Sea-level rise due to both climate change and non-climatic factors threatens coastal settlements, infrastructure, and ecosystems. Projections of mean global sea-level (GSL) rise provide insufficient information to plan adaptive responses; local decisions require local projections that accommodate different risk tolerances and time frames and that can be linked to storm surge projections. Here we present a global set of local sea-level (LSL) projections to inform decisions on timescales ranging from the coming decades through the 22nd century. We provide complete probability distributions, informed by a combination of expert community assessment, expert elicitation, and process modeling. Between the years 2000 and 2100, we project a very likely (90% probability) GSL rise of 0.5-1.2 m under representative concentration pathway (RCP) 8.5, 0.4-0.9 m under RCP 4.5, and 0.3-0.8 m under RCP 2.6. Site-to-site differences in LSL projections are due to varying non-climatic background uplift or subsidence, oceanographic effects, and spatially variable responses of the geoid and the lithosphere to shrinking land ice. The Antarctic ice sheet (AIS) constitutes a growing share of variance in GSL and LSL projections. In the global average and at many locations, it is the dominant source of variance in late 21st century projections, though at some sites oceanographic processes contribute the largest share throughout the century. LSL rise dramatically reshapes flood risk, greatly increasing the expected number of "1-in-10" and "1-in-100" year events.

Using Pacific benthic foraminiferal δ18O and Mg/Ca records, we derive a Cenozoic (66 Ma) global mean sea level (GMSL) estimate that records evolution from an ice-free Early Eocene to Quaternary bipolar ice sheets. These GMSL estimates are statistically similar to “backstripped” estimates from continental margins accounting for compaction, loading, and thermal subsidence. Peak warmth, elevated GMSL, high CO2, and ice-free “Hothouse” conditions (56 to 48 Ma) were followed by “Cool Greenhouse” (48 to 34 Ma) ice sheets (10 to 30 m changes). Continental-scale ice sheets (“Icehouse”) began ~34 Ma (>50 m changes), permanent East Antarctic ice sheets at 12.8 Ma, and bipolar glaciation at 2.5 Ma. The largest GMSL fall (27 to 20 ka; ~130 m) was followed by a >40 mm/yr rise (19 to 10 ka), a slowing (10 to 2 ka), and a stillstand until ~1900 CE, when rates began to rise. High long-term CO2 caused warm climates and high sea levels, with sea-level variability dominated by periodic Milankovitch cycles.

The Last Interglacial (LIG) stage (ca. 130-115 ka), with polar temperatures likely 3-5 • C warmer than today, serves as a partial analogue for low-end future warming scenarios. Multiple indicators suggest that LIG global sea level (GSL) was higher than at present; based upon a small set of local sea level indicators, the Intergovernmental Panel on Climate Change (IPCC)'s Fourth Assessment Report inferred an elevation of approximately 4-6 m. While this estimate may be correct, it is based upon overly simplistic assumptions about the relationship between local sea level and global sea level. Sea level is often viewed as a simple function of changing global ice volume. This perspective neglects local variability, which arises from several factors, including the distortion of the geoid and the elastic and isostatic deformation of the solid Earth by shifting ice masses. Accurate reconstruction of past global and local sea levels, as well as ice sheet volumes, therefore requires integrating globally distributed data sets of local sea level indicators. To assess the robustness of the IPCC's global estimate and search for patterns in local sea level that are diagnostic of meltwater sources, we have compiled a comprehensive database that includes a variety of local sea level indicators from 47 localities, as well as a global sea level record derived from oxygen isotopes. We generate a global synthesis from these data using a novel statistical approach that couples Gaussian process regression to Markov Chain Monte Carlo simulation of geochronological errors. Our analysis strongly supports the hypothesis that global sea level during the Last Interglacial was higher than today, probably peaking between 6-9 m above the present level. This level is close to that expected from the complete melting of the Greenland Ice Sheet, or from major melting of both the Greenland and West Antarctic Ice Sheets. In the period when sea level was within 10 m of the modern value, the fastest rate of sea level rise sustained for a 1 ky period was likely about 80-110 cm per century. Combined with the evidence for mildly higher temperatures during the LIG, our results highlight the vulnerability of ice sheets to even relatively low levels of sustained global warming.

Estimates of climate change damage are central to the design of climate policies. Here, we develop a flexible architecture for computing damages that integrates climate science, econometric analyses, and process models. We use this approach to construct spatially explicit, probabilistic, and empirically derived estimates of economic damage in the United States from climate change. The combined value of market and nonmarket damage across analyzed sectors—agriculture, crime, coastal storms, energy, human mortality, and labor—increases quadratically in global mean temperature, costing roughly 1.2% of gross domestic product per +1°C on average. Importantly, risk is distributed unequally across locations, generating a large transfer of value northward and westward that increases economic inequality. By the late 21st century, the poorest third of counties are projected to experience damages between 2 and 20% of county income (90% chance) under business-as-usual emissions (Representative Concentration Pathway 8.5).