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Causes of slowing-down seasonal CO2 amplitude at Mauna Loa.

Kai WangYilong WangXuhui WangYue HeXiangyi LiRalph F KeelingPhilippe CiaisMartin HeimannShu-Shi PengFrédéric ChevallierPierre FriedlingsteinStephen SitchWolfgang BuermannVivek K AroraVanessa HaverdAtul K JainEtsushi KatoSebastian LienertDanica L LombardozziJulia E M S NabelBenjamin PoulterNicolas VuichardAndy WiltshireNing ZengDan ZhuShilong Piao
Published in: Global change biology (2020)
Changing amplitude of the seasonal cycle of atmospheric CO2 (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 CO2 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 CO2 fertilization. This challenges the view that CO2 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 CO2 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.
Keyphrases
  • climate change
  • particulate matter
  • human health
  • risk assessment
  • air pollution
  • functional connectivity
  • convolutional neural network