Abstract: Objectives: Atmospheric delay is one of the main error sources ininterferometric synthetic aperture radar （ InSAR） surface deformation monitoring. Using the global meteorological model to correct the tropospheric delay has been successfully applied in recent years. In this paper, an InSAR atmospheric correction method is presented, which introduces China's first Generation Global Atmospheric reanalysis data (CRA). Taking into account the physical characteristics of tropospheric meteorological parameters, the method was tested in Los Angeles, Southern California, and evaluated quantitatively. The results show the feasibility of CRA products in InSAR atmospheric correction. Methods： The meteorological parameters such as temperature, water vapor and air pressure are obtained by CRA, taking into account the spatial variation characteristics of atmospheric parameters, according to the vertical stratification characteristics of meteorological data, the piecewise function is used to interpolate in the vertical direction. By considering the spatial variability of the atmosphere, the interpolation is carried out in the horizontal plane. According to the results, the atmospheric delay is calculated along the satellite line of sight. The atmospheric correction result is obtained by difference with the original interferogram. Verify and analyze the results, first, the error analysis is carried out from three aspects: Interferogram standard deviation, spatial correlation and phaseelevation correlation coefficient; second, it is compared with the results of GACOS and PyAPS methods; Finally, 78 interferograms obtained from 40 scenes Sentinel-1 data of Southern California based on short baseline principle are used to carry out sequential deformation measurement experiments, the proposed method is compared with classical SBAS-InSAR results, and verified by GPS data. Results： The results show that: (1) The average standard deviation of the corrected interferogram is reduced by 34.7%, The average standard deviation of 65% interferograms has been reduced by more than 20%., especially for the interferograms which are seriously affected by the atmosphere. It is better than GACOS and PYAPS with an average improvement of 30%. (2) The significant decrease of the expected square variance of the spatial structure function of the interferogram shows that the product can effectively suppress the long-wave atmosphere. (3) The change of fitting coefficient of correlation shows that the product can effectively reduce the atmospheric vertical stratification component caused by the influence of elevation. Depending on the degree of atmospheric influence, CRA can improve the vertical stratification component of the atmosphere, ranging from 20% to 60% or more. (4) It is effective to take the spatial variation of convection into account when establishing a high-resolution InSAR tropospheric delay map using low-resolution global atmospheric model data. Conclusions： This paper confirms that CRA can correct and improve the overall accuracy of deformation monitoring. Through quantitative evaluation, researchers can fully understand the correction effect and performance of this product, which is helpful to promote the application and development of this product. However, due to the differences of external data, follow-up research can combine GNSS data with CRA solution to further improve the accuracy of InSAR atmospheric correction.