Research On The Vertical Thinning Scheme And Assimilation For GPS Occultation Data

Data assimilation is an effective way to improve the quality of initial value for numerical prediction. The multi-source observation data and the background field are organically integrated to produce a more accurate analysis field, which can improve the quality of numerical forecast. The atmospheric temperature and humidity data derived from GPS occultation is an important data type for data assimilation, which have the advantages of high vertical resolution, high accuracy and less affected by cloud and precipitation. However, this data is too dense relative to the GRAPES model layer, and direct assimilation often results in data redundancy,which can reduce quality of analysis. Therefore, it is necessary to thin the data reasonably in order to give full play to GPS occultation atmospheric data on the contribution of the analysis.In order to avoid the data redundancy in the assimilation and improve the quality of the analysis, this paper establishes a new adaptive vertical thinning scheme that takes into account both non-uniform layered characteristics of height-terrain following vertical coordinates and the features of occultation retrieved data. A case and batch test are carried out for old and new thinning program to explore the impact of the new adaptive thinning scheme on the quality of analysis and forecast field.The results of case experiment indicate that GPS radio occultation retrieved data with the new adaptive thinning scheme leads to greater adjustment to the background field, higher quality analysis field and smaller root mean square error of prediction of geopotential height, temperature, specific humidity and wind field if suitable sparse parameter is chosen. In addition, the adaptive thinning scheme has a positive effect on improving the forecast of typhoon tracks, typhoon rainstorm area and intensity. The results of batch experiments show that the root mean square error of analysis field and the prediction field of each physical quantity from the adaptive thinning scheme is smaller than that of the unthinning scheme, which further confirms that the adaptive thinning scheme has a significant improvement in the quality of the analysis field and forecast field.