Effects of soil texture datasets on FGOALS-g3 global long-term simulations

Abstract

Soil physical properties are critical to the energy and water balance between land and atmosphere interactions. Accurate soil data inputs could improve the simulations in land surface models and numerical weather models. However, further efforts are required to access the impact of soil data changes on global long-term simulations for climate system models. The Flexible Global Ocean-Atmosphere-Land System Model: Grid-Point Version 3 (FGOALS-g3) in an Atmospheric Model Intercomparison Project (AMIP) - style configuration with two different soil texture datasets is employed to investigate the role of soil texture in the long-term simulations of hydrological and related atmospheric variables. The results show that the difference in sand and clay content between the two datasets is slight in the global mean but exhibits regional heterogeneity. Updating soil texture data considerably reduced the deviation of global annual mean surface soil moisture, with significant improvements occurring in regions with the most remarkable changes in sandy soil content. However, there is almost no improvement in runoff, precipitation, and temperature on the global annual mean scale due to the complexity of the impact factor. Simulations of long-term soil moisture would be enhanced with more accurate data on soil texture.