The use of radiocarbon &amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;gt;C to constrain carbon dynamics in the soil module of the land surface model ORCHIDEE (SVN r5165)

Tifafi, Marwa; Camino‐Serrano, Marta; Hatté, Christine; Morrás, Héctor José María; Moretti, Lucas; Barbaro, Sebastián; Cornu, Sophie; Guenet, Bertrand

doi:10.5194/gmd-11-4711-2018

Cited by 9 publications

(15 citation statements)

References 42 publications

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“…The above-noted discrepancies between the simulation and the observation highlight both the need for more peat core data collected with more rigorous sampling methodologies and the need to improve the model. In parallel with this study, 14 C dynamics in the soil have been incorporated into the ORCHIDEE-SOM model (Tifafi et al, 2018), which may give us an opportunity to compare simulated 14 C age-depth profiles with dated peat C profiles in the future after being merged with our model.…”

Section: Vertical Profiles Of Peatland Soil Organic Carbonmentioning

confidence: 99%

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Qiu¹

2019

Preprint

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The importance of northern peatlands in the global carbon cycle has been recognized, especially for long-term changes. Yet, the complex interactions between climate and peatland hydrology, carbon storage, and area dynamics make it challenging to represent these systems in land surface models. This study describes how peatlands are included as an independent sub-grid hydrological soil unit (HSU) in the ORCHIDEE-MICT land surface model. The peatland soil column in this tile is characterized by multilayered vertical water and carbon transport and peat-specific hydrological properties. The cost-efficient version of TOPMODEL and the scheme of peatland initiation and development from the DYPTOP model are implemented and adjusted to simulate spatial and temporal dynamics of peatland. The model is tested across a range of northern peatland sites and for gridded simulations over the Northern Hemisphere ( > 30 • N). Simulated northern peatland area (3.9 million km 2 ), peat carbon stock (463 Pg C), and peat depth are generally consistent with observed estimates of peatland area (3.4-4.0 million km 2 ), peat carbon (270-540 Pg C), and data compilations of peat core depths. Our results show that both net primary production (NPP) and heterotrophic respiration (HR) of northern peatlands increased over the past century in response to CO 2 and climate change. NPP increased more rapidly than HR, and thus net ecosystem production (NEP) exhibited a positive trend, contributing a cumulative carbon storage of 11.13 Pg C since 1901, most of it being realized after the 1950s.

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Section: Vertical Profiles Of Peatland Soil Organic Carbonmentioning

confidence: 99%

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Qiu¹

2019

Preprint

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“…Measurements of radiocarbon offer great potential to constrain temporal dynamics of the land carbon cycle in ESMs as well as to assess their performance. However, to date, such comparisons have been limited to a small number of models that simulate C isotopes (e.g., Chen et al, ; Koven et al, ; Tifafi et al, ), as the majority of models do not explicitly represent isotope dynamics. The current coupled climate‐carbon cycle model intercomparison project (C4MIP) of the Coupled Model Inter‐comparison Project Phase 6 (CMIP6) requests model participants to explicitly model radiocarbon and include the corresponding output from the major land and ocean model compartments (Graven et al, ; Jones et al, ).…”

Section: Introductionmentioning

confidence: 99%

Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From C Dynamics

Metzler

Zhu

Riley

et al. 2020

J Adv Model Earth Syst

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Radiocarbon ( 14 C) 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 12 C 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 14 C 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 12 C, and 14 C 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 12 C and 14 C predictions, demonstrating the potential to use this approach in CMIP6 and other model simulations that do not explicitly represent 14 C.Plain Language Summary Models representing ecosystem carbon dynamics are generally complex and difficult to analyze. Comparing different models with different structures is even more challenging due to the variety of processes represented in the models. However, it is possible to use the numerical output of models to reconstruct the original structure using a common mathematical framework. In this manuscript, we demonstrate this approach and apply it to compute radiocarbon dynamics of a land carbon model. The proposed approach can reconstruct the carbon and radiocarbon dynamics of the original model very accurately and can be used to study system-level dynamics of complex contrasting models.

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“…In calibrating the ORCHIDEE-SOM model, Guenet et al (2013) found that including vertical SOC transport was important for accurately simulating the changes in SOC concentrations of bare fallow sites. Using a similar version of ORCHIDEE-SOM model, Tifafi, Camino-Serrano et al (2018) found that varying the SOC diffusion coefficient with soil depth improved the simulated SOC concentration and 14 C profiles. However, Huang et al (2018) found that the carbon input was more important than vertical transport in simulating vertical SOC profiles using a different version of ORCHIDEE, ORCHIDEE-MICT.…”

mentioning

confidence: 99%

“…Only a limited number (probably <3) of vertically resolved soil carbon models with nonlinear kinetics for soil carbon decomposition have been developed, such as the model COMISSION by Ahrens et al (2015), which was recently improved by including additional processes and nutrient cycles (Yu et al, 2020). Most of these models were evaluated using the data from a limited number of sites (<15) (see Koven et al, 2013;Tifafi, Camino-Serrano et al, 2018). Given the usually poor performance of soil carbon models (Todd-Brown et al, 2013), which likely leads to diverging responses of soil carbon to future climate change predicted by ESMs (Wieder et al, 2013), it is necessary to calibrate these models for different ecosystem types and across a wide range of environmental conditions before applying them globally.…”

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confidence: 99%

Microbial Activity and Root Carbon Inputs Are More Important than Soil Carbon Diffusion in Simulating Soil Carbon Profiles

et al. 2021

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Soils are the largest carbon (C) pool in the terrestrial biosphere, storing about 700 Pg C in the top 0.3 m (Batjes, 1996), or 2,300 Pg C in the top 3 m soil (Jobbágy & Jackson, 2000;Tifafi, Guenet et al. 2018). The amount of carbon below 0.3 m soil is about twice the amount, much older and stable than the carbon in the top 0.3 m soil (Fontaine et al., 2007). A recent soil warming study by Qin et al. (2019) found that the response of soil carbon to warming was dominated by soil microbial activities in the surface soil layer (0-0.3 m), but was codominated by low microbial abundance and strong aggregate protection in the deep (>0.3 m) soil layer. Therefore, deep soil carbon was less sensitive to warming and may function as a carbon sink despite global warming. This is also supported by the analysis of Baldesdent et al. (2018) who found that the soil at the depths between 0.3 and 1 m accounted for about 19% of the total soil carbon accumulated over the last five decades.There has been renewed interest within the global modeling community in representing the vertical variation of soil carbon for several reasons: (1) it enables direct comparisons of the simulations with observations of both soil carbon and carbon isotopes ( 13 C and 14 C) (see Elliott et al., 1996); (2) soil carbon in deeper layers is usually older and more stable than the soil carbon in surface layers (Fontaine et al., 2007;Rossel et al., 2019), and the sensitivity to warming is different between stable soil carbon and active soil carbon (Hicks Pries et al., 2017;Qin et al., 2019); and (3) most Earth system models (ESMs) significantly underestimated soil carbon age by a factor of more than 6, and overestimated the soil carbon sequestration potential by a factor of 2 (He et al., 2016;Shi et al., 2020).

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The use of radiocarbon <sup>14</sup>C to constrain carbon dynamics in the soil module of the land surface model ORCHIDEE (SVN r5165)

Cited by 9 publications

References 42 publications

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Mathematical Reconstruction of Land Carbon Models From Their Numerical Output: Computing Soil Radiocarbon From C Dynamics

Microbial Activity and Root Carbon Inputs Are More Important than Soil Carbon Diffusion in Simulating Soil Carbon Profiles

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