We examine a 1000-yr-long forced historical run of the Max Planck Institute Earth System Model (henceforth, past1000) with respect to freshwater-induced sea surface height (SSH) variability in the Arctic Ocean, with a focus on time scales up to and longer than centuries. As a test of the degree to which sea surface height and freshwater content covariability is due to internal climate variability in the model, and how much is due to external forcing, the past1000 results are compared to a control run using the same model, (henceforth, Ctl-P). We find that the freshwater transport associated with circulation changes, the freshwater input at the surface from the atmosphere and runoff, and ice export out of the Arctic jointly contribute to the centennial-scale freshwater variability in the Arctic. Low-frequency winds generate freshwater variability mostly through ocean circulation changes, but appear to be less important compared with earlier studies. The ice transport varies most clearly with Arctic air temperatures, and it appears that ice thickness variability is at least as important as the wind and ocean current transport variability. The largest difference in freshwater forcing in the forced run, compared to Ctl-P, is enhanced precipitation variability driven by the volcanic forcing only present in the forced, past1000 run.

Coastal impacts of climate change and the related mitigation and adaptation needs requires assessments of future sea-level changes. Following a common practice in coastal engineering, probabilistic sea-level projections have been proposed for at least 20 years. This requires a probability model to represent the uncertainties of future sea-level rise, which is not achievable because potential ice sheets mass losses remain poorly understood given the knowledge available today. Here, we apply the principles of extra-probabilistic theories of uncertainties to generate global and regional sea-level projections based on uncertain components. This approach assigns an imprecision to a probabilistic measure, in order to quantify lack of knowledge pertaining to probabilistic projections. This can serve to understand, analyze and communicate uncertainties due to the coexistence of different processes contributing to future sea-level rise, including ice-sheets. We show that the knowledge gained since the 5th Assessment report of the IPCC allows better quantification of how global and regional sea-level rise uncertainties can be reduced with lower greenhouse gas emissions. Furthermore, Europe and Northern America are among those profiting most from a policy limiting climate change to RCP 2.6 versus RCP 4.5 in terms of reducing uncertainties of sea-level rise.

Projections of future sterodynamic sea level change from global climate models are associated with different sources of uncertainty. From a scientific, societal and policy-making perspective, it is relevant to both understand and reduce uncertainty in projections of climate change. Here, we review recent findings which describe, and shed light on, climate model uncertainty focusing particularly on two types of model uncertainty that contribute to the currently large spread in dynamical sea level patterns (i.e., regional sea level relative to the global mean). These uncertainties are: (1) intermodel uncertainty due to differences in models' responses in a warming climate and (2) internal model variability due to an individual model's own climate variability. On timescales longer than about 50 years from now, anthropogenic sterodynamic (dynamic plus global mean) sea level trends from middle- and high-end forcing scenarios will be larger than internal model variability. By 2100, these anthropogenic trends will also be larger than intermodel uncertainty when global mean thermosteric sea level rise and/or melting contributions from land ice are considered along with dynamic sea level changes. Furthermore, we discuss projections of future coastal sea level from the perspective of global climate models as well as from downscaled efforts based on regional climate models. Much knowledge and understanding has been achieved in the last decade from intermodel experiments and studies of sea level process-based model; here, the prospects for improving coastal sea level and reducing sea level uncertainty are discussed.

A major challenge for managing impacts and implementing effective mitigation measures and adaptation strategies for coastal zones affected by future sea level (SL) rise is our limited capacity to predict SL change at the coast on relevant spatial and temporal scales. Predicting coastal SL requires the ability to monitor and simulate a multitude of physical processes affecting SL, from local effects of wind waves and river runoff to remote influences of the large-scale ocean circulation on the coast. Here we assess our current understanding of the causes of coastal SL variability on monthly to multidecadal timescales, including geodetic, oceanographic and atmospheric aspects of the problem, and review available observing systems informing on coastal SL. We also review the ability of existing models and data assimilation systems to estimate coastal SL variations and of atmosphere-ocean global coupled models and related regional downscaling efforts to project future SL changes.We discuss (1) observational gaps and uncertainties, and priorities for the development of an optimal and integrated coastal SL observing system, (2) strategies for advancing model capabilities in forecasting shortterm processes and projecting long-term changes affecting coastal SL, and (3) possible future developments of sea level services enabling better connection of scientists and user communities and facilitating assessment and decision making for adaptation to future coastal SL change.

Coastal impacts of climate change and the related mitigation and adaptation needs requires assessments of future sea-level changes. Following a common practice in coastal engineering, probabilistic sea-level projections have been proposed for at least 20 years. This requires a probability model to represent the uncertainties of future sea-level rise, which is not achievable because potential ice sheets mass losses remain poorly understood given the knowledge available today. Here, we apply the principles of extra-probabilistic theories of uncertainties to generate global and regional sea-level projections based on uncertain components. This approach assigns an imprecision to a probabilistic measure, in order to quantify lack of knowledge pertaining to probabilistic projections. This can serve to understand, analyze and communicate uncertainties due to the coexistence of different processes contributing to future sea-level rise, including ice-sheets. We show that the knowledge gained since the 5th Assessment report of the IPCC allows better quantification of how global and regional sea-level rise uncertainties can be reduced with lower greenhouse gas emissions. Furthermore, Europe and Northern America are among those profiting most from a policy limiting climate change to RCP 2.6 versus RCP 4.5 in terms of reducing uncertainties of sea-level rise.

Several existing statistical and dynamical reconstructions of past regional sea level variability and trends are compared with each other and with tide gauges over the 48 year period 1960-2007, partially predating the satellite altimetry era. Evaluated statistical reconstructions were built from tide-gauge data (TGR), and dynamical reconstructions from ocean data assimilation (ODA) approaches. Although most of the TGRs yield global-mean time series of sea level with trends deviating within only 0.1 mmyr(-1), the spatial anomalies of the trends deviate substantially between the reconstructions over the period predating altimetry. In contrast, TGRs match observed regional trend patterns fairly well during the satellite altimetry era. TGRs match tide-gauge data better than ODA results; however, they exhibit less variability in the open ocean compared to altimetric data. Over the prealtimetry period, all reconstructed regional sea level trend patterns deviate substantially from each other. In terms of detrended correlations in this earlier period, the reconstructions match tide gauges, and each other, much better in the Pacific than in the Atlantic. An ensemble of all TGR and ODA estimates provides some improvements in correlations and trends to both tide gauges and altimetry. Nevertheless, a lack of independent open ocean sea surface height data predating altimetry makes impossible the validation of the ensemble for prealtimetry open ocean sea level trends and variability. Estimating regional sea level changes prior to altimetry therefore remains an unsolved challenge.

We investigate sea level trends and variability as reconstructed from tide gauge data and ocean data assimilations (ODA) over the last 60 years. Tide gauge reconstructions (TGR) are mostly based on statistical approaches using selected EOFs, or trained from variability patterns, from altimetric sea level and tide gauge data to extrapolate regional sea level evolution backward in time. Reconstructions also exist from dynamical ocean modeling approaches with and without data assimilation. We intercompare all results and provide ensemble mean and ensemble spreads to describe estimates of past regional sea level changes and their uncertainties.

Timeseries of observed and projected sea level changes for the 20th and 21st century are analyzed at various coastal locations around the world that are vulnerable to climate change. Observed time series are from tide gauges and altimetry, as well as from reconstructions over the last 50 years. CMIP5 coupled atmosphere-ocean model output of regional sea-level and associated uncertainty estimates are merged with scenario-independent contributions from GIA and dynamic ice to provide time series of coastal sea-level projections to the end of the 21st century. We focus on better quantifying the regional departure of coastal sea level rise from its global average, identify the reasons for the regional departure, and quantify the reasons for the uncertainty in these regional projections. Many of these coastal sea level projections are lower than the global mean change in sea level due to glacial isostatic adjustment, and gravitational changes from loss of land ice and terrestrially stored ground water. In most coastal regions, local deviations from the global mean vary up to ±20 cm which, depending on the location, differ substantially in their underlying causes.

Regional sea surface height variability due to internal climate fluctuations is estimated using preindustrial control runs of 21 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Projected sea level trends of the representative concentration pathway 4.5 (RCP4.5) scenario for 20-, 50-, and 100-yr intervals grow from being largely dominated by internal variability on shorter time scales to being the dominant sea level signal on long time scales. The internal variability is estimated by calculating overlapping trends for the various time scales on the regional sea level control run output from each model. When compared to the ensemble spread of the RCP4.5 scenario trends, the internal variability remains a substantial portion of the spread even after 50 years. The regional ensemble mean trends are mostly larger than the ensemble spread for the 50-yr interval and are larger everywhere, except for part of the central Arctic and the Southern Ocean for the 100-yr projection. Although it is unclear whether the model internal variability estimate will be comparable to long-term variability in the real ocean, the authors compare the strength of the estimate to satellite altimetry and find that altimetry-based trends may be larger in tropical ocean regions, with only limited extratropical regions rising above the internal variability. The authors also analyze a single model's internal variability against its future RCP4.5-projected sea level and show that, by 50 years, many regional sea level trends are larger than the underlying internal variability, though this variability still accounts for more than a third of the trend magnitude for almost half of the extratropical ocean.

Sea-level changes on a wide range of time and space scales. This article considers changes in mean sea level, that is, sea level averaged over a sufficient period of time to remove fluctuations associated with surface waves, tides, and individual storm surge events. Changes in sea level changes over the last hundred years or so and on how it might change over the next one hundred years are or particular interest. However, to understand these changes requires consideration of sea level since the last glacial maximum 20,000 years ago. The longer-term implications of changes in the Earth's climate arising from changes in atmospheric greenhouse gas concentrations are also considered.

The goal of this paper is to provide information on the sea level and upper ocean temperature variability and trends in the Cook Islands region within a global context. Oceanic fisheries variability and change take place within the physical environment. Because the state of the historical data set is not as would be desired, we begin with some review of data distribution issues. We provide some new results from the Cook Islands region but draw upon previous work for information about the global and ocean-basin scale context. There are clear trends over recent decades in sea level and, generally, in upper ocean temperature, but there is also substantial interannual and interdecadal variability, which are larger locally than globally. Because of this variability, it is not possible to say if recent Cook Islands regional trends are representative of longer-term trends, or if longer-term trends have increased recently. Trends in the Cook Islands region over the last four decades are ~0.1–0.3 °C per decade in near surface temperature and ~2–3 cm sea level per decade.

We present regional sea-level projections and associated uncertainty estimates for the end of the 21 st century. We show regional projections of sea-level change resulting from changing ocean circulation, increased heat uptake and atmospheric pressure in CMIP5 climate models. These are combined with model- and observation-based regional contributions of land ice, groundwater depletion and glacial isostatic adjustment, including gravitational effects due to mass redistribution. A moderate and a warmer climate change scenario are considered, yielding a global mean sea-level rise of 0.54 ±0.19 m and 0.71 ±0.28 m respectively (mean ±1σ). Regionally however, changes reach up to 30 % higher in coastal regions along the North Atlantic Ocean and along the Antarctic Circumpolar Current, and up to 20 % higher in the subtropical and equatorial regions, confirming patterns found in previous studies. Only 50 % of the global mean value is projected for the subpolar North Atlantic Ocean, the Arctic Ocean and off the western Antarctic coast. Uncertainty estimates for each component demonstrate that the land ice contribution dominates the total uncertainty.