Upper limit for sea level projections by 2100

We construct the probability density function of global sea level at 2100, estimating that sea level rises larger than 180 cm are less than 5% probable. An upper limit for global sea level rise of 190 cm is assembled by summing the highest estimates of individual sea level rise components simulated by process based models with the RCP8.5 scenario. The agreement between the methods may suggest more confidence than is warranted since large uncertainties remain due to the lack of scenario-dependent projections from ice sheet dynamical models, particularly for mass loss from marine-based fast flowing outlet glaciers in Antarctica. This leads to an intrinsically hard to quantify fat tail in the probability distribution for global mean sea level rise. Thus our low probability upper limit of sea level projections cannot be considered definitive. Nevertheless, our upper limit of 180 cm for sea level rise by 2100 is based on both expert opinion and process studies and hence indicates that other lines of evidence are needed to justify a larger sea level rise this century

Do climate models reproduce complexity of observed sea level changes?

The ability of Atmosphere-Ocean General Circulation Models (AOGCMs) to capture the statistical behavior of sea level (SL) fluctuations has been assessed at the local scale. To do so, we have compared scaling behavior of the SL fluctuations simulated in the historical runs of 36 CMIP5 AOGCMs to that in the longest (>100 years) SL records from 23 tides gauges around the globe. The observed SL fluctuations are known to manifest a power law scaling. We have checked if the SL changes simulated in the AOGCM exhibit the same scaling properties and the long-term correlations as observed in the tide gauge records. We find that the majority of AOGCMs overestimates the scaling of SL fluctuations, particularly in the North Atlantic. Consequently, AOGCMs, routinely used to project regional SL rise, may underestimate the part of the externally driven SL rise, in particular the anthropogenic footprint, in the projections for the 21st century

Uncertainties in long-term twenty-first century process-based coastal sea-level projections

Many processes affect sea level near the coast. In this paper, we discuss the major uncertainties in coastal sea-level projections from a process-based perspective, at different spatial and temporal scales, and provide an outlook on how these uncertainties may be reduced. Uncertainty in centennial global sea-level rise is dominated by the ice sheet contributions. Geographical variations in projected sea-level change arise mainly from dynamical patterns in the ocean response and other geophysical processes. Finally, the uncertainties in the short-duration extreme sea-level events are controlled by near coastal processes, storms and tides

Impact of mass redistribution on regional sea level changes over the South China Sea shelves

This study investigates long-term sea level changes in the South China Sea (SCS) using a validated high-resolution regional ocean model simulation for the Maritime Continent. The contributions of ocean mass redistribution and steric sea level are examined to understand the sea level variations. The ocean bottom pressure (OBP) serves as an indicator of sea level variations linked to alterations in ocean mass flux. The OBP accounts for over 80% of the total sea level change over the shelves, while the steric sea level emerges as the dominant factor, contributing over 50% to the sea level change in the deep SCS. Luzon Strait transport shows a weakening trend in the last six decades, resulting in higher heat accumulation and larger steric expansion in the deep SCS. The ocean mass redistribution acts as a mechanism to balance the contrasting steric induced sea level changes over the deep SCS and shallow continental shelves

Flood damage costs under the sea level rise with warming of 1.5 °C and 2 °C

We estimate a median global sea level rise up to 52 cm (25–87 cm, 5th–95th percentile) and up to 63 cm (27−112 cm, 5th—95th percentile) for a temperature rise of 1.5 °C and 2.0 °C by 2100 respectively. We also estimate global annual flood costs under these scenarios and find the difference of 11 cm global sea level rise in 2100 could result in additional losses of US$1.4 trillion per year (0.25$ 14 trillion per year and US$ 27 trillion per year for global sea level rise of 86 cm (median) and 180 cm (95th percentile), reaching 2.8% of global GDP in 2100. Upper middle income countries are projected to experience the largest increase in annual flood costs (up to 8% GDP) with a large proportion attributed to China. High income countries have lower projected flood costs, in part due to their high present-day protection standards. Adaptation could potentially reduce sea level induced flood costs by a factor of 10. Failing to achieve the global mean temperature targets of 1.5 °C or 2 °C will lead to greater damage and higher levels of coastal flood risk worldwide

A flood damage allowance framework for coastal protection with deep uncertainty in sea-level rise

Future projections of Antarctic ice sheet (AIS) mass loss remain characterized by deep uncertainty (i.e., behavior is not well understood or widely agreed upon by experts). This complicates decisions on long-lived projects involving the height of coastal flood protection strategies that seek to reduce damages from rising sea levels. If a prescribed margin of safety does not properly account for sea-level rise and its uncertainties, the effectiveness of flood protection will decrease over time, potentially putting lives and property at greater risk. We develop a flood damage allowance framework for calculating the height of a flood protection strategy needed to ensure that a given level of financial risk is maintained (i.e., the average flood damage in a given year). The damage allowance framework considers decision-maker preferences such as planning horizons, preferred protection strategies (storm surge barrier, levee, elevation, and coastal retreat), and subjective views of AIS stability. We use Manhattan (New York City)\textemdash with the distribution of buildings, populations, and infrastructure fixed in time\textemdash as an example to show how our framework could be used to calculate a range of damage allowances based on multiple plausible AIS outcomes. Assumptions regarding future AIS stability more strongly influence damage allowances under high greenhouse gas emissions (Representative Concentration Pathway [RCP] 8.5) compared to those that assume strong emissions reductions (RCP2.6). Design tools that specify financial risk targets, such as the average flood damage in a given year, allow for the calculation of avoided flood damages (i.e., benefits) that can be combined with estimates of construction cost and then integrated into existing financial decision-making tools, like benefit-cost or cost-effectiveness analyses

Evidences for a quasi 60-year North Atlantic Oscillation since 1700 and its meaning for global climate change

The North Atlantic Oscillation (NAO) obtained using instrumental and documentary proxy predictors from Eurasia is found to be characterized by a quasi 60-year dominant oscillation since 1650. This pattern emerges clearly once the NAO record is time integrated to stress its comparison with the temperature record. The integrated NAO (INAO) is found to well correlate with the length of the day (since 1650) and the global surface sea temperature record HadSST2 and HadSST3 (since 1850). These findings suggest that INAO can be used as a good proxy for global climate change, and that a 60-year cycle exists in the global climate since at least 1700. Finally, the INAO ~60-year oscillation well correlates with the ~60- year oscillations found in the historical European aurora record since 1700, which suggests that this 60-year dominant climatic cycle has a solar-astronomical origin

Meeting user needs for sea level rise information: a decision analysis perspective

Despite widespread efforts to implement climate services, there is almost no literature that systematically analyses 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

“Chapter 13: Sea Level Change” in Climate Change 2013: The Physical Science Basis: Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change

This chapter considers changes in global mean sea level, regional sea level, sea level extremes, and waves. Confidence in projections of global mean sea level rise has increased since the Fourth Assessment Report (AR4) because of the improved physical understanding of the components of sea level, the improved agreement of process-based models with observations, and the inclusion of ice-sheet dynamical changes

Probabilistic sea level projections at the coast by 2100

As sea level is rising along many low-lying and densely populated coastal areas, affected communities are investing resources to assess and manage future socio-economic and ecological risks created by current and future sea level rise. Despite significant progress in the scientific understanding of the physical mechanisms contributing to sea level change, projections beyond 2050 remain highly uncertain. Here, we present recent developments in the probabilistic projections of coastal mean sea level rise by 2100, which provides a summary assessment of the relevant uncertainties. Probabilistic projections can be used directly in some of the decision frameworks adopted by coastal engineers for infrastructure design and land use planning. However, relying on a single probability distribution or a set of distributions based upon a common set of assumptions can understate true uncertainty and potentially misinform users. Here, we put the probabilistic projections published over the last 5 years into context