卫星云图资料反演的质量控制及变分同化数值试验

NUMERICAL EXPERIMENT ON QUALITY CONTROL AND VARIATIONAL ASSIMILATION OF SATELLITE IMAGE RETRIEVAL

该文针对数值化的 GMS红外卫星云图资料的特点 ,利用改进的统计反演方法分别求出温度和湿度估计场 ,设计了几种订正方案对反演出的温度和湿度进行质量控制 ;控制后的反演场再与常规观测资料进行变分同化 ,最后用 MM4模式进行了模拟对比试验 .结果显示 ,在合理的泛函设计的基础上 ,质量控制的好坏直接影响预报结果 .用分析场格点值进行订正效果优于用测站值直接订正 ,加上对云图反演的值进行系统误差订正后 ,有效提高了降水预报准确率 .值得指出的是 ,加进云图资料后 ,明显改善了模式降水预报的强度和区域 ,与仅用常规探空资料相比更接近于实况 .

According to the characteristics of numerical GMS infrared imagery the improved statistic retrieval method is applied to estimate the temperature and humidity. Several schemes are developed to control the quality of retrieved temperature and humidity in order to correct the errors from the image and the retrieval scheme. The variational assimilation is performed of the corrected retrieval field with the conventional observations followed by a control experiment by the MM4 model.Results show that the quality control is critical to the forecasting based on the rational designed function.The correction with the grid values is better than that of the conventional observation, and with the systematic error correction to the retrieval field included the accuracy of rainfall forecasting is improved.It is worth notice that the scheme with satellite image included can obviously improve the intensity and region forecasting of model rainfall and the prediction is more close to measured precipitation as compared with that only using the conventional observations.