电离层资料同化中的背景场误差特征分析研究

单独依靠观测和模式都无法再现一个准确可靠的电离层环境状态，在气象领域中发展的资料同化技术为解决这个困境提供可能。目前阶段电离层资料同化存在背景模式不够准确、观测误差处理不够系统，以及背景场误差协方差研究严重缺乏等多方面问题。本项目针对背景场误差研究不足的现状，从观测资料入手，利用积累时间较长的测高仪和GPS资料，采用统计方法研究可能导致电离层背景模型与实际观测偏离的电离层扰动（逐日变化等）及空间分布规律；并结合特定背景场模型（如IRI和TIEGCM等）统计背景场与实际观测资料的差异，研究这些差异的空间相关特征，提出背景场误差协方差空间分布模型。在发展和完善现有同化试验系统的基础上，开展资料分析同化实验，验证新的误差协方差的同化效果。本项目的研究可加深对电离层中各种天气尺度变化和扰动机制的认识和理解，提高资料同化分析的准确性，满足无线电、测绘和导航用户越来越强烈的电离层天气分析预报的需求

It is quite difficult to specify the ionosphere electron content in three dimension when only using the observations or the model. By combining the observation and model together, the data assimilation techniques, which is great successful in meteorological, could make it possible to derive a optimal ionosphere background in statistically sense. Currently, there are several deficiency in ionosphere data assimilation, i.e. the inaccuracy of background model, the lacking of carefully evalution the observation deviation and background erro covariance. In this project we put emphasis on studying the structure and character of background erro and its covariance. By using of a longtime ionosonde and GPS data, the ionosphere variation, which usually contribute to the difference between the model and observation, are statistically analysed. When an ionosphere model (i.e. IRI and TIEGCM) is specified as background, the deviation and its spatial correlation character between the model background and the observation are statistically studied, and a new model of background erro covariance is advanced in the end. After refining the present ionosphere data assimilation system, the data assimilation experiment is carried out with the new erro covariance for validation. Our study is able to help to understand the ionospheric variations in the weather scale and improve the data assimilation performance, to meet the challenge of ionosphere specify and forecast from the radio, survey and navigation users.