Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends

被引:635
|
作者
Piao, Shilong [1 ,2 ]
Sitch, Stephen [3 ]
Ciais, Philippe [4 ]
Friedlingstein, Pierre [3 ]
Peylin, Philippe [4 ]
Wang, Xuhui [1 ]
Ahlstrom, Anders [5 ]
Anav, Alessandro [3 ]
Canadell, Josep G. [6 ]
Cong, Nan [1 ]
Huntingford, Chris [7 ]
Jung, Martin [8 ]
Levis, Sam [9 ]
Levy, Peter E. [10 ]
Li, Junsheng [11 ]
Lin, Xin [11 ,12 ]
Lomas, Mark R. [13 ]
Lu, Meng [14 ]
Luo, Yiqi [15 ]
Ma, Yuecun [1 ]
Myneni, Ranga B. [16 ]
Poulter, Ben [4 ]
Sun, Zhenzhong [1 ]
Wang, Tao [4 ]
Viovy, Nicolas [4 ]
Zaehle, Soenke [8 ]
Zeng, Ning [17 ]
机构
[1] Peking Univ, Coll Urban & Environm Sci, Sinofrench Inst Earth Syst Sci, Beijing 100871, Peoples R China
[2] Chinese Acad Sci, Inst Tibetan Plateau Res, Beijing 100085, Peoples R China
[3] Univ Exeter, Coll Engn Comp & Math, Exeter EX4 4QF, Devon, England
[4] CEA CNRS UVSQ, Lab Sci Climat & Environm, F-91191 Gif Sur Yvette, France
[5] Lund Univ, Dept Phys Geog & Ecosyst Sci, SE-22362 Lund, Sweden
[6] CSIRO, Global Carbon Project, Marine & Atmospher Res, Canberra, ACT, Australia
[7] Ctr Ecol & Hydrol, Wallingford OX10 8BB, Oxon, England
[8] Max Planck Inst Biogeochem, D-07701 Jena, Germany
[9] Natl Ctr Atmospher Res, Boulder, CO 80301 USA
[10] Ctr Ecol & Hydrol, Penicuik EH26 0QB, Midlothian, Scotland
[11] Chinese Res Inst Environm Sci, State Key Lab Environm Criteria & Risk Assessment, Beijing 100012, Peoples R China
[12] Beijing Normal Univ, Coll Water Sci, Beijing 100875, Peoples R China
[13] Univ Sheffield, Dept Anim & Plant Sci, Sheffield S10 2TN, S Yorkshire, England
[14] Fudan Univ, Inst Biodivers Sci, Shanghai 200433, Peoples R China
[15] Univ Oklahoma, Dept Microbiol & Plant Biol, Norman, OK 73019 USA
[16] Boston Univ, Dept Geog & Environm, Boston, MA 02215 USA
[17] Univ Maryland, Dept Atmospher & Ocean Sci, College Pk, MD 20740 USA
基金
中国国家自然科学基金;
关键词
carbon cycle; CO2; fertilization; model evaluation; precipitation sensitivity; temperature sensitivity; NITROGEN INTERACTIONS; LAND-USE; INTERANNUAL VARIABILITY; PRIMARY PRODUCTIVITY; VEGETATION DYNAMICS; PLANT GEOGRAPHY; ECOSYSTEM; FOREST; FEEDBACKS; DROUGHT;
D O I
10.1111/gcb.12187
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
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 etal. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO2 sensitivity of NPP is compared to the results from four Free-Air CO2 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 etal. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 +/- 15Pg Cyr-1) than JU11 (118 +/- 6Pg Cyr-1). In response to rising atmospheric CO2 concentration, modeled NPP increases on average by 16% (5-20%) per 100ppm, a slightly larger apparent sensitivity of NPP to CO2 than that measured at the FACE experiment locations (13% per 100ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 +/- 0.8Pg Cyr-1 is remarkably close to the mean value of RLS (2.1 +/- 1.2 Pg Cyr-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 +/- 1.5Pg Cyr-1 degrees C-1, within the uncertainty of what derived from RLS (-3.9 +/- 1.1Pg Cyr-1 degrees 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 CO2 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 CO2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.
引用
收藏
页码:2117 / 2132
页数:16
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