Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations ‐ United Nations Educational, Scientific and Cultural Organization (FAO‐UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning‐up the soil moisture improves near‐surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided. Key Points Updated the WRF soil map with BNU soil data set to show the long‐term effects on soil moisture A long spinning‐up period which depends on latitude of locations is required for soil moisture Updated soil map and spun‐up soil moisture improves the 2 m temperature by 1 degree in most places