Anthropogenic greenhouse gas emissions are causing unprecedented changes to the climate. In 2015, at the United Nations (UN) Conference of the Parties in Paris, France, countries agreed to limit the global mean temperature (GMT) increase to 2°C above preindustrial levels, and to pursue efforts to limit warming to 1.5°C. Due to the long-term irreversibility of sea level rise (SLR), risks to island and coastal populations are not well encapsulated by the goal of limiting GMT warming by 2100. This review article investigates the climate justice implications of temperature targets in light of our increasing understanding of the spatially variable impact and long temporal commitment to rising seas. In particular we highlight the impact that SLR will have on island states and the role of the Alliance of Small Island States (AOSIS) in UN climate negotiations. As a case study we review dual impacts from the Antarctic Ice Sheet under a changing climate: (a) recent climate and ice sheet modeling shows that Antarctic melt has the potential to cause rapid SLR with a distinct spatial pattern leading to AOSIS nations experiencing SLR at least 11% higher than the global average and up to 33% higher; and (b) future ice sheet melt will result in a negative feedback on GMT, thus delaying temperature rise. When considering these impacts in conjunction, justice concerns associated with the Paris Agreement are exacerbated.

In 2015, at the United Nations Conference of the Parties in Paris, France, countries agreed to limit the global mean surface temperature (GMST) increase to 2°C above preindustrial levels, and to pursue efforts to limit it to 1.5°C. However, risks from sea level rise are not well encapsulated by temperature targets. Near term emissions will dictate long term sea level rise responses, but the tendency for policy and negotiations to concentrate on the year 2100 can limit our understanding of intergenerational justice concerns arising from this commitment. Here we present an analysis of the long term spatial variability of sea level rise, and an interdisciplinary review of associated justice considerations from across a wide range of literatures. We center the positioning of the Alliance of Small Island States (AOSIS) to show that AOSIS nations are disproportionately impacted by sea level rise, and that ice sheet instabilities, which could dominate the long term trend in sea level, are associated with feedbacks which can potentially exacerbate climate justice implications.

Previous studies have interpreted Last Interglacial (LIG; ~129-116 ka) sea-level estimates in multiple different ways to calibrate projections of future Antarctic ice-sheet (AIS) mass loss and associated sea-level rise. This study systematically explores the extent to which LIG constraints could inform future Antarctic contributions to sea-level rise. We develop a Gaussian process emulator of an ice-sheet model to produce continuous probabilistic projections of Antarctic sea-level contributions over the LIG and a future high-emissions scenario. We use a Bayesian approach conditioning emulator projections on a set of LIG constraints to find associated likelihoods of model parameterizations. LIG estimates inform both the probability of past and future ice-sheet instabilities and projections of future sea-level rise through 2150. Although best-available LIG estimates do not meaningfully constrain Antarctic mass loss projections or physical processes until 2060, they become increasingly informative over the next 130 years. Uncertainties of up to 50 cm remain in future projections even if LIG Antarctic mass loss is precisely known (+/-5 cm), indicating there is a limit to how informative the LIG could be for ice-sheet model future projections. The efficacy of LIG constraints on Antarctic mass loss also depends on assumptions about the Greenland ice sheet and LIG sea-level chronology. However, improved field measurements and understanding of LIG sea levels still have potential to improve future sea-level projections, highlighting the importance of continued observational efforts.

Astronomical variations in tidal magnitude can strongly modulate the severity of coastal flooding on daily, monthly, and interannual timescales. Here, we present a new quasi-nonstationary skew surge joint probability method (qn-SSJPM) that estimates interannual fluctuations in flood hazard caused by the 18.6 and quasi 4.4-year modulations of tides. We demonstrate that qn-SSJPM-derived storm tide frequency estimates are more precise and stable compared with the standard practice of fitting an extreme value distribution to measured storm tides, which is often biased by the largest few events within the observational period. Applying the qn-SSJPM in the Gulf of Maine, we find significant tidal forcing of winter storm season flood hazard by the 18.6-year nodal cycle, whereas 4.4-year modulations and a secular trend in tides are small compared to interannual variation and long-term trends in sea-level. The nodal cycle forces decadal oscillations in the 1% annual chance storm tide at an average rate of ±13.5 mm/y in Eastport, ME; ±4.0 mm/y in Portland, ME; and ±5.9 mm/y in Boston, MA. Currently (in 2020), nodal forcing is counteracting the sea-level rise-induced increase in flood hazard; however, in 2025, the nodal cycle will reach a minimum and then begin to accelerate flood hazard increase as it moves toward its maximum phase over the subsequent decade. Along the world’s meso-to-macrotidal coastlines, it is therefore critical to consider both sea-level rise and tidal non-stationarity in planning for the transition to chronic flooding that will be driven by sea-level rise in many regions over the next century.

A two-layer model of thermohaline ocean circulation under Antarctic ice shelves is described that predicts sub-oceanic ice-shelf melt rates given the basin geometries and ocean temperatures and salinities at the ice edges. The model builds on a series of similar models, using an upper plume layer and adding a balance-flux approach that enables it to be used for evolving land-ocean geometries without the need to pre-define individual basin outlines. Results are compared to Antarctic melt rates derived from satellite data. The model is shown to work for two simulated configurations of West Antarctica very different from modern. In Supporting Information several alternate model aspects are described, and results are tested against numerical solutions of the basic plume differential equations for 1-D flowlines.

Sea-level rise (SLR) is a long-lasting consequence of climate change because global anthropogenic warming takes centuries to millennia to equilibrate. SLR projections based on climate models support policy analysis, risk assessment and adaptation planning today, despite their large uncertainties. The central range of the SLR distribution is estimated by process-based models. However, risk-averse practitioners often require information about plausible future conditions that lie in the tails of the SLR distribution, which are poorly defined by existing models. Here, a community effort combining scientist and practitioners, builds on a framework of discussing physical evidence to quantify high-end global SLR for practice. The approach is complementary to the IPCC AR6 report and provides further physically plausible high-end scenarios. High-end estimates for the different SLR components are developed for two climate scenarios at two timescales. For global warming of +2 ˚C in 2100 (SSP1-2.6) relative to pre-industrial values our high-end global SLR estimates are up to 0.9 m in 2100 and 2.5 m in 2300. Similarly, for +5 ˚C (SSP5-8.5) we estimate up to 1.6 m in 2100 and up to 10.4 m in 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long-term benefits of mitigation. However, even a modest 2 ˚C warming may cause multi-meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high-end assessments focused on instability mechanisms in Antarctica, while we emphasize the timing of ice-shelf collapse around Antarctica, which is highly uncertain due to low understanding of the driving processes.