摘要
利用AIRS(Atmospheric Infrared Sounder)实际观测资料和采用特征向量反演方法,研究了非红外遥感因子对红外遥感大气温湿廓线反演的辅助作用。这些因子包括:微波探测通道、纬度、地形、表面高度、表面温度、表面气压等。试验结果表明,微波通道可以明显改善对流层中低层(800hPa以下)温度和湿度的反演结果,对800hPa以上没有明显的作用。划分纬度带有助于提高反演精度。在较平坦的地区温度反演的均方根误差远远小于地形起伏较大的地区。而水汽反演误差对地形变化不敏感。增加附加影响因子对改善对流层中低层温度反演精度有十分明显的作用,对中低层湿度反演精度有一定的改善。
Impacts of additional predictors on inverting atmospheric infrared radiance for temperature and humidity profiles are investigated using Atmospheric Infrared Sounder（AIRS） real measurements and empirical orthogonal function expansion method（EOF）. These predictors are microwave channels, latitude, topography, surface altitude, surface temperature, and surface air presure. The results suggest that microwave channels can remarkabely help the improvement of the accuracy of retrieved profiles at lower troposphere （below 800 hPa） and have little effect on that above 800hPa. With the dataset classified by latitude, better retrievals are obtained. The root mean square errors（RMSE） of retrieved tmperature at complicated terrain are significantly greater than that at fiat area. For humidity retrievals it was found that RMSE exhibit weak sensitivity to topography. By use of combined infrared measurements and additional predictors, great improvements have achieved in the retrieval of atmospheric temperature and humidity profdes at lower troposphere.
出处
《热带气象学报》
CSCD
北大核心
2009年第B12期79-84,共6页
Journal of Tropical Meteorology
基金
国家自然科学基金(40475016)
国家民用航天预研究项目(科工技[2002]4402)
湖南省科技重大专项(2008FJ1006)共同资助
关键词
卫星遥感
统计反演方法
红外
高光谱分辨率
大气廓线
Satellite Remote Sensing
Statistical Retrieval Method
Infrared
Hyperspectral
Atmospheric Profile
