Traditional variational data assimilation （VDA） with only one regularization parameter constraint cannot produce optimal error tuning for all observations. In this paper, a new data assimilation method of ＂four dimensional variational data assimilation （4D-Var） with multiple regularization parameters as a weak constraint （Tikh-4D-Var）＂ is proposed by imposing different reg- ularization parameters for different observations. Meanwhile, a new multiple regularization parameters selection method, which is suitable for actual high-dimensional data assimilation system, is proposed based on the posterior information of 4D-Var system. Compared with the traditional single regularization parameter selection method, computation of the proposed multiple regularization parameters selection method is smaller. Based on WRF3.3.1 4D-Vat data assimilation system, initiali- zation and simulation of typhoon Chaba （2010） with the new Tikh-4D-Var method are compared with its counterpart 4D-Var to demonstrate the effectiveness of the new method. Results show that the new Tikh-4D-Var method can accelerate the con vergence with less iterations. Moreover, compared with 4D-Var method, the typhoon track, intensity （including center surface pressure and maximum wind speed） and structure prediction are obviously improved with Tikh-4D-Var method for 72-h pre- diction. In addition, the accuracy of the observation error variances can be reflected by the multiple regularization parameters.
Based on a successful simulation of Typhoon Haikui(2012) using WRF(Weather Research & Forecasting)model with the WSM6 microphysics scheme, a high-resolution model output is presented and analyzed in this study. To understand the cause of the average gridded rainfall stability and increases after Haikui's landfall, this research examines the fields of the physical terms as well as the vapor and condensate distributions and budgets, including their respective changes during the landing process. The environmental vapor supply following the typhoon landfall has no significant difference from that before the landfall. Although Haikui's secondary circulation weakens, this circulation is not conducive to typhoon rainfall stability or increases, although the amounts of the six kinds of water substances(vapor,cloud water, cloud ice, snow, rain, and graupel) increase in the outer region of the typhoon. This reallocation of water substances is essential to the maintenance of rainfall. The six kinds of water substances are classified as vapor, clouds(cloud water and ice) and precipitation(snow, rain, and graupel) to diagnose their budgets. This sorting reveals that the changes in the budgets of different kinds of water substances, caused by the reduced mixing ratios of snow and ice, the water consumption of clouds, and the transformation of graupel, induce increased concentrations of precipitation fallout,which occur closer to the ground after typhoon landfall. In addition, this pattern is an efficient way for Haikui's rainfall to remain stable after its landfall. Thus, the allocation and budget analyses of water substances are meaningful when forecasting the typhoon rainfall stability and increases after landfall.
