基于GPS掩星技术反演大气参数模型的优化

Optimization the inversion model of atmospheric parameter using radio occulation data

准确掌握地球大气中的水气分布 ,了解水气变化趋势对天气现象、全球气侯变化、数值预报具有理论研究及实用价值。以无线电掩星技术为基础 ,利用掩星数据反演大气参数剖面。对原反演模型的不足进行了论证 ,并给出了反演个例。详细地论述了通过引入MM5先验温度T再通过线性迭代的方法反演对流层下部水汽廓线原理 ,给出了优化后模型反演个例。并对模型优化后反演廓线中存在的问题进行了分析 ,提出了下一步优化方向。

To sound water vapor precisely in the troposphere is an essential problem for weather phenomenon research, global climate change research and numerical weather forecast as wall. The main purpose of this paper is to develop an inverse model for atmospheric parameter profiles using radio occulation data. This paper demonstrate the deficiency of the old retrieval model and some atmospheric parameter profiles are obtained. Through the linear retrieval and using the ECMWF′S temperature, new retrieval model is introduced with some atmospheric parameter profiles as well as the analysis of the bug in the atmospheric parameter profiles. Finally, bring forward the next way to optimize the retrieval modal.