Future sea level rise constrained by observations and long-term commitment

Abstract

Sea level has been steadily rising over the past century, predominantly due to anthropogenic climate change. The rate of sea level rise will keep increasing with continued global warming, and, even if temperatures are stabilized through the phasing out of greenhouse gas emissions, sea level is still expected to rise for centuries. This will affect coastal areas worldwide, and robust projections are needed to assess mitigation options and guide adaptation measures. Here we combine the equilibrium response of the main sea level rise contributions with their last century's observed contribution to constrain projections of future sea level rise. Our model is calibrated to a set of observations for each contribution, and the observational and climate uncertainties are combined to produce uncertainty ranges for 21st century sea level rise. We project anthropogenic sea level rise of 28-56 cm, 37-77 cm, and 57-131 cm in 2100 for the greenhouse gas concentration scenarios RCP26, RCP45, and RCP85, respectively. Our uncertainty ranges for total sea level rise overlap with the process-based estimates of the Intergovernmental Panel on Climate Change. The "constrained extrapolation" approach generalizes earlier global semiempirical models and may therefore lead to a better understanding of the discrepancies with processbased projections. 2) with a rate of around 3 cm per decade since 1990 (3, 4). Thermal expansion of the oceans and retreating glaciers are the main contributors to sea level rise in the past century and the near future. On multicentennial timescales, the Greenland and Antarctic ice sheets will likely dominate global sea level rise (5). Future sea level rise will pose challenges to coastal regions around the globe, and robust projections are needed to guide adaptation investment and provide incentives for climate mitigation (6).Projecting sea level relies on the understanding of the processes that drive sea level changes and on reliable data to verify and calibrate models. So-called process-based models now deliver projections for the main components of climate-driven sea level rise-thermal expansion, glaciers and ice caps, the Greenland ice sheet, and the Antarctic ice sheet-although solid ice discharge (SID) from the ice sheets is still difficult to constrain (3). Semiempirical models follow a different approach and use the statistical relation between global mean temperature (7,8) or radiative forcing (9, 10) and sea level from past observations. Without aiming to capture the full physics of the sea level components, they project future sea level assuming that the past statistical relation also holds in the future. Their simpler nature makes them feasible for probabilistic assessments and makes their results easier to reproduce.The long-term multicentennial to millennial sensitivity of the main individual sea level contributors to global temperature changes can be constrained by paleoclimatic data and is more easily computed with currently available process-based large-scale models than are decadal to centenn...

BRICK v0.2, a simple, accessible, and transparent model framework for climate and regional sea-level projections

“…Our framework is designed in such a way that it is possible to plug in other model components to reflect these different values. For example, it would be very interesting to add the component models used for the semiempirical model frameworks of Mengel et al (2016) and Nauels et al (2017).…”

“…These dashed couplings are required for projecting regional sea-level and climate impacts. DOECLIM is the Diffusion-OceanEnergy balance CLIMate model (Kriegler, 2005); GIC-MAGICC is the Glaciers and Ice Caps module from the MAGICC climate model (Meinshausen et al, 2011a); TE is the Thermal Expansion model Mengel et al, 2016); SIMPLE is the Simple Icesheet Model for Projecting Large Ensembles (Bakker et al, 2016); ANTO is the ANTarctic Ocean temperature model; DAIS is the Danish Center for Earth System Science Antarctic Ice Sheet model (Shaffer, 2014); regional sea-level fingerprinting downscales from global sea-level contributions to regional (Slangen et al, 2014); and the model of Van Dantzig (1956) assesses flood risk. rise) components of BRICK are intentionally simple.…”

“…This two-dimensional ocean model is beyond the scope of the simple model framework described presently, but is an excellent subject for future work. Here, we employ a simple zero-dimensional thermal expansion emulator based on the parameterizations of the sea-level rise sub-models of Mengel et al (2016) and that was originally used by Grinsted et al (2010) to model the total global mean sea-level changes. First, an equilibrium sea-level rise from thermal expansion, due to changing global surface temperature (S eq,TE , m), is calculated as…”

“…This parameter is assigned a gamma prior distribution with shape 1.81 and scale 0.00275, which places the 5th and 95th quantiles for τ TE at 82 and 1290 years (Mengel et al, 2016 (Church et al, 2013).…”

“…Semi-empirical modeling (SEM) approaches trade detailed physics for a model that can efficiently project sea level using statistical, but mechanistically motivated, relationships between sea-level changes and climate conditions such as temperature and radiative forcing Jevrejeva et al, 2010;Kopp et al, 2016;Rahmstorf, 2007). Recent work has expanded upon the SEM approach to use simple models to resolve individual contributions to global sea level (Bakker et al, 2017;Mengel et al, 2016;Nauels et al, 2017).…”