基于卫星资料梯度信息的新型变分同化方法对于台风数值模拟的研究

卫星资料凭着卫星遥感的全球性、连续性和高频次观测等优势，成为一种重要的非常规资料源，但卫星观测仍然存在各种各样的观测误差，其中包含由于观测偶然性所造成的统计学上的随机误差及仪器本身和辐射传输模式等造成的系统性偏差，这些误差在很大程度上影响了卫星资料的质量。文中提出了一种能有效订正卫星观测资料系统性偏差的梯度信息同化算法，该方法用一个梯度算子进行模式变量与观测变量的梯度变换，从而达到订正系统性偏差的目的。本文利用WRF（Weather Research Forecast）模式及其同化模式WRFDA（WRF Data Assimilation system），以及AIRS（Atmospheric Infrared Sounder）资料，对台风“圆规”进行了实际的数值模拟和同化试验，数值结果表明，梯度信息同化方法能明显改善台风路径的模拟，在处理可信度较低的资料时仍然适用。另外，通过同化诊断分析，发现卫星资料的系统性偏差对于台风数值模拟有较大影响，而文中提出的梯度信息同化方法能较好的解决此类问题。

A New Variational Assimilation Method for Numerical Typhoon Simulation Based on Gradient Information of Satellite Data

Satellite data has been widely used as a non-conventional meteorological data in numerical weather prediction due to its global coverage and continuous,high-frequency observations.However,there are a variety of observation errors in satellite observations,including the random errors caused by the contingency of observations and systematic errors brought by the instrument itself and introduced by the Community Radiative Transfer Model,which influence the quality of satellite data to a large extent.A method of gradient information assimilation to correct the systematic errors of satellite data is proposed in this paper,which uses a gradient operator to make gradient transformation between the model variables and observation variables and realize the objective to eliminate the systematic errors.A numerical simulation of typhoon Kompasu is then conducted using the WRF (Weather Research Forecast) and WRFDA (WRF Data Assimilation system) model as well as the AIRS (Atmospheric Infrared Sounder) data.The results indicate that the method of gradient information assimilation can greatly improve the simulation of Kompasu''s track,and the method can also be applied to process data of low reliability.In addition,through the assimilation diagnosis analysis,it is found that the systematic deviation of the satellite data has a great impact on numerical simulation of typhoons,and the gradient information assimilation method proposed in this paper can solve this kind of problem.