广西对流尺度数值预报模式产品在南宁的应用初探

Application of Guangxi convective scale numerical prediction model products in Nanning

利用广西对流尺度数值预报模式的部分产品、1h广西区域自动站气象观测资料、850hPa及500hPa实况形势场、雷达组合反射率资料、雷达外推客观预报产品,采用时间横向、纵向对比法,通过选取典型个例,对广西对流尺度数值预报模式产品(主要针对降水及雷达组合反射率产品)与实况进行分时段对比分析,并研究模式偏差的可能原因。结果表明,在0~3h中广西对流尺度数值预报模式产品比雷达外推客观预报产品可用性低,3~6h(特别是4~6h)段可用性明显增加;模式非整点逐12min产品比整点产品模拟结果更接近实况;在明显系统影响下,能提前4~6h准确预报出对流演变趋势,对局地降水也有很好指示意义,但范围和位置有偏差,有一定空报;在弱系统影响下,能提前4~6h较准确地预报出局地强降水的演变,对短时预报预警有积极的参考意义,但局部降水强度存在较明显偏差,范围偏大,空报较多;对锋面造成的大风演变有很好的指示意义。

Using products of Guangxi convective scale model, 1-hour meteorological observation data of Guangxi regional automatic station, 850hPa and 500hPa actual situation field, radar combined reflectivity data,and radar extrapolated objective prediction products, using time horizontal and vertical comparison methods, and selecting typical cases, the convective scale model products(mainly for precipitation and radar combined reflectivity products) in Guangxi were compared with the actual situation in different periods, and the possible causes of model deviation were studied. The results show that the availability of Guangxi convective scale numerical prediction model products is lower than that of radar extrapolation objective prediction products in 0 ~3h, and the availability of 3~6h(especially 4~6h) increases significantly. The simulation results of the model 12-miniute non-integer hour product are closer to the reality than that of the integer hour product. Under the obvious system influence, it can accurately predict the evolution trend of convection 4~6 hours in advance, and has good indication significance for local precipitation, but there is deviation in scope and position, and a certain possibility of vacancy forecast. Under weak system influence, it can accurately predict the evolution of local heavy precipitation 4 ~6h in advance, which has a positive reference significance for short-term prediction and early warning, but there are obvious deviations in local precipitation intensity, overestimation of range and more vacancy forecasts. It has a good indication of the evolution of gales caused by the front.