Authors: J. T. Anderegg, B. D. Smith, and Y. Malyshev
Journal: Global Biogeochemical Cycles
Publication Date: April 2020
Summary:
Soil carbon is a critical component of the global carbon cycle, and it is important to accurately simulate soil carbon levels in Earth system models (ESMs) in order to make reliable predictions about future climate change. However, there is currently a lack of consensus among ESMs on how soil carbon levels will respond to future climate change. This study aims to identify the sources of these inconsistencies and to assess their implications for model–observation agreement.
The study uses a suite of ESM simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to investigate the differences in soil carbon simulations across models. The simulations are compared to observations of soil carbon levels from the SoilGrids database. The study finds that there is a wide range in soil carbon simulations across models, with some models predicting increases in soil carbon levels and others predicting decreases. The study also finds that there are large uncertainties in soil carbon simulations, particularly in tropical regions.
The study concludes that the lack of consensus among ESMs in their simulations of soil carbon levels is due to a number of factors, including:
* Differences in the way that soil carbon processes are represented in models
* Uncertainties in the input data used to drive models
* Structural errors in models
The study also finds that the inconsistencies in soil carbon simulations across models have implications for model–observation agreement. Models that predict higher soil carbon levels tend to have better agreement with observations of atmospheric CO2 concentrations, but they have worse agreement with observations of soil carbon levels. This suggests that there is a trade-off between model–observation agreement for soil carbon and atmospheric CO2 concentrations.
The study concludes that more work is needed to improve the representation of soil carbon processes in ESMs and to reduce the uncertainties in soil carbon simulations. This will help to improve the accuracy of model predictions of future climate change and to better understand the role of soil carbon in the global carbon cycle.
