A review of the global soil property maps for Earth system models
Author:
Dai Yongjiu, Shangguan Wei, Wei Nan, Xin Qinchuan, Yuan Hua, Zhang Shupeng, Liu ShaofengORCID, Lu XingjieORCID, Wang DagangORCID, Yan Fapeng
Abstract
Abstract. Soil is an important regulator of Earth system processes,
but remains one of the least well-described data layers in Earth system
models (ESMs). We reviewed global soil property maps from the perspective of
ESMs, including soil physical and chemical and biological properties, which
can also offer insights to soil data developers and users. These soil
datasets provide model inputs, initial variables, and benchmark datasets. For
modelling use, the dataset should be geographically continuous and scalable and
have uncertainty estimates. The popular soil datasets used in ESMs are often
based on limited soil profiles and coarse-resolution soil-type maps with
various uncertainty sources. Updated and comprehensive soil information
needs to be incorporated into ESMs. New generation soil datasets derived
through digital soil mapping with abundant, harmonized, and quality-controlled soil observations and environmental covariates are preferred to
those derived through the linkage method (i.e. taxotransfer rule-based
method) for ESMs. SoilGrids has the highest accuracy and resolution among
the global soil datasets, while other recently developed datasets offer
useful compensation. Because there is no universal pedotransfer function, an
ensemble of them may be more suitable for providing derived soil properties to
ESMs. Aggregation and upscaling of soil data are needed for model use, but
can be avoided by using a subgrid method in ESMs at the expense of increases
in model complexity. Producing soil property maps in a time series still remains
challenging. The uncertainties in soil data need to be estimated and
incorporated into ESMs.
Funder
National Natural Science Foundation of China Ministry of Science and Technology of the People's Republic of China
Publisher
Copernicus GmbH
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