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The effective climate sensitivity (EffCS) of models in the Coupled Model Intercomparison Project 6 (CMIP6) has increased relative to CMIP5. We explore the implications of this for global mean sea‐level (GMSL) change projections in 2100 for three emissions scenarios. CMIP6 projections of global surface air temperature are substantially higher than in CMIP5, but projections of global mean thermal expansion are not. Using these projections as input to construct projections of GMSL change with IPCC AR5 methods, the 95th percentile of GMSL change at 2100 only increases by 3–7 cm. Projected rates of GMSL rise around 2100 increase more strongly, though, implying more pronounced differences beyond 2100 and greater committed sea‐level rise. Intermodel differences in GMSL projections indicate that EffCS‐based model selection may substantially alter the ensemble projections. GMSL change in 2100 is accurately predicted by time‐integrated temperature change, and thus requires reducing emissions early to be mitigated. Plain Language Summary: Climate sensitivity measures how much the Earth's surface warms for a given increase in greenhouse gas concentration. In the new generation of global climate models, climate sensitivity has increased. We explore how the simulations of these models affect global mean sea‐level (GMSL) rise projections in 2100 for three different emissions scenarios. We compute GMSL projections based on simulated global surface warming (which affects land‐ice melt) and thermal expansion of the ocean, using the methods of the fifth Assessment Report of the Intergovernmental Panel on Climate Change. The latest projections of global surface warming are substantially higher than the previous projections, whereas the projections of global thermal expansion are not. Consequently, the upper limits of our GMSL projections increase by 3–7 cm depending on the emissions scenario. This difference will likely become more pronounced beyond 2100. Depending on climate sensitivity, GMSL projections for individual models can differ substantially, implying that using only a subset of models selected based on their climate sensitivity may substantially alter GMSL projections. Since GMSL in 2100 can be predicted well by the cumulative sum of surface warming up to 2100, it is important to reduce the emission of greenhouse gases early to mitigate GMSL rise. Key Points: The 95th percentile of total sea‐level change projections in 2100 is up to 7 cm higher for the Coupled Model Intercomparison Project 6 (CMIP6) ensemble than for the CMIP5 ensembleThe 95th percentile of projected sea‐level rise rates near 2100 is up to 21% larger, implying more pronounced differences beyond 2100Depending on climate sensitivity, individual models can project global mean sea‐level rise substantially outside the ensemble 5%–95% range [ABSTRACT FROM AUTHOR]

Changes in ocean properties and circulation lead to a spatially non-uniform pattern of ocean dynamic sea-level change (DSLC). The projections of ocean dynamic sea level presented in the IPCC AR5 were constructed with global climate models (GCMs) from the Coupled Model Intercomparison Project 5 (CMIP5). Since CMIP5 GCMs have a relatively coarse resolution and exclude tides and surges it is unclear whether they are suitable for providing DSLC projections in shallow coastal regions such as the Northwestern European Shelf (NWES). One approach to addressing these shortcomings is dynamical downscaling – i.e. using a high-resolution regional model forced with output from GCMs. Here we use the regional shelf seas model AMM7 to show that, depending on the driving CMIP5 GCM, dynamical downscaling can have a large impact on DSLC simulations in the NWES region. For a business-as-usual greenhouse gas concentration scenario, we find that downscaled simulations of twenty-first century DSLC can be up to 15.5 cm smaller than DSLC in the GCM simulations along the North Sea coastline owing to unresolved processes in the GCM. Furthermore, dynamical downscaling affects the simulated time of emergence of sea-level change (SLC) above sea-level variability, and can result in differences in the projected change of the amplitude of the seasonal cycle of sea level of over 0.3 mm/yr. We find that the difference between GCM and downscaled results is of similar magnitude to the uncertainty of CMIP5 ensembles used for previous DSLC projections. Our results support a role for dynamical downscaling in future regional sea-level projections to aid coastal decision makers. [ABSTRACT FROM AUTHOR]

The northern North Atlantic comprises a dynamically complex area with distinct topographic features, making it challenging to model oceanic features with global climate models. As climate models form the basis for assessment reports of future regional sea level rise, model evaluation is important. In this study, the representation of regional sea level in this area is evaluated in 18 climate models that contributed to phase 5 of the Coupled Model Intercomparison Project. Modeled regional dynamic height is compared to observations from an altimetry-based record over the period 1993-2012 in terms of mean dynamic topography, interannual variability, and linear trend patterns. As models are expected to reproduce the location and magnitude but not the timing of internal variability, the observations are compared to the full 150-yr historical simulations using 20-yr time slices. This approach allows one to examine modeled natural variability versus observed changes and to assess whether a forced signal is detectable over the 20-yr record or whether the observed changes can be explained by internal variability. The models perform well with respect to mean dynamic topography. However, model performances degrade when interannual variability and linear trend patterns are considered. The modeled regionwide average steric and dynamic sea level rise is larger than estimated from observations, and the marked observed increase in the subpolar gyre is not consistent with a forced response but rather a result of internal variability. Using a simple weighting scheme, it is shown that the results can be used to reduce uncertainties in sea level projections. [ABSTRACT FROM AUTHOR]

Sea level change is one of the major consequences of climate change and is projected to affect coastal communities around the world. Here, global mean sea level (GMSL) change estimated by 12 climate models from phase 5 of the World Climate Research Programme's Climate Model Intercomparison Project (CMIP5) is compared to observational estimates for the period 1900-2015. Observed and simulated individual contributions to GMSL change (thermal expansion, glacier mass change, ice sheet mass change, landwater storage change) are analyzed and compared to observed GMSL change over the period 1900-2007 using tide gauge reconstructions, and over the period 1993-2015 using satellite altimetry estimates. The model-simulated contributions explain 50% ± 30% (uncertainties 1.65 σ unless indicated otherwise) of the mean observed change from 1901-20 to 1988-2007. Based on attributable biases between observations and models, a number of corrections are proposed, which result in an improved explanation of 75% ± 38% of the observed change. For the satellite era (from 1993-97 to 2011-15) an improved budget closure of 102% ± 33% is found (105% ± 35% when including the proposed bias corrections). Simulated decadal trends increase over the twentieth century, both in the thermal expansion and the combined mass contributions (glaciers, ice sheets, and landwater storage). The mass components explain the majority of sea level rise over the twentieth century, but the thermal expansion has increasingly contributed to sea level rise, starting from 1910 onward and in 2015 accounting for 46% of the total simulated sea level change. [ABSTRACT FROM AUTHOR]

Changes in Earth's climate are influenced by internal climate variability and external forcings, such as changes in solar radiation, volcanic eruptions, anthropogenic greenhouse gases (GHG), and aerosols. Although the response of surface temperature to external forcings has been studied extensively, this has not been done for sea level. Here, a range of climate model experiments for the twentieth century is used to study the response of global and regional sea level change to external climate forcings. Both the global mean thermosteric sea level and the regional dynamic sea level patterns show clear responses to anthropogenic forcings that are significantly different from internal climate variability and larger than the difference between models driven by the same external forcing. The regional sea level patterns are directly related to changes in surface winds in response to the external forcings. The spread between different realizations of the same model experiment is consistent with internal climate variability derived from preindustrial control simulations. The spread between the different models is larger than the internal variability, mainly in regions with large sea level responses. Although the sea level responses to GHG and anthropogenic aerosol forcing oppose each other in the global mean, there are differences on a regional scale, offering opportunities for distinguishing between these two forcings in observed sea level change. [ABSTRACT FROM AUTHOR]