1. Toward more realistic projections of soil carbon dynamics by Earth system models
- Author
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Luo, Y, Ahlström, A, Allison, SD, Batjes, NH, Brovkin, V, Carvalhais, N, Chappell, A, Ciais, P, Davidson, EA, Finzi, A, Georgiou, K, Guenet, B, Hararuk, O, Harden, JW, He, Y, Hopkins, F, Jiang, L, Koven, C, Jackson, RB, Jones, CD, Lara, MJ, Liang, J, McGuire, AD, Parton, W, Peng, C, Randerson, JT, Salazar, A, Sierra, CA, Smith, MJ, Tian, H, Todd-Brown, KEO, Torn, M, Van Groenigen, KJ, Wang, YP, West, TO, Wei, Y, Wieder, WR, Xia, J, Xu, X, and Zhou, T
- Subjects
Meteorology & Atmospheric Sciences ,Atmospheric Sciences ,Geochemistry ,Oceanography - Abstract
Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.
- Published
- 2016