Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1088/1748-9326/aa6fd8 |
Climate data induced uncertainty in model-based estimations of terrestrial primary productivity | |
Wu, Zhendong1,2; Ahlstrom, Anders1,3; Smith, Benjamin1; Ardo, Jonas1; Eklundh, Lars1; Fensholt, Rasmus2; Lehsten, Veiko1,4 | |
2017-06-01 | |
发表期刊 | ENVIRONMENTAL RESEARCH LETTERS |
ISSN | 1748-9326 |
出版年 | 2017 |
卷号 | 12期号:6 |
文章类型 | Article |
语种 | 英语 |
国家 | Sweden; Denmark; USA; Switzerland |
英文摘要 | Model-based estimations of historical fluxes and pools of the terrestrial biosphere differ substantially. These differences arise not only from differences between models but also from differences in the environmental and climatic data used as input to the models. Here we investigate the role of uncertainties in historical climate data by performing simulations of terrestrial gross primary productivity (GPP) using a process-based dynamic vegetation model (LPJ-GUESS) forced by six different climate datasets. We find that the climate induced uncertainty, defined as the range among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 11 Pg C yr(-1) globally (9% of mean GPP). We also assessed a hypothetical maximum climate data induced uncertainty by combining climate variables from different datasets, which resulted in significantly larger uncertainties of 41 Pg C yr(-1) globally or 32% of mean GPP. The uncertainty is partitioned into components associated to the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (climate data range) and the apparent sensitivity of the modeled GPP to the driver (apparent model sensitivity). We find that LPJ-GUESS overestimates GPP compared to empirically based GPP data product in all land cover classes except for tropical forests. Tropical forests emerge as a disproportionate source of uncertainty in GPP estimation both in the simulations and empirical data products. The tropical forest uncertainty is most strongly associated with shortwave radiation and precipitation forcing, of which climate data range contributes higher to overall uncertainty than apparent model sensitivity to forcing. Globally, precipitation dominates the climate induced uncertainty over nearly half of the vegetated land area, which is mainly due to climate data range and less so due to the apparent model sensitivity. Overall, climate data ranges are found to contribute more to the climate induced uncertainty than apparent model sensitivity to forcing. Our study highlights the need to better constrain tropical climate, and demonstrates that uncertainty caused by climatic forcing data must be considered when comparing and evaluating carbon cycle model results and empirical datasets. |
英文关键词 | climate datasets GPP uncertainty LPJ-GUESS apparent model sensitivity climate data range global carbon cycle |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000413806800001 |
WOS关键词 | GLOBAL VEGETATION MODELS ; NET PRIMARY PRODUCTION ; AIR CO2 ENRICHMENT ; CARBON-CYCLE ; ECOSYSTEM CARBON ; LAND-COVER ; DYNAMICS ; BALANCE ; TEMPERATURE ; VARIABILITY |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/32092 |
专题 | 气候变化 |
作者单位 | 1.Lund Univ, Dept Phys Geog & Ecosyst Sci, Solvegatan 12, SE-22362 Lund, Sweden; 2.Univ Copenhagen, Dept Geosci & Nat Resource Management, DK-1350 Copenhagen, Denmark; 3.Stanford Univ, Sch Earth Energy & Environm Sci, Dept Earth Syst Sci, Stanford, CA 94305 USA; 4.Swiss Fed Inst Forest Snow & Landscape Res WSL, Zurcherstr 11, CH-8903 Birmensdorf, Switzerland |
推荐引用方式 GB/T 7714 | Wu, Zhendong,Ahlstrom, Anders,Smith, Benjamin,et al. Climate data induced uncertainty in model-based estimations of terrestrial primary productivity[J]. ENVIRONMENTAL RESEARCH LETTERS,2017,12(6). |
APA | Wu, Zhendong.,Ahlstrom, Anders.,Smith, Benjamin.,Ardo, Jonas.,Eklundh, Lars.,...&Lehsten, Veiko.(2017).Climate data induced uncertainty in model-based estimations of terrestrial primary productivity.ENVIRONMENTAL RESEARCH LETTERS,12(6). |
MLA | Wu, Zhendong,et al."Climate data induced uncertainty in model-based estimations of terrestrial primary productivity".ENVIRONMENTAL RESEARCH LETTERS 12.6(2017). |
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