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  • 标题:Soil Respiration Phenology Improves Modeled Phase of Terrestrial net Ecosystem Exchange in Northern Hemisphere
  • 本地全文:下载
  • 作者:K. Arthur Endsley ; John S. Kimball ; Rolf H. Reichle
  • 期刊名称:Journal of Advances in Modeling Earth Systems
  • 电子版ISSN:1942-2466
  • 出版年度:2022
  • 卷号:14
  • 期号:2
  • 页码:n/a-n/a
  • DOI:10.1029/2021MS002804
  • 语种:English
  • 出版社:John Wiley & Sons, Ltd.
  • 摘要:Abstract In the northern hemisphere, terrestrial ecosystems transition from net sources of CO2 to the atmosphere in winter to net ecosystem carbon sinks during spring. The timing (or phase) of this transition, determined by the balance between ecosystem respiration (RECO) and primary production, is key to estimating the amplitude of the terrestrial carbon sink. We diagnose an apparent phase bias in the RECO and net ecosystem exchange (NEE) seasonal cycles estimated by the terrestrial carbon flux (TCF) model framework and investigate its link to soil respiration mechanisms. Satellite observations of vegetation canopy conditions, surface meteorology, and soil moisture from the NASA SMAP Level 4 Soil Moisture product are used to model a daily carbon budget for a global network of eddy covariance flux towers. Proposed modifications to TCF include: the inhibition of foliar respiration in the light (the Kok effect); a seasonally varying litterfall phenology; an O2 diffusion limitation on heterotrophic respiration (RH); and a vertically resolved soil decomposition model. We find that RECO phase bias can result from bias in RECO magnitude and that mechanisms which reduce northern spring RECO, like substrate and O2 diffusion limitations, can mitigate the phase bias. A vertically resolved soil decomposition model mitigates this bias by temporally segmenting and lagging RH. Applying these model enhancements at continuous soil respiration (COSORE) sites verifies their improvement of RECO and NEE skill compared to in situ observations (up to ΔRMSE = −0.76 g C m−2 d−1). Ultimately, these mechanisms can improve prior estimates of NEE for atmospheric inversion studies.
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