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Causes of slowing‐down seasonal CO 2 amplitude at Mauna Loa
Author(s) -
Wang Kai,
Wang Yilong,
Wang Xuhui,
He Yue,
Li Xiangyi,
Keeling Ralph F.,
Ciais Philippe,
Heimann Martin,
Peng Shushi,
Chevallier Frédéric,
Friedlingstein Pierre,
Sitch Stephen,
Buermann Wolfgang,
Arora Vivek K.,
Haverd Vanessa,
Jain Atul K.,
Kato Etsushi,
Lienert Sebastian,
Lombardozzi Danica,
Nabel Julia E. M. S.,
Poulter Benjamin,
Vuichard Nicolas,
Wiltshire Andy,
Zeng Ning,
Zhu Dan,
Piao Shilong
Publication year - 2020
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/gcb.15162
Subject(s) - biome , northern hemisphere , atmospheric sciences , environmental science , climate change , climatology , carbon cycle , physics , ecology , ecosystem , biology , geology
Changing amplitude of the seasonal cycle of atmospheric CO 2 (SCA) in the northern hemisphere is an emerging carbon cycle property. Mauna Loa (MLO) station (20°N, 156°W), which has the longest continuous northern hemisphere CO 2 record, shows an increasing SCA before the 1980s ( p < .01), followed by no significant change thereafter. We analyzed the potential driving factors of SCA slowing‐down, with an ensemble of dynamic global vegetation models (DGVMs) coupled with an atmospheric transport model. We found that slowing‐down of SCA at MLO is primarily explained by response of net biome productivity (NBP) to climate change, and by changes in atmospheric circulations. Through NBP, climate change increases SCA at MLO before the 1980s and decreases it afterwards. The effect of climate change on the slowing‐down of SCA at MLO is mainly exerted by intensified drought stress acting to offset the acceleration driven by CO 2 fertilization. This challenges the view that CO 2 fertilization is the dominant cause of emergent SCA trends at northern sites south of 40°N. The contribution of agricultural intensification on the deceleration of SCA at MLO was elusive according to land–atmosphere CO 2 flux estimated by DGVMs and atmospheric inversions. Our results also show the necessity to adequately account for changing circulation patterns in understanding carbon cycle dynamics observed from atmospheric observations and in using these observations to benchmark DGVMs.