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Impact of Soil Datasets on the Global Simulation of Land Surface Processes

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    This study aims to evaluate the effect of two, new, global soil datasets on global land surface simulation, based for the first time on the Common Land Model (CoLM). The effects of the two soil datasets, namely GSDE (Global Soil Dataset for Earth System Model) and Soil Grids (SG), on the model simulation results were studied. The differences between these two data sets were compared and analyzed for five soil properties, namely sand, clay, gravel, organic carbon, and bulk density, and the impact, caused by those differences, on the estimated soil characteristic parameters as well as the hydraulic and thermal variables in the model were discussed. The results show that the global spatial distribution of soil characteristic parameters is mainly influenced by soil particle size distribution (sand, silt, and clay), and also by gravel, organic matter, and bulk density. The effect of the soil datasets on the global simulation varies across different regions. Their effect on the hydrological variables (the maximum value of Re is ±100%) is greater than that on the soil thermodynamic variables (Re<±10%) and on the surface radiation variables (Re<±5%). The soil volumetric water content in central and northwest Canada, southeastern Russia, and midwest and central Australia is quite different, and the total runoff in low latitudes area shows great variance. Thermal variables show some differences in northern Africa, northwestern Canada, and north-central Russia. Comparing the simulated soil moisture with site observations, the performance of the two datasets is similar and there is a certain deviation from the site observations. More specifically, the values based on the SG data are closer to the observation values. The results show that there is an increase of about 0.01 to 0.02 using the SG data compared with the GSDE data at the Molly Caren site. This study shows that the model simulation results are significantly affected by different datasets and that soil data with higher accuracy, such as the SG data, are preferable for model use. Further studies on the effect of soil properties on land surface modeling are required.

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李文耀,魏楠,黄丽娜,上官微.2020.土壤数据集对全球陆面过程模拟的影响[J].气候与环境研究,25(5):555-574. LI Wenyao, WEI Nan, HUANG Lina, SHANGGUAN Wei.2020. Impact of Soil Datasets on the Global Simulation of Land Surface Processes[J]. Climatic and Environmental Research (in Chinese],25(5):555-574.

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  • Received:March 04,2020
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  • Online: September 27,2020
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