Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections
The Coupled Model Intercomparison Project Phase 5 “representative concentration pathways” (CMIP5 RCP) simulations quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ due to: 1) forcing; 2) the representation of the climate sy...
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ftdatacite:10.7282/t3rr217t 2023-05-15T15:11:19+02:00 Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections Little, Christopher M. Horton, Radley M. Kopp, Robert E. Oppenheimer, Michael Yip, Stan 2015 application/pdf https://dx.doi.org/10.7282/t3rr217t https://scholarship.libraries.rutgers.edu/esploro/outputs/journalArticle/991031550031304646 en eng Rutgers University Open Sea level--Mathematical models article-journal ScholarlyArticle Journal article Text 2015 ftdatacite https://doi.org/10.7282/t3rr217t 2022-03-10T11:01:47Z The Coupled Model Intercomparison Project Phase 5 “representative concentration pathways” (CMIP5 RCP) simulations quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ due to: 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 differentiation (“emergence”) of RCPs, depend upon the relative magnitude of these sources of uncertainty at different lead times. Here, we partition uncertainty in CMIP5 projections of sea level, at a global and local scale, using a 164-member ensemble of 21st 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 21st 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 5 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. Article in Journal/Newspaper Arctic Arctic Ocean North Atlantic DataCite Metadata Store (German National Library of Science and Technology) Arctic Arctic Ocean |
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language |
English |
topic |
Sea level--Mathematical models |
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Sea level--Mathematical models Little, Christopher M. Horton, Radley M. Kopp, Robert E. Oppenheimer, Michael Yip, Stan Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections |
topic_facet |
Sea level--Mathematical models |
description |
The Coupled Model Intercomparison Project Phase 5 “representative concentration pathways” (CMIP5 RCP) simulations quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ due to: 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 differentiation (“emergence”) of RCPs, depend upon the relative magnitude of these sources of uncertainty at different lead times. Here, we partition uncertainty in CMIP5 projections of sea level, at a global and local scale, using a 164-member ensemble of 21st 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 21st 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 5 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. |
format |
Article in Journal/Newspaper |
author |
Little, Christopher M. Horton, Radley M. Kopp, Robert E. Oppenheimer, Michael Yip, Stan |
author_facet |
Little, Christopher M. Horton, Radley M. Kopp, Robert E. Oppenheimer, Michael Yip, Stan |
author_sort |
Little, Christopher M. |
title |
Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections |
title_short |
Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections |
title_full |
Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections |
title_fullStr |
Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections |
title_full_unstemmed |
Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections |
title_sort |
uncertainty in twenty-first-century cmip5 sea level projections |
publisher |
Rutgers University |
publishDate |
2015 |
url |
https://dx.doi.org/10.7282/t3rr217t https://scholarship.libraries.rutgers.edu/esploro/outputs/journalArticle/991031550031304646 |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean North Atlantic |
genre_facet |
Arctic Arctic Ocean North Atlantic |
op_rights |
Open |
op_doi |
https://doi.org/10.7282/t3rr217t |
_version_ |
1766342189623803904 |