Antarctic meltwater alters future projections of climate and sea level

Domain: earth_science
Published: 2025-10-29
Editorial outcome: major_revision

Abstract
Imperfect understanding of ice sheet-climate interactions poses challenges for projecting the impacts of ice sheet mass loss on future climate and sea level. Here we couple a dynamic Antarctic ice sheet model and global climate model to simulate ice sheet-climate interactions. In our single-model, single-member modeling framework, we find sea level and climate projections are significantly modified from uncoupled simulations neglecting Antarctic meltwater under RCP8.5 and RCP4.5. Antarctic meltwater yields surface air temperatures up to 1.5°C higher in parts of the Northern Hemisphere, while broadly dampening temperature rise in the Southern Hemisphere. Due to radiative feedback changes, both emissions scenarios have global mean surface temperature warming ~0.3°C lower in the coupled scenario than the control by 2100, with a maximum anomaly of ~1°C at 2200 under RCP8.5. This slows Antarctica’s contribution to global mean sea level rise. Total Antarctic sea level contributions under RCP8.5 (2100: ~0.3 m, 2200: >3 m) include substantial contributions from East Antarctica, though not under RCP4.5 (2100: ~0.1 m, 2200: >1 m). Regionally, projected sea level is up to 0.9 m higher in the Pacific than the global mean Antarctic contribution under RCP8.5 at 2200.

Introduction
The climate system is undergoing unprecedented changes as atmospheric greenhouse gas concentrations continue to rise1. The resulting energy imbalance has accelerated ice sheet mass loss and sea level rise, which are projected to continue in coming centuries2. Current pledges submitted by parties to the United Nations Framework Convention on Climate Change are insufficient for meeting the Paris Agreement’s Long-Term Temperature Goal of limiting global mean surface temperature (GMST) rise to “well below” 2°C above pre-industrial values while “pursuing efforts” to limit it to 1.5°C3. These pledges imply a 2.4-2.6°C GMST rise by 2100, while current policies imply 2.7°C warming4,5. Insufficient global mitigation risks are locking in large-scale ice sheet mass loss, exposing people and ecosystems around the world to substantial sea level rise. By 2060, over one billion people could be living in low elevation (<10 m above sea level) coastal areas, increasing the risks of sea level rise impacts for socially and geographically vulnerable populations6,7. Understanding interactions between ice sheets and the broader climate system will be key to constraining future Antarctic ice sheet (AIS) stability, global climate, and sea level8,9 which in turn has implications for global policy and climate justice10.

Observations confirm that the AIS increasingly contributed to global mean sea level rise (GMSLR) in recent decades11, while model projections suggest that the AIS could become the dominant contributor to GMSLR in the coming centuries2. Incursions of Antarctic circumpolar deep water in ice shelf cavities have been implicated as a cause of recent mass loss and grounding line retreat in sectors of East Antarctica12. Surface melt is currently observed to various extents across many ice shelves13 and is expected to become more frequent and longer lasting under medium to high emissions scenarios14. Additionally, continued atmospheric warming increases the potential for meltwater-driven hydrofracturing15, with ice shelves which provide substantial buttressing, being especially vulnerable16.

As the AIS loses mass, meltwater and solid ice enter the Southern Ocean. The current generation of global climate models participating in phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively) lack interactive marine-based ice sheets capable of simulating dynamic ice sheet evolution, such as grounding line retreat, while iteratively coevolving with other climate model components17. As a result, CMIP5-6 simulations underestimate ice sheet melt responses under increasing greenhouse gas concentrations, and the impact of meltwater discharge on future climate and sea level17–19. In turn, meltwater-induced climate responses impact ice sheet evolution and consequently the timing and magnitude of future GMSLR. The locations of ice sheet mass loss determine the spatial distribution of sea level responses around the world, emphasizing the need to consider gravitational, rotational, and Earth deformation effects on sea level10,20,21 in addition to climate-ice sheet interactions.

To assess climatic responses to greenhouse gas forcing and AIS discharge, prior modeling studies have conducted freshwater forcing experiments by adding meltwater to the Southern Ocean22–26. Despite variations in the location, quantity, and timing of freshwater input in these studies, modeled responses have several commonalities, including expanded Southern Ocean sea-ice, delayed GMST rise, increased ocean stratification, and subsurface ocean warming around the Antarctic margin. Warmer subsurface ocean temperatures and slowed atmospheric warming impact ice sheet evolution through increased basal melt and delayed surface melt, respectively. To better understand these interactions and more far-field impacts of Antarctic meltwater on the global climate system, dynamic ice sheets should be interactively embedded within global climate models27 and efforts to achieve this are advancing28. Recently, numerical experiments using coupling schemes under climate change projection scenarios have been used to assess climate-ice sheet feedbacks29,30 and a Southern Ocean meltwater forcing intercomparison project is underway17.

Here, we present results from numerical simulations in which coupling is implemented between the Community Earth System Model (CESM) 1.2, a coupled global climate model which includes interactive atmosphere, ocean, land, and sea-ice modules31, and the Penn State University ice sheet model (PSU3D), a dynamic-thermodynamic ice sheet model32–34; (See Methods). We then use a global sea level model that includes 3D viscosity structure35,36 to understand the spatially variable sea level response resulting from Antarctic mass loss in our coupled ice sheet-climate simulations. Our coupling setup exchanges liquid and solid ice sheet discharge from PSU3D to coastal surface level grid cells in CESM, and passes 2m air temperature, 400m ocean temperature, and precipitation fields from CESM back to PSU3D. CESM does not simulate cavity circulation under floating ice shelves so bias-corrected ocean temperatures from CESM are extrapolated under ice shelves in PSU3D. Latent heat from solid ice discharge in PSU3D is accounted for in CESM. Latent heat from liquid melt is accounted for in PSU3D and therefore not reflected in modeled ocean temperatures in CESM. Ice sheet topography in CESM is fixed, while changes in topography evolve in PSU3D. As a result, changes in ice sheet surface height and extent simulated in PSU3D are not felt by the CESM atmosphere or land surface model. Temperature and precipitation values received by PSU3D are lapse rate corrected and surface melt is calculated with a positive degree day scheme, accounting for the partial refreezing of meltwater in the firn layer. Marine ice cliff instability (MICI) dynamics are included (See Methods), providing substantially more meltwater forcing than most previous climate-ice sheet studies. While the validity of MICI remains contested37, the intent here is to explore the global impact of meltwater forcing while including brittle ice dynamics which have informed high-end sea level projections.

We explore changes in climate and sea level under future emissions scenarios RCP4.5 and RCP8.5 from 2005 to 2215. RCP scenarios were used rather than SSPs to make the best use of prior model simulations. RCP4.5 approximately corresponds to SSP2-4.5 and RCP8.5 to SSP5-8.538. While global mitigation efforts should preclude the RCP8.5 scenario in the long-term, we include this scenario because it tracks historical CO2 emissions39 and provides a useful case study for understanding coupled modeling responses. We include RCP4.5 as it results in end-of-century temperatures that are around or slightly above 2°C40. Within the text, ‘coupled’ refers to the simulations with interactive coupling between the ice sheet model and climate model and ‘control’ (or ‘uncoupled’) refer to the simulations with no interactive AIS which are equivalent to a standard CESM1.2 simulation, which produces minimal meltwater41. Due to computational constraints, simulations have one ensemble member per emissions scenario. There is no interactive Greenland Ice Sheet in any simulations presented here as we focus on the Antarctic response. This work builds upon the one-way coupled modeling protocol of Sadai et al. (2020) by implementing interactive coupling.

Results
Antarctic contribution to global mean sea level rise
In agreement with modern observations (See Methods), we find that from 2005-2020 the West Antarctic Ice Sheet (WAIS) contributes to a sea level rise while the East Antarctic Ice Sheet (EAIS) displays a slight mass gain (Supplementary Fig. 1, Supplementary Table 1). Under RCP8.5, the EAIS begins consistently contributing to sea level rise by 2030, and by 2040 under RCP4.5. Under RCP8.5, the EAIS mass loss increases mainly due to ice shelf melting under a warming atmosphere, leading to an increase in iceberg calving and ice cliff failure at marine-terminating ice margins. As a result, the GMSLR contribution from the EAIS surpasses that from the WAIS by 2080 (Supplementary Table 1). By 2100, cumulative GMSLR contributions from West and East Antarctica are similar: 0.15 m from WAIS and 0.19 m from EAIS, producing a total contribution of 0.34 m (Fig. 1e, Supplementary Table 1). This is on the upper end of the 0.03–0.34 m range projected for Antarctica in IPCC AR6 under RCP8.52 and consistent with uncoupled climate-ocean-ice sheet simulations that also included ice cliff calving processes34. The WAIS contribution by 2100 is dominated by Thwaites Glacier retreating on reverse-sloped bedrock (i.e., from Marine Ice Sheet Instability, MISI, driven retreat) (Fig. 1c). Both Thwaites and Pine Island glaciers are mostly lost in the RCP8.5 simulation by the mid-22nd century. By 2200, both the Ross and Filchner-Ronne ice shelves collapse, the EAIS margin undergoes widespread mass loss, the Antarctic peninsula thins, and the WAIS retreats (Fig. 1d). Despite the onset of MISI in West Antarctica, the EAIS remains the dominant contributor to GMSLR through the end of the RCP8.5 simulation. The total GMSLR contribution from Antarctica by 2200 is 3.37 m, of which 1.75 m is sourced from the EAIS and 1.62 m from the WAIS (Fig. 1f, Supplementary Table 1).

Under RCP4.5, lower greenhouse gas forcing limits the AIS GMSLR contribution to 0.13 m by 2100 with 0.1 m from WAIS and 0.03 m from EAIS (Fig. 1e, Supplementary Table 1). The pattern of ice loss mirrors that of RCP8.5 with Thwaites Glacier retreating and Ronne-Filchner thinning, but ice shelf thinning is less extensive overall, particularly in the EAIS (Fig. 1a). By 2200 the AIS GMSLR contribution reaches 1.17 m with 0.97 m from WAIS and 0.2 m from EAIS (Fig. 1f, Supplementary Table 1). The long-term view shows the impact of reducing greenhouse gas forcing; while WAIS still retreats substantially, large sections of the EAIS and portions of the Antarctic peninsula remain intact under RCP4.5 thereby limiting the AIS contribution to GMSLR.

Polar climate response
As CESM has static ice sheet topography, while PSU3D has evolving ice sheet topography, air temperatures noted here represent advected changes from evolving ocean conditions and do not reflect changes in the local land surface within CESM. In our coupled RCP8.5 experiment, surface air temperature (SAT) increases ~2–4°C by 2100 across the Southern Ocean and AIS (Fig. 2a). Regionally, this is ~1–4°C cooler than the uncoupled simulation (Fig. 2b). By the end of the 22nd century, there is widespread 5–10°C warming across the ice sheet, especially in the Ross and Weddell Sea regions, although this is up to ~7°C cooler than the uncoupled control simulation across the coastal region (Supplementary Fig. 2a, b). Under RCP4.5, SAT increases by ~1-2°C by 2100 in the coupled simulation, except in the region of the Ross Sea where temperatures are lower by the end of 2100 and 2200 as compared to the start of the simulation (Supplementary Figs. 3a, 4a). Compared to the uncoupled simulation, SAT is ~1°C cooler by 2100, although the coupled simulation is slightly warmer in a few locations (Supplementary Fig. 3b). By 2200 the cooler temperatures in the coupled simulation as compared to the control are more pronounced with the largest difference in the Ross Sea (Supplementary Fig. 4b).

Throughout the RCP8.5 simulation, precipitation over the Southern Ocean increases (Fig. 2c; Supplementary Fig. 2c), although this change is less than in the uncoupled simulation (Fig. 2d; Supplementary Fig. 2d). The same overall patterns are found in RCP4.5 except the coupled simulation has slightly more precipitation than the control around Queen Maud and Wilkes Land by 2100 (Supplementary Fig. 3c, d). By 2200, precipitation in the coupled simulation has increased (Supplementary Fig. 4c) but is consistently lower in the RCP4.5 coupled simulation compared to the control (Supplementary Fig. 4d).

By 2100, under RCP8.5, ocean temperatures at 400 m depth warm substantially across the Southern Ocean (Fig. 2e), driven by freshwater-induced stratification and reduced vertical mixing. The greatest warming is in the Weddell Sea, with a 3°C temperature rise compared to the start of the simulation; the Ross Sea and EAIS margin near Wilkes Land warm by ~1°C. The end of century difference between the coupled and control simulations (Fig. 2f), as compared to the warming over time in the coupled simulation (Fig. 2e), shows that much of the warming is due to meltwater forcing. By 2200, 400 m ocean temperatures show widespread ~2°C warming relative to the start of the simulation (Supplementary Fig. 2e), with the Ross Sea ~4°C warmer in the coupled simulation than the control (Supplementary Fig. 2f). Under RCP4.5, the Weddell Sea and region around Wilkes Land are 3°C and 1°C warmer, respectively, by 2100 (Supplementary Fig. 3e). As in RCP8.5, much of this warming is due to the impact of meltwater (Supplementary Fig. 3f). By 2200 in RCP4.5, warming intensifies with ~2°C warming across the Southern Ocean since the start of the simulation (Supplementary Fig. 4e) and temperatures in the Ross and Weddell Seas up to 4°C higher in the coupled simulation than the control (Supplementary Fig. 4f).

The impacts of these climatic changes on the ice sheet explain the mass loss and contribution to GMSLR. Increases in SAT drive surface melt and induce hydrofracturing and ice shelf thinning while the accumulated ocean heat (i.e., warming at 400 m) increases basal melt under buttressing ice shelves. The concentration of heat in the Ross and Weddell Seas flips cold ice-shelf cavity circulation to warm cavity circulation patterns, accelerating loss of the large ice shelves, triggering MISI and in some places, ice cliff calving.

Global climate response
Our coupled simulations show that the impacts of AIS discharge into the Southern Ocean are felt globally (Fig. 3). In both RCP4.5 and RCP8.5, freshwater forcing begins suppressing greenhouse gas induced GMST rise by the middle of the 21st century (Fig. 3c). Under RCP8.5, GMST is 0.33°C lower by 2100 and 1.05°C lower by 2200 in the coupled simulation than in the control (Fig. 3d; Table 1). Under RCP4.5, GMST in the coupled simulation is 0.29°C lower by 2100 and 0.31°C lower by 2200 than in the control (Fig. 3d, Table 1). Compared to prior uncoupled experiments with the same models26, the impact of Antarctic meltwater on GMST is reduced due to the delayed ice sheet mass loss, and, therefore, lower meltwater input, that results from the interactive coupling.

The delayed GMST warming resulting from Southern Ocean freshwater forcing in our coupled simulations is caused by both a stronger ocean heat uptake efficiency (i.e., more efficient heat storage in the subsurface ocean) and a stronger atmospheric radiative feedback (i.e., more efficient radiative damping at the top of the atmosphere) (ref. 42; See Methods). The former is owing to the increased ocean stratification and vertical heat redistribution in the Southern Ocean manifested as subsurface warming (Fig. 2f). The latter is due to the broad surface cooling in both the Southern Ocean and the tropical Pacific driven by freshwater forcing and large-scale teleconnections (Supplementary Fig. 6)42–44. The Southern Ocean cooling anomalies and sea-ice expansion locally enhance surface albedo feedback, whereas the tropical East Pacific surface cooling drives a more-stabilizing cloud feedback and lapse-rate feedback, resulting from the strengthened tropical west-east zonal sea surface temperature gradient45,46. The net radiative feedback parameter over the 21st century is therefore strengthened from −1.02 W/m²/K to −1.13 W/m²/K in the coupled RCP8.5 simulation, corresponding to a 0.4°C decrease in effective climate sensitivity (from 3.8°C to 3.4°C) relative to the uncoupled control simulation. The results are qualitatively consistent with the findings in our prior uncoupled freshwater forcing simulations26,42.

Although GMST increases at a slower rate compared to our control simulations, the coupled simulations exhibit strong regional SAT variations (Fig. 3a, b). For example, by 2100 in RCP8.5, surface air temperatures over the Southern Ocean are ~1–1.5°C cooler, central and east Asia and the North Pacific are 0.3°C warmer, and the North Atlantic, including Greenland, eastern North America and western Europe are 1-2°C warmer than in the uncoupled simulation (Fig. 3a). By 2200 in RCP8.5 (Supplementary Fig. 5a), anomalous cooling over the Southern Ocean continues, with temperatures >3°C cooler in the coupled experiment near the Antarctic continent. By 2100 under RCP4.5 the difference between the coupled and control experiments shows a bipolar temperature pattern with anomalous cooling in the Southern Hemisphere and anomalous warming in the Northern Hemisphere but the pattern differs from that seen in RCP8.5 with no strong warming over the North Atlantic and instead more diffuse warming across Asia, North Africa, and the Pacific Ocean (Fig. 3b). By 2200 in RCP4.5, anomalous cooling of ~1°C occurs over the Southern Ocean and Arctic with slight warming across much of the Northern Hemisphere and the most pronounced warming of ~0.5°C along the Pacific coast of North America (Supplementary Fig. 5c).

The higher temperatures in the North Atlantic and North Pacific point to the existence of a bipolar seesaw, a pattern previously identified in Southern Ocean freshwater forcing experiments43,47,48. In RCP8.5, future slowing of the Atlantic Meridional Overturning Circulation (AMOC), defined as the maximum overturning at 24-26°N, is found to be largely delayed (Fig. 4a). In the coupled RCP8.5 simulation, the AMOC remains stronger than in the control from 2075 until the end of the simulation. The maximum difference between AMOC strength in the two simulations occurs at 2100 when the strongest signal of enhanced warming in both air (Fig. 3b) and sea surface temperatures (Supplementary Fig. 6) is observed in the coupled simulation. In RCP4.5, both the coupled and control simulations exhibit initial AMOC weakening followed by a partial recovery beginning after 2125. Under RCP4.5 whether the coupled or control simulation shows stronger AMOC strength is variable over time (Fig. 4a). In addition, northward heat transport is found to decrease under both RCP8.5 and RCP4.5 forcing (Fig. 4b). The largest differences occur at low-to-mid northern latitudes where the Atlantic Ocean is most effective at transporting heat northward.

Coupled meltwater simulations under both RCP8.5 and RCP4.5 show a robust northward shift of the intertropical convergence zone, due to zonal-mean energetic constraints associated with the anomalous inter-hemispheric surface temperature gradient49. In the Southern Hemisphere, wide-spread surface cooling is accompanied with broad drying while in the Northern Hemisphere, precipitation generally increases (Fig. 3 and Supplementary Fig. 5), which may arise from both local temperature changes or remote tropical teleconnections50. Under RCP8.5, zonal mean precipitation in the control simulation changes little over time (Fig. 3g) while in the coupled simulation it enhances north of the equator and diminishes to the south (Fig. 3h).

Broader Implications of Antarctic Ice Loss
Antarctic mass loss has important implications for people around the world. Fully understanding the potential impact of Antarctica’s contribution to sea level necessitates analyzing the spatial pattern of the sea level response. Global sea level change patterns from ice sheet mass loss are spatially variable due to gravitational, rotational, and Earth deformational (GRD) effects51. Using a 3D viscoelastic Earth structure model (See Methods) which includes anomalously low viscosities under the WAIS allows us to account for the sea level impact of water expulsion into the open ocean from formerly ice-covered areas undergoing uplift due to glacial isostatic adjustment52. Patterns of sea level change from GRD effects vary spatially and temporally depending on the regions of Antarctic mass loss21,51. Consistent with prior research10,21 we find that regions northward of 30°S will experience sea level rise higher than the Antarctic contribution to GMSLR regardless of emissions scenario and timescales. However, the most heavily impacted regions vary (Fig. 5). Under RCP4.5 by 2100 the Indian, Pacific, and Atlantic Ocean basins, including the Caribbean, experience 0.03 m higher regional sea level rise than the global mean (Fig. 5a). By 2200 the pattern is similar but the difference between the highest impacted regions increases by an order of magnitude to 0.3 m (Fig. 5c). Under RCP8.5 by 2100, most of the Pacific basin is projected to experience regional sea level rise of up to 0.09 m higher than the GMSLR of 0.34 m (Fig. 5b). This pattern remains at 2200 with areas in the central Pacific experiencing 0.9 m more regional sea level rise than the GMSLR of 3.37 m while the Indian and Atlantic Ocean basins experience 0.6 and 0.7 m higher regional sea levels, respectively (Fig. 5d). These regional changes are solely based on the Antarctic response but realized sea level would also depend on Greenland mass loss, thermosteric responses, and other factors which are not accounted for here21,53.

Contrasting the global sea level response to the influence of meltwater on GMST has implications for global mitigation efforts and climate (in)justice10. Under RCP8.5, the timing when GMST exceeds 1.5–2°C above preindustrial (defined here following IPCC AR6 as when the 20-year rolling mean exceeds 1.5–2°C above the 1850–1900 average) is minimally affected by the meltwater induced delay in GMST rise (Supplementary Fig. 7a). This is because these warming values are surpassed before the meltwater-induced delayed warming effect strengthens. In our simulations, under high emissions (RCP8.5) 1.5°C is passed by 2026 and 2°C is delayed by 1 year in the coupled simulation. Under RCP4.5, 1.5°C and 2°C are each delayed by 1 year in the coupled simulation (Supplementary Fig. 7b). Given that these are single model runs with one set of models, how meltwater effects and other climate feedbacks impact the timing of different temperature thresholds remains deeply uncertain.

While the timing of the Long-Term Temperature Goal is minimally impacted, the long-term difference in GMST when accounting for meltwater input and feedbacks is substantial (Table 1) and relevant for informing future global mitigation target setting. The strength of the delayed GMST warming that occurs from Antarctic meltwater forcing should be considered alongside other climate feedbacks, such as the anticipated enhanced warming effect of permafrost melt. The combined impacts of climatic changes that influence GMST with other impacts such as sea level rise could pose substantial challenges if a GMST-based metric was used to inform international policy post-210010. In this study we find that GMST is 1.05°C lower under RCP8.5 by 2200 in the coupled simulation compared to the control, but this relatively cooler climate trajectory is commensurate with an Antarctic GMSLR contribution of 3.37 m and regional sea level rise of up to 4.3 m in the Pacific (Fig. 5d). Under RCP4.5, GMST is 0.31°C lower in the coupled simulation by 2200 while Antarctica’s contribution to GMSLR is 1.17 m and regional sea level rise of up to 1.5 m occurs in the Pacific and Indian Ocean basins and Caribbean Sea (Fig. 5c). In other words, while the loss of ice sheet mass results in a slightly lower GMST rise in the coupled simulations, it drives substantial sea level rise. This supports previous work which has argued that focusing on GMST as a metric to inform climate action could exacerbate climate justice concerns10. Even with a slower rate of warming, any continued increase in sea level poses risks to island and coastal communities, and raises wide-ranging issues of intergenerational inequity and distributive injustice10. The implications for justice and policy are complex and influenced by many other factors that require further detailed study.

Methods
Model descriptions and initialization
The climate model used is Community Earth System Model 1.2.2 with Community Atmospheric Model 5 atmospheric physics (CESM1-CAM5)31. CESM1.2 is a coupled global Earth system model containing interactive ocean, atmosphere, sea-ice, and land models linked via a coupler. The continent and ocean boundaries do not change in CESM1.2. CESM1.2 does not include fully interactive Greenland or Antarctic ice sheets58. It was run with 1° resolution for the ocean and sea-ice components and 0.9×1.25° resolution for the atmosphere and land components. The model grid has a displaced pole over Greenland. It is initialized with 20th century restart files. Simulations spanning the period from 2005-2200 and were conducted under Representative Concentration Pathway RCP8.5 and RCP4.559.

The Antarctic ice sheet model used is the Penn State University ice sheet model (PSU3D)32,33. PSU3D is a three-dimensional ice sheet model that approximates ice flow using hybrid ice dynamics with an imposed parameterization of ice flux across the grounding line60, allowing for realistic simulation of grounding line retreat32. In these simulations it is run at a 10 km resolution with basal sliding coefficients obtained from an inverse run matching modeled surface elevations and observations61. Initial conditions were from DeConto et al. 34, which included simulations using offline CESM1.2 forcing. Bed topographic boundary conditions use Bedmap262. We use CESM1.2 and PSU3D with Bedmap2 boundary conditions to make the best use of previously run control experiments.

Models were run on the NCAR Cheyenne high performance computing system63. For the control scenarios, there is no freshwater forcing provided by the PSU3D ice sheet model. Testing determined that our RCP8.5 control matched the SAT evolution of the standard CMIP5 CESM1 simulation for RCP8.5, which is used for the time series in Fig. 364. For RCP4.5, data from CESM1-CAM5_rcp45_r1i1p1 obtained from the CMIP5 data repository was used as a control65. Preindustrial temperature data was obtained from the CMIP5 data repository66.

Coupling methodology
CESM1.2 and PSU3D are run with an annual interactive coupling scheme allowing for a dynamic response of the ice sheet to changes in the climate model, and response of the climate system to ice sheet freshwater discharge. The annual coupling is accomplished as follows67. An initial climatology is used to force PSU3D for one model year (2005), provided from a standard CESM1.2 control simulation lacking additional meltwater forcing. The ice sheet model is then run for one model year to provide liquid water and solid ice discharge from the ice sheet, interpolated onto the CESM1.2 ocean grid at the nearest coastal ocean cell from where the mass loss occurs in the ice sheet. Latent heat is accounted for as solid ice melts. The ice sheet model internally determines which types of ice sheet discharge exit as a solid or liquid. Latent heat of the solid ice discharge phase change is accounted for in the climate model while latent heat for liquid fields is accounted for within the ice sheet model32. Latent heat from fields the ice sheet counts as liquid is accounted for within the ice sheet model. This may underestimate the delayed warming effect of ice sheet discharge on global climate; therefore, the extent of the delayed warming effect seen in this study should be taken as a lower bound. The fields the ice sheet model outputs as liquid melt components include ice sheet basal melt, sub-ocean ice face melt, percolation of meltwater to the base, and the counter effect of basal refreezing while the solid ice discharge forcing contains ice lost from calving and cliff failure. Liquid and solid discharge components enter the climate model at the surface ocean level55,68. While injecting freshwater at depth can lead to more mixing and a deeper mixed layer and work with other ocean models has shown the depth of freshwater input to have an effect in other models69, previous work with CESM indicates that there is little difference in CESM1-simulated ocean surface temperature, salinity, and sea-ice responses when freshwater is applied at depth versus in experiments where freshwater is added at the surface41. Following the calculation of interpolated liquid and solid ice sheet discharge, CESM1.2 is then run for one model year to obtain a meltwater-perturbed climatology. Ocean temperature at 400 m depth, 2 m surface air temperatures, and precipitation are then passed back to the ice sheet. The ice sheet model is built to intake ocean temperatures at 400 m as this depth level is representative of where warm deep water enters the Amundsen Sea Embayment70,71.

Initial surface topography is provided to the climate sheet model by the ice sheet model at the first timestep. At subsequent timesteps, deviations between the input topography and evolving ice sheet topography are accommodated via lapse rate corrections for temperature and precipitation70. The fraction of input precipitation that falls as snow versus rain is parameterized based on the input surface air temperature. The ice sheet model surface mass balance calculations account for surface melting and refreezing as well as percolation of liquid water below the ice sheet surface layer. Surface melt is calculated via a positive degree day scheme, which calculates melt from the input temperature and precipitation, with melt beginning at -1°C based on observational relationships72.

Ocean forcing of the ice sheet
The ocean melt rate parameterization is a quadratic function of the temperature difference between the nearest ocean grid cell and the depth-dependent freezing temperature which is defined as follows.

Ocean melt = (K T ρw c W ) / (L f ρi) |T o − T f | (T o − T f ) (1)

Where T o is input 400 m ocean temperature, T f is the freezing-point temperature at the base of the ice at a given depth, ρ w and ρ i are the densities of water and ice, c W is the specific heat of ocean water, L f is the latent heat of fusion, K T is a transfer factor, and K is a set of tunable parameters32.

This parameterization has been shown to be one of the best performing options for representing both integrated shelf melt and grounding line melt73. Melting at submerged vertical ice faces is calculated from the ocean melt rate of surrounding grid cells and increased by a scaling factor of 2 to better match observations. This scaling factor is lower than the scaling factor of 10 which was used in previous uncoupled ice sheet simulations34,70.

To bring the ocean temperatures being passed to the ice sheet into closer agreement with observational values, the ocean temperature at 400 m is bias corrected using World Ocean Atlas 2018 observational temperatures74,75. As CESM1.2 does not have ocean cavities under ice shelves, ocean temperatures are taken from the static edge of the continent using a grid-cell-by-grid-cell stepping approach to determine the ocean temperature at the ice shelf edge wherever it is available in the ocean model. The ice sheet model interpolates them to the ice sheet grid and linearly extrapolates a value back into the interior of the shelf. To avoid a small number of warm grid cells from having an oversized impact on melt rates when interpolated over a large shelf, a single value is calculated as the average of all ocean grid cells in polygons specifying each ice shelf’s area and that one value is interpolated under that shelf. To bring melt rates in the Amundsen Sea region into closer alignment with observational values, a 2.5°C anomaly is added in that region, similar to the bias corrections applied in previous work with PSU3D34,70.

Calving sensitivity and cliff failure
As in previous work with PSU3D, surface crevasse depth is influenced by surface melt and rainwater, assuming a quadratic relationship between meltwater production (R) and crevasse penetration depth (d w).

d w = CALVLIQ R 2 (2)

This meltwater enhanced crevassing (d w) influences ice shelf hydrofracturing and calving33,34. To bring mass loss from calving in line with observations over the modern period the CALVLIQ parameter is set to 35 m-1 yr2.

As used here, the ice sheet model accounts for enhanced calving at thick (O 1000 m) marine-terminating ice fronts that have lost their buttressing ice shelves, leaving tall subaerial ice cliffs prone to brittle failure76. Ice cliff calving occurs at calving fronts where the stresses exceed the yield strength. The cliff calving parameterization is applied as a horizontal wastage with a maximum rate of 7.7e3 m/y34. We note that the role of marine ice cliff calving in future Antarctic ice loss remains contested37,77, with much of the uncertainty caused by a lack of observations and poorly constrained physical properties of damaged glacial ice78,79.

Model validation
Before the coupled run was integrated, several shorter tests were done under transient climate forcing from 2005-2020 to check for consistency between model results and existing observational measurements. The total modeled rate of basal melt around the continent from 2005-2017 is 1343.21 Gt/yr67, in alignment with rates from 80 [1280-1628 Gt/yr] and 81 [1010-1310 Gt/yr]. The total modeled calving rate over this period is 974.874 Gt/yr67, slightly below the estimate of 1177-1465 Gt/yr in ref. 80. The modeled basal melt rates at the Pine Island, Thwaites, Ross, and Ronne-Filchner ice shelves are 36.4, 35.1, 0.28, and 0.27 m/yr, respectively67 as compared to 81 [14, 26.7, 0.3, 0.2 m/yr] and 82 [16.2, 17.2, 0.3, 0.3 m/yr]. While modeled rates of ice loss are higher than the average observed melt rates at PIG and Thwaites, the total sea level rise contribution from the WAIS is in line with observations and areas of higher melt rates (up to 43 m/yr) have been seen at the Thwaites grounding line83. From 2005 to 2017, the total modeled AIS sea level rise contribution is 2 mm, lower than the 7.4 ± 1.5 mm Antarctic contribution reported for 1992–202011 implying that the coupled simulation is slightly underestimating sea level rise contributions during this observational period. The spatial patterns of changes in ice thickness from 2005 to 2020 compare well with observations from 84 (their Fig. 1 compared to our Supplementary Fig. 1).

Sea level rise calculations
Global mean sea level contributions are calculated using the modified volume above flotation (VAF) method which accounts for the rise or fall of bedrock elevation below grounded ice which changes VAF but does not alter sea level85.

Geographically variable sea level changes accounting for gravitational, Earth rotational86 and Maxwell viscoelastic deformational87 effects are calculated by solving the sea level equation51,88. Calculations account for migrating shorelines and inundation of areas freed of marine grounded ice88,89. We adopt the finite volume sea level solver to solve the sea level equation on a global tetrahedral grid including 3D variations in Earth’s rheological structure35. We adopt the 3D viscosity structure and laterally varying lithospheric thickness model EM3D_L90 based on ANT-20 regional seismic tomography model91 in Antarctica and S362ANI global seismic tomography model92 across the rest of the globe. Lithosphere thickness in the model is based on 93 over Antarctica and a global model94 elsewhere. Globally, the adopted computational grid has an average spatial (lateral and radial) resolution of 12 km from the surface to the Mohorovičić Discontinuity (MOHO), 25 km to 220 km depth, and 50 km to the core mantle boundary. The grid is regionally refined in Antarctica, with a resolution of 6 km to the base of the MOHO, 12 km to 220 km depth, and 25 km to 350 km depth36. The ice sheet model provides the initial topography in Antarctica, and this is merged with ETOPO2 elsewhere.

Global energy budget analysis
The ocean heat uptake efficiency parameter (κ) and the radiative feedback parameter (λ) are calculated as:

κ = dN / dT, λ = d(N − F) / dT, (3)

Where dN is the global-mean net top of atmosphere radiation imbalance, dF is effective radiative forcing and dT is the global-mean near-surface air temperature change42. Based on the global-mean energy budget framework95,96, the transient global warming rate (dT/dt) can be approximated as:

dT/dt = (dF/dt) / (κ − λ) (4)

Where we substitute values of κ or λ from control or coupled simulations to isolate the impacts of ocean heat uptake efficiency or radiative feedback on the global warming rate42. Effective climate sensitivity is calculated as:

EffCS = −F 2x / λ (5)

Where F 2x represents the effective radiative forcing from a doubling of atmospheric carbon dioxide. The value of F 2x in CESM1.2 is 3.88 W m2 97. EffCS is an analog to equilibrium climate sensitivity except using λ from a transient state assuming λ remains constant until equilibrium42.

Data visualization
Spatial sea level maps were created in ArcGIS using a Goode homolosine ocean-oriented projection10,98. Figures 1–3 and supplemental figures were created with Cartopy99. Sea level maps use country outlines provided by Natural Earth shapefiles: Pacific groupings, 1:10m countries, 1:50m Tiny Country Points. On some figures scientific colormaps are from 100, 101.

Data availability
The climate data and spatial sea level mapping data generated in this study and referenced in the paper have been deposited in the University of Massachusetts Amherst ScholarWorks repository (https://doi.org/10.7275/6t64-wy56)102. The climate model data fields and spatial sea level data not referenced in this paper are available for non-commercial use from the corresponding authors due to difficulties hosting a large dataset externally. The ice sheet model data is available in the ScholarWorks repository (https://doi.org/10.7275/6t64-wy56)102. Data for the 1850-1900 baseline and CMIP5 RCP8.5 and RCP4.5 simulations are available from the Centre for Environmental Data Analysis64–66. Natural Earth country boundary data is available at www.naturalearthdata.com.

Code availability
CESM1.2 is available from the National Center for Atmospheric Research. The PSU3D code is available in the ScholarWorks repository102, please contact DP and RD for assistance running it. The 3D GIA model is available from the code’s developer Konstantin Latychev. Scripts for running the models and creating the figures are in the data repository (https://doi.org/10.7275/6t64-wy56).

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "See attached PDF\n[Editorial Note: This attachment is displayed at the end of this file]", "reviewer_2": "Summary\n--\nSadai et al. couple a older (CMIP5 era) version of the Community Earth System Model to a complex model of the Antarctic\nice sheet, and perform simulations of mid- and high-level climate change scenarios with and without the ice sheet coupling\nenabled to show its impact on a number of regional and global climate metrics. Coupling of ice sheets into complex climate\nmodels appropriate for CMIP-type projections is an important and emerging area of science and they demonstrate and\nanalyse a number of notable features that result from their coupling which are significant and worth publicising to a general\naudience. The paper is clearly written, with appropriate figures and referencing. For me, the main weaknesses is the degree\nto which the quantitative extent of some of their results - which follow from a simulation of Antarctic ice sheet mass loss that\nis at the very top end of the IPCC-assessed range and a highly parameterized anomaly coupling method, with no attempt to\naddress any model uncertainty - is likely to be highly model dependent. This is not uncommon for this new area of research,\nbut I think the authors could help their readers by doing more to put the their ice sheet simulation in the context of other\nstudies and guard against readers seeing the numbers they put on their consequent global changes as \"likely\" features of\nfuture climate change, rather than the illustrations of the potential of possible physical mechanisms in the climate system that\nthey are.\nGeneral Comments\n--\nAs far as positive's go, my comments in the Summary pretty much say it all. This was an interesting and enjoyable paper to\nread. The increased sophistication of the climate model, the detail in the physical analysis of impacts of ice sheet coupling in\nthe climate system and translation of the mean sea level changes to region patterns via global sea level modelling all make\nthis a significant step forward from previous Nature Communication publications on this topic (e.g Park et al 2023).\nI think this is an important paper that highlights important, unappreciated potential global impacts of ice sheet coupling.\nHowever, I think it's also important that the audience is aware of the relevant limitations (which are not uncommon for this\nfield) of the modelling system that produces the simulations, and that readers can consider the quantitative detail they're\nbeing shown appropriately. That level of model description might not be what is usually considered appropriate for this\njournal, but the approximations in their method and model are an important factor in the results they get and I think that\nreaders ought to have some awareness of the very broad physical approximations going on under the hood of the\ninteractively icy parts of the model, compared to what they perhaps expect from the explicit physics in other parts of a CMIP\nclimate model like CESM-CAM.\nI am a little concerned this is lost by rather briefly summarising it all at the end; there is a just simple reference to a previous\npaper for the ice sheet initialisation, no real sensitivity test on tuning the fundamental ocean coupling parameterisation in\ntheir system, or the implications of the sizable, regionally-dependent anomaly adjustment that allows it to work with the\nclimate model biases. The surface coupling between the ice and CESM does not seem to be mentioned at all, and I do not\nthink it has been documented elsewhere? In terms of checking the performance of the coupled ice sheet/climate system the\nfirst paragraph \"Model Validation\" section is welcome, but pretty much a broad-brush bare minimum of what I'd really want to\nsee in terms of having any real confidence in interpreting the results quantitatively. I realise Nat Comm is not a place that\nwelcomes that level of detail, hence my suggestion that a stronger caveat emptor be put on taking the numbers reported too\nliterally.\nOn top of the considerable uncertainty in the detail that arises from being unsure of the model formulation, the reponses\nbeing analysed are probably at the outer edge of what is considered likely. The loss of mass from the ice sheet is at the top of the IPCC range, with a model that I think includes a somewhat controversial parameterisation of Marine Ice Cliff Instability, forced by a Scenario that is now considered an extreme at 2100 but they use extended to 2200. Their ocean coupling\nmechanism is likely to further amplify the climate response - their parameterisation effectively immediately flushes cold melt\nfrom the cavity and puts it in exactly the place where it will most increase stratification and exacerbate the sub-shelf warm\nwater that the melt calculation sees, guaranteeing a positive feedback. It's all physically possible, but far from the only set of\nphysically plausible responses. Since there is no uncertainty analysis presented it would be easy for resulting sea level rise\nand GMST-mitigation numbers they report to be misinterpreted, rather than being seen as perhaps an upper plausible limit\non the possible Antarctic contribution.\nA large degree of model dependence is an unavoidable fact in this emerging area of science. I hope that the authors are\ninvolved in ongoing multi-model comparisons, like eg ISMIP7 (https://theghub.org/groups/ismip6/wiki) or MISOMIP2,\nespecially, considering their coupled abilities and ambitions to include an interactive GrIS, in coupled experiments of those\nprojects. Some coupled experiments were proposed in ISMIP6 (Nowicki et al. 2016 Geosci. Model Dev.), and it is likely that\nmore will be for CMIP7, with a focus, as here, on Antarctica.\nSpecific comments\n--\nlines 113,390,647: \"fully coupled\" is an ambiguous and usually inaccurate term for any model of the Earth System, including\nthis one. Many possible component couplings are simplistically parameterised or omitted entirely, and if \"fully\" is meant\nsimply to indicate that all the components that the modellers wanted to include are permitted to exchange information, it is\nvague and subjective.\nlines 120,646: I think an explicit comment on the non-use of the coupled Greenland ice sheet component of CESM would be\ngood. CESM has been a a pioneer of work with ice sheet coupling and is known for its interactive GrIS which you've actively\ndecided not to use here.\nline 122: it might help orient readers to note that, if I read it right, this is an evolution of the same model and simulation\nprotocol used in Sadai et al. 2020, with the important difference that now the models are interactively coupled together.\nline 123: it would be helpful to note how these older scenarios map onto more recent IPCC AR6 SSP framework - and\nideally onto the public thinking on the sorts of Scenarios that are now considered realistic and are being proposed for the\nnext round of climate projections (https://wcrp-cmip.org/scenariomip-cmip7-proposal). While it's not untrue to say that\nRCP8.5 is policy-relevant to mid-century, it is very extreme after that. RCP8.5's most plausible use for me is as the \"useful\ncase study for understanding coupled modeling responses\" - and that's justification enough, but this is what should be\nforegrounded, not the suggestion of policy relevance that risks subsequent results being misinterpreted.\nline 139: Following cliff collapse, do the atmosphere, ocean and sea-ice models in CESM see a change in domain that\nmight change their boundary condition calculations for the ice sheet?\nline 166: \"melt-water induced suppression...\" does this affect EAIS and WAIS equally? The implication that cooling\nautomatically implies a reduction loss from AIS ignores the significant response in AIS snowfall that many climate models\nsee with warming - in that case, for some timescales at least, cooling implies a milder increase in AIS snow and a net\nincrease in AIS mass loss. I'd like to see a little more of what happens on the surface in this model. Could the authors show\nwhat the snow response in the RCPs in this model means for AIS VAF, the precipitation shown in figure 2c isn't enough to\nsee what's going on here.\nFigure 3c, 3d, 4c: I didn't understand why the RCP4.5 lines only go to 2100 in these plots\nline 307: Solving the global sea-level equation is a valuable addition to this paper, rather than just stopping with the global\nmean sea level numbers. Does the change in solid earth eg WAIS uplift affect the ice sheet model as it runs, impact the\nmelting of WAIS as suggested by Gomez'15? Have mass change from Greenland or redistribution of ocean properties from\nthe climate model been included or just mass from AIS? If not, although it's fair to report these numbers as the influence of\nAIS (possibly the dominant one?) on regional sea-level within what will be a wider picture that includes other influences, I'm\nconcerned that if this is just one component towards a very non-linear global picture the numbers reported in this part could\nbe misinterpreted.\nline 333: The acronym LTTG is explained in passing very early on, and then only used, once, toward the very end of the\npaper, by which time I'd forgotten what it meant. Could the full term be used here for clarity?\nline 395: Although there's not a lot of coupled simulations of this sort for context, I think it would be helpful to include some\nbroader multi-model context of the AIS contribution to sea level, eg the standalone ISMIP6 AIS mass loss projections\n(Seroussi et al. 2020). This would highlight the model dependency and very wide spread (both net positive and negative sea\nlevel contributions are possible) of the state of knowledge in the community - adding interactive coupling to models does not\nreduce that uncertainty and is not the reason (as far as I can tell) that Park23 and Siahaan22 get sea level contributions of\nopposite signs.\nline 660: ice sheet model initial conditions are really important in terms of determining the ice sheet behaviour over the\nfollowing century or two. I'd prefer more detail upfront than just a reference to go look elsewhere. In particular, in this context\nof a coupled climate - ice sheet model are these ice initial conditions in equilibrium with some climate forcing from CESM?\nDo they have an initial overall trend in VAF that is either baked into the initialisation or dependent on a systematic bias in\nCESM boundary conditions that will give a signal regardless of the climate forcing or coupling they'll see in the future\nsimulations?\nline 665: I'm a bit confused by the setup of the uncoupled control. Is this saying that the RCP8.5 control has no AIS fresh\nwater flux at all? Not even surface runoff, or mass from inventory capped snowpack that keeps ice sheet \"in balance\". Are\nyour experiments showing the impact of coupled water fluxes, or just of having some water coming from AIS at all.\nCompared to what is said in Sadai et al. 2020 - I thought both experiment and control had flux, it's just that one was fixed and\nthe other varying?\nline 692: This sort of coupling is not without precedent, but it is very simple and putting both liquid and solid fresh water into\nthe ocean at the surface, at the coastline, is likely to enhance the stratification effect and make the feedback to the melt\nparameterisation stronger. Solid discharge and its latent heat requirements for melting would be spread and diluted over a\nmuch wider area in reality and even if in CESM it makes no difference whether you put the coastal melt in at the surface or\ndepth as quoted, it's unrealistic either way - and the different approaches have. been shown to make a difference in other\nmodels (Mathiot et al. Geosci. Model Dev. 2017) so this isn't really a justification that it really doesn't matter if the\nparameterisation does this.\nline 714: I think the use and tuning of the (somewhat controversial (Edwards et al 2019, Nature)) parameterisation of Marine\nIce Cliff Instability in PSU3D needs highlighting. I assume it is used here, since the main text talks about ice cliff failure, but it\ndoes not appear in this model description. The fact that the significance of this aspect of model physics and how it should be\nimplemented in a model is debated in the community should should be perhaps be noted in the main text for a general\naudience if it is playing a significant role in the result of the ice sheet simulation.\nline 671: I would like some description of the surface coupling. I don't think this is mentioned at all, and I'm surprised this is\nnot more important in CESM's response to such large AIS warming. Is it based on how CESM deals with surface coupling to\nGreenland or an external PDD scheme or some other downscaled mass/energy balance modelling? As already noted I\nwanted to see more on what the model was doing with snow change component of the AIS VAF budget. My understanding\nis that CESM (newer versions at least) have a very significant increase in snowfall, which would act to mitigate the discharge\nor loss in the first century at least - this sort of result isn't apparent in your simulations and the precipitation in figure 2 is not\ndetailed enough to interpret in this way. Does the surface topography change in PSU3D affect the CESM topography - I\nwould assume so, and with ice thickness changes of many 100s of metres I imagine it would be important to the climate\nmodel response, but I don't think this is explicitly mentioned anywhere? Do the atmosphere, ocean and sea-ice models in\nCESM ever see a change in domain that might change their boundary condition calculations for the ice sheet, say after shelf\ncollapse?\nline 692: This section describes a really important part of how your model is representing the interactions you are reporting\non and I felt it was passed over rather lightly. You mention that you use a (new?) scaling factor of 2, but the previously used\nvalue, 5 times larger, reproduces observations better? Then despite this scaling, a general bias correction is used. And then,\nan extra 3 degree correction is added for a particular key region. This all comes across as a bit arbitrary, and tuned to\nreproduce a specific modern state - with this level of detail it's little difficult to trust when it's going to be used to assess the\nsensitivity of the model to a change to a very different future state. When other cavities (eg Ross, Filchner) flip to warm ocean\nconditions like current Amundsen, do they get the same extra 3 degrees in the coupling parameterisation too? Since you've\nalready corrected for ocean biases appropriate for the modern day regimes, does the 3 degree term need to be applied to all\nwarm water shelves, whenever and wherever they are seen?\nline 731: PIG and Thwaites being relatively poor matches to obs is a bit worrying - they are small areas, so won't affect your\ntotal WAIS contribution evaluation, but are crucial for the dynamic sensitivity of WAIS, which you then see as being less than\nEAIS in the simulations.\nline 749: 1.5cm at what date, or is that a constant offset?\nline 742: Is the topographic information from the solid earth model coupled to anything, either\nCESM or PSU3D?\nline 787, 794: saying that data will be made available upon acceptance and that model code is available upon request -\nneither allowing for peer review of this manuscript - is far from best practice in terms of open and reproducible science.", "reviewer_3": "Summary / Key results\nThis paper presents results from coupled climate-Antarctic ice sheet model simulations under future emissions scenarios\nRCP 4.5 and RCP 8.5 to evaluate the impact of feedbacks from ice-climate interactions. The outputs are then used to project\nglobal sea level rise. The authors find that surface warming is delayed at 2100 compared to simulations where the ice sheet\nis not coupled to the climate model. The contribution of the Antarctic Ice Sheet to global sea level rise is less than that in the\nuncoupled simulation. Sea level rise is spatially uneven, with the Pacific experiencing a larger increase in mean sea level\nthan other regions.\nSignificance\nThis is an interesting study that shows a reduction in warming and subsequent melting of the Antarctic Ice Sheet when a\ncoupled ice sheet is included in future climate simulations. The most commonly cited future projections from CMIP5/6 do not\ninclude meltwater or an interactive ice sheet; the authors here demonstrate that there are important interactions and\nfeedbacks that these experiments are neglecting and that need to be taken into account to obtain accurate projections.\nI am not entirely convinced of the study’s novelty. I note that similar experiments have been done before (which the authors\ncite): Park et al. (2023) and Siahaan et al. (2022). How is this work significantly different and/or how does it advance our\nunderstanding? The authors should articulate this more clearly.\nValidity/ Data and methodology/Analytical approach\nThe data analysis and interpretation is sound and the conclusions are justified. The authors have done a good job designing\nthe experiments so that the specific impacts of meltwater and the coupled ice sheet/climate can be isolated. However, I have\na few questions/concerns:\n• The models are coupled on a relatively coarse timescale, as they only exchange information once every year. This could\nbe sufficient for ice sheet processes which react relatively slowly, but seasonal effects could be important for atmosphere,\nocean and sea ice.\n• The climate model does not explicitly represent ice shelves, which limits the ability to infer basal melting rates underneath\nthe main ice shelves (Ross, Filchner-Ronne, etc).\n• Melt from the Greenland Ice Sheet was not included in the simulation; this is okay for an Antarctic-focused study, but how\nmight the results change when Greenland is included? For example, I would expect the pattern of sea level rise to change\nsubstantially with the reduction in solid ice mass in the Northern Hemisphere.\n• The climate model used, CESM1.2, is relatively old (from the CMIP5 generation) and low-resolution when it comes to\natmosphere-ice-ocean interactions. For example, it does not represent coastal polynyas and Antarctic Bottom Water\nformation correctly. How might this limit the conclusions?\nSuggested improvements\n• It would be helpful to comment on processes on sub-grid and sub-annual spatial/temporal scales and whether or not these\ncould be important.\n• I would like a brief discussion of how the results might change if the impacts of melt from the Greenland Ice Sheet are\nincluded (even if it is only in reference to other work)\nClarity and context\nThe paper is very clearly written and is placed in the appropriate context\nReferences\nReferences are appropriate\nYour expertise: My expertise is mainly in climate and earth system modelling. I am less familiar with sea level and GIA\nmodelling and do not feel qualified to evaluate this portion of the manuscript.\nMinor comments\nIntroduction\nLine 73: over what time frame? More references?\nLine 76: “various extents” is very vague. Surface melt in Antarctica is currently limited and not a significant contributor to\nmass loss; how extensive is surface melt in terms of area, amount of freshwater? What regions are we talking about?\n(Antarctic Peninsula yes; others?)\nLine 80: which ice shelves are you referring to? Or is this just a general statement?\nLine 122: “simulations” -> “simulation”\nLines 122-125: You justify the use of RCP 8.5 but not RCP 4.5—why this scenario?\nResults\nLine 139: The representation of ice cliff calving processes in models can be controversial, did you do any simulations where\nyou tested the sensitivity of the results to including this process?\nLines 163-168: Note that the effect of adding meltwater forcing is much bigger than the coupling effect.\nLines 182-183: temperature in the Ross Sea region is actually lower, this is very interesting! Why is that?\nLines 194-195: “By 2200 precipitation has increased and is consistently lower in the RCP4.5 coupled simulation …” this\ndoesn’t make sense, if precipitation increased it can’t be lower\nPolar climate response section: what about sea ice coverage/extent? How important is that? How much do precipitation\nchanges contribute to surface mass balance changes over Antarctica?\nFig 3: Why does the RCP 4.5 simulation timeseries stop in 2100? I thought this was also run to 2200?\nLines 313-314: “regions northward of 30°S will experience sea level rise higher than the Antarctic contribution to GMSLR”:\nthis is confusing because it’s not as simple as saying Antarctica contributed x amounts of SLR in this location. It would be\nbetter to give this number relative to global means.\nLines 330-331: “Given that these are single model runs with one set of models, policy implications are limited in the short\nterm.” This isn’t quite the right phrasing here and mixes several concepts. Yes, your study is limited to one model, and this\nmeans there is substantial uncertainty in the numbers, but this is separate from the policy implications of the results.\nLines 343-346: “These combined impacts exacerbate climate justice concerns as SLR presents risks to recognition\njustice for island and coastal communities, including the Alliance of Small Island States, and wide-ranging issues of\nintergenerational inequity and distributive injustice” You’ve mentioned climate justice several times; acknowledging that this\nis a serious issue, it’s not really the focus of this paper and seems like an odd thing to be emphasizing here in the results\nFig 5: nice figure!\nDiscussion\nLines 380-381: “Paleoclimate evidence shows signs of past ice sheet retreat in deep EAIS subglacial basins and while\nfuture model projections show differing responses.” This sentence is grammatically incorrect, not sure how to interpret it\nLines 392-393: “An important next step will be the addition of an interactively coupled Greenland Ice Sheet model.” Yes, I\nthink this is very important and could affect the global patterns that you see. A bit more discussion of this aspect would be\nhelpful. What have others found when they coupled the GrIS?\nLine 397: which intermediate complexity model? How much of an improvement is CESM 1.2?\nImpact of ice shelf cavities not being explicitly represented? More discussion of study limitations is needed (annual time step\netc)\nMethods:\nWhy do you show results for RCP 4.5 only to 2100? Text says you ran to 2200, if not please correct\nIs a time step of one year really enough? Are there seasonal feedbacks that are not accounted for?\nOcean forcing of the ice sheet: is a bias correction based on present day values appropriate for future projections?"}, "author_response": ""}, {"round": 2, "reviewer_comments": {"reviewer_1": "Reviewer: Xylar Asay-Davis\nI would like to thank the authors for addressing my comments in the first round of reviews. I feel that my comments have all\nbeen addressed either by changing the manuscript or by explaining why they have chosen not to make the changes. In\nparticular, the revised text now explains the methodology in a way that covers my earlier concerns about latent heat. I\nbelieve the paper is now ready for publication.\nEven so, two concerns about the methodology used in this study remain for me that I will state in the hopes that they are\nhelpful in the authors’ future work.\nFirst is that it is not really adequate for the ice sheet model to account for latent heat in the coupled system. For ice to melt,\nthat heat has to come from somewhere else in the climate and that is, by definition, not the ice. So future coupling should\nextract that heat from the atmosphere or the ocean.\nSecond, in Burgard et al (2022), it is clearly stated (section 2.2.1) that they have chosen to use temperature profiles in their\nparameterization in order to account for variability in the thermocline:\n“Over the past decades, several simple parameterisations of the link between the ocean properties in front of the ice shelf\nand the melt at the base of ice shelves have been proposed. While some earlier simple parameterisations were based on\nsea-floor or vertically integrated ocean properties, recent results point to the importance of the thermocline depth for melt\nrates (e.g. De Rydt et al., 2014; Favier et al., 2019). This is why we account for vertical profiles of the input properties in the\nfollowing.”\nBecause of this difference compared with your approach, using a temperature value at a single depth, I do not think it\nnecessarily follows that the quadratic parameterization as you are using it will lead to an accurate representation of melt.", "reviewer_2": "Thanks to the authors for consideration of the points raised by myself and the other Reviewers and their revision of the\nmanuscript. It's been a while since the original submission, so I pretty much read this again with fresh eyes and the benefit of\nseeing things that the other reviewers had pointed out. I found myself still wanting to make the same set of General\ncomments as I see in my first review - you can read them there rather than have me reiterate here. While the authors have\nanswered all my Specific comments in some way or other, I'm still left pretty uncomfortable with the degree of focus on the\nheadline figures of temperature change and GMSL from their simulation while very important context of the very significant\nuncertainty of their simplified modelling choices is moved to the end or sidelined into the almost-appendix\nMethod section. This is a significant issue for me, and one that I feel would lead me to ideally recommend a different journal for publication of this study. I'm not as big a fan of non-anonymous review as Reviewer #1, but I think I must semi-deanonymise myself to explain my reasoning and personal biases, in case that helps with an editorial decision. I was an author on Siahaan et al'22, one of the previous coupled climate--icesheet modelling studies cited in this submission and highlighted by Reviewer #3 as being close enough to the thrust of this study to bring its novelty into question. The model and icesheet coupling we used there is, in a number of ways, significantly more sophisticated than what is being used here and based on much more explicit modelling of the relevant physics: UKESM is a CMIP climate model a generation newer than CESM1.2, with two-way coupling of the Greenland and Antarctic ice sheets (AIS) to both the ocean and atmosphere components of the climate (following the clarification in the authors rebuttal I believe they need to modify their current claims to two-way ice--climate coupling in this paper, see [1]) via explicit firn modelling with atmosphere energy and water fluxes at the surface and of the ocean circulation under floating ice shelves. I'm not outlining all this to suggest that the authors' approach here is too simplistic or invalid - I do not think that at all, there are plenty of advantages to other ways of approaching these questions - just to highlight that there is a very broad spectrum of approaches to climate-icesheet coupling in the community, and that the simulation results you get will depend very significantly on how a model has been set up and which physics and coupling pathways are included or excluded. An immediate example here would be Reviewer #1's concerns regarding how latent heat from some of the coupled flux from the ice sheet is been handled in this study - the authors have made a methodological choice concerning this, and whether one agrees with that or not it is recognised that even this one aspect of the coupling set up has the potential for significant impact on the simulation result.\nSo, I am personally uncomfortable with a focus on headline, 2-decimal-place precision reporting of climate metrics from\nsimulations such as these without sufficient /preceding/ explanation of the setup and its implications. In the case of Siahaan\net al'22, we had a preceding paper on the methods of coupling (Smith et al, JAMES 2021), and significant discussion of the\ninitialisation of the model and other features before analysis of any simulation results. That was the level of context we felt\nwas appropriate - I'm sure it could be argued that that other approaches could also be valid - but I think you can see why I\nwould feel that there is far from enough context given here in lines 113-117, and uncomfortable that much of what context\nthere is is in a Methods section that is placed outside the main body of the paper. For me, the Methods contains crucial\ninformation for thinking critically about the numbers being quoted, much of which should be available to readers before they\nsee the numbers. It could be argued that Park et al '23 provide a precedent for the approach currently taken by the authors - I\nwould like to further risk de-anonimising myself by stating that I was asked to review that paper too, was also on record as\nbeing unhappy with the presentation that was used there and I don't think it does the reputation or utility of the climate\nmodelling community any good to continuing reporting simulation results in this fashion (see [2]).\nIf this study is to remain in a journal like this that requires the Methods to remain essentially as an appendix, for me I would\nlike to see noted, in the main body of the paper before the results, at least the sort of statements that are currently in the\nMethods section noting that: the ocean under floating ice shelves is not modelled by CESM1.2 so ice shelf boundary\nconditions are here provided by extrapolating open ocean conditions from a pre-chosen, fixed depth; regionally varying, time\ninvariant bias adjustments are used with those extrapolated ocean fields; all solid and liquid freshwater flux from the ice\nsheet is all returned to the ocean in the surface layer next to the coast which will likely provide an upper bound on the impact\nof AIS freshwater flux on ocean stratification and cooling; latent heat required to melt ice shelves is not removed from the\nocean; changes in ice sheet surface height and ice extent are not coupled back to the atmosphere or land surface model;\nsurface melt is calculated on the ice sheet grid with an empirical PDD scheme using surface height corrections for\ntemperature and the amount and phase of precipitation; the ice sheet model uses a parameterisation of cliff calving which is\ncontested in the ice sheet modelling community and likely provides an upper bound on mass loss from the AIS.\n[1] In the authors' reply to my queries about the surface modelling and coupling, if I understand correctly they say that the\nsurface height changes in PSU3D are not seen by CESM after the initial timestep. I think this is an important thing to note for\ntwo reasons. One, I think they must modify how they talk about two-way coupling between the climate and ice sheet models.\nThere is two-exchange of information between the ice sheet and the ocean, but not directly between the ice sheet and the\natmosphere. The atmosphere does see information influenced by the changing ice sheet, but only very indirectly, through\nthe effect of AIS freshwater flux on ocean surface temperatures. The important influence of surface height on atmospheric\nconditions - and, in the case of significant glacial retreat, the change of surface type and albedo, seems to be neglected. So,\neg line 113, I think should more accurately claim a \"two-way coupling between /the ocean component of/ CESM [...] and\nPSU3D\". Secondly, if this is true I'm concerned by what is meant when changes in surface air temperature over Antarctica\nare reported, eg line 178. Are these surface temperatures from CESM that have not seen any change in the local surface,\nonly the influence of advected changes in open ocean temperature, or are they what PSU3D sees following lapse rate\ncorrections? In the case of surface air temperatures \"where the Ross and Weddell ice shelves once existed\", how can these\npossibly be accurate, even if lapse rate-adjusted, if the temperatures are based on a climate model that still has ice shelf\nsurface types in those locations? This needs significant clarification and possible caveating in the text if such numbers are to\nbe quoted.\n[2] Reviewer#3 made a comment that started \"I am not entirely convinced of this study's novelty [...]\", and the authors' reply\nincluded the statement \"While there were similar studies that were able to be submitted earlier, I do not think that should\npreclude my work being published\", and continues to note the importance of reproducibility and comparison in science. I\nagree with all the above statements, but would extend the philosophical direction of the discussion by proposing that the\nimportance of those things places some moral burden on authors of later papers such as this to attempt to present their\nresults in ways that aid that comparison. It is not a very useful addition to the literature to simply report more headline metrics\nfrom a similar set of simulations and say, \"well, we used a different model\". There are limits as to how far that is practical or\npossible of course, but a presentation that at least details the difference in approach from earlier studies, along with relative\nstrengths and weaknesses is of far more utility. To the previous similar literature noted by Reviewer #3, I would like to\ninclude the authors' own work (Sadai et al '20) where the authors conduct similar simulations with a one-way coupled model.\nHaving had the clarification in the authors' reply to me that the control experiment in the present study is equivalent to a\nstandard CESM1.2 with no kind of Antarctic flux given to the ocean, throughout the first 3 subsections of Results I really\nwanted to know more precisely how any of these numbers differ from the authors earlier findings with the one-way coupled\nmodel. How much of these changes are the same as in Sadai et al'20 and due to the ocean seeing any significant AIS\nfreshwater flux at all, and what is from the two-way coupling now in the models. I think this is only briefly touched on (lines\n233, 252). Could equivalent metrics from the one-way model be reported more fully here, rather than expecting readers to cross\nreference many details back to the earlier paper?\nA few other specific things in the rebuttals to the Reviewers jumped out at me:\nGeneral response to reviewers, RCP4.5 after 2100: I may be misinterpreting the comment that has been made, but with all\ndue respect to whatever practical constraints the authors found themselves under: I personally think that, as a principle,\nknowingly sending out unfinished figures and results for peer review, with the deliberate intention of adding more information\nafter one round of review has already been conducted, is rather disrespectful toward your reviewers and the time and effort\nthey are putting into thinking about your submission. I would strongly recommend you avoid doing this again in the future.\nReviewer#1: \"I have one major concern about the methodology\". On my reading of this comment and the authors' reply, I do\nnot think they have clearly addressed the concern I think is being raised - that the latent heat associated with melting the ice\nthat the coupling supplies back to the ocean as liquid flux has not been accounted for by cooling the ocean model as it\nwould in reality. This is one of the many parts of the coupling system I would like to see prominently flagged, early in the\npaper, along with its likely impact in the simulation to aid interpretation of the results\nReviewer#2: \"model code [...] was not developed for this paper\". It's not clear to me whether the coupling system being used\nis part of what the authors say will be published by other model developers, but the Abstract to their paper uses the active\ntense, saying \"here we couple [...]\", so I think either there is some burden on the authors to provide model code whose\nresults are being described here, or statements like those in the Abstract should be changed along the lines of expressing\nthat in this paper they are more simply using code that they don't have responsibility for.\nExtended Data Figure 8: given the small size of the pixels with valid information, this figure effectively just shows location of\ndischarge as the gradation in the colour-scale is unrecognisable in the figure itself. Perhaps a multi-panel set of regional\nzooms might be useful if the variation in the amount of discharge with space is what the authors really want to show.", "reviewer_3": "The authors have improved the manuscript and mostly addressed the reviewers’ comments.\nHowever, my original concern about the novelty of the work remains. I understand that there can be substantial delays in\npublishing PhD work. I also understand that not everything can be included and that choices have to be made in order to\ncomplete the research within a reasonable timeframe. Unfortunately, advances in modelling can happen quickly and what\nmight have been state-of-the-art and new at the start of a PhD is often not as ground-breaking 5 years later. I agree with the\nauthors that there is merit in reproducing existing work and carrying out similar types of studies with different models,\nscenarios, forcings, etc. The manuscript is worthy of publication in general. However, for a high-impact journal such as\nNature Communications, I would expect it to be a more significant advance on previous work. As an example of what could\nconstitute a significant advance and/or make this work more appropriate for the journal, the authors could include sub-\nannual temporal coupling/analyses, a coupled Greenland Ice Sheet model, or an ocean model with ice shelf cavities."}, "author_response": "General response to reviewers:\nWe are grateful to these three reviewers for their time and effort in providing such detailed and\nconstructive feedback on our paper. There were several topics brought up which appeared in\nmore than one review so we will address those here and then address comments specific to\neach reviewer below.\nRCP4.5 after 2100: The missing RCP4.5 data for the second half of the simulations was not a\nplotting mistake, rather it was due to significant stability issues with the end of life of the\nsupercomputer these simulations were being run on. Given the supercomputer stability issues\nand the long number of years this work had been in progress for, we decided to submit the\npaper while the second half of RCP4.5 was still running and add the rest in after the first round\nof review. All plots which did not include RCP4.5 data have now been updated and the fourth\npanel was added to the sea level mapping figure (Fig. 5) with the spatial map for the later half of\nthe RCP4.5 simulation.\nSurface level forcing: We agree that there isn’t agreement within the community on how\nrobust responses are with surface level only freshwater forcing. The ocean and sea ice\nresponses to surface level forcing vary between models. We have added the Mathiot et al.\npaper to the references in the discussion of the surface level forcing in the Methods section.\nWhile the NEMO model described in the Mathiot et al. paper finds major effects on ocean\nvariables we point here to prior work by Pauling et al. with the CESM1 ocean model showing\nthat the depth has minimal impact in the model we are using in this study. The approach of\nusing surface level only forcing is a common methodology across freshwater forcing studies.\nThe relevant part of the Methods section now reads:\n“While injecting freshwater at depth can lead to more mixing and a deeper mixed layer\nand work with other ocean models have shown the depth of freshwater input to have an\neffect in other models (Mathiot et al., 2017), previous work with CESM indicates that\nthere is little difference in CESM1-simulated ocean surface temperature, salinity, and\nsea-ice responses when freshwater is applied at depth versus in experiments where\nfreshwater is added at the surface (Pauling et al., 2016).”\nFace melt parameterization and ocean temperature bias correction: The factor of 2 in the\nface melt parameterization used in our paper is not necessarily more conservative than the\nfactor of 10 in DeConto & Pollard, 2016, it is just the factor that was needed to bring the output\nmore into alignment with observations when forcing the ice sheet model with a hotter ocean\n(CESM1) compared to a colder ocean (CCSM4 as in DP16). Here is the description of the\nscheme from DeConto & Pollard, 2016:\n“Melting of vertical ice surfaces in direct contact with ocean water is derived from the\noceanic melt rate (OM) of surrounding grid cells, but is increased by a scaling factor of\n10, producing more realistic calving front positions and in better agreement with\nhydrographic melt rate observations and detailed modelling” which cites Slater, D. A.,\nNienow, P. W., Cowton, T. R., Goldberg, D. N. & Sole, A. J. Effect of near-terminus\nsubglacial hydrology on tidewater glacier submarine melt rates. Geophys. Res. Lett. 42,\n2861–2868 (2015).\nFurthermore, face melt is a negligible field in these simulations. It reaches a maximum of 515\nand 590 Gt/yr across the full simulation period in the two scenarios.\nThe ocean temperature bias correction is only applied in the Amundsen Sea region. We also\nnote that the previous version of the paper had a typo, the bias correction is 2.5˚C rather than\n3˚C. This is a lower correction than has been used in many studies with this model (see\nDeConto & Pollard, 2016 for a longer explanation). The bias correction is static throughout the\nsimulations and does not change in magnitude or regions. Only the Ross and Weddell cavities\nflip to warm circulation over the simulations and this bias correction is not added in these\nregions."}, {"round": 3, "reviewer_comments": {"reviewer_2": "Thanks to the authors for their further revisions and clarifications in their response. Having read them I'm happier with their presentation of the tools they've used in this study and that there's more up-front context in which to consider the results.\nReviewer 3 still notes concerns about the novelty of the work. For me the \"Broader Implications [...]\" section is the strongest and most significant part of the study - if rebalancing of content were to be done to highlight the newer aspects I'd suggest cutting some of the quantitative detail in \"Polar climate response\" and \"Global climate response\" in favour of extending that later section.\nI noted some further suggestions on phrasing and presentation as I read through again, but in general I'd be pleased for this to go forward now.\nspecific suggestions\n--\nl28: \"Imperfect model treatment [...]\" is not untrue, but I think there's a more fundamental point in that we lack important understanding of these interactions, and the sentence as it is sets up an expectation that you will be presenting a (more) perfect treatment of those interactions than has been used in the past, which I don't think is true - you address some of these interactions, in some different ways to how they have been used in the past. How about \"Imperfect understanding of ice sheet-climate interactions [...]\" ?\nl32: If I understand the control run you compare to correctly, the results in this paper show the impact of including or neglecting AIS meltwater input entirely, not just the impact of coupled feedbacks that can control how much is produced. Here, and elsewhere, I'd clarify this by talking talking about \"meltwater input and feedbacks\", rather than just stressing only the feedback part.\nl34: Can you clarify at what date, under what Scenario, this maximum temperature anomaly is reached?\nl36: A delay has units of time - I know what you mean, but the saying warming is /delayed/ by 0.3C at 2100 feels wrong.\nl38-40: Your call, but I personally simply wouldn't highlight these headline figures in the Abstract, at this level of precision, with no indication of uncertainty, unless you think they're defensible, usable projection numbers, and I don't think your method (or anyone else's) justifies such quantitative certainty.\nl108: It would be more correct to describe Park et al '23 and Siahaan et al. '22 as simulations using climate change projection scenarios than freshwater forcing experiments, I think\nl133: A desire to \"explore the global impact of meltwater forcing\" is not a justification of why your model has an implementation of MICI. A statement about exploring the high end of projections of ice mass loss would be a more direct motivation.\nl145: It would help readers here to explicitly say what your control \"standard CESM1.2 simulation\" does (or, does not do) for meltwater/iceberg input from AIS in a climate change scenario.\nl165: Is some degree of MISI in the Amundsen sector already underway in your ice sheet initial state before the experiment starts, which is implied in some initialisation methods? Is it clear how much of the WAIS retreat you see in your experiments is a forced response to the different Scenarios?\nl189: To help readers, I'd remind them at the start of this paragraph (not the end) that the air temperatures reported do not reflect changes in surface height or type since CESM does not see those.\nl314: Figure 3 title: I think this title is too general, given the degree of ice-climate coupling in the model and the actual analysis you're showing. As at line 32, maybe \"Effect of AIS meltwater input on future climate\"?\nl451 (and somewhere else): \"have attempted coupling ice sheet models\" I think you can be more positive than this, your work (and others) actually \"have coupled ice sheet models to climate models\".\n(Remarks on code availability)", "reviewer_3": "I acknowledge and appreciate the effort that the authors have made in responding to all three of the reviewers’ comments.\nThey have now added helpful details on their methodology and modified terminology to clarify the nature of the coupling.\nDespite this, having read through Reviewer #2’s comments and the authors’ response, it leaves me wanting to know more\nabout the model and coupling structure and the processes that are and are not included. I do think that the modelling\ncommunity would be better served for this paper to be published in a long-format journal where the methodological choices\ncan be thoroughly explored and compared with other studies. As the authors admit, the word count limit of this journal does\nnot permit such a full exploration. The main contribution of this study for me is an understanding of how model configurations\nand coupling schemes influence results, rather than the results themselves. This is a rather technical discussion but is what I\nwould prefer to read. Ultimately it is a decision for the editor to make, but I think that this study will actually be viewed and\ncited more if it appears in a more specialized journal.\n(Remarks on code availability)"}, "author_response": "We are pleased to hear that our previous round of edits was helpful in strengthening the paper.\nspecific suggestions\n--\nl28: \"Imperfect model treatment [...]\" is not untrue, but I think there's a more fundamental point in that we lack important understanding of these interactions, and the sentence as it is sets up an expectation that you will be presenting a (more) perfect treatment of those interactions than has been used in the past, which I don't think is true - you address some of these interactions, in some different ways to how they have been used in the past. How about \"Imperfect understanding of ice sheet-climate interactions [...]\" ?\nWe have taken this suggestion and updated the wording.\nl32: If I understand the control run you compare to correctly, the results in this paper show the impact of including or neglecting AIS meltwater input entirely, not just the impact of coupled feedbacks that can control how much is produced. Here, and elsewhere, I'd clarify this by talking talking about \"meltwater input and feedbacks\", rather than just stressing only the feedback part.\nWe have changed this to “we find sea level and climate projections are significantly modified from uncoupled simulations neglecting Antarctic meltwater under RCP8.5 and RCP4.5 emissions scenarios.”\nWe also updated line 371: “While the timing of the Long-Term Temperature Goal is minimally impacted, the long-term difference in GMST when accounting for meltwater input and feedbacks is substantial.”\nl34: Can you clarify at what date, under what Scenario, this maximum temperature anomaly is reached?\nThis has been added to the updated abstract to say “with a maximum anomaly of ~1°C at 2200 under RCP8.5.”\nl36: A delay has units of time - I know what you mean, but the saying warming is /delayed/ by 0.3C at 2100 feels wrong.\nWe have updated the wording to remove the word delay.\nl38-40: Your call, but I personally simply wouldn't highlight these headline figures in the Abstract, at this level of precision, with no indication of uncertainty, unless you think they're defensible, usable projection numbers, and I don't think your method (or anyone else's) justifies such quantitative certainty.\nWe have updated this to give more general ranges. The updated abstract is as follows:\n“Imperfect understanding of ice sheet-climate interactions poses challenges for projecting the impacts of ice sheet mass loss on future climate and sea level. Here we couple a dynamic Antarctic ice sheet model and global climate model to simulate ice sheet-climate interactions. In our single-model, single-member modeling framework, we find sea level and climate projections are significantly modified from uncoupled simulations neglecting Antarctic meltwater under RCP8.5 and RCP4.5. Antarctic meltwater yields surface air temperatures up to 1.5°C higher in parts of the Northern Hemisphere, while broadly dampening temperature rise in the Southern Hemisphere. Due to radiative feedback changes, both emissions scenarios have global mean surface temperature warming ~0.3°C lower in the coupled scenario than the control at 2100, with a maximum anomaly of ~1°C at 2200 under RCP8.5. This slows Antarctica’s contribution to global mean sea level rise. Total Antarctic sea level contributions under RCP8.5 (2100: ~0.3 m, 2200: >3 m) include substantial contributions from East Antarctica, though not under RCP4.5 (2100: ~0.1 m, 2200: ~1 m). Regionally, projected sea level is up to 0.9 m higher in the Pacific than the global mean Antarctic contribution under RCP8.5 at 2200.”\nl108: It would be more correct to describe Park et al '23 and Siahaan et al. '22 as simulations using climate change projection scenarios than freshwater forcing experiments, I think\nIn the introduction this has been updated to: “Recently, numerical experiments using coupling schemes under climate change projection scenarios have been used to assess climate-ice sheet feedbacks (Park et al., 2023; Siahaan et al., 2022)”\nl133: A desire to \"explore the global impact of meltwater forcing\" is not a justification of why your model has an implementation of MICI. A statement about exploring the high end of projections of ice mass loss would be a more direct motivation.\nWe have updated the wording to:\n“While the validity of MICI remains contested (Morlighem et al., 2024), the intent here is to explore the global impact of meltwater forcing while including brittle ice dynamics which have informed high end sea level rise projections.”\nl145: It would help readers here to explicitly say what your control \"standard CESM1.2 simulation\" does (or, does not do) for meltwater/iceberg input from AIS in a climate change scenario.\nThis has been updated to:\n“Within the text, ‘coupled’ refers to the simulations with interactive coupling between the ice sheet model and climate model and ‘control’ (or ‘uncoupled’) refers to the simulations with no interactive AIS which are equivalent to a standard CESM1.2 simulation which produces minimal meltwater (Pauling et al., 2016).”\nl165: Is some degree of MISI in the Amundsen sector already underway in your ice sheet initial state before the experiment starts, which is implied in some initialisation methods? Is it clear how much of the WAIS retreat you see in your experiments is a forced response to the different Scenarios?\nThere was very minimal WAIS retreat in the 200-year constant forcing tests. As noted in the first round of reviewer responses “In terms of an initial VAF trend we did check that before running the simulations by running 100 year tests with constant modern day climate forcing of the ice sheet and found changes of 0.008 m under RCP8.5 and 0.02 under RCP4.5. Since these were substantially smaller than the forced signal we deemed this acceptable.”\nl189: To help readers, I'd remind them at the start of this paragraph (not the end) that the air temperatures reported do not reflect changes in surface height or type since CESM does not see those.\nThis sentence was moved to the start of the paragraph.\nl314: Figure 3 title: I think this title is too general, given the degree of ice-climate coupling in the model and the actual analysis you're showing. As at line 32, maybe \"Effect of AIS meltwater input on future climate\"?\nThank you, we have taken the suggestion and updated it to “Effect of Antarctic meltwater input on future climate.\"\nl451 (and somewhere else): \"have attempted coupling ice sheet models\" I think you can be more positive than this, your work (and others) actually \"have coupled ice sheet models to climate models\".\nThank you, we have updated this, though we could not find a second instance of this language."}]

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