Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties
Multi-model averaging techniques provide opportunities to extract additional information from large ensembles of simulations. In particular, present-day model skill can be used to evaluate their potential performance in future climate simulations. Multi-model averaging methods have been used ex...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2018-02-01
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| Series: | Earth System Dynamics |
| Online Access: | https://www.earth-syst-dynam.net/9/153/2018/esd-9-153-2018.pdf |
| _version_ | 1818989985106231296 |
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| author | J.-F. Exbrayat A. A. Bloom P. Falloon A. Ito T. L. Smallman M. Williams |
| author_facet | J.-F. Exbrayat A. A. Bloom P. Falloon A. Ito T. L. Smallman M. Williams |
| author_sort | J.-F. Exbrayat |
| collection | DOAJ |
| description | Multi-model averaging techniques provide opportunities to
extract
additional information from large ensembles of simulations. In
particular, present-day model skill can be used to evaluate their
potential performance in future climate simulations. Multi-model
averaging methods have been used extensively in climate and
hydrological sciences, but they have not been used to constrain
projected plant productivity responses to climate change, which is
a major uncertainty in Earth system modelling. Here, we use three
global observationally orientated estimates of current net primary
productivity (NPP) to perform a reliability ensemble averaging (REA) method
using 30 global simulations of the 21st century change in NPP based
on the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP)
<q>business as usual</q> emissions scenario. We find that the three
REA methods support an increase in global NPP by the end of the 21st
century (2095–2099) compared to 2001–2005, which is 2–3 %
stronger than the ensemble ISIMIP mean value of
24.2 Pg C y<sup>−1</sup>. Using REA also leads to a 45–68 %
reduction in the global uncertainty of 21st century NPP projection,
which strengthens confidence in the resilience of the
CO<sub>2</sub> fertilization effect to climate change. This reduction
in uncertainty is especially clear for boreal ecosystems although it
may be an artefact due to the lack of representation of nutrient
limitations on NPP in most models. Conversely, the large uncertainty
that remains on the sign of the response of NPP in semi-arid regions
points to the need for better observations and model development in
these regions. |
| first_indexed | 2024-12-20T19:47:10Z |
| format | Article |
| id | doaj.art-8bfd8662ddd845db9aac3085cb12fe00 |
| institution | Directory Open Access Journal |
| issn | 2190-4979 2190-4987 |
| language | English |
| last_indexed | 2024-12-20T19:47:10Z |
| publishDate | 2018-02-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Earth System Dynamics |
| spelling | doaj.art-8bfd8662ddd845db9aac3085cb12fe002022-12-21T19:28:24ZengCopernicus PublicationsEarth System Dynamics2190-49792190-49872018-02-01915316510.5194/esd-9-153-2018Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertaintiesJ.-F. Exbrayat0A. A. Bloom1P. Falloon2A. Ito3T. L. Smallman4M. Williams5School of GeoSciences and National Centre for Earth Observation, University of Edinburgh, Edinburgh, EH9 3FF, UKJet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USAMet Office Hadley Centre, Fitzroy Road, Exeter, EX1 3PB, UKNational Institute for Environmental Studies, Tsukuba, JapanSchool of GeoSciences and National Centre for Earth Observation, University of Edinburgh, Edinburgh, EH9 3FF, UKSchool of GeoSciences and National Centre for Earth Observation, University of Edinburgh, Edinburgh, EH9 3FF, UKMulti-model averaging techniques provide opportunities to extract additional information from large ensembles of simulations. In particular, present-day model skill can be used to evaluate their potential performance in future climate simulations. Multi-model averaging methods have been used extensively in climate and hydrological sciences, but they have not been used to constrain projected plant productivity responses to climate change, which is a major uncertainty in Earth system modelling. Here, we use three global observationally orientated estimates of current net primary productivity (NPP) to perform a reliability ensemble averaging (REA) method using 30 global simulations of the 21st century change in NPP based on the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) <q>business as usual</q> emissions scenario. We find that the three REA methods support an increase in global NPP by the end of the 21st century (2095–2099) compared to 2001–2005, which is 2–3 % stronger than the ensemble ISIMIP mean value of 24.2 Pg C y<sup>−1</sup>. Using REA also leads to a 45–68 % reduction in the global uncertainty of 21st century NPP projection, which strengthens confidence in the resilience of the CO<sub>2</sub> fertilization effect to climate change. This reduction in uncertainty is especially clear for boreal ecosystems although it may be an artefact due to the lack of representation of nutrient limitations on NPP in most models. Conversely, the large uncertainty that remains on the sign of the response of NPP in semi-arid regions points to the need for better observations and model development in these regions.https://www.earth-syst-dynam.net/9/153/2018/esd-9-153-2018.pdf |
| spellingShingle | J.-F. Exbrayat A. A. Bloom P. Falloon A. Ito T. L. Smallman M. Williams Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties Earth System Dynamics |
| title | Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties |
| title_full | Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties |
| title_fullStr | Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties |
| title_full_unstemmed | Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties |
| title_short | Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties |
| title_sort | reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties |
| url | https://www.earth-syst-dynam.net/9/153/2018/esd-9-153-2018.pdf |
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