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It is well‐known that soil carbon composition and turnover rate vary with soil depth, and the responses of soil carbon to global change in deeper soil layers may differ from those near the surface. Therefore, vertically resolved soil carbon models are needed for accurately predicting future soil carbon under global warming. In this study, we developed a vertically resolved soil carbon model by including vertical transport of soil carbon and using Michaelis‐Menten kinetics for soil carbon decomposition by microbes. The model was calibrated against six sites with the observed profiles of both soil carbon concentration and 14C measurements, and against 91 forest sites with soil carbon concentrations across a wide range of climate and soil conditions for four forest types in Europe and China. Results of independent model validation at another 93 sites showed that the calibrated model explained 40%–94% of the observed variance of soil carbon concentrations at different depths. Model sensitivity analysis showed that microbial activity and root carbon inputs are more important than soil carbon diffusion in simulating soil carbon profile. Results from our study highlight the need for detailed measurements of soil microbial activities and root carbon input at different soil depths in the field. Key Points: A vertically resolved soil carbon model‐based microbial kinetics is developedThe model explains 40%–94% of field observations from 93 forest sites in Europe and ChinaRoot‐carbon input has strongest influences on soil organic carbon concentration profiles [ABSTRACT FROM AUTHOR]

First‐order organic matter decomposition models are used within most Earth System Models (ESMs) to project future global carbon cycling; these models have been criticized for not accurately representing mechanisms of soil organic carbon (SOC) stabilization and SOC response to climate change. New soil biogeochemical models have been developed, but their evaluation is limited to observations from laboratory incubations or few field experiments. Given the global scope of ESMs, a comprehensive evaluation of such models is essential using in situ observations of a wide range of SOC stocks over large spatial scales before their introduction to ESMs. In this study, we collected a set of in situ observations of SOC, litterfall and soil properties from 206 sites covering different forest and soil types in Europe and China. These data were used to calibrate the model MIMICS (The MIcrobial‐MIneral Carbon Stabilization model), which we compared to the widely used first‐order model CENTURY. We show that, compared to CENTURY, MIMICS more accurately estimates forest SOC concentrations and the sensitivities of SOC to variation in soil temperature, clay content and litter input. The ratios of microbial biomass to total SOC predicted by MIMICS agree well with independent observations from globally distributed forest sites. By testing different hypotheses regarding (using alternative process representations) the physicochemical constraints on SOC deprotection and microbial turnover in MIMICS, the errors of simulated SOC concentrations across sites were further decreased. We show that MIMICS can resolve the dominant mechanisms of SOC decomposition and stabilization and that it can be a reliable tool for predictions of terrestrial SOC dynamics under future climate change. It also allows us to evaluate at large scale the rapidly evolving understanding of SOC formation and stabilization based on laboratory and limited filed observation. [ABSTRACT FROM AUTHOR]