基于卫星云参数的短时降水动态估测方法

Dynamical Estimation of Short-Time Precipitation from Satellite Cloud Parameters

利用实时FY-2静止气象卫星红外云图和区域中尺度地面自动监测网加密降水资料,通过对云图进行参数化处理,采用动态相关方法分析长波红外分裂窗双谱组合、长波红外水汽双谱组合、亮温面积等各类卫星云参数与不同级别降水强度的关系,寻找当时与降水强度的最佳相关云参数化因子建立短时降水动态估测模型,并利用实时最新降水估测模型对未来3 h降水进行估测预报应用。模型估测的降水分布与实际降水分布比较接近,短时强降水中心估测与实况基本吻合,但在高山地形条件下降水估测值略偏小。

Based on the hourly infrared cloud images from the geostationary meteorological satellite（FY-2） and the enhanced precipitation observation from the regional mesoscale surface automatic weather observation network,through the parameterization of cloud images,the relationship between cloud parameters and precipitation rate of different categories are analyzed by using the dynamical correlation method.The cloud parameters include the two-band combination of long-wave infrared and split-window,the two-band combination of long-wave infrared and water vapor,and brightness temperature,etc.Through the above analysis,a dynamical estimation model of precipitation nowcasting is built based on the optimal correlation between precipitation rate and related cloud parameters.The new estimation model was applied in real time to three-hour precipitation forecast.The distribution of forecasted precipitation is similar to that from observation.The precipitation centers are roughly in agreement with the observed centers,but the estimated precipitation rates are lower than the observed in high mountain areas.