Partitioning uncertainty in ocean carbon uptake projections: Internal variability, emission scenario, and model structure

被引:59
作者
Lovenduski, Nicole S. [1 ,2 ]
McKinley, Galen A. [3 ]
Fay, Amanda R. [3 ]
Lindsay, Keith [4 ]
Long, Matthew C. [4 ]
机构
[1] Univ Colorado, Dept Atmospher & Ocean Sci, Boulder, CO 80309 USA
[2] Univ Colorado, Inst Arctic & Alpine Res, Boulder, CO 80309 USA
[3] Univ Wisconsin, Dept Atmospher & Ocean Sci, Madison, WI USA
[4] Natl Ctr Atmospher Res, Climate & Global Dynam Lab, POB 3000, Boulder, CO 80307 USA
基金
美国国家科学基金会;
关键词
EARTH SYSTEM MODEL; NATURAL VARIABILITY; SPATIOTEMPORAL VARIABILITY; CO2; UPTAKE; TRENDS; DRIVERS; FLUXES; ACIDIFICATION; COMPONENTS; EMERGENCE;
D O I
10.1002/2016GB005426
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
We quantify and isolate the sources of projection uncertainty in annual-mean sea-air CO2 flux over the period 2006-2080 on global and regional scales using output from two sets of ensembles with the Community Earth System Model (CESM) and models participating in the 5th Coupled Model Intercomparison Project (CMIP5). For annual-mean, globally-integrated sea-air CO2 flux, uncertainty grows with prediction lead time and is primarily attributed to uncertainty in emission scenario. At the regional scale of the California Current System, we observe relatively high uncertainty that is nearly constant for all prediction lead times, and is dominated by internal climate variability and model structure, respectively in the CESM and CMIP5 model suites. Analysis of CO2 flux projections over 17 biogeographical biomes reveals a spatially heterogenous pattern of projection uncertainty. On the biome scale, uncertainty is driven by a combination of internal climate variability and model structure, with emission scenario emerging as the dominant source for long projection lead times in both modeling suites.
引用
收藏
页码:1276 / 1287
页数:12
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