Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)
AffiliationUniv Arizona, Dept Hydrol & Atmospher Sci
MetadataShow full item record
PublisherIOP PUBLISHING LTD
CitationInfluence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4) 2016, 11 (12):124029 Environmental Research Letters
JournalEnvironmental Research Letters
Rights© 2016 IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence.
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AbstractLand carbon sensitivity to atmospheric CO2 concentration (bL) and climate warming (gL) is a crucial part of carbon-climate feedbacks that affect the magnitude of future warming. Although these sensitivities can be estimated by earth system models, their dependence on model representation of land carbon dynamics and the inherent model assumptions has rarely been investigated. Using the widely used Community Land Model version 4 as an example, we examine how bL and gL vary with prescribed versus dynamic vegetation covers. Both sensitivities are found to be larger with dynamic compared to prescribed vegetation on decadal timescale in the late twentieth century, with a more robust difference in gL. The latter is a result of dynamic vegetation model deficiencies in representing the competitions between deciduous versus evergreen trees and tree versus grass over the tropics and subtropics. The biased vegetation cover changes the regional characteristics of carbon-nitrogen cycles such that plant productivity responds less strongly to the enhancement of nitrogen mineralization with warming, so more carbon is lost to the atmosphere with rising temperature. The result calls for systematic evaluations of land carbon sensitivities with varying assumptions for land cover representations to help prioritize development effort and constrain uncertainties in carbon-climate feedbacks.
NoteOpen access journal
VersionFinal published version
SponsorsNSF; DOE; NSF [AGS-0944101]; DOE [DE-SC0006693, DE-AC05-76RL01830]; DOE Office of Science, Regional and Global Climate Modeling Program; [NSFC41305096]
Except where otherwise noted, this item's license is described as © 2016 IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence.