A review on the global soil datasets for earth system modeling

Global soil dataset is a pillar to the challenge of earth system modeling. But it is one of the most important uncertainty sources for Earth System Models (ESMs). Soil datasets function as model parameters, initial variables and benchmark datasets for model calibration, validation and comparison. For modeling use, the dataset should be geographically continuous, scalable and with uncertainty estimates. The popular soil datasets used in ESMs are often based on limited soil profiles and coarse resolution soil maps. Updated and comprehensive soil information needs to be incorporated in ESMs. New generation soil datasets derived by digital soil mapping with abundant soil observations and environmental covariates are preferred to those by the linkage method for ESMs. Because there is no universal pedotransfer function, an ensemble of them may be more suitable to provide secondary soil parameters to ESMs. Aggregation and upscaling of soil data are needed for model use but can be avoid by taking a subgrid method in ESMs at the cost of increases in model complexity. Uncertainty of soil data needs to be incorporated in ESMs.