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Title: Role of CO2, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: A multimodel analysis

Journal Article · · Biogeosciences (Online)
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [9];  [10];  [3];  [4];  [6];  [11];  [12];  [13];  [14]
  1. Univ. of Maryland, College Park, MD (United States). Dept. of Atmospheric and Oceanic Science; Potsdam Inst. for Climate Impact Research, Telegraphenberg, Potsdam (Germany)
  2. Univ. of Maryland, College Park, MD (United States). Dept. of Atmospheric and Oceanic Science; Univ. of Maryland, College Park, MD (United States). Earth System Science Interdisciplinary Center
  3. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Joint Global Change Research Inst.
  4. Univ. of Exeter (United Kingdom). College of Engineering Mathematics and Physical Sciences
  5. National Inst. for Environmental Studies, Tsukuba (Japan). Center for Global Environmental Research
  6. Univ. of Illinois, Urbana, IL (United States). Dept. of Atmospheric Sciences
  7. Univ. of Maryland, College Park, MD (United States). Dept. of Atmospheric and Oceanic Science
  8. Inst. of Applied Energy (IAE), Tokyo (Japan). Global Environment Program Research & Development Division
  9. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Earth Sciences Division
  10. Montana State Univ., Bozeman, MT (United States). Inst. on Ecosystems and Department of Ecology
  11. Univ. of Bern (Switzerland). Climate and Environmental Physics, Physics Inst.
  12. Commissariat a l'Energie Atomique et aux Energies Alternatives (CEA CNRS UVSQ), Gif-sur-Yvette (France). Laboratoire des Sciences du Climat et de l'Environnement
  13. Met Office, Exeter (United States). Hadley Centre
  14. Max Planck Society, Jena (Germany). Max Planck Inst. for Biogeochemistry, Biogeochemical Integration Dept.
+ Show Author Affiliations

We examined the net terrestrial carbon flux to the atmosphere (FTA) simulated by nine models from the TRENDY dynamic global vegetation model project during 1961–2012 for its seasonal cycle and amplitude trend. While some models exhibit similar phase and amplitude compared to atmospheric inversions, with spring drawdown and autumn rebound, others tend to rebound early in summer. The model ensemble mean underestimates the magnitude of the seasonal cycle by 40 % compared to atmospheric inversions. Global FTA amplitude increase (19 ± 8 %) and its decadal variability from the model ensemble are generally consistent with constraints from surface atmosphere observations. However, models disagree on attribution of this long-term amplitude increase, with factorial experiments attributing 83 ± 56 %, −3 ± 74 % and 20 ± 30 % to rising CO2, climate change and land use/cover change, respectively. Seven out of the nine models suggest that CO2 fertilization is a stronger control — with the notable exception of VEGAS, which attributes approximately equally to the three factors. Generally, all models display an enhanced seasonality over the boreal region in response to high-latitude warming, but a negative climate contribution from part of the Northern Hemisphere temperate region, and the net result is a divergence over climate change effect. Six of the nine models show land use/cover change amplifies the seasonal cycle of global FTA: some are due to forest regrowth while others are caused by crop expansion or agricultural intensification, as revealed by their divergent spatial patterns. We also discovered a moderate cross-model correlation between FTA amplitude increase and increase in land carbon sink (R2 = 0.61). Our results suggest that models can show similar results in some benchmarks with different underlying mechanisms, therefore the spatial traits of CO2 fertilization, climate change, and land use/cover changes are crucial in determining the right mechanisms in seasonal carbon cycle change as well as mean sink change.

Research Organization:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC02-05CH11231; AC05-76RL01830
OSTI ID:
1377492
Alternate ID(s):
OSTI ID: 1406826
Report Number(s):
PNNL-SA-118615; ark:/13030/qt9tq4z262
Journal Information:
Biogeosciences (Online), Vol. 13, Issue 17; ISSN 1726-4189
Publisher:
European Geosciences UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 21 works
Citation information provided by
Web of Science

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Cited By (2)

Comprehensive Evaluation of Machine Learning Techniques for Estimating the Responses of Carbon Fluxes to Climatic Forces in Different Terrestrial Ecosystems journal February 2018
Evaluation and uncertainty analysis of regional-scale CLM4.5 net carbon flux estimates journal January 2018

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