特征向量数量对反演大气参数的影响

The Influence of the Amount of Eigenvector to Retrieval Clear Sky Air Parameter

大气温湿信息是天气预报、研究和业务的主要参数。具有通道多、信息量大、光谱窄等优点的AIRS已逐渐成为大气垂直探测的主流和方向。如何从卫星观测到的辐射测值推算出大气参数显得尤为重要。本文运用特征向量法反演晴空大气温度、臭氧廓线,试验不同数量的特征向量对反演晴空大气温度等参数精度的影响。结果表明适当增加特征向量的数量,对改进反演大气温度、臭氧廓线的精度有明显改善。

The information of the atmospheric temperature and moisture is the main parameter of the weather forecast, the research and the service, As the most advanced infrared atmospheric remote sensing instrument, AIRS （Atmospheric Infrared Sounder）.has become the mainstream and direction of the atmospheric vertical detector. How to calculate the atmosphere parameter from the satellite observation value appears especially importantly. This article is based on the eigenvector regression algorithm retrieving the clear sky temperature and ozone profile. By testing the amount of the eigenvectors, we final find that the retrieval precision of atmopheric temperature and ozone profile is proved when eigenvectors is added appropriately.