It is essential to understand the causes of sea level extremes in order to anticipate and respond to coastal flooding (inundation), and to adapt to sea level rise. We investigate a series of inundation events which occurred across the western Pacific over several consecutive days during December 2008, causing severe impacts to five Pacific Island nations. These events were not associated with commonly identified causes: tropical cyclones or unusually large astronomical tides. Instead, the dissipation of wind-waves generated by distant extra-tropical cyclones (swell) was the main cause, although regional sea level variability, including recent accelerated rise, significantly contributed to the severity of impact experienced at many locations. The implication of recent sea level rise in the severity of these events suggests that episodic swell will increasingly cause major impacts of the nature described herein, although such impacts will continue to be modulated by El Niño/Southern Oscillation (ENSO) variability in the region. Significantly, tide gauges recorded little evidence of extreme sea levels during the event, implying that causes of extreme sea levels inferred from tide gauge analysis are unlikely to include this important cause of inundation. Therefore, any assessment of inundation risk predicated on tide gauge information (as well as larger scale sea level information such as satellite altimetry) may fail at many locations in the Pacific. To be accurate, such efforts must include information on the relationship between wave climate, wave forecasts and local extreme water levels. Further development of related early warning systems will become more pertinent as modern SLR continues to add to the magnitude of extremes

Objectively derived resolution-dependent criteria are defined for the detection of tropical cyclones in model simulations and observationally based analyses. These criteria are derived from the wind profiles of observed tropical cyclones, averaged at various resolutions. Both an analytical wind profile model and two-dimensional observed wind analyses are used. The results show that the threshold wind speed of an observed tropical cyclone varies roughly linearly with resolution. The criteria derived here are compared to the numerous different criteria previously employed in climate model simulations. The resulting method provides a simple means of comparing climate model simulations and reanalyses.

Despite widespread efforts to implement climate services, there is almost no literature that systematically analyzes users' needs. This paper addresses this gap by applying a decision analysis perspective to identify what kind of mean sea level rise (SLR) information is needed for local coastal adaptation decisions. We first characterize these decisions, then identify suitable decision analysis approaches and the sea level information required, and finally discuss if and how these information needs can be met given the state of the art of sea level science. We find that four types of information are needed: (i) probabilistic predictions for short‐term decisions when users are uncertainty tolerant; (ii) high‐end and low‐end SLR scenarios chosen for different levels of uncertainty tolerance; (iii) upper bounds of SLR for users with a low uncertainty tolerance; and (iv) learning scenarios derived from estimating what knowledge will plausibly emerge about SLR over time. Probabilistic predictions can only be attained for the near term (i.e., 2030–2050) before SLR significantly diverges between low and high emission scenarios, for locations for which modes of climate variability are well understood and the vertical land movement contribution to local sea levels is small. Meaningful SLR upper bounds cannot be defined unambiguously from a physical perspective. Low‐ to high‐end scenarios for different levels of uncertainty tolerance and learning scenarios can be produced, but this involves both expert and user judgments. The decision analysis procedure elaborated here can be applied to other types of climate information that are required for mitigation and adaptation purposes.

Sea level rise (SLR) is a long‐lasting consequence of climate change because global anthropogenic warming takes centuries to millennia to equilibrate for the deep ocean and ice sheets. 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 scientists and practitioners builds on a framework of discussing physical evidence to quantify high‐end global SLR for practitioners. 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 (RCP2.6/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 a (RCP8.5/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 here we emphasize the importance of the timing of ice shelf collapse around Antarctica. This is highly uncertain due to low understanding of the driving processes. Hence both process understanding and emission scenario control high‐end SLR.