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Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO 2 trends
Open accessAbstract
The purpose of this study was to evaluate 10 process‐based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity ( GPP ) is compared with flux‐tower‐based estimates by Jung et al . [ Journal of Geophysical Research 116 (2011) G00J07] ( JU 11). The net primary productivity ( NPP ) apparent sensitivity to climate variability and atmospheric CO 2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO 2 sensitivity of NPP is compared to the results from four Free‐Air CO 2 Enrichment ( FACE ) experiments. The simulated global net biome productivity ( NBP ) is compared with the residual land sink ( RLS ) of the global carbon budget from Friedlingstein et al . [ Nature Geoscience 3 (2010) 811] ( FR 10). We found that models produce a higher GPP (133 ± 15 Pg C yr −1 ) than JU 11 (118 ± 6 Pg C yr −1 ). In response to rising atmospheric CO 2 concentration, modeled NPP increases on average by 16% (5–20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO 2 than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr −1 is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr −1 ). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980–2009. Both model‐to‐model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is −3.0 ± 1.5 Pg C yr −1 °C −1 , within the uncertainty of what derived from RLS (−3.9 ± 1.1 Pg C yr −1 °C −1 ). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO 2 and climate, the agreement between modeled and observation‐based GPP and NBP can be fortuitous. Carbon–nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO 2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.
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A large and persistent carbon sink in the world’s forests
Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A., Phillips, O. L., Shvidenko, A., Lewis, S. L., Canadell, J. G., et al. (2011) · Science · doi:10.1126/science.1201609 · Cited by 8,458
Self-citationClimate–Carbon Cycle Feedback Analysis: Results from the C4MIP Model Intercomparison
Friedlingstein, P., Cox, P., Betts, R., Bopp, L., von Bloh, W., Brovkin, V., Cadule, P., Doney, S., Eby, M., Fung, I., et al. (2006) · Journal of Climate · doi:10.1175/jcli3800.1 · Cited by 2,902
Self-citationRecent patterns and mechanisms of carbon exchange by terrestrial ecosystems
Schimel, D. S., House, J. I., Hibbard, K. A., Bousquet, P., Ciais, P., Peylin, P., Braswell, B. H., Apps, M. J., Baker, D., Bondeau, A., et al. (2001) · Nature · doi:10.1038/35102500 · Cited by 1,379
Self-citationNet carbon dioxide losses of northern ecosystems in response to autumn warming
Piao, S., Ciais, P., Friedlingstein, P., Peylin, P., Reichstein, M., Luyssaert, S., Margolis, H., Fang, J., Barr, A., Chen, A., et al. (2008) · Nature · doi:10.1038/nature06444 · Cited by 1,157
Self-citationThe annual net flux of carbon to the atmosphere from changes in land use 1850–1990*
Houghton, R. A. (1999) · Tellus B: Chemical and Physical Meteorology · doi:10.3402/tellusb.v51i2.16288 · Cited by 852
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Self-citationIncreased atmospheric vapor pressure deficit reduces global vegetation growth
Yuan, W., Zheng, Y., Piao, S., Ciais, P., Lombardozzi, D., Wang, Y., Ryu, Y., Chen, G., Dong, W., Hu, Z., et al. (2019) · Science Advances · doi:10.1126/sciadv.aax1396 · Cited by 1,762
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Piao, S., Yin, G., Tan, J., Cheng, L., Huang, M., Li, Y., Liu, R., Mao, J., Myneni, R. B., Peng, S., et al. (2015) · Global Change Biology · doi:10.1111/gcb.12795 · Cited by 874
Self-citationAsynchronous carbon sink saturation in African and Amazonian tropical forests
Hubau, W., Lewis, S. L., Phillips, O. L., Affum-Baffoe, K., Beeckman, H., Cuní-Sanchez, A., Daniels, A. K., Ewango, C. E. N., Fauset, S., Mukinzi, J. M., et al. (2020) · Nature · doi:10.1038/s41586-020-2035-0 · Cited by 782
Metadata
- Authors
- Piao, S., Sitch, S., Ciais, P., Friedlingstein, P., Peylin, P., Wang, X., Ahlström, A., Anav, A., Canadell, J. G., Cong, N., Huntingford, C., Jung, M., Levis, S., Levy, P. E., Li, J., Lin, X., Lomas, M. R., Lu, M., Luo, Y., Ma, Y., Myneni, R. B., Poulter, B., Sun, Z., Wang, T., Viovy, N., Zaehle, S., & Zeng, N.
- Venue
- Global Change Biology
- Publisher
- Wiley
- Published
- 2013-04-03
- Volume
- 19
- Issue
- 7
- Pages
- 2117-2132
- ISSN
- 1354-1013 (ISSN-L)
- 1365-2486
- OpenAlex
- W2116673487
- Cited by
- 763
- References
- 5
- FWCI
- 46.84
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Piao, S., Sitch, S., Ciais, P., Friedlingstein, P., Peylin, P., Wang, X., Ahlström, A., Anav, A., Canadell, J. G., Cong, N., Huntingford, C., Jung, M., Levis, S., Levy, P. E., Li, J., Lin, X., Lomas, M. R., Lu, M., Luo, Y., . . . Zeng, N. (2013). Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO 2 trends. Global Change Biology. https://doi.org/10.1111/gcb.12187
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