Representing Nitrogen, Phosphorus, and Carbon Interactions in the E3SM Land Model: Development and Global Benchmarking

Zhu, Qing; Riley, William J.; Tang, Jinyun; Collier, Nathan; Hoffman, Forrest M.; Yang, Xiaojuan; Bisht, Gautam

doi:10.1029/2018ms001571

Cited by 99 publications

(124 citation statements)

References 91 publications

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“…We therefore expect that the simplification would only cause minor uncertainty in the spatial variability of SOC loss which was compared with the spatial variability of land surface C fluxes in our analysis. As demonstrated in Figure S1 and other publications (Chen et al, ; Zhu et al, ), the ELMv1‐ECA‐CNP approach can well capture the spatial variability of SOC content in surface soils. The ELM‐Erosion model has three spatially variable free parameters for calibrating soil erosion and sediment yield, including one for rainfall‐driven erosion, one for runoff‐driven erosion, and one for sediment transport capacity (Tan et al, ).…”

Section: Methodssupporting

confidence: 57%

A substantial role of soil erosion in the land carbon sink and its future changes

Tan

Leung

et al. 2020

Global Change Biology

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Realistic representation of land carbon sink in climate models is vital for predicting carbon climate feedbacks in a changing world. Although soil erosion that removes land organic carbon has increased substantially since the onset of agriculture, it is rarely included in the current generation of climate models. Using an Earth system model (ESM) with soil erosion represented, we estimated that on average soil erosion displaces 5% of newly fixed land organic carbon downslope annually in the continental United States. In the lower Mississippi river basin and the Cascades, the fraction can be as large as 40%. About 12% of the eroded organic carbon is eventually exported to inland waters, which is equal to 14% of the simulated net carbon gain by terrestrial ecosystems. By comparing the eroded organic carbon export to rivers with the particulate organic carbon export to oceans, we demonstrated that a large fraction of the carbon export to rivers could have been mineralized in inland waters. Importantly, with a direct comparison of eroded and exported soil organic carbon and land net carbon uptake, we found that ESMs that ignore soil erosion likely offset the erosional carbon loss by increasing heterotrophic respiration implicitly. But as soil erosion and heterotrophic respiration respond differently to a warming climate, this unrealistic compensation would lead to biased predictions of future land carbon sink.

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Section: Methodssupporting

confidence: 57%

A substantial role of soil erosion in the land carbon sink and its future changes

Tan

Leung

et al. 2020

Global Change Biology

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“…ELMv1‐ECA has been evaluated against multiple global‐scale observations of ecosystem C, water, and energy stocks and fluxes using ILAMB (Collier et al, ; Zhu et al, ) and short‐term nutrient cycling observations and global‐scale partitioning of N losses (Riley et al, ; Zhu & Riley, ). Overall, model benchmarking shows improvement from the precursor CLM4.5 predictions, and in particular for this study, more accurate estimates of spatially distributed soil C stocks (Zhu et al, ).…”

Section: Methodsmentioning

confidence: 99%

“…We first give a mathematical overview of the approach and then present examples of its use. We test our approach by comparing our computed values to output from the ELMv1‐ECA model (Chen et al, ; Riley et al, ; Tang & Riley, ; Zhu et al, ), the land component of the Exascale Earth System Model (E3SM) model, which explicitly represents radiocarbon and is therefore an appropriate test case to evaluate our proposed method. We evaluate the modeled radiocarbon values along the entire vertically resolved soil profile and across all represented soil and litter pools over time.…”

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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“…A major development is the modularization of the model structure in FATES so that boundary conditions and vegetation can be coupled with ESM land models. FATES is integrated into the E3SM Land Model (ELM) Zhu et al, 2019) and within the Community Land Model (CLM) Wieder et al, 2019) coupled to the Community Earth 230 System Model (Hurrell et al, 2013). In this study we used ELM-FATES.…”

Section: Forest Regrowth Simulation In Elm-fatesmentioning

confidence: 99%

Landsat NIR band and ELM-FATES sensitivity to forest disturbances and regrowth in the Central Amazon

Negrón‐Juárez

Holm

Faybishenko

et al. 2019

Preprint

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<p><strong>Abstract.</strong> Forest disturbance and regrowth are key processes in forest dynamics but detailed information of these processes is difficult to obtain in remote forests as the Amazon. We used chronosequences of Landsat satellite imagery to determine the sensitivity of surface reflectance from all spectral bands to windthrow, clearcutting, and burning and their successional pathways of forest regrowth in the Central Amazon. We also assess whether the forest demography model Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM-FATES, accurately represents the changes for windthrow and clearcut. The results show that all spectral bands from Landsat satellite were sensitive to the disturbances but after 3 to 6 years only the Near Infrared (NIR) band had significant changes associated with the successional pathways of forest regrowth for all the disturbances considered. In general, the NIR decreased immediately after disturbance, increased to maximum values with the establishment of pioneers and early-successional tree species, and then decreased slowly and almost linearly to pre-disturbance conditions with the dynamics of forest succession. Statistical methods predict that NIR will return to pre-disturbance values in about 39 years (consistent with observational data of biomass regrowth following windthrows), and 36 and 56 years for clearcut and burning. The NIR captured the observed successional pathways of forest regrowth after clearcut and burning that diverge through time. ELM-FATES predicted higher peaks of initial forest responses (e.g., biomass, stem density) after clearcuts than after windthrows, similar to the changes in NIR. However, ELM-FATES predicted a faster recovery of forest structure and canopy-coverage back to pre-disturbance conditions for windthrows compared to clearcuts. The similarity of ELM-FATES predictions of regrowth patterns after windthrow and clearcut to those of the NIR results suggest that the dynamics of forest regrowth for these disturbances are represented with appropriate fidelity within ELM-FATES and useful as a benchmarking tool.</p>

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Representing Nitrogen, Phosphorus, and Carbon Interactions in the E3SM Land Model: Development and Global Benchmarking

Cited by 99 publications

References 91 publications

A substantial role of soil erosion in the land carbon sink and its future changes

A substantial role of soil erosion in the land carbon sink and its future changes

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

Landsat NIR band and ELM-FATES sensitivity to forest disturbances and regrowth in the Central Amazon

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