大气气溶胶的空间谱特征分析和多尺度同化研究

近年来，大范围的雾霾与局地的严重污染常常相伴发生，这种不同空间尺度的混合污染与气溶胶分布的多尺度特征密切相关。但当前的大气化学模式对多尺度混合污染的分析和预报能力不足，这主要是因为资料同化难以对观测和模式的多尺度信息进行有效融合，且对气溶胶的多尺度分布及其影响机制等方面的认识不够深入。本项目将基于气溶胶的地面观测资料、卫星AOD资料，以及WRF-Chem大气化学模式产品，利用谱分析方法研究气溶胶的空间多尺度特征，揭示影响多尺度特征的物理机制。在此基础上，构造气溶胶变量的多尺度背景误差协方差，估计观测资料误差，设计多尺度同化理论模型和技术方案，构建基于WRF-Chem模式的气溶胶变量多尺度同化系统，并进行试验验证。通过本项目的研究，将加深对气溶胶多尺度特征理论机制的认识，有效提高资料同化对多尺度信息的融合能力，为气溶胶的精细化分析和预报提供理论和技术支撑。

In recent years, the large scale haze usually occurs together with the local heavy pollution. This kind of mixed pollution with different spatial scales is closely related to the multiscale characteristics of the aerosol distribution. But current regional atmospheric chemistry models are limited for multiscale pollution forecasts. This is mainly because model data assimilation method cannot assimilate the aerosol multiscale information effectively. Meanwhile, our understanding of the distribution rules, scale divisions and influencing mechanism is not enough. In this project, we will carry out the following studies. The first is to study the spatial multiscale feature of aerosol, using spectral analysis method to calculate the spectrum from the ground observation data, satellite AOD data and numerical model products. The results will help us to understand the physical mechanism of the aerosol multiscale characteristics. The second is to estimate multiscale background error covariance matrices and multiscale observation errors. The third is to study the theory model and the technical solution of the aerosol multiscale assimilation. At last, a multiscale assimilation system for the WRF-Chem model will be estimated to assimilate aerosol variables, and this system will be verified by experiments of assimilation and forecast. Through these studies, we expect to understand the theoretical mechanism of aerosol multiscale characteristics, and to improve the capability of assimilating multiscale information in the data assimilation system. These studies will provide theoretical and technical supports for the fine analysis and forecast of aerosols.