Application Of CNOP On High-impact Weather In The Middle-lower Yangtze Area

In order to improve the numerical prediction of high-impact weather events in the middle-lower branches of Yangtze River, an adaptive observation experiment for a winter storm case (a high-impact weather event) is presented in this paper using the conditional nonlinear optimal perturbation (CNOP) method based on dry energy norm condition and24hours accumulated rainfall error norm condition respectively. Analyzed in detail the pattern of conditional nonlinear optimal perturbation was calculated and the feature of sensitive areas was defined by CNOP method. Furthermore, a set of observing system simulation experiments (OSSEs) is performed to evaluate the effectiveness and feasibility of the method based on different norm conditions in determining the sensitivity area, and further analyzed the reasons for improving the24hours precipitation forecast in the verification area.The main conclusions in this paper as follows:1. Through analysis the structure of CNOP which calculated by conditional nonlinear optimal perturbation method based on dry energy norm condition and24hours accumulated rainfall error norm condition respectively, it is found that the structure of CNOP has the local features in the horizontal direction, and presents an obvious baroclinic structure in the vertical direction, which could partly explain the reasons for the rapid development of CNOP.2. The structure of CNOP which calculated by conditional nonlinear optimal perturbation method based on different norm conditions are differences. Besides, the sensitive areas which defined by CNOP method based on different norm conditions are differences obviously. Which is to say that the sensitive areas which defined by CNOP method depended on norm conditions.3. By improving the quality of the initial conditions in the sensitivity areas which identified by the CNOP method based on the dry energy norm condition and24hours accumulated rainfall error norm condition respectively, the24-h accumulated rainfall prediction errors and total energy prediction errors in the verification region are significantly reduced compared to the "truth". Further analyses reveal that the improvements of the initial conditions (such as the water vapor flux and the low-level cold air activities) in the sensitivity area can not only well describe the initial structures of the high-impact weather system but also more accurately reproduce the temporal evolution features of the weather system, thus resulting in the decrease of the prediction errors in the verification region. The results indicate that it is feasible to use CNOP method in the study or practice of the targeting observations for high-impact weather events in the middle-lower branches of Yangtze River. In addition, through comparative analysis, the CNOP method based on precipitation error norm codition is better than the CNOP method based on dry energy norm condition in identifying the sensitive areas corresponding to the winter storm.