Synthesizing long-term sea level rise projections – the MAGICC sea level model v2.0
Sea level rise (SLR) is one of the major impacts of global warming; it will threaten coastal populations, infrastructure, and ecosystems around the globe in coming centuries. Well-constrained sea level projections are needed to estimate future losses from SLR and benefits of climate protection and a...
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ftleibnizopen:oai:oai.leibnizopen.de:juQqsIYBdbrxVwz6rHef 2023-05-15T14:01:52+02:00 Synthesizing long-term sea level rise projections – the MAGICC sea level model v2.0 Nauels, Alexander Meinshausen, Malte Mengel, Matthias Lorbacher, Katja Wigley, Tom M.L. 2017 application/pdf https://doi.org/10.34657/388 https://oa.tib.eu/renate/handle/123456789/3803 eng eng München : European Geopyhsical Union CC BY 3.0 Unported https://creativecommons.org/licenses/by/3.0/ CC-BY Geoscientific Model Development, Volume 10, Issue 6, Page 2495-2524 Climate conditions hydrological modeling ice sheet mass balance parameterization prediction sea level change software uncertainty analysis 500 article Text 2017 ftleibnizopen https://doi.org/10.34657/388 2023-03-06T00:12:14Z Sea level rise (SLR) is one of the major impacts of global warming; it will threaten coastal populations, infrastructure, and ecosystems around the globe in coming centuries. Well-constrained sea level projections are needed to estimate future losses from SLR and benefits of climate protection and adaptation. Process-based models that are designed to resolve the underlying physics of individual sea level drivers form the basis for state-of-the-art sea level projections. However, associated computational costs allow for only a small number of simulations based on selected scenarios that often vary for different sea level components. This approach does not sufficiently support sea level impact science and climate policy analysis, which require a sea level projection methodology that is flexible with regard to the climate scenario yet comprehensive and bound by the physical constraints provided by process-based models. To fill this gap, we present a sea level model that emulates global-mean long-term process-based model projections for all major sea level components. Thermal expansion estimates are calculated with the hemispheric upwelling-diffusion ocean component of the simple carbon-cycle climate model MAGICC, which has been updated and calibrated against CMIP5 ocean temperature profiles and thermal expansion data. Global glacier contributions are estimated based on a parameterization constrained by transient and equilibrium process-based projections. Sea level contribution estimates for Greenland and Antarctic ice sheets are derived from surface mass balance and solid ice discharge parameterizations reproducing current output from ice-sheet models. The land water storage component replicates recent hydrological modeling results. For 2100, we project 0.35 to 0.56m (66% range) total SLR based on the RCP2.6 scenario, 0.45 to 0.67m for RCP4.5, 0.46 to 0.71m for RCP6.0, and 0.65 to 0.97m for RCP8.5. These projections lie within the range of the latest IPCC SLR estimates. SLR projections for 2300 yield median ... Article in Journal/Newspaper Antarc* Antarctic glacier Greenland Ice Sheet LeibnizOpen (The Leibniz Association) Antarctic Greenland |
institution |
Open Polar |
collection |
LeibnizOpen (The Leibniz Association) |
op_collection_id |
ftleibnizopen |
language |
English |
topic |
Climate conditions hydrological modeling ice sheet mass balance parameterization prediction sea level change software uncertainty analysis 500 |
spellingShingle |
Climate conditions hydrological modeling ice sheet mass balance parameterization prediction sea level change software uncertainty analysis 500 Nauels, Alexander Meinshausen, Malte Mengel, Matthias Lorbacher, Katja Wigley, Tom M.L. Synthesizing long-term sea level rise projections – the MAGICC sea level model v2.0 |
topic_facet |
Climate conditions hydrological modeling ice sheet mass balance parameterization prediction sea level change software uncertainty analysis 500 |
description |
Sea level rise (SLR) is one of the major impacts of global warming; it will threaten coastal populations, infrastructure, and ecosystems around the globe in coming centuries. Well-constrained sea level projections are needed to estimate future losses from SLR and benefits of climate protection and adaptation. Process-based models that are designed to resolve the underlying physics of individual sea level drivers form the basis for state-of-the-art sea level projections. However, associated computational costs allow for only a small number of simulations based on selected scenarios that often vary for different sea level components. This approach does not sufficiently support sea level impact science and climate policy analysis, which require a sea level projection methodology that is flexible with regard to the climate scenario yet comprehensive and bound by the physical constraints provided by process-based models. To fill this gap, we present a sea level model that emulates global-mean long-term process-based model projections for all major sea level components. Thermal expansion estimates are calculated with the hemispheric upwelling-diffusion ocean component of the simple carbon-cycle climate model MAGICC, which has been updated and calibrated against CMIP5 ocean temperature profiles and thermal expansion data. Global glacier contributions are estimated based on a parameterization constrained by transient and equilibrium process-based projections. Sea level contribution estimates for Greenland and Antarctic ice sheets are derived from surface mass balance and solid ice discharge parameterizations reproducing current output from ice-sheet models. The land water storage component replicates recent hydrological modeling results. For 2100, we project 0.35 to 0.56m (66% range) total SLR based on the RCP2.6 scenario, 0.45 to 0.67m for RCP4.5, 0.46 to 0.71m for RCP6.0, and 0.65 to 0.97m for RCP8.5. These projections lie within the range of the latest IPCC SLR estimates. SLR projections for 2300 yield median ... |
format |
Article in Journal/Newspaper |
author |
Nauels, Alexander Meinshausen, Malte Mengel, Matthias Lorbacher, Katja Wigley, Tom M.L. |
author_facet |
Nauels, Alexander Meinshausen, Malte Mengel, Matthias Lorbacher, Katja Wigley, Tom M.L. |
author_sort |
Nauels, Alexander |
title |
Synthesizing long-term sea level rise projections – the MAGICC sea level model v2.0 |
title_short |
Synthesizing long-term sea level rise projections – the MAGICC sea level model v2.0 |
title_full |
Synthesizing long-term sea level rise projections – the MAGICC sea level model v2.0 |
title_fullStr |
Synthesizing long-term sea level rise projections – the MAGICC sea level model v2.0 |
title_full_unstemmed |
Synthesizing long-term sea level rise projections – the MAGICC sea level model v2.0 |
title_sort |
synthesizing long-term sea level rise projections – the magicc sea level model v2.0 |
publisher |
München : European Geopyhsical Union |
publishDate |
2017 |
url |
https://doi.org/10.34657/388 https://oa.tib.eu/renate/handle/123456789/3803 |
geographic |
Antarctic Greenland |
geographic_facet |
Antarctic Greenland |
genre |
Antarc* Antarctic glacier Greenland Ice Sheet |
genre_facet |
Antarc* Antarctic glacier Greenland Ice Sheet |
op_source |
Geoscientific Model Development, Volume 10, Issue 6, Page 2495-2524 |
op_rights |
CC BY 3.0 Unported https://creativecommons.org/licenses/by/3.0/ |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.34657/388 |
_version_ |
1766271924377223168 |