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Partitioning uncertainty in ocean carbon uptake projections: Internal variability, emission scenario, and model structure
Author(s) -
Lovenduski Nicole S.,
McKinley Galen A.,
Fay Amanda R.,
Lindsay Keith,
Long Matthew C.
Publication year - 2016
Publication title -
global biogeochemical cycles
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.512
H-Index - 187
eISSN - 1944-9224
pISSN - 0886-6236
DOI - 10.1002/2016gb005426
Subject(s) - biome , environmental science , coupled model intercomparison project , climatology , flux (metallurgy) , projection (relational algebra) , climate model , earth system science , uncertainty analysis , atmospheric sciences , scale (ratio) , climate change , meteorology , geology , geography , mathematics , ecosystem , statistics , oceanography , ecology , materials science , cartography , algorithm , metallurgy , biology
We quantify and isolate the sources of projection uncertainty in annual‐mean sea‐air CO 2 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 CO 2 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 CO 2 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.