While the authors of the linked reference are all well regarded ice modeling scientists; to me this reference illustrates how painfully slow the consensus building process is for risk assessment associated with ice sheet modeling driven by projected future climate change scenarios. While I concur with the reference that ice shelf response to climate change is one of the key mechanisms determining future ice mass loss from Antarctica, I believe that the cited model projections all significantly underestimated the ice shelf responses that we have seen this year in the Amundsen Sea Embayment, ASE; and the MISI models used explicitly do not consider MICI-type mechanisms.
Therefore, in my opinion, the most significant finding of the cited study is that:
"We thus have to conclude that uncertainty with respect to the ice dynamic contribution of Antarctica due to future warming is still increasing and thus that coastal planning has to take into account that multi-decadal sea level projections are likely to change with an increasing understanding of the ice dynamics and their representation in ice sheet models."
Thus the big issue is will consensus climate science officially recognize the significant risk of abrupt ice mass loss from Antarctica this century before, or after, key Antarctic marine glaciers have already crossed they thresholds for 'irreversible' continuing ice mass loss this century:
Levermann, A., Winkelmann, R., Albrecht, T., Goelzer, H., Golledge, N. R., Greve, R., Huybrechts, P., Jordan, J., Leguy, G., Martin, D., Morlighem, M., Pattyn, F., Pollard, D., Quiquet, A., Rodehacke, C., Seroussi, H., Sutter, J., Zhang, T., Van Breedam, J., Calov, R., DeConto, R., Dumas, C., Garbe, J., Gudmundsson, G. H., Hoffman, M. J., Humbert, A., Kleiner, T., Lipscomb, W. H., Meinshausen, M., Ng, E., Nowicki, S. M. J., Perego, M., Price, S. F., Saito, F., Schlegel, N.-J., Sun, S., and van de Wal, R. S. W.: Projecting Antarctica's contribution to future sea level rise from basal ice shelf melt using linear response functions of 16 ice sheet models (LARMIP-2), Earth Syst. Dynam., 11, 35–76,
https://doi.org/10.5194/esd-11-35-2020, 2020.
https://www.earth-syst-dynam.net/11/35/2020/Abstract
The sea level contribution of the Antarctic ice sheet constitutes a large uncertainty in future sea level projections. Here we apply a linear response theory approach to 16 state-of-the-art ice sheet models to estimate the Antarctic ice sheet contribution from basal ice shelf melting within the 21st century. The purpose of this computation is to estimate the uncertainty of Antarctica's future contribution to global sea level rise that arises from large uncertainty in the oceanic forcing and the associated ice shelf melting. Ice shelf melting is considered to be a major if not the largest perturbation of the ice sheet's flow into the ocean. However, by computing only the sea level contribution in response to ice shelf melting, our study is neglecting a number of processes such as surface-mass-balance-related contributions. In assuming linear response theory, we are able to capture complex temporal responses of the ice sheets, but we neglect any self-dampening or self-amplifying processes. This is particularly relevant in situations in which an instability is dominating the ice loss. The results obtained here are thus relevant, in particular wherever the ice loss is dominated by the forcing as opposed to an internal instability, for example in strong ocean warming scenarios. In order to allow for comparison the methodology was chosen to be exactly the same as in an earlier study (Levermann et al., 2014) but with 16 instead of 5 ice sheet models. We include uncertainty in the atmospheric warming response to carbon emissions (full range of CMIP5 climate model sensitivities), uncertainty in the oceanic transport to the Southern Ocean (obtained from the time-delayed and scaled oceanic subsurface warming in CMIP5 models in relation to the global mean surface warming), and the observed range of responses of basal ice shelf melting to oceanic warming outside the ice shelf cavity. This uncertainty in basal ice shelf melting is then convoluted with the linear response functions of each of the 16 ice sheet models to obtain the ice flow response to the individual global warming path. The model median for the observational period from 1992 to 2017 of the ice loss due to basal ice shelf melting is 10.2 mm, with a likely range between 5.2 and 21.3 mm. For the same period the Antarctic ice sheet lost mass equivalent to 7.4 mm of global sea level rise, with a standard deviation of 3.7 mm (Shepherd et al., 2018) including all processes, especially surface-mass-balance changes. For the unabated warming path, Representative Concentration Pathway 8.5 (RCP8.5), we obtain a median contribution of the Antarctic ice sheet to global mean sea level rise from basal ice shelf melting within the 21st century of 17 cm, with a likely range (66th percentile around the mean) between 9 and 36 cm and a very likely range (90th percentile around the mean) between 6 and 58 cm. For the RCP2.6 warming path, which will keep the global mean temperature below 2 ∘C of global warming and is thus consistent with the Paris Climate Agreement, the procedure yields a median of 13 cm of global mean sea level contribution. The likely range for the RCP2.6 scenario is between 7 and 24 cm, and the very likely range is between 4 and 37 cm. The structural uncertainties in the method do not allow for an interpretation of any higher uncertainty percentiles. We provide projections for the five Antarctic regions and for each model and each scenario separately. The rate of sea level contribution is highest under the RCP8.5 scenario. The maximum within the 21st century of the median value is 4 cm per decade, with a likely range between 2 and 9 cm per decade and a very likely range between 1 and 14 cm per decade.
Extract: "In summary, for each emission scenario the procedure works as follows (each of the items is described in more detail below and in Levermann et al., 2014).
1. Randomly select a global mean temperature realization of the respective RCP scenario from the 600 MAGICC 6.0 realizations constrained by the observed temperature record. The time series start in 1850 and end in 2100.
2. Randomly select one of 19 CMIP5 models in order to obtain a scaling factor and a time delay for the relation between global mean surface air temperature and subsurface ocean warming in the respective regional sector in the Southern Ocean.
3. Randomly select a melting sensitivity in order to scale the regional subsurface warming outside the cavity of the Antarctic ice shelves onto basal ice shelf melting.
4. Select an ice sheet model that is forced via its linear response function with the time series of the forcing obtained from steps 1–3.
5. Compute the sea level contribution of this specific Antarctic ice sheet sector according to linear response theory.
6. Repeat steps 1–5 20 000 times with different random selections in each of the steps in order to obtain a probability distribution of the sea level contribution of each Antarctic sector and each carbon emission scenario.
Thus, the 20 000 selections are obtained by randomly choosing one temperature time series, one CMIP5 ocean model, one melt sensitivity, and one ice sheet model. The procedure is also used for each of the ice sheet models separately. In this case the random selection in step 4 is replaced by a fixed selection of the model. The procedure is illustrated in Fig. 1. For the computation of the total sea level contribution from all Antarctic sectors together, the forcing is selected consistently for all sectors. That means that for each of the 20 000 computations of the sea level contribution one global mean temperature realization is selected, as is one ocean model for the subsurface temperature scaling and one basal melt sensitivity. Although there are other possibilities, this approach was chosen because it preserves the forcing structure as provided by the ocean models. Details of steps 1–5 are given in the upcoming subsections.
…
However, due to the very large potential sea level contribution of Antarctica and its high sea level commitment compared to the other contributions (Levermann et al., 2013), the rate of change increases strongly over the century. Under the RCP8.5 scenario the median rate of sea level contribution by the end of the 21st century from basal-melt-induced ice loss from Antarctica alone is with 4.1 mm yr−1 larger than the mean rate of sea level rise observed at the beginning of this century (Dangendorf et al., 2019; Hay et al., 2015; Oppenheimer et al., 2019).
Although the method described here has a large number of caveats it provides an estimate of the role of the uncertainty in the oceanic forcing for the uncertainty in Antarctica's future contribution to sea level rise. By comparison with the earlier study using the same method but only three ice sheet models of an earlier model generation, we find a shift of the sea level contribution to higher values and an increase in the ranges of uncertainty. We thus have to conclude that uncertainty with respect to the ice dynamic contribution of Antarctica due to future warming is still increasing and thus that coastal planning has to take into account that multi-decadal sea level projections are likely to change with an increasing understanding of the ice dynamics and their representation in ice sheet models. This study provides an estimate of the uncertainty in the future contribution of Antarctica to global sea level rise only based on known ice dynamics but including the full range of forcing uncertainty. It substantiates the result of the previous study that Antarctica can become the largest contributor to global sea level rise in the future, in particular if carbon emissions are not abated."
Caption: "Figure 11 Projections from all models of the future sea level contribution of the different Antarctic sectors following the procedure depicted in Fig. 1 and detailed in Sect. 2. The white line represents the median value, the dark shading the likely range (66th percentile around the median), and the light shading the very likely range (90th percentile around the median)."