Simulating soil organic carbon in yedoma deposits during the Last Glacial Maximum in a land surface model

Zhu, Dan; Peng, Shushi; Ciais, Philippe; Zech, Roland; Krinner, Gerhard; Zimov, S. A.; Grosse, Guido

doi:10.1002/2016gl068874

Cited by 26 publications

(44 citation statements)

References 49 publications

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“…21), but generate lower values than those from SoilGrids in BONA and BOAS. ORCHIDEE-MICT tends to underestimate SOC density in deep soils below ∼ 1 m. This underestimation is maybe because the model does not include the sedimentation of soils that characterized peat formation during the Holocene or simulation of loess carbon or yedoma deposits during the last glacial period Zhu et al, 2016). Further, spin-up was performed with the coarse approximating assumption that Holocene climate is equal to the recent climate.…”

Section: Soil Carbonmentioning

confidence: 99%

“…Decomposition of soil carbon is calculated at each layer as a function of soil temperature, moisture, and texture Zhu et al, 2016). Vertical mixing of soil carbon due to cryoturbation (mixing of soil layers induced by repeated freeze-thaw cycles) and bioturbation are accounted for by adding a diffusion term in the soil carbon equation:…”

Section: Soil Carbon Discretizationmentioning

confidence: 99%

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ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation

et al. 2018

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Abstract. The high-latitude regions of the Northern Hemisphere are a nexus for the interaction between land surface physical properties and their exchange of carbon and energy with the atmosphere. At these latitudes, two carbon pools of planetary significance -those of the permanently frozen soils (permafrost), and of the great expanse of boreal forestare vulnerable to destabilization in the face of currently observed climatic warming, the speed and intensity of which are expected to increase with time. Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes. To this end, this study lays out relevant new parameterizations in the ORCHIDEE-MICT land surface model. These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO 2 fluxes, in addition to a recently developed fire module. Outputs from ORCHIDEE-MICT, when forced by two climate input datasets, are extensively evaluated against (i) temperature gradients between the atmosphere and deep soils, (ii) the hydrological components comprising the water balance of the largest highlatitude basins, and (iii) CO 2 flux and carbon stock observations. The model performance is good with respect to empirical data, despite a simulated excessive plant water stress andPublished by Copernicus Publications on behalf of the European Geosciences Union. 122M. Guimberteau et al.: ORCHIDEE-MICT, a LSM for the high latitudes a positive land surface temperature bias. In addition, acute model sensitivity to the choice of input forcing data suggests that the calibration of model parameters is strongly forcingdependent. Overall, we suggest that this new model design is at the forefront of current efforts to reliably estimate future perturbations to the high-latitude terrestrial environment.

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Section: Soil Carbonmentioning

confidence: 99%

Section: Soil Carbon Discretizationmentioning

confidence: 99%

ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation

et al. 2018

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“…We used the LSM ORCHIDEE-MICT Zhu et al, 2016) (in the following simply referred to as ORCHIDEE) to construct a carbon emulator that describes the carbon pools and fluxes exactly as in ORCHIDEE (Fig. 1a).…”

Section: Modeling Framework Conceptmentioning

confidence: 99%

Global soil organic carbon removal by water erosion under climate change and land use change during AD 1850–2005

et al. 2018

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Abstract. Erosion is an Earth system process that transports carbon laterally across the land surface and is currently accelerated by anthropogenic activities. Anthropogenic land cover change has accelerated soil erosion rates by rainfall and runoff substantially, mobilizing vast quantities of soil organic carbon (SOC) globally. At timescales of decennia to millennia this mobilized SOC can significantly alter previously estimated carbon emissions from land use change (LUC). However, a full understanding of the impact of erosion on land-atmosphere carbon exchange is still missing. The aim of this study is to better constrain the terrestrial carbon fluxes by developing methods compatible with land surface models (LSMs) in order to explicitly represent the links between soil erosion by rainfall and runoff and carbon dynamics. For this we use an emulator that represents the carbon cycle of a LSM, in combination with the Revised Universal Soil Loss Equation (RUSLE) model. We applied this modeling framework at the global scale to evaluate the effects of potential soil erosion (soil removal only) in the presence of other perturbations of the carbon cycle: elevated atmospheric CO 2 , climate variability, and LUC. We find that over the period AD 1850-2005 acceleration of soil erosion leads to a total potential SOC removal flux of 74 ± 18 Pg C, of which 79 %-85 % occurs on agricultural land and grassland. Using our best estimates for soil erosion we find that including soil erosion in the SOC-dynamics scheme results in an increase of 62 % of the cumulative loss of SOC over 1850-2005 due to the combined effects of climate variability, increasing atmospheric CO 2 and LUC. This additional erosional loss decreases the cumulative global carbon sink on land by 2 Pg of carbon for this specific period, with the largest effects found for the tropics, where deforestation and agricultural expansion increased soil erosion rates significantly. We conclude that the potential effect of soil erosion on the global SOC stock is comparable to the effects of climate or LUC. It is thus necessary to include soil erosion in assessments of LUC and evaluations of the terrestrial carbon cycle.

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“…In these four peatland models, the water table depth was calculated from a bucket model. In the context of Earth system modeling, the land surface processes are better represented by multilayer schemes, such as multilayer plant canopy and root, multilayer snow, multilevel soil carbon, and energy budgets (Best et al, 2011;Mcgrath et al, 2016;Zhu et al, 2016). To model peatlands consistently in land surface models, a multilayer soil hydrology scheme is needed.…”

Section: Introductionmentioning

confidence: 99%

ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO<sub>2</sub>, water, and energy fluxes on daily to annual scales

et al. 2018

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Abstract. Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO 2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5 • grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (V cmax ) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r 2 = 0.76; NashSutcliffe modeling efficiency, MEF = 0.76) and ecosystem respiration (ER, r 2 = 0.78, MEF = 0.75), with lesser accuracy for latent heat fluxes (LE, r 2 = 0.42, MEF = 0.14) and and net ecosystem CO 2 exchange (NEE, r 2 = 0.38, MEF = 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r 2 values (0.57-0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r 2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r 2 < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized V cmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average V cmax value.

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Simulating soil organic carbon in yedoma deposits during the Last Glacial Maximum in a land surface model

Cited by 26 publications

References 49 publications

ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation

ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation

Global soil organic carbon removal by water erosion under climate change and land use change during AD 1850–2005

ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO<sub>2</sub>, water, and energy fluxes on daily to annual scales

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Simulating soil organic carbon in yedoma deposits during the Last Glacial Maximum in a land surface model

Cited by 26 publications

References 49 publications

ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation

ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation

Global soil organic carbon removal by water erosion under climate change and land use change during AD 1850–2005

ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO&lt;sub&gt;2&lt;/sub&gt;, water, and energy fluxes on daily to annual scales

Contact Info

Product

Resources

About

ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO<sub>2</sub>, water, and energy fluxes on daily to annual scales