Comparison With Global Soil Radiocarbon Observations Indicates Needed Carbon Cycle Improvements in the E3SM Land Model
Abstract
We evaluated global soil organic carbon (SOC) stocks and turnover time predictions from a global land model (ELMv1-ECA) integrated in an Earth System Model (E3SM) by comparing them with observed soil bulk and Δ14C values around the world. We analyzed observed and simulated SOC stocks and Δ14C values using machine learning methods at the Earth System Model grid cell scale (~200 km). In grid cells with sufficient observations, the model provided reasonable estimates of soil carbon stocks across soil depth and Δ14C values near the surface but underestimated Δ14C at depth. Among many explanatory variables, soil albedo index, soil order, plant function type, air temperature, and SOC content were major factors affecting predicted SOC Δ14C values. The influences of soil albedo index, soil order, and air temperature were primarily important in the shallow subsurface (≤30 cm). We also performed sensitivity studies using different vertical root distributions and decomposition turnover times and compared to observed SOC stock and Δ14C profiles. The analyses support the role of vegetation in affecting soil carbon turnover, particularly in deep soil, possibly through supplying fresh carbon and degrading physical-chemical protection of SOC via root activities. Allowing for grid cell-specific rooting and decomposition rates substantially reduced discrepancies between observedmore »
- Authors:
-
[1];
[1];
[1];
[2];
[2];
[2]
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Climate and Ecosystem Sciences Div.
- Univ. of California, Irvine, CA (United States). Dept. of Earth System Sciences
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1572816
- Alternate Identifier(s):
- OSTI ID: 1510558
- Grant/Contract Number:
- AC02-05CH11231; AC02‐05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Geophysical Research. Biogeosciences
- Additional Journal Information:
- Journal Volume: 124; Journal Issue: 5; Journal ID: ISSN 2169-8953
- Publisher:
- American Geophysical Union
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 58 GEOSCIENCES; Earth System Models; advanced land modeling; soil organic carbon; radiocarbon; statistical analysis; machine learning
Citation Formats
Chen, Jinsong, Zhu, Qing, Riley, William J., He, Yujie, Randerson, James T., and Trumbore, Susan. Comparison With Global Soil Radiocarbon Observations Indicates Needed Carbon Cycle Improvements in the E3SM Land Model. United States: N. p., 2019.
Web. doi:10.1029/2018jg004795.
Chen, Jinsong, Zhu, Qing, Riley, William J., He, Yujie, Randerson, James T., & Trumbore, Susan. Comparison With Global Soil Radiocarbon Observations Indicates Needed Carbon Cycle Improvements in the E3SM Land Model. United States. https://doi.org/10.1029/2018jg004795
Chen, Jinsong, Zhu, Qing, Riley, William J., He, Yujie, Randerson, James T., and Trumbore, Susan. Mon .
"Comparison With Global Soil Radiocarbon Observations Indicates Needed Carbon Cycle Improvements in the E3SM Land Model". United States. https://doi.org/10.1029/2018jg004795. https://www.osti.gov/servlets/purl/1572816.
@article{osti_1572816,
title = {Comparison With Global Soil Radiocarbon Observations Indicates Needed Carbon Cycle Improvements in the E3SM Land Model},
author = {Chen, Jinsong and Zhu, Qing and Riley, William J. and He, Yujie and Randerson, James T. and Trumbore, Susan},
abstractNote = {We evaluated global soil organic carbon (SOC) stocks and turnover time predictions from a global land model (ELMv1-ECA) integrated in an Earth System Model (E3SM) by comparing them with observed soil bulk and Δ14C values around the world. We analyzed observed and simulated SOC stocks and Δ14C values using machine learning methods at the Earth System Model grid cell scale (~200 km). In grid cells with sufficient observations, the model provided reasonable estimates of soil carbon stocks across soil depth and Δ14C values near the surface but underestimated Δ14C at depth. Among many explanatory variables, soil albedo index, soil order, plant function type, air temperature, and SOC content were major factors affecting predicted SOC Δ14C values. The influences of soil albedo index, soil order, and air temperature were primarily important in the shallow subsurface (≤30 cm). We also performed sensitivity studies using different vertical root distributions and decomposition turnover times and compared to observed SOC stock and Δ14C profiles. The analyses support the role of vegetation in affecting soil carbon turnover, particularly in deep soil, possibly through supplying fresh carbon and degrading physical-chemical protection of SOC via root activities. Allowing for grid cell-specific rooting and decomposition rates substantially reduced discrepancies between observed and predicted Δ14C values and SOC content. Furthermore, our results highlight the need for more explicit representation of roots, microbes, and soil physical protection in land models.},
doi = {10.1029/2018jg004795},
journal = {Journal of Geophysical Research. Biogeosciences},
number = 5,
volume = 124,
place = {United States},
year = {Mon Apr 08 00:00:00 EDT 2019},
month = {Mon Apr 08 00:00:00 EDT 2019}
}
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