GRAPES-MESO模式浅对流参数化的改进与试验

参考Berg 等2005、2013年提出的扰动对流触发函数方法,对GRAPES-Meso模式积云对流参数化方案(KF eta)中的浅对流激发进行改进设计和试验,将单一的温、湿度触发改为对近地层进行一组温度、湿度扰动后的触发,并且用与该组扰动相关的边界层温、湿度分布确定的联合概率密度函数(JPDF)来表征浅对流云的特征参量及计算浅对流的强度。 着重分析了改进方案的浅对流激发、浅对流对环境场的反馈、模式地面降水和2 m气温的相关响应等,并与原方案和相关观测比较,验证了改进方案的合理性。 结果显示,改进方案比原方案能较早地激发出浅对流,且浅对流的激发频次高,浅对流激发的增加致使在模式低层距地数百米至2—3 km的垂直层内对环境温、湿度场和云雨水反馈增大,对GRAPES-Meso浅对流激发偏弱有改进作用,并对格点尺度与次网格尺度降水分配比不协调有改进。 对连续两个月批量试验的检验表明,浅对流激发的改进,可对GRAPES-Meso的24 h降水预报技巧的提高和2 m气温偏差的减小等产生不同程度的正影响。

An improvement of the shallow convection parameterization scheme in the GRAPES-Meso

An improvement on the trigger function of the shallow convection scheme in the GRAPES-Meso has been designed and tested referring the treatment suggested by Berg, et al (2005, 2013), in which the trigger function is related to the distribution of temperature and humidity in the convective surface layer determined by the Joint Probability Density Functions (JPDF). The results show that more shallow convection could be triggered and occur in an earlier simulation time than the original one, and the stronger feedbacks of temperature, moisture and water vapor condensate of cloud to model grid scale are correspondingly identified in the lower layers from several hundred meters to about 2-3 km above the ground; with an improvement in the shallow convection, there is a positive impact on the fraction of subgrid/grid scale precipitation to the total precipitation of GRAPES-Meso. The verification for the forecast results of 2-month experiment indicates that the improvement of the trigger function of shallow convection scheme could result in the better performances of 24 h forecasts of accumulative precipitation and surface air temperature.