Evaluating Model Simulations of Twentieth-Century Sea-Level Rise. Part II: Regional Sea-Level Changes

Abstract

Twentieth-century regional sea level changes are estimated from 12 climate models from phase 5 of the Climate Model Intercomparison Project (CMIP5). The output of the CMIP5 climate model simulations was used to calculate the global and regional sea level changes associated with dynamic sea level, atmospheric loading, glacier mass changes, and ice sheet surface mass balance contributions. The contribution from groundwater depletion, reservoir storage, and dynamic ice sheet mass changes are estimated from observations as they are not simulated by climate models. All contributions are summed, including the glacial isostatic adjustment (GIA) contribution, and compared to observational estimates from 27 tide gauge records over the twentieth century . A general agreement is found between the simulated sea level and tide gauge records in terms of interannual to multidecadal variability over 1900-2015. But climate models tend to systematically underestimate the observed sea level trends, particularly in the first half of the twentieth century. The corrections based on attributable biases between observations and models that have been identified in Part I of this two-part paper result in an improved explanation of the spatial variability in observed sea level trends by climate models. Climate models show that the spatial variability in sea level trends observed by tide gauge records is dominated by the GIA contribution and the steric contribution over 1900-2015. Climate models also show that it is important to include all contributions to sea level changes as they cause significant local deviations; note, for example, the groundwater depletion around India, which is responsible for the low twentieth-century sea level rise in the region.

How Well Do AR5 Sea Surface-Height Model Projections Match Observational Rates of Sea-Level Rise at the Regional Scale?

“…It is worthwhile appreciating differences between the current paper and the contemporary analysis undertaken in Meyssignac et al (2017) [10]. This recently published work compared 20th- Figure 7.…”

“…It is worthwhile appreciating differences between the current paper and the contemporary analysis undertaken in Meyssignac et al (2017) [10]. This recently published work compared 20th-century regional sea-level trends between an ensemble of 12 climate-model simulations using enhanced input on a range of sea-level contributions and that of 29 tide-gauge observations.…”

“…Both studies provide broad agreement between observational and simulated sea levels when error margins are taken into consideration and within the limits of the respective analyses undertaken. A logical next step might be to reapply the techniques espoused in this paper to the gridded outputs of the enhanced climate-model simulations developed in Meyssignac et al (2017) [10] when they are available.…”

“…A companion paper [10], provided a detailed evaluation of model performance at the regional scale by comparing these enhanced ensemble climate model outputs of SSH to tide gauge data (spanning the same period) at 27 sites around the world. The analysis concluded that for most of the tide gauge records, climate models tend to underestimate the observed twentieth-century trends.…”

Contributions to 21st century projections of extreme sea-level change around the UK

“…The UKCP18 projections are rooted in the sea-level methods of the IPCC AR5 , based on CMIP5 climate model simulations (Taylor et al 2012) under the RCP climate change scenarios (Meinshausen et al 2011). Recent assessment of CMIP5 model simulations demonstrates their ability to reproduce the main components of global and regional rise over the historical record (Slangen et al 2017, Meyssignac et al 2017 and promotes confidence in their ability to provide useful projections of future change. The main innovations to the UKCP18 sea-level projections relative to IPCC AR5 are: (i) inclusion of the scenario-dependent estimates of Antarctic dynamic ice input from Levermann et al 2014;(ii) use of a regression approach to estimate the regional oceanographic changes that better isolates the climate change signal from CMIP5 simulations (e.g.…”