The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Evaluating the Land and Ocean Components of the Global Carbon Cycle in the CMIP5 Earth System Models
Open accessAbstract
The authors assess the ability of 18 Earth system models to simulate the land and ocean carbon cycle for the present climate. These models will be used in the next Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) for climate projections, and such evaluation allows identification of the strengths and weaknesses of individual coupled carbon–climate models as well as identification of systematic biases of the models. Results show that models correctly reproduce the main climatic variables controlling the spatial and temporal characteristics of the carbon cycle. The seasonal evolution of the variables under examination is well captured. However, weaknesses appear when reproducing specific fields: in particular, considering the land carbon cycle, a general overestimation of photosynthesis and leaf area index is found for most of the models, while the ocean evaluation shows that quite a few models underestimate the primary production.The authors also propose climate and carbon cycle performance metrics in order to assess whether there is a set of consistently better models for reproducing the carbon cycle. Averaged seasonal cycles and probability density functions (PDFs) calculated from model simulations are compared with the corresponding seasonal cycles and PDFs from different observed datasets. Although the metrics used in this study allow identification of some models as better or worse than the average, the ranking of this study is partially subjective because of the choice of the variables under examination and also can be sensitive to the choice of reference data. In addition, it was found that the model performances show significant regional variations.
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Cites
An Overview of CMIP5 and the Experiment Design
Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-11-00094.1 · Cited by 14,052
An estimate of global primary production in the ocean from satellite radiometer data
Longhurst, A., Sathyendranath, S., Platt, T., & Caverhill, C. (1995) · Journal of Plankton Research · doi:10.1093/plankt/17.6.1245 · Cited by 1,480
Indirect radiative forcing of climate change through ozone effects on the land-carbon sink
Sitch, S., Cox, P. M., Collins, W. J., & Huntingford, C. (2007) · Nature · doi:10.1038/nature06059 · Cited by 1,019
Self-citationSmith, P., Davies, C. A., Ogle, S., Zanchi, G., Bellarby, J., Bird, N., Boddey, R. M., McNamara, N. P., Powlson, D., Cowie, A., et al. (2012) · Global Change Biology · doi:10.1111/j.1365-2486.2012.02689.x · Cited by 185
Climate projections: Past performance no guarantee of future skill?
Reifen, C., & Toumi, R. (2009) · Geophysical Research Letters · doi:10.1029/2009gl038082 · Cited by 144
Cited by
Atmospheric component of the MPI‐M Earth System Model: ECHAM6
Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S., Salzmann, M., Schmidt, H., Bader, J., Block, K., et al. (2013) · Journal of Advances in Modeling Earth Systems · doi:10.1002/jame.20015 · Cited by 1,379
Zhu, Z., Bi, J., Pan, Y., Ganguly, S., Anav, A., Xu, L., Samanta, A., Piao, S., Nemani, R., & Myneni, R. (2013) · Remote Sensing · doi:10.3390/rs5020927 · Cited by 912
Self-citationJoint control of terrestrial gross primary productivity by plant phenology and physiology
Xia, J., Niu, S., Ciais, P., Janssens, I. A., Chen, J., Ammann, C., Arain, A., Blanken, P. D., Cescatti, A., Bonal, D., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1413090112 · Cited by 438
Self-citationJones, C. D., Arora, V., Friedlingstein, P., Bopp, L., Brovkin, V., Dunne, J., Graven, H., Hoffman, F., Ilyina, T., John, J. G., et al. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-2853-2016 · Cited by 365
Self-citationFeng, Z., De Marco, A., Anav, A., Gualtieri, M., Sicard, P., Tian, H., Fornasier, F., Tao, F., Guo, A., & Paoletti, E. (2019) · Environment International · doi:10.1016/j.envint.2019.104966 · Cited by 361
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Metadata
- Authors
- Anav, A., Friedlingstein, P., Kidston, M., Bopp, L., Ciais, P., Cox, P., Jones, C., Jung, M., Myneni, R., & Zhu, Z.
- Venue
- Journal of Climate
- Publisher
- American Meteorological Society
- Published
- 2013-09-09
- Volume
- 26
- Issue
- 18
- Pages
- 6801-6843
- ISSN
- 0894-8755 (ISSN-L)
- 1520-0442
- OpenAlex
- W2149884823
- Cited by
- 502
- References
- 5
- FWCI
- 32.74
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Anav, A., Friedlingstein, P., Kidston, M., Bopp, L., Ciais, P., Cox, P., Jones, C., Jung, M., Myneni, R., & Zhu, Z. (2013). Evaluating the Land and Ocean Components of the Global Carbon Cycle in the CMIP5 Earth System Models. Journal of Climate. https://doi.org/10.1175/jcli-d-12-00417.1
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.