.2.4.2]] )

| CMIP5 ensemble ''zos'' field after polynomial drift removal

| Distribution derived from CMIP6 ensemble ''zos'' field after linear drift removal (Supplementary Material 9.SM.4.2 and 9.SM.4.3)

|-
| Gravitational, rotational, and deformational effects ( [[#9.6.3.2|Section 9.6.3.2]] )

| colspan="2"| Sea level equation solver ( [[#Slangen--2014b|Slangen et al., 2014b]] ) driven by projections of ice-sheet, glacier, and land-water storage changes

|-
| Glacial isostatic adjustment and other drivers of vertical land motion [[#9.6.3.2|Section 9.6.3.2]] )

| Glacial Isostatic Adjustment model, with ice history from mean of the Australian National University (ANU) and ICE-5G reconstructions

| Spatio-temporal statistical model of tide gauge data (updated from [[#Kopp--2014|Kopp et al., 2014]] ) (Supplementary Material 9.SM.4.6)

|}

<sup>a</sup> Ice-sheet models include some of the larger islands in the Antarctic periphery, so there is some overlap in the projected glacier contribution and the projected Antarctic contribution, but the effect is estimated to be on the order of 0.5–1 cm or less ( [[#Edwards--2021|Edwards et al., 2021]] ).

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<span id="global-mean-thermosteric-sea-level-rise"></span>
===== 9.6.3.2.1 Global mean thermosteric sea level rise =====

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In AR5 and SROCC, global mean thermosteric sea level rise was derived from the 21 members of the CMIP5 ensemble that provided the required variables ( [[#9.2.4.1|Section 9.2.4.1]] ). The AR5 and SROCC removed drift estimated based on a pointwise polynomial fit to pre-industrial control simulations. They extended projections to scenarios not provided by the models by calculating the heat content of the climate system from GMST and net radiative flux, and converting this to global mean thermosteric sea level rise using each model’s diagnosed expansion efficiency coefficient. The AR5 and SROCC derived the associated uncertainties by assuming a normal distribution, with the 5th–95th percentile CMIP5 ensemble interpreted as the ''likely'' range. In this Report, global mean thermosteric sea level rise is derived from a two-layer energy budget emulator consistent with the assessment of ECS and TCR ( [[#9.2.4.1|Section 9.2.4.1]] ; Supplementary Material 9.SM.4.2 and 9.SM.4.3). Despite the change in methodology, this leads to a ''likely'' global mean thermosteric contribution (17th–83rd percentile) between 1995–2014 and 2100 that represents a minimal change from AR5 and SROCC (Table 9.8).

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===== 9.6.3.2.2 Greenland Ice Sheet =====

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The AR5 and SROCC projected the Greenland surface-mass balance using a cubic polynomial fit to a regional climate model as a function of global mean surface temperature (with a log-normal scaling factor reflecting uncertainty in surface-mass balance models, and another scaling factor reflecting the positive feedback of ice-sheet elevation changes on mass loss), and the dynamic contribution was estimated based on a multi-model assessment interpolated as a quadratic function of time.

For processes whose projections we have at least ''medium confidence'' in, the updated projections use emulated Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) projections of the Greenland Ice Sheet ( [[#9.4.1.3|Section 9.4.1.3]] ; Figure 9.17; Tables 9.2 and 9.7; Box 9.3). Since the ISMIP6 emulator does not account for temporal correlation, a parametric fit to the ISMIP6 results is used to calculate rates of change (Supplementary Material 9.SM.4.4). For projections beyond 2100 (when the ISMIP6 simulations end), the polynomial fit is extrapolated based on two alternate approaches: (i) an assumption of constant rates of mass change after 2100; and (ii) for SSP1-2.6 and SSP5-8.5, a quadratic function of time extending to 2300 based on the multi-model assessment of contributions under RCP2.6 and RCP8.5 at 2300 ( [[#9.4.1.4|Section 9.4.1.4]] ). Differences between the two approaches are small up to 2150, and since the latter approach is not available for all scenarios, only the former (constant rates) is used for time series projections up to 2150. Both approaches are used for examining uncertainty in the timing of different levels of GMSL rise and to inform projections for the year 2300 ( [[#9.4.1.4|Section 9.4.1.4]] ). For 2100, the ISMIP6 emulator yields the ''likely'' contribution from the Greenland Ice Sheet shown in Table 9.2 and Figure 9.17, representing a slight narrowing from AR5 projections.

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===== 9.6.3.2.3 Antarctic Ice Sheet =====

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For the Antarctic Ice Sheet (AIS), AR5 applied a temperature-based scaling approach for SMB and a quadratic function of time, calibrated to a multi-model assessment, for dynamic contributions. The SROCC used a new assessment based on the results of five process-based studies ( [[#9.4.2.5|Section 9.4.2.5]] ). For processes in whose projections we have at least ''medium confidence'' , the ''likely range'' projections for the AIS are based on: (i) the emulated ISMIP6 ensemble; and (ii) the LARMIP-2 ensemble, augmented with AR5 parametric Antarctic SMB model. The GMSL projections are produced with both distributions and combined in a ‘p-box’ ( [[#Kriegler--2005|Kriegler and Held, 2005]] ; [[#Le%20Cozannet--2017|Le Cozannet et al., 2017]] ), which represents the upper and lower bounds of the distribution ( [[#9.4.2.5|Section 9.4.2.5]] , Box 9.3 and Table 9.3). A ''likely'' range is then identified, spanning the lower of the two 17th percentile projections and the higher of the two 83rd percentile projections, <sup>[[#footnote-000|5]]</sup> with the median taken as the mean of the medians of the two projections. Since the ISMIP6 emulator does not account for temporal correlation, the AR5 parametric AIS model is substituted for the emulator in the p-box for rates of change. As AR5 projections are modestly lower than those from the ISMIP6 emulator, this substitution modestly broadens the ''likely'' range at the low end for projections of rate and changes beyond 2100. For projections beyond 2100 (when the ISMIP6 and LARMIP-2 simulations end), the AIS simulations are extrapolated using the same two approaches as the Greenland Ice Sheet (GrIS) projections ( [[#9.4.1.4|Section 9.4.1.4]] ). The ''likely'' ranges to 2100 are consistent with SROCC (Table 9.8).

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<span id="low-confidence-ice-sheet-projections"></span>
===== 9.6.3.2.4 Low confidence ice-sheet projections =====

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To test the possible effect of additional ice-sheet processes for which there is ''low confidence'' (Sections 9.4.1.3, 9.4.1.4, 9.4.2.5, 9.4.2.6 and 9.6.3.1, and Box 9.4), two additional approaches are considered. For both the Greenland and Antarctic ice sheets, we produce sensitivity cases employing the SEJ projections of [[#Bamber--2019|Bamber et al. (2019)]] , mapping 2°C and 5°C stabilization scenarios to SSP1-2.6 and SSP5-8.5, respectively. For the AIS, we produce an additional sensitivity case using projections, which incorporate MICI ( [[#DeConto--2021|DeConto et al., 2021]] ), mapping projections for RCP2.6 and RCP8.5 to SSP1-2.6 and SSP5-8.5. For the Greenland Ice Sheet, the SEJ projections indicate the potential for outcomes outside the corresponding ''likely'' ranges (Table 9.8). For the AIS, there is no evidence from these studies to suggest an important role under lower-emissions scenarios for processes in whose projections we have ''low confidence'' . By contrast, for SSP5-8.5, the SEJ and MICI projections exhibit 17th–83rd percentile ranges of 0.02–0.56 m and 0.19–0.53 m by 2100, consistent with one another but considerably broader than the ''likely'' contribution for ''medium confidence'' processes of 0.03–0.34 m. This lower level of agreement for higher-emissions scenarios reflects the ''deep uncertainty'' in the AIS contribution to GMSL change under higher-emissions scenarios (Box 9.4). This ''deep uncertainty'' grows after 2100: by 2150, under SSP5-8.5, ''medium confidence'' processes ''likely'' lead to a –0.1–0.7 m AIS contribution, while SEJ- and MICI-based projections indicate 0.0–1.1 m and 1.4–3.7 m, respectively.

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<span id="glaciers-2"></span>
===== 9.6.3.2.5 Glaciers =====

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In AR5 and SROCC, global glacier mass changes were derived from a power law of integrated global mean surface temperature change fit to results from four different glacier models. The updated projections use emulated GlacierMIP projections ( [[#9.5.1.3|Section 9.5.1.3]] ; Box 9.3). Since the GlacierMIP emulator does not account for temporal correlation and terminates, along with the GlacierMIP simulations, in 2100, we employ a parametric fit to the GlacierMIP simulations, with a functional form similar to that employed by AR5, to calculate rates of change and extrapolate changes beyond 2100 (up to a maximum potential contribution of 0.32 m; see Supplementary Material 9.SM.4.5). This approach leads to a median glacier contribution that is a minimal change (Table 9.8) from AR5 and SROCC and a modest narrowing of ''likely'' ranges ( [[#9.5.1.3|Section 9.5.1.3]] ). For RCP2.6, AR5 projected 0.10 (0.04 to 0.16, ''likely'' range) m, compared to 0.09 (0.07 to 0.11) m projected for SSP1-2.6. For RCP8.5, AR5 projected a ''likely'' contribution of 0.17 (0.09 to 0.25) m, compared to 0.18 (0.15 to 0.21) m projected here.

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<span id="land-water-storage"></span>
===== 9.6.3.2.6 Land-water storage =====

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In AR5 and SROCC, the groundwater depletion contribution to GMSL rise was based on combining results from two approaches: one assuming a continuation of early 21st-century trends ( [[#Konikow--2011|Konikow, 2011]] ); and the other using land-surface hydrology models ( [[#Wada--2012|Wada et al., 2012]] ). Together, these yielded a range of about 0.02–0.09 m of GMSL rise by 2080–2099. The rate of water impoundment in reservoirs was likewise based on two approaches: one assuming the continuation of the average rate over 1971–2010 (and thus –0.01 to –0.03 m by 2080–2099; [[#Chao--2008|Chao et al., 2008]] ); and the other assuming no net impoundment after 2010 ( [[#Lettenmaier--2009|Lettenmaier and Milly, 2009]] ). Together, these yield a GMSL contribution from groundwater impoundment of –0.03 to 0 m. Combining groundwater depletion and water impoundment led AR5 and SROCC to infer a projected range of –0.01 to +0.11 m by 2100.

In the updated projections, a statistical relationship is applied, linking historical and future SSP global population to dam impoundment and groundwater extraction ( [[#Rahmstorf--2012|Rahmstorf et al., 2012]] ; [[#Kopp--2014|Kopp et al., 2014]] ). The population/groundwater depletion relationship is calibrated based on the same studies used in AR5 ( [[#Konikow--2011|Konikow, 2011]] ; [[#Wada--2012|Wada et al., 2012]] ), reduced by about 20% to account for water retained on land ( [[#Wada--2016|Wada et al., 2016]] ). The population/dam impoundment relationship is calibrated based on [[#Chao--2008|Chao et al. (2008)]] . However, while historically dam impoundment has been declining with population, recent literature shows that planned dam construction considerably exceeds the historical trend ( [[#Zarfl--2015|Zarfl et al., 2015]] ; [[#Hawley--2020|Hawley et al., 2020]] ). Over 2020–2040, the impoundment contribution to GMSL rise based on past trends would be about –0.1 mm yr <sup>–1</sup> , compared to about –0.5 mm yr <sup>–1</sup> if all currently planned dams are built ( [[#Hawley--2020|Hawley et al., 2020]] ) and the statistical projection is therefore augmented by an additional –0.4 to 0.0 mm yr <sup>–1</sup> over 2020–2040 to account for the possible effects of planned dam construction. As in AR5 and SROCC, climatically driven changes to land-water storage (LWS) have not been included in published sea level projections, as they are not well quantified (e.g., [[#Jensen--2019|Jensen et al., 2019]] ) or are considered negligible (e.g., permafrost, [[#9.5.2|Section 9.5.2]] ). This approach yields a ''likely'' global-mean land-water storage contribution (Figure 9.27, Table 9.8) that is slightly lower and narrower than the AR5 and SROCC ''likely'' ranges. Since the projections are explicitly population driven, these projections also exhibit a weak scenario dependence, with a contribution around 0.01 m higher under SSP3 than under other scenarios.

<div id="_idContainer067" class="Basic-Text-Frame"></div>

'''Table 9.8''' '''|''' '''Global mean sea level projections between 199''' '''5–2''' '''014 and 2100 for total change and individual contributions, median values, (likely ) ranges of the process-based model ensemble''' for RCP 2.6 (from AR5 ( [[#Church--2013a|Church et al., 2013a]] ) and SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] )) and SSP1-2.6 (this Report), and for RCP8.5 (from AR5 ( [[#Church--2013a|Church et al., 2013a]] ) and SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] )) and SSP5-8.5 (this Report). Values for AR5 ( [[#Church--2013a|Church et al., 2013a]] ) and SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ) are adjusted from the 1986–2005 baseline used in past reports. Only the Antarctic contribution changed between AR5 ( [[#Church--2013a|Church et al., 2013a]] ) and SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ). Unshaded cells represent processes in which there is ''medium confidence'' ; shading indicates the inclusion of processes in which there is ''low confidence'' . For the MICI- and SEJ-based projections, parenthetical numbers represent the 17th–83rd percentile of the associated probability distributions, not assessed ''likely'' ranges.

{| class="wikitable"
|-
|
| colspan="2"| '''RCP2.6'''

| colspan="3"| '''SSP1-2.6'''

|-
| m relative to 1995–2014

| '''AR5'''

| '''SROCC'''

| Medium confidence '''processes'''

| '''MICI'''

| '''SEJ'''

|-
| '''Thermal expansion ( [[#9.2.4.1|Section 9.2.4.1]] )'''

| colspan="2"| 0.14 (0.10–0.19) m

| colspan="3"| 0.14 (0.11–0.18) m

|-
| '''Greenland [[#9.4.1.3|Section 9.4.1.3]] )'''

| colspan="2"| 0.07 (0.03–0.11) m

| colspan="2"| 0.06 (0.01–0.10) m

| 0.13 (0.07–0.30) m

|-
| '''Antarctica ( [[#9.4.2.5|Section 9.4.2.5]] )'''

| 0.06 (–0.04 to +0.16) m

| 0.04 (0.01–0.11) m

| 0.11 (0.03–0.27) m

| 0.08 (0.06–0.12) m

| 0.09 (–0.01 to +0.25) m

|-
| '''Glaciers ( [[#9.5.1.3|Section 9.5.1.3]] )'''

| colspan="2"| 0.10 (0.04–0.16) m

| colspan="3"| 0.09 (0.07–0.11) m

|-
| '''Land-water storage ( [[#9.6.3.2|Section 9.6.3.2]] )'''

| colspan="2"| 0.05 (–0.01 to +0.11) m

| colspan="3"| 0.03 (0.01–0.04) m

|-
|
|-
| '''Total (2100)'''

| 0.41 (0.25–0.58) m

| 0.40 (0.26–0.56) m

| 0.44 (0.33–0.62) m

| 0.41 (0.35–0.48) m

| 0.53 (0.38–0.79) m

|-
| '''Total (2150)'''

| 0.29–0.63 m

| 0.56 (0.40–0.73) m

| 0.68 (0.46–0.99) m

| 0.74 (0.62–0.91) m

| 0.84 (0.56–1.34) m

|-
|
|-
| '''GMSL rate, 2080–2100 (mm''' '''yr''' <sup>–1</sup> ''')'''

| 4.4 (2.0–6.8) mm yr <sup>–1</sup>

| 4 (2–6) mm yr <sup>–1</sup>

| 5.2 (3.2–8.0) mm yr <sup>–1</sup>

| 5.1 (4.3–6.2) mm yr <sup>–1</sup>

| 5.9 (2.8–11.0) mm yr <sup>–1</sup>

|-
|
| colspan="2"|
| colspan="3"|
|-
|
| colspan="2"| '''RCP8.5'''

| colspan="3"| '''SSP5-8.5'''

|-
| m relative to 1995–2014

| '''AR5'''

| '''SROCC'''

| Medium confidence '''processes'''

| '''MICI'''

| '''SEJ'''

|-
| '''Thermal expansion ( [[#9.2.4.1|Section 9.2.4.1]] )'''

| colspan="2"| 0.31 (0.24–0.38) m

| colspan="3"| 0.30 (0.24–0.36) m

|-
| '''Greenland [[#9.4.1.3|Section 9.4.1.3]] )'''

| colspan="2"| 0.14 (0.08–0.27) m

| colspan="2"| 0.13 (0.09–0.18) m

| 0.23 (0.10–0.59) m

|-
| '''Antarctica ( [[#9.4.2.5|Section 9.4.2.5]] )'''

| 0.04 (–0.08 to +0.14) m

| 0.12 (0.03–0.28) m

| 0.12 (0.03–0.34) m

| 0.34 (0.19–0.53) m

| 0.21 (0.02–0.56) m

|-
| '''Glaciers ( [[#9.5.1.3|Section 9.5.1.3]] )'''

| colspan="2"| 0.17 (0.09–0.25) m

| colspan="3"| 0.18 (0.15–0.20) m

|-
| '''Land-water storage ( [[#9.6.3.2|Section 9.6.3.2]] )'''

| colspan="2"| 0.05 (–0.01 to +0.11) m

| colspan="3"| 0.03 (0.01–0.04) m

|-
|
|-
| '''Total (2100)'''

| 0.71 (0.49–0.95) m

| 0.81 (0.58–1.07) m

| 0.77 (0.63–1.01) m

| 0.99 (0.82–1.19) m

| 1.00 (0.70–1.60) m

|-
| '''Total (2150)'''

| 0.34–1.35 m

| 1.27 (0.80–1.79) m

| 1.32 (0.98–1.88) m

| 3.48 (2.57–4.82) m

| 1.79 (1.22–2.94) m

|-
|
|-
| '''GMSL rate, 2080–2100 (mm''' '''yr''' <sup>–1</sup> ''')'''

| 11.2 (7.5–15.7) mm yr <sup>–1</sup>

| 15 (10–20) mm yr <sup>–1</sup>

| 12.1 (8.6–17.6) mm yr <sup>–1</sup>

| 23.1 (17.5–30.1) mm yr <sup>–1</sup>

| 16.0 (9.8–28.9) mm yr <sup>–1</sup>

|}

<div id="9.6.3.2.7" class="h4-container"></div>

<span id="ocean-dynamic-sea-level"></span>
===== 9.6.3.2.7 Ocean dynamic sea level =====

<div id="h4-13-siblings" class="h4-siblings"></div>

In AR5 and SROCC, the ocean dynamic sea level contribution to RSL projections was derived from the CMIP5 ensemble, after removing the drift estimate based on pre-industrial control simulations. This Report uses updated simulations from the CMIP6 ensemble ( [[#9.2.4.2|Section 9.2.4.2]] ; Supplementary Material 9.SM.4.2) to project the ocean dynamic sea level contribution to RSL change ( [[#9.2.4.2|Section 9.2.4.2]] ; Figure 9.26). To produce ocean dynamic sea level projections consistent with the global mean thermosteric projections from the two-layer energy budget emulator, we follow the approach of [[#Kopp--2014|Kopp et al. (2014)]] , employing a correlation between global-mean thermosteric sea level change and ocean dynamic sea level derived from the CMIP6 ensemble (Supplementary Material 9.SM.4.3). Since CMIP6 models are of fairly coarse resolution (typically about 100 km), and even the models participating in HighResMIP (near 10 km resolution) do not capture all the phenomena that contribute to coastal ocean dynamic sea level change, there is ''low confidence'' in the details of ocean dynamic sea level change along the coast ( [[#9.2.3.6|Section 9.2.3.6]] ) and in semi-enclosed basins, such as the Mediterranean, where coarse models can misrepresent key dynamic processes. Regional high-resolution models can improve projections of coastal ocean dynamic sea level change ( [[IPCC:Wg1:Chapter:Chapter-12#12.4|Section 12.4]] ; [[#Hermans--2020|Hermans et al., 2020]] ), but have not been implemented at a global scale.

<div id="_idContainer069" class="Basic-Text-Frame"></div>

[[File:d23f047f4d21a35d1c98ce5e92f027cf IPCC_AR6_WGI_Figure_9_26.png]]

'''Figure 9.26''' '''|''' '''Median global mean and regional relative sea level projections (m) by contribution for the SSP1-2.6 and SSP5-8.5 scenarios. Upper time series:''' Global mean contributions to sea level change as a function of time, relative to 1995–2014. '''Lower maps:''' Regional projections of the sea level contributions in 2100 relative to 1995–2014 for SSP5-8.5 and SSP1-2.6. Vertical land motion is common to both Shared Socio-economic Pathways (SSPs). Further details on data sources and processing are available in the chapter data table (Table 9.SM.9).

<div id="9.6.3.2.8" class="h4-container"></div>

<span id="gravitational-rotational-and-deformational-effects"></span>
===== 9.6.3.2.8 Gravitational, rotational and deformational effects =====

<div id="h4-14-siblings" class="h4-siblings"></div>

Gravitational, rotational, and deformational (GRD) effects (Box 9.1) lead to distinct variations in the RSL change pattern, which are similar across a range of benchmarked GRD solvers ( [[#Martinec--2018|Martinec et al., 2018]] ; [[#Palmer--2020|Palmer et al., 2020]] ). There is ''high confidence'' in the understanding of GRD processes. RSL rise associated with GRD is ''very likely'' to be largest in the Pacific, due to the combined effects of projected GrIS, AIS and glacier mass loss ( ''high confidence'' ) (e.g., [[#Kopp--2014|Kopp et al., 2014]] ; [[#Slangen--2014b|Slangen et al., 2014b]] ; [[#Larour--2017|Larour et al., 2017]] ; [[#Mitrovica--2018|Mitrovica et al., 2018]] ). The GRD effect associated with mass loss from an ice sheet is sensitive to the spatial distribution of that mass loss. For example, the GRD contribution to RSL rise in Australia will be larger for Antarctic mass loss sourced fromthe Antarctic Peninsula than for Antarctic mass loss sourced fromThwaites Glacier. In parts of north-eastern North America and north-western Europe, GRD effects associated with mass loss from southern Greenland will lead to an RSL fall, whereas mass loss from northern Greenland will lead to an RSL rise ( ''high confidence'' ) (Figure 9.26; [[#Larour--2017|Larour et al., 2017]] ; [[#Mitrovica--2018|Mitrovica et al., 2018]] ). The AR5 and SROCC computed RSL patterns using a gravitationally self-consistent GRD solver given the amounts, locations and timing of the projected barystatic sea level changes driven by glaciers, ice sheets and LWS ( [[#Church--2013b|Church et al., 2013b]] ). A similar GRD solver is used in the updated projections (following [[#Slangen--2014b|Slangen et al., 2014b]] ). The Earth model used is based on the Preliminary reference Earth model (PREM: [[#Dziewonski--1981|Dziewonski and Anderson, 1981]] ), and is elastic, compressible and radially stratified.

<div id="9.6.3.2.9" class="h4-container"></div>

<span id="glacial-isostatic-adjustment-and-other-drivers-of-vertical-land-motion"></span>
===== 9.6.3.2.9 Glacial isostatic adjustment and other drivers of vertical land motion =====

<div id="h4-15-siblings" class="h4-siblings"></div>

Glacial Isostatic Adjustment (GIA) leads to vertical land motion (VLM; see Box 9.1) and changes in sea surface height, both of which contribute to RSL change. GIA uncertainty is caused by uncertainty in the rheological structure of the solid Earth, which drives the longer-term viscous Earth deformation, as well as uncertainty in the modelled global ice history (e.g., [[#Whitehouse--2018|Whitehouse, 2018]] ). In AR5 and SROCC, GIA contributions to RSL change were calculated using a sea level equation solver with an ice-sheet history taken as the mean of the ICE5G ( [[#Peltier--2015|Peltier et al., 2015]] ) and ANU ( [[#Lambeck--2014|Lambeck et al., 2014]] ) ice-sheet models. Since AR5, new global models are emerging that more rigorously treat ice and Earth structure uncertainty ( [[#Caron--2018|Caron et al., 2018]] ). However, there is also a growing recognition that lateral variations in Earth structure limit the utility of global models that treat the solid Earth as though it were laterally uniform ( [[#Love--2016|Love et al., 2016]] ; [[#Huang--2019|Huang et al., 2019]] ; T. [[#Li--2020|]] [[#Li--2020|]] [[#Li--2020|Li et al., 2020]] ).

As noted by SROCC, VLM from sources other than GIA – including tectonics and mantle dynamic topography, volcanism, compaction, and anthropogenic subsidence – can be locally important, producing VLM rates comparable to or greater than rates of GMSL change. Complete global projections of these processes are not available because of the small spatial scales, the sensitivity of subsidence to local human activities, and the stochasticity of tectonics ( [[#Wöppelmann--2016|Wöppelmann and Marcos, 2016]] ; [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ). Therefore, integrated RSL projections to date have either included only the component of VLM associated with GIA (as in AR5 and SROCC), or used a constant long-term background rate of change (including both GIA and other long-term drivers of VLM) estimated from historical tide gauge trends (e.g., [[#Kopp--2014|Kopp et al., 2014]] ). The updated projections use the second approach and extrapolate the field of long-term background rates of RSL change, including long-term VLM derived from tide gauges, to global coverage using a spatio-temporal statistical approach (Supplementary Material 9.SM.4.6; [[#Kopp--2014|Kopp et al., 2014]] ). The combined GIA and long-term VLM is assumed to be scenario independent and constant over the projected period. In areas where rapid subsidence occurs in a cluster of tide gauges (e.g., the western Gulf of Mexico), the associated rates are interpolated between the tide gauges. In areas where the available tide gauges exhibit large, tectonically driven VLM that changes considerably in rate over short distances (e.g., Alaska and the Bering Strait), a sizable uncertainty propagates into the RSL projections (Figure 9.26). Rates of RSL rise are likely to be underestimated due to subsidence in shallow strata that are not recorded by tide gauges ( [[#Keogh--2019|Keogh and Törnqvist, 2019]] ) and in some locations may therefore be minimum values, especially if anomalously high subsidence rates associated with fluid extraction are also considered (e.g., [[#Minderhoud--2017|Minderhoud et al., 2017]] ). Therefore, depending on location, there is ''low'' to ''medium confidence'' in the GIA and VLM projections employed in this Report. In many regions, higher-fidelity projections would require more detailed regional analysis.

<div id="9.6.3.3" class="h3-container"></div>

<span id="sea-level-projections-to-2150-based-on-shared-socio-economic-pathway-scenarios"></span>
==== 9.6.3.3 Sea Level Projections to 2150 Based on Shared Socio-economic Pathway Scenarios ====

<div id="h3-50-siblings" class="h3-siblings"></div>

Up to 2050, consistent with AR5 and SROCC, GMSL projections exhibit little scenario dependence ( ''high confidence'' ) (Figure 9.27 and Table 9.9) with ''likely'' ( ''medium confidence'' ) sea level rise between the baseline period (1995–2014) and 2050 of 0.19 (0.16–0.25) m under SSP1-2.6 and 0.23 (0.20–0.30) m under SSP5-8.5. These projections fall centrally within the range of published projections for RCP2.6 and RCP8.5 ( [[#9.6.3.1|Section 9.6.3.1]] ).

<div id="_idContainer070" class="Basic-Text-Frame"></div>

'''Table 9.9''' '''|''' '''Global mean sea level projections for five Shared Socio-economic Pathway (SSP) scenarios, relative to a baseline of 199''' '''5–2''' '''014, in metres.''' Individual contributions are shown for the year 2100. Median values ( ''likely'' ranges) are shown. Average rates for total sea level change are shown in mm yr <sup>–1</sup> . Unshaded cells represent processes in whose projections there is ''medium confidence'' . Shaded cells incorporate a representation of processes in which there is ''low confidence'' ; in particular, the SSP5-8.5 ''low confidence'' column shows the 17th–83rd percentile range from a p-box including SEJ- and MICI-based projections rather than an assessed ''likely'' range. Methods are described in 9.6.3.2.

{| class="wikitable"
|-
|
| '''SSP1-1.9'''

| '''SSP1-2.6'''

| '''SSP2-4.5'''

| '''SSP3-7.0'''

| '''SSP5-8.5'''

| '''SSP5-8.5''' Low Confidence

|-
| '''Thermal expansion'''

| 0.12 (0.09–0.15)

| 0.14 (0.11–0.18)

| 0.20 (0.16–0.24)

| 0.25 (0.21–0.30)

| 0.30 (0.24–0.36)

| 0.30 (0.24–0.36)

|-
| '''Greenland'''

| 0.05 (0.00–0.09)

| 0.06 (0.01–0.10)

| 0.08 (0.04–0.13)

| 0.11 (0.07–0.16)

| 0.13 (0.09–0.18)

| 0.18 (0.09–0.59)

|-
| '''Antarctica'''

| 0.10 (0.03–0.25)

| 0.11 (0.03–0.27)

| 0.11 (0.03–0.29)

| 0.11 (0.03–0.31)

| 0.12 (0.03–0.34)

| 0.19 (0.02–0.56)

|-
| '''Glaciers'''

| 0.08 (0.06–0.10)

| 0.09 (0.07–0.11)

| 0.12 (0.10–0.15)

| 0.16 (0.13–0.18)

| 0.18 (0.15–0.21)

| 0.17 (0.11–0.21)

|-
| '''Land-water Storage'''

| 0.03 (0.01–0.04)

| 0.03 (0.01–0.04)

| 0.03 (0.01–0.04)

| 0.03 (0.02–0.04)

| 0.03 (0.01–0.04)

| 0.03 (0.01–0.04)

|-
|
|-
| '''Total (2030)'''

| 0.09 (0.08–0.12)

| 0.09 (0.08–0.12)

| 0.09 (0.08–0.12)

| 0.10 (0.08–0.12)

| 0.10 (0.09–0.12)

| 0.10 (0.09–0.15)

|-
| '''Total (2050)'''

| 0.18 (0.15–0.23)

| 0.19 (0.16–0.25)

| 0.20 (0.17–0.26)

| 0.22 (0.18–0.27)

| 0.23 (0.20–0.29)

| 0.24 (0.20–0.40)

|-
| '''Total (2090)'''

| 0.35 (0.26–0.49)

| 0.39 (0.30–0.54)

| 0.48 (0.38–0.65)

| 0.56 (0.46–0.74)

| 0.63 (0.52–0.83)

| 0.71 (0.52–1.30)

|-
| '''Total (2100)'''

| 0.38 (0.28–0.55)

| 0.44 (0.32–0.62)

| 0.56 (0.44–0.76)

| 0.68 (0.55–0.90)

| 0.77 (0.63–1.01)

| 0.88 (0.63–1.60)

|-
| '''Total (2150)'''

| 0.57 (0.37–0.86)

| 0.68 (0.46–0.99)

| 0.92 (0.66–1.33)

| 1.19 (0.89–1.65)

| 1.32 (0.98–1.88)

| 1.98 (0.98–4.82)

|-
|
|-
| '''Rate (204''' '''0–2060)'''

| 4.1 (2.8–6.0)

| 4.8 (3.5–6.8)

| 5.8 (4.4–8.0)

| 6.4 (5.0–8.7)

| 7.2 (5.6–9.7)

| 7.9 (5.6–16.1)

|-
| '''Rate (2080–2100)'''

| 4.2 (2.4–6.6)

| 5.2 (3.2–8.0)

| 7.7 (5.2–11.6)

| 10.4 (7.4–14.8)

| 12.1 (8.6–17.6)

| 15.8 (8.6–30.1)

|}

Beyond 2050, the scenarios increasingly diverge. Between the baseline period (1995–2014) and 2100, processes in whose projection there is ''medium confidence'' drive ''likely'' GMSL rise of 0.44 (0.32–0.62) m and 0.77 (0.63–1.01) m under SSP1-2.6 and SSP5-8.5, respectively (Tables 9.8, 9.9). While derived using substantially updated methods, these projections are broadly consistent with SROCC, which projected ''likely'' GMSL rise of 0.41 (0.26–0.56) m and 0.81 (0.58–1.07) m under RCP2.6 and RCP8.5, respectively, over this period. They are modestly higher than those of AR5, which projected ''likely'' GMSL rise of 0.41 (0.25–0.58) m under RCP2.6 and 0.71 (0.49–0.95) m under RCP8.5 (Figure 9.25, Table 9.8). They are also broadly consistent with projections produced by driving AR5 methods with CMIP6 temperature and thermal expansion projections, which leads to 0.44 (0.27–0.61) m under SSP1-2.6 and 0.73 (0.49–1.02) m under SSP5-8.5 ( [[#Hermans--2021|Hermans et al., 2021]] ). The SSP1-2.6 and SSP5-8.5 projections are consistent with the ranges of published projections for RCP2.6 and RCP8.5 that do not incorporate MICI or SEJ ( [[#9.6.3.1|Section 9.6.3.1]] ).

<div id="_idContainer072" class="_idGenObjectStyleOverride-1"></div>

[[File:5985eebb8bd48aff38effb27264ccbea IPCC_AR6_WGI_Figure_9_27.png]]

'''Figure 9.27''' '''|''' '''Projected global mean sea level rise under different Shared Socio-economic Pathway (SSP) scenarios.''' ''Likely'' global mean sea level (GMSL) change for SSP scenarios resulting from processes in whose projection there is ''medium confidence'' . Projections and ''likely'' ranges at 2150 are shown on right. Lightly shaded ranges and thinner lightly shaded ranges on the right show the 17th–83rd and 5th–95th percentile ranges for projections including ''low confidence'' processes for SSP1-2.6 and SSP5-8.5 only, derived from a p-box including structured expert judgement and marine ice-cliff instability projections. Black lines show historical GMSL change, and thick solid and dash-dotted black lines show the mean and ''likely'' range extrapolating the 1993–2018 satellite altimeter trend and acceleration. Further details on data sources and processing are available in the chapter data table (Table 9.SM.9).

The ''likely'' GMSL projections for SSP3-7.0 and SSP5-8.5 are consistent with a continuation of the GMSL satellite-observed rate ( ''very likely'' 3.25 [2.88–3.61] mm yr <sup>–1</sup> ) and acceleration ( ''very likely'' 0.094 [0.082–0.115] mm yr <sup>–2</sup> ) of GMSL rise over 1993–2018 (Table 9.5 and [[IPCC:Wg1:Chapter:Chapter-2#2.3.3.3|Section 2.3.3.3]] ), which would imply a ''likely'' GMSL rise of 0.24 m (0.23–0.25 m) by 2050 and 0.73 m (0.69–0.77 m) by 2100. This extrapolation would also imply a ''likely'' rate of GMSL rise of 7.5 (7.4–7.6) mm yr <sup>–1</sup> over 2040–2060 and 11.2 (10.6–11.8) mm yr <sup>–1</sup> over 2080–2100. Over the satellite period, the observed acceleration has been driven primarily by ice-sheet contributions ( [[#9.6.1.2|Section 9.6.1.2]] and Table 9.5); in the median projections for SSP3-7.0 and SSP5-8.5, these accelerations are projected to continue at a slightly lower level, while the GMSL acceleration is augmented by an acceleration of thermal expansion and glacier loss associated with rising global temperature. Overall, these extrapolations imply that, under SSP1-1.9, SSP1-2.6, and SSP2-4.5, the GMSL acceleration is projected to decrease from its current level.

While ice-sheet processes in whose projection there is ''low confidence'' have little influence up to 2100 on projections under SSP1-1.9 and SSP1-2.6 (Table 9.9), this is not the case under higher emissions scenarios, where they could lead to GMSL rise well above the ''likely'' range. In particular, under SSP5-8.5, ''low-confidence'' processes could lead to a total GMSL rise of 0.6–1.6 m over this time period (17th–83rd percentile range of p-box, including SEJ- and MICI-based projections), with 5th–95th percentile projections extending to 0.5–2.3 m ( ''low confidence'' ). The assessed ''low confidence'' range is slightly narrower than, but broadly consistent with, the full 0.4–2.4 m range of published 5th–95th percentile projections for RCP8.5 since AR5 ( [[#9.6.3.1|Section 9.6.3.1]] ) – including those based on SEJ or incorporating MICI – and highlights the ''deep uncertainty'' in GMSL rise under the highest emissions scenarios (Box 9.4). The assessment of the potential contribution of processes in which there is ''low confidence'' to GMSL rise by 2100 is broadly consistent with the AR5’s assessment ( [[#Church--2013b|Church et al., 2013b]] ), which concluded that collapse of marine-based sectors of the AIS could cause several tenths of a metre of GMSL rise above the ''likely'' range.

While prior assessment reports, starting with the First Assessment Report ( [[#Warrick--1990|Warrick et al., 1990]] ), have focused on projecting GMSL up to the year 2100, time has progressed, and the year 2100 is now within the time frame of some long-term infrastructure decisions. For this reason, projections up to the year 2150 are also highlighted (Table 9.9). Over this time period, assuming no acceleration in ice-sheet mass fluxes after 2100, processes in which there is ''medium confidence'' lead to GMSL rise of 0.5–1.0 m under SSP1-2.6 and 1.0–1.9 m under SSP5-8.5. Processes in which there is ''low confidence'' could drive GMSL rise under SSP5-8.5 to 1.0–4.8 m (17th–83rd percentile) or even 0.9–5.4 m (5th–95th percentile).

Median projected RSL changes are shown in Figure 9.28, with driving factors highlighted in Figure 9.26. Approximately 60% (SSP1-1.9) to 70% (SSP5-8.5) of the global coastline has a projected median 21st century regional RSL rise within ±20% of the global mean increase ( ''medium confidence'' ). Consistent with AR5, loss of land ice mass will be an important contributor to spatial patterns in RSL change ( ''high confidence'' ), with ocean dynamic sea level being particularly important as a dipolar contributor in the north-west Atlantic, a positive contributor in the Arctic Ocean, and a negative contributor in the Southern Ocean south of the Antarctic Circumpolar Current ( ''medium confidence'' ) [[#9.2.4.2|Section 9.2.4.2]] ). As today, VLM will remain a major driver of RSL change ( ''high confidence'' ). Uncertainty in RSL projections is greatest in tectonically active areas in which VLM varies over short distances (e.g., Alaska) and in areas potentially subject to large ocean dynamic sea level change (e.g., the north-western Atlantic) ( ''high confidence'' ).

<div id="_idContainer074" class="Basic-Text-Frame"></div>

[[File:24f4f2d5f1718be2009d41874e62fcbd IPCC_AR6_WGI_Figure_9_28.png]]

'''Figure 9.28''' '''|''' '''Regional sea level change at 2100 for different scenarios (with respect to 199''' '''5–2''' '''014).''' Median regional relative sea level change from 1995–2014 up to 2100 for: '''(a)''' SSP1-1.9; '''(b)''' SSP1-2.6; '''(c)''' SSP2-4.5; '''(d)''' SSP3-7.0; '''(e)''' SSP5-8.5; and '''(f)''' width of the likely range for SSP3-7.0. The high uncertainty in projections around Alaska and the Aleutian Islands arises from the tectonic contribution to vertical land motion, which varies greatly over short distances in this region. Further details on data sources and processing are available in the chapter data table (Table 9.SM.9).

An alternative perspective on uncertainty in future sea level rise is provided by looking at uncertainty in time rather than elevation; that is, looking at the range of dates when specific thresholds of sea level rise are projected to be crossed (Figure 9.29). Considering only ''medium confidence'' processes, GMSL rise is ''likely'' to exceed 0.5 m between about 2080 and 2170 under SSP1-2.6 and between about 2070 and 2090 under SSP5-8.5. It is ''likely'' to exceed 1.0 m between about 2150 and some point after 2300 under SSP1-2.6, and between about 2100 and 2150 under SSP5-8.5. It is ''unlikely'' to exceed 2.0 m until after 2300 under SSP1-2.6, while it is ''likely'' to do so between about 2160 and 2300 under SSP5-8.5. However, processes in whose projections there is ''low confidence'' could lead to substantially earlier exceedances under higher emissions scenarios: under SSP5-8.5, 1.0 m could be exceeded by about 2080 and 2.0 m could be exceeded by about 2110 (17th percentile of p-box, incorporating projections based on SEJ and MICI), with 5th percentile projections as early as about 2070 for 1.0 m and 2090 for 2.0 m.

<div id="_idContainer076" class="Basic-Text-Frame"></div>

[[File:aac96d66d6c3036c972bc39d071d4a58 IPCC_AR6_WGI_Figure_9_29.png]]

'''Figure''' '''9.29 |''' '''Timing of when global mean sea level (GMSL) thresholds of 0.5, 1.0, 1.5 and 2.0 m are exceeded, based on four different ice-sheet projection methods informing post-2100 projections.''' Methods are labelled based on their treatment of ice sheets. ‘No acceleration’ assumes constant rates of mass change after 2100. ‘Assessed ice sheet’ models post-2100 ice-sheet losses using a parametric fit (Supplementary Material 9.SM.4) extending to 2300 based on a multi-model assessment of contributions under RCP2.6 and RCP8.5 at 2300. Structured expert judgement (SEJ) employs ice-sheet projections from [[#Bamber--2019|Bamber et al. (2019)]] . Marine ice-cliff instability (MICI) combines the parametric fit (Supplementary Material 9.SM3.4) for Greenland with Antarctic projections based on [[#DeConto--2021|DeConto et al. (2021)]] . Circles, thick bars and thin bars represent the 50th, 17th–83rd and 5th–95th percentiles of the exceedance timing for the indicated projection method. Further details on data sources and processing are available in the chapter data table (Table 9.SM.9).

<div id="9.6.3.4" class="h3-container"></div>

<span id="sea-level-projections-up-to-2100-based-on-global-warming-levels"></span>
==== 9.6.3.4 Sea Level Projections up to 2100 Based on Global Warming Levels ====

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Global warming levels represent a new dimension of integration in the AR6 cycle ( [[IPCC:Wg1:Chapter:Chapter-1#1.6.2|Section 1.6.2]] , Cross-Chapter Box 11.1). The SR1.5 ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ) concluded that, based on an assessment of GMSL projections published for 1.5°C and 2.0°C scenarios, there is ''medium agreement'' that GMSL in 2100 would be 0.04–0.16 m higher in a 2°C warmer world, compared to a 1.5°C warmer world based on 17–84% confidence interval projections (0.00–0.24 m based on 5–95% confidence interval projections) with a central value of around 0.1 m. The SR1.5 did not attempt to standardize the definition of warming-level scenarios, or to examine additional warming levels. No new integrated GMSL projections for 1.5°C or 2.0°C scenarios have been published since SR1.5.

Most of the contributors to GMSL are more closely tied to time-integrated GSAT than instantaneous GSAT ( [[#Hermans--2021|Hermans et al., 2021]] ), which means that sea level projections by warming level can only be interpreted if the warming levels are linked to a specific time frame. Here, the warming level projections are defined based on the 2081–2100 GSAT anomaly (Supplementary Material 9.SM.4.7). Different pathways in GSAT can be followed to reach a certain temperature level, which affects the temporal evolution of the different contributors to sea level change. For instance, there will be different ice-sheet and glacier responses to a fast increase to a peak warming of 2°C in 2050, followed by a plateau or a decrease, compared to a gradual increase to the same level of warming in 2100. The sea level projections presented might include different pathways to the same warming level in 2100, which is reflected in the uncertainty ranges, and should therefore be interpreted as illustrative of sea level scenarios under a certain warming level.

Projections of ''likely'' 21st-century GMSL rise along climate trajectories leading to different increases in GSAT between 1850–1900 and 2081–2100 are shown in Table 9.10, along with the SSPs for which the temperature-level projections are most closely aligned. For example, considering only processes in which there is ''medium confidence'' , from the baseline period (1995–2014) up to 2100, GMSL in a 2°C scenario is ''likely'' to rise by 0.40–0.69, which is intermediate between the projections for SSP1-2.6 and SSP2-4.5. GMSL in a 4°C scenario is ''likely'' to rise by 0.58–0.92 m, similar to the projection for SSP3-7.0. Consistent with the discussion in [[#9.6.3.3|Section 9.6.3.3]] , there is ''deep uncertainty'' in the projections for temperature levels above 3°C, and alternative approaches to projecting ice-sheet changes may yield substantially different projections in 4°C and 5°C futures. For example, employing SEJ ice-sheet projections ( [[#Bamber--2019|Bamber et al., 2019]] ) instead of the projections for ''medium confidence'' processes only leads to a 17th–83rd percentile rise between the baseline period (1995–2014) and 2100 of 0.7–1.6 m, rather than 0.7–1.1 m in a 5°C scenario.

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'''Table 9.10''' '''|''' '''Global mean sea level (GMSL) projections and commitments for exceedance of five global warming levels, defined by sorting GSAT change in 208''' '''1–2''' '''100 with respect to 185''' '''0–1''' '''900.''' Median values and ( ''likely'' ) ranges are in metres relative to a 1995–2014 baseline. Rates are in mm yr <sup>–1</sup> . Unshaded cells represent processes in whose projections there is ''medium confidence'' . Shaded cells incorporate a representation of processes in which there is ''low confidence'' ; in particular, the SSP5-8.5 ''low confidence'' column shows the 17th–83rd percentile range from a p-box, including projections based on structured expert judgement (SEJ) and marine ice cliff instability (MICI) rather than an assessed ''likely'' range. Methods are described in 9.6.3.2.

{| class="wikitable"
|-
|
| '''1.5''' ° '''C'''

| '''2.0''' ° '''C'''

| '''3.0''' ° '''C'''

| '''4.0''' ° '''C'''

| '''5.0''' ° '''C'''

| '''SSP5-8.5''' Low Confidence

|-
| '''Closest SSPs'''

| SSP1-2.6

| SSP1-2.6/SSP2-4.5

| SSP2-4.5/SSP3-7.0

| SSP3-7.0

| SSP5-8.5

|
|-
|
|-
| '''Total (2050)'''

| 0.18 (0.16–0.24) m

| 0.20 (0.17–0.26) m

| 0.21 (0.18–0.27) m

| 0.22 (0.19–0.28) m

| 0.25 (0.22–0.31) m

| 0.24 (0.20–0.40) m

|-
| '''Total (2100)'''

| 0.44 (0.34–0.59) m

| 0.51 (0.40–0.69) m

| 0.61 (0.50–0.81) m

| 0.70 (0.58–0.92) m

| 0.81 (0.69–1.05) m

| 0.88 (0.63–1.60) m

|-
| '''Rate (2040–2060)'''

| 4.1 (2.9–5.7) mm yr <sup>–1</sup>

| 5.0 (3.7–7.0) mm yr <sup>–1</sup>

| 6.0 (4.6–8.1) mm yr <sup>–1</sup>

| 6.4 (5.0–8.6) mm yr <sup>–1</sup>

| 7.2 (5.7–9.8) mm yr <sup>–1</sup>

| 7.9 (5.6–16.1) mm yr <sup>–1</sup>

|-
| '''Rate (2080–2100)'''

| 4.3 (2.6–6.4) mm yr <sup>–1</sup>

| 5.5 (3.4–8.4) mm yr <sup>–1</sup>

| 7.8 (5.3-–11.6) mm yr <sup>–1</sup>

| 9.9 (7.1–14.3) mm yr <sup>–1</sup>

| 11.7 (8.5–17.0) mm yr <sup>–1</sup>

| 15.8 (8.6–30.1) mm yr <sup>–1</sup>

|-
|
|-
| '''2000-yr commitment'''

| 2 to 3 m

| 2 to 6 m

| 4 to 10 m

| 12 to 16 m

| 19 to 22 m

|
|-
| '''10,000-yr commitment'''

| 6 to 7 m

| 8 to 13 m

| 10 to 24 m

| 19 to 33 m

| 28 to 37 m

|
|}

<div id="9.6.3.5" class="h3-container"></div>

<span id="multi-century-and-multi-millennial-sea-level-rise"></span>
==== 9.6.3.5 Multi-century and Multi-millennial Sea Level Rise ====

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Neither AR5 nor SROCC discussed the sea level commitment associated with historical emissions. Since AR5, new evidence has suggested that historical emissions up to 2016 will lead to a ''likely'' committed sea level rise (i.e., the rise that would occur in the absence of additional emissions) of 0.7–1.1 m up to 2300, while pledged emissions through 2030 increase the committed rise to 0.8–1.4 m ( [[#Nauels--2019|Nauels et al., 2019]] ).

Between the baseline period (1995–2014) and 2300, AR5 projected a GMSL rise of 0.38–0.82 m under a non-specific low-emissions scenario and 0.9–3.6 m under a non-specific high-emissions scenario (Table 9.11). The SROCC projected 0.6–1.0 m under RCP2.6 and 2.3–5.3 m under RCP8.5 ( ''low confidence'' ). RCP-based projections for 2300 published since AR5 span a broader range, even excluding studies employing SEJ or MICI, with 17th–83rd percentile projections ranging from 0.3–2.9 m for RCP2.6 and 1.7–6.8 m for RCP8.5 (Table 9.SM.8; [[#Kopp--2014|Kopp et al., 2014]] , 2017; [[#Nauels--2017|Nauels et al., 2017]] , 2019; [[#Bamber--2019|Bamber et al., 2019]] ; [[#Palmer--2020|Palmer et al., 2020]] ). Conservatively extending the ISMIP6- and LARMIP-2-based projections beyond 2100 by assuming no subsequent change in ice-sheet mass flux rates (an approach similar to that adopted by [[#Palmer--2020|Palmer et al. (2020)]] for the Greenland Ice Sheet and for the Antarctic Ice Sheet dynamics) leads to a GMSL change up to 2300 of 0.8–2.0 m under SSP1-2.6 and 1.9–4.1 m under SSP5-8.5 (17th–83rd percentile), while incorporating the ice-sheet contributions for 2300 assessed in [[#9.4.1.4|Section 9.4.1.4]] and [[#9.4.2.6|Section 9.4.2.6]] leads to 0.6–1.5 m and 2.2–5.9 m, respectively. Incorporating Antarctic results from a model with MICI ( [[#9.4.2.4|Section 9.4.2.4]] ), using RCP forcing to inform SSP-based projections, leads to 1.4–2.1 m for SSP1-2.6 and 9.5–16.2 m for SSP5-8.5 ( [[#DeConto--2021|DeConto et al., 2021]] ). Incorporating the SEJ-based ice-sheet projections of [[#Bamber--2019|Bamber et al. (2019)]] for 2°C and 5°C stabilization scenarios yields 1.0–3.1 m for SSP1-2.6, and 2.4–6.3 m for SSP5-8.5, although because of the differences in scenarios, the SSP1-2.6 estimates may be overestimated and the SSP5-8.5 may be underestimated. The eightfold uncertainty range across projection methods under SSP5-8.5 reflects ''deep uncertainty'' in the multi-century response of ice sheets to strong climate forcing.

Taking into account all these approaches, including published projections for RCP2.6, under SSP1-2.6 GMSL will rise between 0.3 and 3.1 m by 2300 ( ''low confidence'' ). This projection range indicates that, while SROCC projections under low emissions to 2300 are consistent with no ice-sheet acceleration after 2100, there is the possibility of a much broader range of outcomes at the high end, reflected in the range of published GMSL projections. Under SSP5-8.5, GMSL will rise between 1.7 and 6.8 m by 2300 in the absence of MICI and by up to 16 m considering MICI, a wider range than AR5 or SROCC assessments, but consistent with published projections ( ''low confidence'' ).

On still longer time scales, AR5 concluded with ''low confidence'' that the multi-millennial GMSL commitment sensitivity to warming was about 1–3 m °C <sup>–1</sup> GSAT increase. Two process-model studies since AR5 ( [[#Clark--2016|Clark et al., 2016]] ; [[#Van%20Breedam--2020|Van Breedam et al., 2020]] ) indicate higher commitments (Figure 9.30). Ice sheets dominate the multi-millennial sea level commitment (Sections 9.4.1.4 and 9.4.2.6), but the two studies disagree on the relative contribution of the Greenland and Antarctic ice sheets. Notably, processes such as MICI ( [[#9.4.2.4|Section 9.4.2.4]] ) that are a major factor behind the ''deep uncertainty'' in century-scale AIS response do not appear to have a substantial effect on the multi-millennial magnitude ( [[#DeConto--2016|DeConto and Pollard, 2016]] ). Only one of the studies of multimillennial GMSL commitments includes scenarios consistent with 1.5°C of peak warming ( [[#Clark--2016|Clark et al., 2016]] ); this study suggests a 2000-year commitment at 1.5°C of about 2.3–3.1 m, with approximately an additional 1.4–2.3 m commitment between 1.5°C and 2.0°C (i.e., about 3 to 5 m °C <sup>–1</sup> ). Taken together, both studies show a 2000-year GMSL commitment of about 2–6 m for peak warming of about 2°C, 4–10 m for 3°C, 12–16 m for 4°C, and 19–22 m for 5°C ( ''medium agreement'' , ''limited evidence'' ) (Table 9.10). GMSL rise continues after 2000 years, leading to a 10,000-year commitment of about 6–7 m for 1.5°C of peak warming (based on [[#Clark--2016|Clark et al., 2016]] ), and based on both studies of about 8–13 m for 2.0°C, 10–24 m for 3.0°C, 19–33 m for 4.0°C, and 28–37 m for 5°C ( ''medium agreement'' , ''limited evidence'' ) (Table 9.10).

An indicative metric for the equilibrium sea level response can be provided by comparing paleo GSAT and GMSL during past multimillennial warm periods (Sections 2.3.1.1, 2.3.3.3 and 9.6.2; Figure 9.9). However, caution is needed as the present and past warm periods differ in astronomical and other forcings (Cross-chapter Box 2.1) and in terms of polar amplification. The Last Interglacial ( ''likely'' 5–10 m higher GMSL than today and 0.5°C–1.5°C warmer than 1850–1900; [[#9.6.2|Section 9.6.2]] ; Table 9.6) is consistent with the [[#Clark--2016|Clark et al. (2016)]] projections for the 10,000-year commitment associated with 1.5°C of warming. Similarly, the Mid-Pliocene Warm Period ( ''very likely'' 5–25 m higher GMSL than today and ''very likely'' 2.5°C–4°C warmer) ( [[#9.6.2|Section 9.6.2]] ; Table 9.6) is consistent with the range of 10,000-year commitments associated with 2.5–4°C of warming, but GMSL reconstructions provide only a weak, broad constraint on model-based projections. An additional paleo constraint comes from the Early Eocene Climatic Optimum, which indicates that 10–18°C of warming is associated with ice-free conditions and a ''likely'' GMSL rise of 70–76 m (Sections 2.3.3 and 9.6.2). Together with model-based projections ( [[#Clark--2016|Clark et al., 2016]] ; [[#Van%20Breedam--2020|Van Breedam et al., 2020]] ), this period suggests that commitment to ice-free conditions would occur for peak warming of about 7°C–13°C ( ''medium agreement,'' ''limited evidence'' ).

On the basis of modelling studies, paleo constraints, single-ice-sheet studies finding multimillennial nonlinear responses from both the Greenland and Antarctic ice sheets (Sections 9.4.1.4 and 9.4.2.6), and the underlying physics, we conclude that GMSL commitment is nonlinear in peak warming on time scales of both 2,000 and 10,000 years ( ''medium confidence)'' and exceeds the AR5 assessment of 1–3 m °C <sup>–1</sup> ( ''medium agreement'' , ''limited evidence'' ) (Table 9.9). Although thermosteric sea level will start to decline slowly about 2,000 years after emissions cease, the slower responses from the Greenland and Antarctic ice sheets mean that GMSL will continue to rise for 10,000 years under most scenarios ( ''medium confidence'' ).

Since AR5, a small number of modelling studies have examined the reversibility of the multimillennial sea level commitment under carbon dioxide (CO <sub>2</sub> ) removal, solar radiation modification or local ice shelf engineering. The slow response of the deep ocean to forcing leads to global-mean thermosteric sea level fall occurring long afterward, even if CO <sub>2</sub> levels are restored after a transient increase: global mean thermosteric sea level rise takes more than a millennium to reverse ( [[#Ehlert--2018|Ehlert and Zickfeld, 2018]] ). Rapid reversion to pre-industrial CO <sub>2</sub> concentrations has been found to be ineffective at fostering regrowth of the AIS ( [[#DeConto--2021|DeConto et al., 2021]] ) but may reduce the multimillennial sea level commitment ( [[#DeConto--2016|DeConto and Pollard, 2016]] ). Altering sub-ice-shelf bathymetry ( [[#Wolovick--2018|Wolovick and Moore, 2018]] ) or triggering ice shelf advance through massive snow deposition ( [[#Feldmann--2019|Feldmann et al., 2019]] ) might interrupt marine ice sheet instability ( [[#9.4.2.4|Section 9.4.2.4]] ) and thus reduce sea level commitment. A reversion to pre-industrial Greenland Ice Sheet temperatures with solar radiation modification is projected to stop mass loss in Greenland but leads to minimal regrowth ( [[#Applegate--2015|Applegate and Keller, 2015]] ). Based on ''limited evidence'' , carbon dioxide removal, solar radiation modification, and local ice-shelf engineering may be effective at reducing the yet-to-be-realized sea level commitment, but ineffective at reversing GMSL rise ( ''low confidence'' ).

<div id="_idContainer078" class="Basic-Text-Frame"></div>

'''Table 9.11''' '''|''' '''Global mean sea level (GMSL) projections between 199''' '''5–2''' '''014 and 2300 for total change and individual contributions. Low emissions projections from: AR5 ( [[#Church--2013b|Church et al., 2013b]] ); RCP2.6 from SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ) and published projections (Table 9.SM.8); and SSP1-2.6 (from this Report). High emissions projections from: AR5 ( [[#Church--2013b|Church et al., 2013b]] ); RCP8.5 from SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ) and published projections (Table 9.SM.8); and SSP5-8.5 (this Report).''' Values for AR5 ( [[#Church--2013b|Church et al., 2013b]] ) and SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ) are adjusted from the 1986–2005 baseline used in past reports. Only total values are shown for published ranges. Only the Antarctic contribution changed between AR5 ( [[#Church--2013b|Church et al., 2013b]] ) and SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ). If a range is given, it is the 17th–83rd percentile range.

{| class="wikitable"
|-
|
| '''Low'''

| colspan="2"| '''RCP2.6'''

| colspan="4"| '''SSP1-2.6'''

|-
| m relative to 1995–2014

| '''AR5'''

| '''SROCC'''

| '''Post-AR5 Published Range'''

| '''No Ice-sheet Acceleration After 2100'''

| '''Assessed Ice-sheet Contribution'''

| '''MICI'''

| '''SEJ'''

|-
| '''Thermal expansion'''

| colspan="2"| 0.07–0.46 m

|
| colspan="4"| 0.19–0.35 m

|-
| '''Greenland'''

| colspan="2"| 0.14 m

|
| 0.22–0.39 m

| colspan="2"| 0.11–0.25 m

| 0.28–1.28 m

|-
| '''Antarctica'''

| colspan="2"| 0.21–0.25 m

|
| –0.05 to +1.14 m

| –0.14 to +0.78 m

| 0.71–1.35 m

| –0.11 to +1.56 m

|-
| '''Glaciers'''

| colspan="2"| n/a

|
| colspan="4"| 0.12–0.29 m

|-
| '''Land-water storage'''

| –0.03 m

| 0.07–0.37 m

|
| colspan="4"| 0.05–0.10 m

|-
|
|-
| '''Total (2300)'''

| 0.38–0.82 m

| 0.57–1.04 m

| 0. 3–2.9 m

| 0.8–2.0 m

| 0.6–1.5 m

| 1.4–2.1 m

| 1. 0–3.1 m

|-
|
|-
|
| '''High'''

| colspan="2"| '''RCP8.5'''

| colspan="4"| '''SSP5-8.5'''

|-
| m relative to 1995–2014

| '''AR5'''

| '''SROCC'''

| '''Post-AR5 Published Range Without (with) MICI'''

| '''No Ice-Sheet Acceleration after 2100'''

| '''Assessed Ice-sheet Contribution'''

| '''MICI'''

| '''SEJ'''

|-
| '''Thermal expansion'''

| colspan="2"| 0.28–1.80 m

|
| colspan="4"| 0.92–1.51 m

|-
| '''Greenland'''

| colspan="2"| 0.30–1.18 m

|
| 0.53–0.88 m

| colspan="2"| 0.32–1.75 m

| 0.40–2.23 m

|-
| '''Antarctica'''

| 0.02–0.19 m

| 0.60–2.89 m

|
| –0.39 to +1.55 m

| –0.28 to +3.13 m

| 6.87–13.54 m

| 0.03–3.05 m

|-
| '''Glaciers'''

| colspan="2"| 0.29–0.39 m

|
| colspan="4"| 0.32 m

|-
| '''Land-water storage'''

| colspan="2"| n/a

|
| colspan="4"| 0.05–0.10 m

|-
|
|-
| '''Total (2300)'''

| 0.89–3.56 m

| 2.25– 5.34 m

| 1.7–6.8 (up to 14.1) m

| 1.7–4.0 m

| 2.2–5.9 m

| 9.5–16.2 m

| 2.4– 6.3 m

|}

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[[File:844eaaa3c81cd3a84b1f38cbbbb50487 IPCC_AR6_WGI_Figure_9_30.png]]

'''Figure 9.30''' '''|''' '''Global mean sea level (GMSL) commitment as a function of peak global surface air temperature.''' From models ( [[#Clark--2016|Clark et al., 2016]] ; [[#DeConto--2016|DeConto and Pollard, 2016]] ; [[#Garbe--2020|Garbe et al., 2020]] ; [[#Van%20Breedam--2020|Van Breedam et al., 2020]] ) and paleo data on 2000-year '''(lower row)''' and 10,000 year '''(upper row)''' time scales. Columns indicate different contributors to GMSL rise (from left to right: total GMSL change, Antarctic Ice Sheet, Greenland Ice Sheet, global mean thermosteric sea level rise, and glaciers). Further details on data sources and processing are available in the chapter data table (Table 9.SM.9).

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'''Box 9.4 | High-end Storyline of 21st-century Sea Level Rise'''

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In this box, we outline a storyline (Glossary, Box 10.2; [[#Shepherd--2018|Shepherd et al., 2018]] ) for high-end sea level projections for 2100. This storyline considers processes whose quantification is highly uncertain regarding the timing of their possible onset and/or their potential to accelerate sea level rise. These processes are therefore not considered for the assessed upper bound of ''likely'' sea level rise by 2100 in section 9.6.3.3, as the ''likely'' range includes only processes that can be projected skilfully with at least ''medium confidence'' (based on ''agreement'' and ''evidence'' ).

As noted by SROCC, stakeholders with a low risk tolerance (e.g., those planning for coastal safety in cities and long-term investment in critical infrastructure) may wish to consider global-mean sea level rise above the assessed ''likely'' range by the year 2100, because ‘ ''likely'' ’ implies an assessed likelihood of up to 16% that sea level rise by 2100 will be higher (see also [[#Siegert--2020|Siegert et al., 2020]] ). Because of our limited understanding of the rate at which some of the governing processes contribute to long-term sea level rise, we cannot currently robustly quantify the likelihood with which they can cause higher sea level rise before 2100 ( [[#Stammer--2019|Stammer et al., 2019]] ).

In light of such ''deep uncertainty'' , we employ a storyline approach in examining the potential for, and early warning signals of a high-end sea level scenario unfolding within this century. In doing so, we note upfront that the main uncertainty related to high-end sea level rise is ‘when’ rather than ‘if’ it arises: the upper limit of 1.01 m of ''likely'' sea level range by 2100 for the SSP5-8.5 scenario will be exceeded in any future warming scenario on time scales of centuries to millennia ( ''high confidence'' ), but it is uncertain how quickly the long-term committed sea level will be reached ( [[#9.6.3.5|Section 9.6.3.5]] ). Hence, global mean sea level might rise well above the ''likely'' range before 2100, which is reflected by assessments of ice-sheet contributions based on structured expert judgement ( [[#Bamber--2019|Bamber et al., 2019]] ) leading to a 95th percentile of projected future sea level rise as high as 2.3 m in 2100 ( [[#9.6.3.3|Section 9.6.3.3]] ).

A plausible storyline for such high-end sea level rise in 2100 assumes a strong warming scenario ( [[IPCC:Wg1:Chapter:Chapter-4#4.8|Section 4.8]] ). The storyline considers faster-than-projected disintegration of marine ice shelves and the abrupt, widespread onset of marine ice cliff instability (MICI) and marine ice sheet instability (MISI) in Antarctica ( [[#9.4.2.4|Section 9.4.2.4]] ), and faster-than-projected changes in both the surface mass balance and dynamical ice loss in Greenland. While conceptual studies provide ''medium evidence'' of these processes, substantial uncertainties and ''low agreement'' in quantifying their future evolution arise from limited process understanding, limited availability of evaluation data, missing or crude representation in model simulations, their high sensitivity to uncertain boundary conditions and parameters, and/or uncertain atmosphere and ocean forcing (Sections 9.4.1.2; 9.4.2.2).

In Antarctica, high warming might lead to floating ice shelves starting to break up earlier than expected due to processes not yet accounted for in ice-sheet models or in current climate models used to force ice-sheet projections. Such processes include hydrofracturing driven by surface meltwater, and increase in ocean thermal forcing driven by ocean circulation changes (Sections 9.2.2.3, 9.2.3.2 and 9.4.2.3; [[#Hellmer--2012|Hellmer et al., 2012]] , 2017; [[#Silvano--2018|Silvano et al., 2018]] ; [[#Hazel--2020|Hazel and Stewart, 2020]] ). In particular, the Thwaites and Pine Island Glacier ice shelves could potentially disintegrate this century, which might trigger MICI before 2100 ( [[#DeConto--2016|DeConto and Pollard, 2016]] ; [[#DeConto--2021|DeConto et al., 2021]] ). MISI could potentially develop earlier and faster than simulated by the majority of models if fast flowing ice streams follow plastic, instead of currently assumed more viscous, sliding laws ( [[#Sun--2020|Sun et al., 2020]] ). Oceanic feedbacks could drive high-end sea level rise by changes in the meltwater-driven overturning circulation in ice cavities that cause additional melting ( [[#Jeong--2020|Jeong et al., 2020]] ); by a warming of the ocean water in contact with the ice shelves due to increased stratification and thus reduced vertical mixing (Sections 9.2.2.3 and 9.2.3.2; [[#Golledge--2019|Golledge et al., 2019]] ; [[#Moorman--2020|Moorman et al., 2020]] ; [[#Sadai--2020|Sadai et al., 2020]] ); or by an increase in sea ice cover due to increased ocean stratification ( [[#9.3.2.1|Section 9.3.2.1]] ), which could reduce the amount of warm, moist air that reaches the continent, and limit the mass gain from snowfall over the ice sheet ( [[#Sadai--2020|Sadai et al., 2020]] ).

In Greenland, stronger mass loss than currently projected might also occur ( [[#Aschwanden--2019|Aschwanden et al., 2019]] ; [[#Khan--2020|Khan et al., 2020]] ; T. [[#Slater--2020|]] [[#Slater--2020|Slater et al., 2020]] ). For example, warming-induced dynamical changes in atmospheric circulation could enhance summer blocking and produce more frequent extreme melt events over Greenland similar to the record mass loss of more than 500 Gt in summer 2019 ( [[#9.4.1.1|Section 9.4.1.1]] ; [[#Delhasse--2018|Delhasse et al., 2018]] ; [[#Sasgen--2020|Sasgen et al., 2020]] ). Cloud processes in polar areas that are not well represented in models could further enhance surface melt ( [[#Hofer--2019|Hofer et al., 2019]] ), as could feedbacks between surface melt and the increasing albedo from meltwater, detritus and pigmented algae ( [[#9.4.1.1|Section 9.4.1.1]] ; [[#Cook--2020|Cook et al., 2020]] ). The same ice dynamical processes associated with basal melt and MISI discussed for Antarctica could also occur in Greenland, as long as the ice sheet is in contact with the ocean.

The strength of all these processes is currently understood to depend strongly on global mean temperature and polar amplification, with additional linkages through feedback from global mean sea level ( [[#Gomez--2020|Gomez et al., 2020]] ). These dependencies on a joint forcing imply that processes are strongly correlated. Hence, both their uncertainties and their possible cascading contribution to high-end sea level rise are expected to combine. Therefore, high-end sea level rise can occur if one or two processes related to ice-sheet collapse in Antarctica result in an additional sea level rise at the maximum of their plausible ranges (Sections 9.4.2.5 and 9.6.3.3; Table 9.7) or if several of the processes described in this box result in individual contributions to additional sea level rise at moderate levels. In both cases, global-mean sea level rise by 2100 would be substantially higher than the assessed ''likely'' range, as indicated by the projections including ''low confidence'' processes reaching in 2100 as high as 1.6 m at the 83rd percentile and 2.3 m at the 95th percentile ( [[#9.6.3.3|Section 9.6.3.3]] ).

Identifying the potential drivers of a high-end sea level rise allows identification of sites and observables that can provide early warnings of a much faster sea level rise than the ''likely'' range of this and previous reports. One potential site for such monitoring is Thwaites Glacier, which is melting faster in some places and slower in others than models simulate. At this glacier, the effect of tides and channelling of warm water flows on the melting is evident ( [[#Milillo--2019|Milillo et al., 2019]] ), making the floating ice shelf potentially vulnerable to breakup from hydrofracturing, driven by surface meltwater, much earlier than expected. In addition, the glacier is retreating towards a zone with deeper bedrock, which at its present rate of retreat would be reached in 30 years ( [[#Yu--2019|Yu et al., 2019]] ). Thwaites Glacier is therefore a strong candidate to experience large-scale MISI and/or MICI ( [[#Golledge--2019|Golledge et al., 2019]] ; [[#DeConto--2021|DeConto et al., 2021]] ), making it the ideal site for monitoring early warning signals of accelerated sea level rise from Antarctica. Such signals could possibly be observed within the next few decades ( [[#Scambos--2017|Scambos et al., 2017]] ).

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