Analysis Of Typical Rainstorm Cases And Improvement Of Wind Field Interpolation

Heavy rain is one of the most common severe weather in China in the summer.In particular,a wide range of continuous heavy rain and torrential heavy rain not only affects industrial and agricultural production,but also endangers people's lives and cause serious economic losses.There are the many factors affecting the storm forecast,and wind is one of the important factors.It may have a significant impact on the evolution of the rainstorm mesoscale system and the intensity and distribution of the associated rainstorms.Because the wind field is a vector,it is a very important task in data assimilation of the wind field to interpolate wind field data of irregular site wind field data and regular pattern grid points without affecting interpolation accuracy.This paper analyzes the problem of how to effectively interpolate horizontal wind field data,improve the initial quality of numerical models,and improve techniques of heavy rain forecast.This paper analyzes the heavy rain on June 1,2015 in the Jianghan Plain and the extreme rain in the Tianshan Mountains on June 9 by synoptic method,and the influence of the wind field on the intensity of the storm's center was emphatically studied.The results show that the occurrence and development of heavy rain depend not only on the large-scale situation,but also have a close relationship with the mesoscale wind field.The wind is one of the sensitive factors affecting the heavy rain.Then,we study the interpolation of wind field data.Firstly,there was a single point experiment of wind data interpolation.The results showed that: when the wind direction of the wind field is the same,indirect interpolation(that is,the north-south v,east-west u wind value interpolation calculation)and direct interpolation(that is,the use of wind direction and wind speed values are interpolated to obtain the same wind speed and wind direction value;when the wind field has divergence convergence,wind speed and wind direction values obtained by indirect interpolation and direct interpolation are inconsistent.Then the ideal test is conducted.The experimental results show that the wind speed error distribution obtained by indirect interpolation and direct interpolation is basically the same,and the error size is similar.The error of indirect interpolation is less than direct interpolation.Whether it is direct wind direction interpolation or indirect wind direction interpolation,there is a deviation of 10-20° in the wind direction.There are certain deficiencies in the two schemes of wind field interpolation,which needs optimization and improvement.Finally,optimize the interpolation scheme for wind data,and increase the temperature difference weight factor in the indirect interpolation scheme.By analyzing the correlation between the temperature and the wind field data root means squared error,and improving the wind field interpolation scheme.The results show that the correlation between temperature root-mean-square error distribution and root mean square error of the wind field is higher at lower levels,and the correlation between the root means square error distribution of the temperature and the root mean square error of the wind field gradually decreases at the middle and high levels.Based on the analysis of the correlation between temperature and wind field root mean square error,the interpolation scheme is optimized by adding the temperature difference weight factor in the indirect interpolation scheme.The result shows that the wind field obtained by the improved indirect interpolation is closer to the real value.