AMSU-A (Advanced Microwave Sounding Unit-A) measurements for channels that are sensitive to the surface over land have not been widely assimilated into numerical weather prediction (NWP) models due to complicated land surface features. In this paper, the impact of AMSU-A assimilation over land in Southwest Asia is investigated with the Weather Research and Forecasting (WRF) model. Four radiance assimilation experiments with different land-surface schemes are designed, then compared and verified against radiosonde observations and global analyses. Besides the surface emissivity calculated from the emissivity model and surface temperature from the background field in current WRF variational data assimilation (WRF-VAR) system, the surface parameters from the operational Microwave Surface and Precipitation Products System (MSPPS) are introduced to understand the influence of surface parameters on AMSU-A assimilation over land. The sensitivity of simulated brightness temperatures to different surface configurations shows that using MSPPS surface alternatives significantly improves the simulation with reduced root mean square error (RMSE) and allows more observations to be assimilated. Verifications of 24-h temperature forecasts from experiments against radiosonde observations and National Centers for Environmental Prediction (NCEP) global analyses show that the experiments using MSPPS surface alternatives generate positive impact on forecast temperatures at lower atmospheric layers, especially at 850 hPa. The spatial distribution of RMSE for forecast temperature validation indicates that the experiments using MSPPS surface temperature obviously improve forecast temperatures in the mountain areas. The preliminary study indicates that using proper surface temperature is important when assimilating lower sounding channels of AMSU-A over land.
基于Global Positioning System(GPS)掩星数据在平流层具有较高准确性、稳定性的优势,本文尝试用新一代GPS掩星观测——the Constellation Observing System for Meteorology,Ionosphere,and Climate(COSMIC)资料验证不同卫星平台上先进的微波探测仪(AMSU)的平流层观测结果.通过COSMIC大气温度廓线与AMSU辐射传输模式结合,得到模拟亮温,然后与AMSU平流层观测进行匹配比较.分析表明GPS掩星数据能够作为一个相对独立的参量检验NOAA15、16、18卫星平台内部的偏差.通过一年数据的比较验证,初步显示不同卫星平台的AMSU观测亮温在平流层低层都偏低,并且NOAA18平台的亮温偏低程度明显大于NOAA15、16.AMSU亮温偏差在极地冬季较为显著,尤其南极地区NOAA18的偏差幅度达到1.8K.结合24小时内AMSU观测亮温偏差变化及其样本分布特征,可以看到明显的太阳辐射差异可能是导致AMSU观测亮温在极地偏差显著的主要原因.