Towards regional projections of twenty-first century sea-level change based on IPCC SRES scenarios

Abstract

Sea-level change is often considered to be globally uniform in sea-level projections. However, local relative sea-level (RSL) change can deviate substantially from the global mean. Here, we present maps of twenty-first century local RSL change estimates based on an ensemble of coupled climate model simulations for three emission scenarios. In the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4), the same model simulations were used for their projections of global mean sea-level rise. The contribution of the small glaciers and ice caps to local RSL change is calculated with a glacier model, based on a volume-area approach. The contributions of the Greenland and Antarctic ice sheets are obtained from IPCC AR4 estimates. The RSL distribution resulting from the land ice mass changes is then calculated by solving the sea-level equation for a rotating, elastic Earth model. Next, we add the pattern of steric RSL changes obtained from the coupled climate models and a model estimate for the effect of Glacial Isostatic Adjustment. The resulting ensemble mean RSL pattern reveals that many regions will experience RSL changes that differ substantially from the global mean. For the A1B ensemble, local RSL change values range from -3.91 to 0.79 m, with a global mean of 0.47 m. Although the RSL amplitude differs, the spatial patterns are similar for all three emission scenarios. The spread in the projections is dominated by the distribution of the steric contribution, at least for the processes included in this study. Extreme ice loss scenarios may alter this picture. For individual sites, we find a standard deviation for the combined contributions of approximately 10 cm, regardless of emission scenario.

The contribution of glacial isostatic adjustment to projections of sea‐level change along the Atlantic and Gulf coasts of North America

“…Future sea-level changes will be spatially variable [Milne et al, 2009;Cazenave and Cozannet, 2014] and so risk assessment should be based on local rather than global projections [Field et al, 2014]. Various mechanisms both internal and external to the world's oceans lead to these departures from the global mean change, which can be considerable in some regions [Slangen et al, 2012;Carson et al, 2016].…”

The Sea Level Response to External Forcings in Historical Simulations of CMIP5 Climate Models*

“…In the past century, global mean sea level has risen by 19 6 2 cm and it is projected to rise by another 28-98 cm by 2100 (relative to 1986-2005), depending on the level of anthropogenic greenhouse gas emissions, and potentially several decimeters more if there is a collapse of a portion of the Antarctic Ice Sheet (Church et al 2013). However, past and future sea level change is not spatially uniform and is projected to locally deviate more than 10% from the global mean in almost 30% of the ocean area (Slangen et al 2014a).…”

“…However, these contributions are important to include when studying total sea level change, as each can add mass to the ocean and have a significant regional signature, especially close to the source of the mass change (e.g., Church et al 2013;Slangen et al 2012Slangen et al , 2014a. During the twentieth century in regions away from the ice sheets (the so-called far field), the high spatial variation of the DSL dominates the relatively smooth spatial patterns that are caused by mass redistribution and their related gravitational, rotational, and deformational effects.…”

An assessment of uncertainties in using volume-area modelling for computing the twenty-first century glacier contribution to sea-level change

“…Examples are volume-length scaling (Oerlemans et al, 2007;Leclercq et al, 2011), volume-area scaling (e.g. Bahr et al, 1997;Van de Wal and Wild, 2001), or volumearea-length scaling (Radić and Hock, 2011). These methods 674 A.…”

“…Additionally, the required mass balance changes may be obtained by using seasonal sensitivity characteristics (Oerlemans and Reichert, 2000), by modelling the changes in mass balance profiles (Raper and Braithwaite, 2006), by applying a simplified mass balance model (Radić and Hock, 2011), or by using a relation between mass balance sensitivity and precipitation (e.g. Gregory and Oerlemans, 1998;Van de Wal and Wild, 2001). An even more direct way to obtain a global estimate of GIC changes is to use a scaling relation between global temperature change and total ice volume without area size classes or latitudinal dependence, as applied in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) (see Appendix 10.A.3 in Meehl et al, 2007b).…”