Are Terrestrial Biosphere Models Fit for Simulating the Global Land Carbon Sink?

被引:43
|
作者
Seiler, Christian [1 ]
Melton, Joe R. [1 ]
Arora, Vivek K. [2 ]
Sitch, Stephen [3 ]
Friedlingstein, Pierre [4 ]
Anthoni, Peter [5 ]
Goll, Daniel [6 ]
Jain, Atul K. [7 ]
Joetzjer, Emilie [8 ,9 ]
Lienert, Sebastian [10 ,11 ]
Lombardozzi, Danica [12 ]
Luyssaert, Sebastiaan [13 ]
Nabel, Julia E. M. S. [14 ]
Tian, Hanqin [15 ]
Vuichard, Nicolas [16 ]
Walker, Anthony P. [17 ]
Yuan, Wenping [18 ]
Zaehle, Soenke [19 ]
机构
[1] Environm & Climate Change Canada, Climate Proc Sect, Victoria, BC, Canada
[2] Environm & Climate Change Canada, Canadian Ctr Climate Modelling & Anal, Victoria, BC, Canada
[3] Univ Exeter, Coll Life & Environm Sci, Exeter, Devon, England
[4] Univ Exeter, Coll Engn Math & Phys Sci, Exeter, Devon, England
[5] Karlsruhe Inst Technol, Inst Meteorol & Climate Res, Atmospher Environm Res, Garmisch Partenkirchen, Germany
[6] IPSL, Lab Sci Climat & Environm, Gif Sur Yvette, France
[7] Univ Illinois, Dept Atmospher Sci, 105 S Gregory Ave, Urbana, IL 61801 USA
[8] Univ Toulouse, CNRS, CNRM, Meteo France, Toulouse, France
[9] INRAE, UMR1434, SILVA, Champenoux, France
[10] Univ Bern, Phys Inst, Climate & Environm Phys, Bern, Switzerland
[11] Univ Bern, Oeschger Ctr Climate Change Res, Bern, Switzerland
[12] Natl Ctr Atmospher Res, Terr Sci Sect, Climate & Global Dynam, POB 3000, Boulder, CO 80307 USA
[13] Vrije Univ Amsterdam, Dept Ecol Sci, Fac Sci, Amsterdam, Netherlands
[14] Max Planck Inst Meteorol, Hamburg, Germany
[15] Auburn Univ, Sch Forestry & Wildlife Sci, Auburn, AL USA
[16] Univ Paris Saclay, CNRS, CEA, IPSL,UVSQ,Lab Sci Climat & Environm, Gif Sur Yvette, France
[17] Oak Ridge Natl Lab, Environm Sci Div, Climate Change Sci Inst, POB 2008, Oak Ridge, TN 37831 USA
[18] Sun Yat Sen Univ, Zhuhai Key Lab Dynam Urban Climate & Ecol, Guangdong Prov Key Lab Climate Change & Nat Disas, Sch Atmospher Sci, Zhuhai, Peoples R China
[19] Max Planck Inst Biogeochem, Jena, Germany
基金
欧盟地平线“2020”;
关键词
biogeochemical cycles; processes; and modeling; biosphere; atmosphere interactions; carbon cycling; SOURCE COMMUNITY SUCCESSOR; NET ECOSYSTEM EXCHANGE; SURFACE SCHEME CLASS; LEAF-AREA; CLASSIC V1.0; CO2; BIOMASS; ASSIMILATION; EMISSIONS; SATELLITE;
D O I
10.1029/2021MS002946
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The Global Carbon Project estimates that the terrestrial biosphere has absorbed about one-third of anthropogenic CO2 emissions during the 1959-2019 period. This sink-estimate is produced by an ensemble of terrestrial biosphere models and is consistent with the land uptake inferred from the residual of emissions and ocean uptake. The purpose of our study is to understand how well terrestrial biosphere models reproduce the processes that drive the terrestrial carbon sink. One challenge is to decide what level of agreement between model output and observation-based reference data is adequate considering that reference data are prone to uncertainties. To define such a level of agreement, we compute benchmark scores that quantify the similarity between independently derived reference data sets using multiple statistical metrics. Models are considered to perform well if their model scores reach benchmark scores. Our results show that reference data can differ considerably, causing benchmark scores to be low. Model scores are often of similar magnitude as benchmark scores, implying that model performance is reasonable given how different reference data are. While model performance is encouraging, ample potential for improvements remains, including a reduction in a positive leaf area index bias, improved representations of processes that govern soil organic carbon in high latitudes, and an assessment of causes that drive the inter-model spread of gross primary productivity in boreal regions and humid tropics. The success of future model development will increasingly depend on our capacity to reduce and account for observational uncertainties.
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页数:36
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