Systematic diurnal bias of the CMA-MESO model in southern China: Characteristics and correction

Model error is an important source of numerical weather prediction (NWP) errors. Among model errors, the systematic diurnal bias plays role in high-resolution models. The main purpose this study to explore characteristics a NWP southern China and reduce improve forecast results, hence providing better background field for data assimilation. Based on Meteorological Administration Meso-scale (CMA-MESO) model, 15-day sequential experiment was performed China, results were analyzed. A correction scheme (SBCS) based analysis increments designed CMA-MESO comparative experiments carried out. showed that has apparent biases, differ among variables. large mainly found lower layers, it concentrated areas with complex underlying surface horizontal distribution, such as Qinghai-Tibet Plateau South Coast. partly reduced biases model. mean meridional wind, zonal potential temperature, water vapor mixing ratio by 45%, 35%, 20%, 10%, respectively, root square errors (RMSEs) approximately 5%. This revealed which may be caused variation thermal dynamic exchange surfaces. effectiveness also verified, had good prospects more reference information models