Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From 12C Dynamics
Abstract Radiocarbon (14C) is a powerful tracer of the global carbon cycle that is commonly used to assess carbon cycling rates in various Earth system reservoirs and as a benchmark to assess model performance. Therefore, it has been recommended that Earth System Models (ESMs) participating in the C...
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doaj-3f158c6cafb146d191106297604d95552021-04-08T18:46:33ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662020-01-01121n/an/a10.1029/2019MS001776Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From 12C DynamicsHolger Metzler0Qing Zhu1William Riley2Alison Hoyt3Markus Müller4Carlos A. Sierra5Max Planck Institute for Biogeochemistry Jena GermanyClimate and Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA USAClimate and Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA USAMax Planck Institute for Biogeochemistry Jena GermanyMax Planck Institute for Biogeochemistry Jena GermanyMax Planck Institute for Biogeochemistry Jena GermanyAbstract Radiocarbon (14C) is a powerful tracer of the global carbon cycle that is commonly used to assess carbon cycling rates in various Earth system reservoirs and as a benchmark to assess model performance. Therefore, it has been recommended that Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 report predicted radiocarbon values for relevant carbon pools. However, a detailed representation of radiocarbon dynamics may be an impractical burden on model developers. Here, we present an alternative approach to compute radiocarbon values from the numerical output of an ESM that does not explicitly represent these dynamics. The approach requires computed 12C stocks and fluxes among all carbon pools for a particular simulation of the model. From this output, a time‐dependent linear compartmental system is computed with its respective state‐transition matrix. Using transient atmospheric 14C values as inputs, the state‐transition matrix is then applied to compute radiocarbon values for each pool, the average value for the entire system, and component fluxes. We demonstrate the approach with ELMv1‐ECA, the land component of an ESM model that explicitly represents 12C, and 14C in 7 soil pools and 10 vertical layers. Results from our proposed method are highly accurate (relative error <0.01%) compared with the ELMv1‐ECA 12C and 14C predictions, demonstrating the potential to use this approach in CMIP6 and other model simulations that do not explicitly represent 14C.https://doi.org/10.1029/2019MS001776carbon cycle modelscompartmental systemsradiocarbonmodel diagnosticsdynamical systemsEarth system models |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Holger Metzler Qing Zhu William Riley Alison Hoyt Markus Müller Carlos A. Sierra |
spellingShingle |
Holger Metzler Qing Zhu William Riley Alison Hoyt Markus Müller Carlos A. Sierra Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From 12C Dynamics Journal of Advances in Modeling Earth Systems carbon cycle models compartmental systems radiocarbon model diagnostics dynamical systems Earth system models |
author_facet |
Holger Metzler Qing Zhu William Riley Alison Hoyt Markus Müller Carlos A. Sierra |
author_sort |
Holger Metzler |
title |
Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From 12C Dynamics |
title_short |
Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From 12C Dynamics |
title_full |
Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From 12C Dynamics |
title_fullStr |
Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From 12C Dynamics |
title_full_unstemmed |
Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From 12C Dynamics |
title_sort |
mathematical reconstruction of land carbon models from their numerical output: computing soil radiocarbon from 12c dynamics |
publisher |
American Geophysical Union (AGU) |
series |
Journal of Advances in Modeling Earth Systems |
issn |
1942-2466 |
publishDate |
2020-01-01 |
description |
Abstract Radiocarbon (14C) is a powerful tracer of the global carbon cycle that is commonly used to assess carbon cycling rates in various Earth system reservoirs and as a benchmark to assess model performance. Therefore, it has been recommended that Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 report predicted radiocarbon values for relevant carbon pools. However, a detailed representation of radiocarbon dynamics may be an impractical burden on model developers. Here, we present an alternative approach to compute radiocarbon values from the numerical output of an ESM that does not explicitly represent these dynamics. The approach requires computed 12C stocks and fluxes among all carbon pools for a particular simulation of the model. From this output, a time‐dependent linear compartmental system is computed with its respective state‐transition matrix. Using transient atmospheric 14C values as inputs, the state‐transition matrix is then applied to compute radiocarbon values for each pool, the average value for the entire system, and component fluxes. We demonstrate the approach with ELMv1‐ECA, the land component of an ESM model that explicitly represents 12C, and 14C in 7 soil pools and 10 vertical layers. Results from our proposed method are highly accurate (relative error <0.01%) compared with the ELMv1‐ECA 12C and 14C predictions, demonstrating the potential to use this approach in CMIP6 and other model simulations that do not explicitly represent 14C. |
topic |
carbon cycle models compartmental systems radiocarbon model diagnostics dynamical systems Earth system models |
url |
https://doi.org/10.1029/2019MS001776 |
work_keys_str_mv |
AT holgermetzler mathematicalreconstructionoflandcarbonmodelsfromtheirnumericaloutputcomputingsoilradiocarbonfrom12cdynamics AT qingzhu mathematicalreconstructionoflandcarbonmodelsfromtheirnumericaloutputcomputingsoilradiocarbonfrom12cdynamics AT williamriley mathematicalreconstructionoflandcarbonmodelsfromtheirnumericaloutputcomputingsoilradiocarbonfrom12cdynamics AT alisonhoyt mathematicalreconstructionoflandcarbonmodelsfromtheirnumericaloutputcomputingsoilradiocarbonfrom12cdynamics AT markusmuller mathematicalreconstructionoflandcarbonmodelsfromtheirnumericaloutputcomputingsoilradiocarbonfrom12cdynamics AT carlosasierra mathematicalreconstructionoflandcarbonmodelsfromtheirnumericaloutputcomputingsoilradiocarbonfrom12cdynamics |
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1721533919711461376 |