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The Q10 value represents the soil respiration sensitivity to temperature often used for the parameterization of the soil decomposition process has been assumed to be a constant in conventional numerical models, whereas it exhibits significant spatial and temporal variation in the observations. This study develops a new parameterization method for determining Q10 by considering the soil respiration dependence on soil temperature and moisture obtained by multiple regression for each vegetation type. This study further investigates the impacts of the new parameterization on the global terrestrial carbon flux. Our results show that a nonuniform spatial distribution of Q10 tends to better represent the dependence of the soil respiration process on heterogeneous surface vegetation type compared with the control simulation using a uniform Q10. Moreover, it tends to improve the simulation of the relationship between soil respiration and soil temperature and moisture, particularly over cold and dry regions. The modification has an impact on the soil respiration and carbon decomposition process, which changes gross primary production (GPP) through controlling nutrient assimilation from soil to vegetation. It leads to a realistic spatial distribution of GPP, particularly over high latitudes where the original model has a significant underestimation bias. Improvement in the spatial distribution of GPP leads to a substantial reduction of global mean GPP bias compared with the in situ observation-based reference data. The results highlight that the enhanced sensitivity of soil respiration to the subsurface soil temperature and moisture introduced by the nonuniform spatial distribution of Q10 has contributed to improving the simulation of the terrestrial carbon fluxes and the global carbon cycle.

Improvement of Soil Respiration Parameterization in a Dynamic Global Vegetation Model and Its Impact on the Simulation of Terrestrial Carbon Fluxes