多源观测数据在LAPS三维云量场分析中的应用

该文将我国FY-2C气象卫星通道数据、地面观测数据、雷达数据融合进入LAPS (Local Analysis Prediction System) 三维数据分析系统中，获得了三维云量场分布，并采用北京地区2009年11月9日08:00(北京时，下同) 和华南地区2008年6月12日14:00个例，设计了5种试验对LAPS融合的云量场进行分析。结果表明:LAPS云分析中，地面观测对云底结构起主要订正作用，雷达观测对云中、低部信息起主要订正作用，而卫星云图数据对云顶分布订正效果显著，卫星资料是获得客观三维云量场不可或缺的数据。

The Application of Multi-source Data to Three-dimensional Cloud Amount Analysis in LAPS

The quantitative three-dimensional cloud data is important in nowcasting and the modeling of weather and climate. Therefore, 5 schemes are designed to construct three-dimensional cloud amount data from FY-2C satellite data, radar data, ground observation data using LAPS (Local Analysis Prediction System) developed by NOAA ERSL. The roles of each data in LAPS system are also analyzed. Scheme 1 uses background data only, and Scheme 2 adds ground observation data. Scheme 3 employs background data and FY-2C satellite data, Scheme 4 uses background data and radar data, and Scheme 5 takes background data, ground observation data, radar data and FY-2C satellite data into consideration.The analysis indicates that every data is important in order to get more objective three-dimensional cloud distribution. Ground observation data gives information of cloud base and cloud amount for the lower atmosphere. Satellite infrared brightness temperature and visible reflectance provide cloud top height and cloud amount in the upper atmosphere. Radar data can help to construct three-dimensional cloud field in the middle and lower level. Combining all these data can provide more objective information of three-dimensional cloud amount.Comparing column cloud amount deduced by LAPS with satellite visible and infrared image shows that the cloud distribution when assimilating all these data is more consistent with real situation. Moreover, the satellite data is one of the most important data in cloud analysis in LAPS.