Impact of Soil Moisture on Winter 2-m Temperature Forecast in Northern China

 The causes of the underestimated diurnal 2-m temperature range and the overestimated 2-m specific humidity in Northern China’s winter in the Rapid-refresh Multi-scale Analysis and Prediction System - Short Term (RMAPS-ST) system are investigated. Three simulations based on RMAPS-ST are conducted from Nov. 1st, 2016 to Feb. 28th, 2017. Further analyses show that the partitioning of surface upward sensible heat fluxes and downward ground heat fluxes might be the main contributing factor in 2-m temperature forecast biases. In this study, two simulations are conducted to examine the effect of soil moisture initialization and soil hydraulic property on the 2-m temperature and 2-m specific humidity forecast biases. Firstly, the High-Resolution Land Data Assimilation System (HRLDAS) is used to provide an alternative soil moisture initialization, and the result shows that the drier soil moisture leads to noticeable change in energy partition at the land surface, which in turn results in improved prediction of the diurnal 2-m temperature range, although it also enlarges the 2-m specific humidity bias in some parts of the domain. Secondly, a soil texture dataset developed by Beijing Normal University (BNU) and a revised hydraulic parameters are applied to provide a more detailed description of soil properties, which could further improve the 2-m specific humidity biases. In summary, the combination of using optimized soil moisture initialization, updated soil map and revised soil hydraulic parameters can help improve the 2-m temperature and 2-m specific humidity prediction in RMAPS-ST.