Reducing uncertainty in projections of terrestrial carbon uptake
Carbon uptake by the oceans and terrestrial biosphere regulates atmospheric carbon dioxide concentration and affects Earth’s climate, yet global carbon cycle projections over the next century are highly uncertain. Here, we quantify and isolate the sources of projection uncertainty in cumulative ocea...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2017-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/aa66b8 |
| _version_ | 1797748261819252736 |
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| author | Nicole S Lovenduski Gordon B Bonan |
| author_facet | Nicole S Lovenduski Gordon B Bonan |
| author_sort | Nicole S Lovenduski |
| collection | DOAJ |
| description | Carbon uptake by the oceans and terrestrial biosphere regulates atmospheric carbon dioxide concentration and affects Earth’s climate, yet global carbon cycle projections over the next century are highly uncertain. Here, we quantify and isolate the sources of projection uncertainty in cumulative ocean and terrestrial carbon uptake over 2006–2100 by performing an analysis of variance on output from an ensemble of 12 Earth System Models. Whereas uncertainty in projections of global ocean carbon accumulation by 2100 is <100 Pg C and driven primarily by emission scenario, uncertainty in projections of global terrestrial carbon accumulation by 2100 is >160 Pg C and driven primarily by model structure. To statistically reduce uncertainty in terrestrial carbon projections, we devise schemes to weight the models based on their ability to represent the observed change in carbon accumulation over 1959–2005. The weighting schemes incrementally reduce uncertainty to a minimum value of 125 Pg C in 2100, but this reduction requires an impractical observational constraint. We suggest that a focus on reducing multi-model spread may not make terrestrial carbon cycle projections more reliable, and instead advocate for accurate observations, improved process understanding, and a multitude of modeling approaches. |
| first_indexed | 2024-03-12T16:02:23Z |
| format | Article |
| id | doaj.art-2b0e6b96cb9f46a0b940080ff6a4a750 |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T16:02:23Z |
| publishDate | 2017-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-2b0e6b96cb9f46a0b940080ff6a4a7502023-08-09T14:33:11ZengIOP PublishingEnvironmental Research Letters1748-93262017-01-0112404402010.1088/1748-9326/aa66b8Reducing uncertainty in projections of terrestrial carbon uptakeNicole S Lovenduski0Gordon B Bonan1Department of Atmospheric and Oceanic Sciences and Institute of Arctic and Alpine Research , University of Colorado, Boulder, CO, United States of America; Author to whom any correspondence should be addressed.Climate and Global Dynamics Laboratory , National Center for Atmospheric Research, Boulder, CO, United States of AmericaCarbon uptake by the oceans and terrestrial biosphere regulates atmospheric carbon dioxide concentration and affects Earth’s climate, yet global carbon cycle projections over the next century are highly uncertain. Here, we quantify and isolate the sources of projection uncertainty in cumulative ocean and terrestrial carbon uptake over 2006–2100 by performing an analysis of variance on output from an ensemble of 12 Earth System Models. Whereas uncertainty in projections of global ocean carbon accumulation by 2100 is <100 Pg C and driven primarily by emission scenario, uncertainty in projections of global terrestrial carbon accumulation by 2100 is >160 Pg C and driven primarily by model structure. To statistically reduce uncertainty in terrestrial carbon projections, we devise schemes to weight the models based on their ability to represent the observed change in carbon accumulation over 1959–2005. The weighting schemes incrementally reduce uncertainty to a minimum value of 125 Pg C in 2100, but this reduction requires an impractical observational constraint. We suggest that a focus on reducing multi-model spread may not make terrestrial carbon cycle projections more reliable, and instead advocate for accurate observations, improved process understanding, and a multitude of modeling approaches.https://doi.org/10.1088/1748-9326/aa66b8carbon cycleterrestrial ecosystem modelcarbon sinksclimate model |
| spellingShingle | Nicole S Lovenduski Gordon B Bonan Reducing uncertainty in projections of terrestrial carbon uptake Environmental Research Letters carbon cycle terrestrial ecosystem model carbon sinks climate model |
| title | Reducing uncertainty in projections of terrestrial carbon uptake |
| title_full | Reducing uncertainty in projections of terrestrial carbon uptake |
| title_fullStr | Reducing uncertainty in projections of terrestrial carbon uptake |
| title_full_unstemmed | Reducing uncertainty in projections of terrestrial carbon uptake |
| title_short | Reducing uncertainty in projections of terrestrial carbon uptake |
| title_sort | reducing uncertainty in projections of terrestrial carbon uptake |
| topic | carbon cycle terrestrial ecosystem model carbon sinks climate model |
| url | https://doi.org/10.1088/1748-9326/aa66b8 |
| work_keys_str_mv | AT nicoleslovenduski reducinguncertaintyinprojectionsofterrestrialcarbonuptake AT gordonbbonan reducinguncertaintyinprojectionsofterrestrialcarbonuptake |