scholarly journals A new dataset of soil Carbon and Nitrogen stocks and profiles from an instrumented Greenlandic fen designed to evaluate land-surface models

2020 ◽  
Author(s):  
Xavier Morel ◽  
Birger Ulf Hansen ◽  
Christine Delire ◽  
Per Lennart Ambus ◽  
Mikhail Mastepanov ◽  
...  
Keyword(s):  
Soil Carbon ◽  
Greenhouse Gas ◽  
Land Surface ◽  
High Water Content ◽  
Land Surface Models ◽  
Complete Evaluation ◽  
Carbon And Nitrogen ◽  
Soil Carbon And Nitrogen ◽  
C Cycle ◽  
Surface Models

Abstract. Arctic and boreal peatlands play a major role in the global carbon (C) cycle. They are particularly efficient at sequestering carbon due to their high-water content which makes primary productivity exceed decomposition rates. Though, their future in a climate-change context is quite uncertain in terms of carbon emissions and carbon sequestration. Nuuk-fen site is a well-instrumented greenlandic site of particular interest for testing and validating land-surface models with monitoring of soil physical variables and greenhouse gas fluxes (CH4 and CO2). But knowledge of soil carbon stocks and profiles is missing. This is a crucial shortcoming for a complete evaluation of models, as soil carbon is one of the primary drivers of CH4 and CO2 soil emissions. To tackle this issue, we measured for the first time soil carbon and nitrogen density, profiles and stocks in the Nuuk peatland, at the exact location of fluxes monitoring. Measurements were made along two transects. Measurements horizontal resolution is 5 meter, vertical resolution ranges from 5 to 10 cm. Mean soil carbon density is 50.2 kgC.m−3. These new data are in the range of those encountered in other arctic peatlands. This new dataset can contribute to further develop joint modelisation of greenhouse gas emissions and soil carbon in land-surface models. The dataset is open-access and available at https://doi.org/10.1594/PANGAEA.909899 (Morel et al., 2019b).

scholarly journals A new dataset of soil carbon and nitrogen stocks and profiles from an instrumented Greenlandic fen designed to evaluate land-surface models

2020 ◽  
Vol 12 (4) ◽  
pp. 2365-2380
Author(s):  
Xavier Morel ◽  
Birger Hansen ◽  
Christine Delire ◽  
Per Ambus ◽  
Mikhail Mastepanov ◽  
...  
Keyword(s):  
Soil Carbon ◽  
Greenhouse Gas ◽  
Land Surface ◽  
High Water Content ◽  
Land Surface Models ◽  
Carbon And Nitrogen ◽  
Soil Carbon And Nitrogen ◽  
C Cycle ◽  
Surface Models ◽  
Carbon And Nitrogen Stocks

Abstract. Arctic and boreal peatlands play a major role in the global carbon (C) cycle. They are particularly efficient at sequestering carbon because their high water content limits decomposition rates to levels below their net primary productivity. Their future in a climate-change context is quite uncertain in terms of carbon emissions and carbon sequestration. Nuuk fen is a well-instrumented Greenlandic fen with monitoring of soil physical variables and greenhouse gas fluxes (CH4 and CO2) and is of particular interest for testing and validating land-surface models. But knowledge of soil carbon stocks and profiles is missing. This is a crucial shortcoming for a complete evaluation of models, as soil carbon is one of the primary drivers of CH4 and CO2 soil emissions. To address this issue, we measured, for the first time, soil carbon and nitrogen density, profiles and stocks in the Nuuk peatland (64∘07′51′′ N, 51∘23′10′′ W), colocated with the greenhouse gas measurements. Measurements were made along two transects, 60 and 90 m long and with a horizontal resolution of 5 m and a vertical resolution of 5 to 10 cm, using a 4 cm diameter gouge auger. A total of 135 soil samples were analyzed. Soil carbon density varied between 6.2 and 160.2 kg C m−3 with a mean value of 50.2 kg C m−3. Mean soil nitrogen density was 2.37 kg N m−3. Mean soil carbon and nitrogen stocks are 36.3 kg C m−2 and 1.7 kg N m−2. These new data are in the range of those encountered in other arctic peatlands. This new dataset, one of very few in Greenland, can contribute to further development of joint modeling of greenhouse gas emissions and soil carbon and nitrogen in land-surface models. The dataset is open-access and available at https://doi.org/10.1594/PANGAEA.909899 (Morel et al., 2019b).

Greenhouse gas mitigation potential of the world’s grazing lands: Modeling soil carbon and nitrogen fluxes of mitigation practices

2015 ◽  
Vol 207 ◽  
pp. 91-100 ◽  
Author(s):  
Benjamin B. Henderson ◽  
Pierre J. Gerber ◽  
Tom E. Hilinski ◽  
Alessandra Falcucci ◽  
Dennis S. Ojima ◽  
...  
Keyword(s):  
Soil Carbon ◽  
Greenhouse Gas ◽  
Greenhouse Gas Mitigation ◽  
Mitigation Potential ◽  
Carbon And Nitrogen ◽  
Nitrogen Fluxes ◽  
Soil Carbon And Nitrogen ◽  
Grazing Lands

scholarly journals Lower boundary conditions in land surface models – effects on the permafrost and the carbon pools: a case study with CLM4.5

2020 ◽  
Vol 13 (3) ◽  
pp. 1663-1683 ◽  
Author(s):  
Ignacio Hermoso de Mendoza ◽  
Hugo Beltrami ◽  
Andrew H. MacDougall ◽  
Jean-Claude Mareschal
Keyword(s):  
Heat Flux ◽  
Soil Carbon ◽  
Land Surface ◽  
Lower Boundary ◽  
Surface Model ◽  
Seasonal Temperature ◽  
Land Surface Models ◽  
Near Surface ◽  
Recent Climate ◽  
Surface Models

Abstract. Earth system models (ESMs) use bottom boundaries for their land surface model (LSM) components which are shallower than the depth reached by surface temperature changes in the centennial timescale associated with recent climate change. Shallow bottom boundaries reflect energy to the surface, which along with the lack of geothermal heat flux in current land surface models, alter the surface energy balance and therefore affect some feedback processes between the ground surface and the atmosphere, such as permafrost and soil carbon stability. To evaluate these impacts, we modified the subsurface model in the Community Land Model version 4.5 (CLM4.5) by setting a non-zero crustal heat flux bottom boundary condition uniformly across the model and by increasing the depth of the lower boundary from 42.1 to 342.1 m. The modified and original land models were run during the period 1901–2005 under the historical forcing and between 2005 and 2300 under forcings for two future scenarios of moderate (Representative Concentration Pathway 4.5; RCP4.5) and high (RCP8.5) emissions. Increasing the thickness of the subsurface by 300 m increases the heat stored in the subsurface by 72 ZJ (1 ZJ = 1021 J) by the year 2300 for the RCP4.5 scenario and 201 ZJ for the RCP8.5 scenario (respective increases of 260 % and 217 % relative to the shallow model), reduces the loss of near-surface permafrost area in the Northern Hemisphere between 1901 and 2300 by 1.6 %–1.9 %, reduces the loss of intermediate-depth permafrost area (above 42.1 m depth) by a factor of 3–5.5 and reduces the loss of soil carbon by 1.6 %–3.6 %. Each increase of 20 mW m−2 of the crustal heat flux increases the temperature at 3.8 m (the soil–bedrock interface) by 0.04±0.01 K. This decreases near-surface permafrost area slightly (0.3 %–0.8 %) and produces local differences in initial stable size of the soil carbon pool across the permafrost region, which reduces the loss of soil carbon across the region by as much as 1.1 %–5.6 % for the two scenarios. Reducing subsurface thickness from 42.1 to 3.8 m, used by many LSMs, produces a larger effect than increasing it to 342.1 m, because 3.8 m is not enough to damp the annual signal and the subsurface closely follows the air temperature. We determine the optimal subsurface thickness to be 100 m for a 100-year simulation and 200 m for a simulation of 400 years. We recommend short-term simulations to use a subsurface of at least 40 m, to avoid the perturbation of seasonal temperature propagation.

scholarly journals Lower boundary conditions in Land Surface Models. Effects on the permafrost and the carbon pools

2018 ◽  
Author(s):  
Ignacio Hermoso de Mendoza ◽  
Hugo Beltrami ◽  
Andrew H. MacDougall ◽  
Jean-Claude Mareschal
Keyword(s):  
Heat Flux ◽  
Soil Carbon ◽  
Land Surface ◽  
Lower Boundary ◽  
Surface Model ◽  
Land Surface Models ◽  
Near Surface ◽  
Recent Climate ◽  
Surface Models ◽  
Rcp 8.5

Abstract. Earth System Models (ESMs) use bottom boundaries for their land surface model components which are shallower than the depth reached by surface temperature changes in the centennial time scale associated with recent climate change. Shallow bottom boundaries reflect energy to the surface, which along with the lack of geothermal heat flux in current land surface models, alter the surface energy balance and therefore affect some feedback processes between the ground surface and the atmosphere, such as permafrost and soil carbon stability. To evaluate these impacts, we modified the subsurface model in the Community Land Model version 4.5 (CLM4.5) by setting a non-zero crustal heat flux bottom boundary condition and by increasing the depth of the lower boundary by 300 m. The modified and original land models were run during the period 1901–2005 under the historical forcing and between 2005–2300 under two future scenarios of moderate (RCP 4.5) and high (RCP 8.5) emissions. Increasing the thickness of the subsurface by 300 m increases the heat stored in the subsurface by 72 ZJ (1 ZJ = 1021 J) by year 2300 for the RCP 4.5 scenario and 201 ZJ for the RCP 8.5 scenario (respective increases of 260 % and 217 % relative to the shallow model), reduces the loss of near-surface permafrost between 1901 and 2300 by 1.6 %–1.9 %, and reduces the loss of soil carbon by 1.6 %–3.6 %. Each increase of 0.02 W m−2 of the crustal heat flux increases the temperature at the soil-bedrock frontier by 0.4 ± 0.01 K, which decreases near-surface permafrost area slightly (0.3–0.8 %), but reduces the loss of soil carbon by as much as 1.1 %–5.6 % for the two scenarios.

scholarly journals Carbon-nitrogen coupling under three schemes of model representation: Traceability analysis

2018 ◽  
Author(s):  
Zhenggang Du ◽  
Ensheng Weng ◽  
Jianyang Xia ◽  
Lifen Jiang ◽  
Yiqi Luo ◽  
...  
Keyword(s):  
Land Surface ◽  
Storage Capacity ◽  
N Uptake ◽  
C:N Ratio ◽  
Land Surface Models ◽  
Plant N Uptake ◽  
Coupled Models ◽  
C Storage ◽  
C Cycle ◽  
Surface Models

Abstract. The interaction between terrestrial carbon (C) and nitrogen (N) cycles has been incorporated into more and more land surface models. However, the scheme of C-N coupling differs greatly among models, and how these diverse representations of C-N interactions will affect C-cycle modeling remains unclear. In this study, we explored how the simulated ecosystem C storage capacity in the terrestrial ecosystem (TECO) model varies with three different commonly-used schemes of C-N coupling. The three schemes (SM1, SM2, and SM3) have been used in three different coupled C-N models (i.e., TECO-CN 2.0, CLM 4.5, and O-CN, respectively). They differ mainly in the stoichiometry of C and N in vegetation and soils, plant N uptake strategies, pathways of N import, and the competition between plants and microbes for soil mineral N. We incorporated them into the C-only version of TECO model, and evaluated their impacts on the C cycle with a traceability framework. Our results showed that all of the three C-N schemes resulted in significant reductions in steady-state C storage capacity compared with the C-only version, but the magnitude varied with −23 %, −30 % and −54 % for SM1, SM2, SM3, respectively. The reduced C storage capacity is the combination of decreases in net primary productivity (NPP) by −29 %, −15 % and −45 % with changes of mean C residence time (MRT) by 9 %, −17 % and −17 % for SM1, SM2, and SM3, respectively. The divergent NPP are mainly attributed to the different assumptions on plant N uptake, plant tissue C:N ratio, down-regulation photosynthesis, and biological N fixation. In comparison, the alternative representations of the plant and microbe competition strategy and the plant N uptake, combining with the flexible C:N ratio in vegetation and soils, led to a notable spread MRT. These results highlight that the diverse assumptions on N process representation among different C-N coupled models could cause additional uncertainty to land surface models. Understanding their difference can help us to improve the capability of models to predict future biogeochemical cycles on land.

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