4.7 Article

Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections

Journal

JOURNAL OF CLIMATE
Volume 28, Issue 2, Pages 838-852

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-14-00453.1

Keywords

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Funding

  1. Science, Technology and Environmental Policy program in the Woodrow Wilson School of Public and International Affairs at Princeton University
  2. Carbon Mitigation Initiative in the Princeton Environmental Institute
  3. Structures of Coastal Resilience project
  4. Risky Business Initiative
  5. NOAA's Regional Integrated Sciences and Assessments (RISA) program

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The representative concentration pathway (RCP) simulations included in phase 5 of the Coupled Model Intercomparison Project (CMIP5) quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ because of 1) forcing, 2) the representation of the climate system in atmosphere-ocean general circulation models (AOGCMs), and 3) the presence of unforced (internal) variability. Global and local sea level rise projections derived from these simulations, and the emergence of distinct responses to the four RCPs depend on the relative magnitude of these sources of uncertainty at different lead times. Here, the uncertainty in CMIP5 projections of sea level is partitioned at global and local scales, using a 164-member ensemble of twenty-first-century simulations. Local projections at New York City (NYSL) are highlighted. The partition between model uncertainty, scenario uncertainty, and internal variability in global mean sea level (GMSL) is qualitatively consistent with that of surface air temperature, with model uncertainty dominant for most of the twenty-first century. Locally, model uncertainty is dominant through 2100, with maxima in the North Atlantic and the Arctic Ocean. The model spread is driven largely by 4 of the 16 AOGCMs in the ensemble; these models exhibit outlying behavior in all RCPs and in both GMSL and NYSL. The magnitude of internal variability varies widely by location and across models, leading to differences of several decades in the local emergence of RCPs. The AOGCM spread, and its sensitivity to model exclusion and/or weighting, has important implications for sea level assessments, especially if a local risk management approach is utilized.

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