Study On Combination Technology Of Multi-source Observed Data Into LAPS System And Its Application To GRAPES Model

Source codes of preprocess module is revised and extended so that it has been capable of combining MICAPS numerous data including surface, sounding and other intensive data into the Local Analysis and Prediction System (LAPS), which is introduced by Institute of Heavy Rain, Chinese Meteorological Administration. Preprocessed programs of cloud-tracked wind data from FY2C/D satellite incorporated into the LAPS system is devised and composed under the condition of no source codes. And interface routines between the Global/Regional Assimilation and Prediction System (GRAPES) and LAPS system is developed and it's first time in China. Guangdong and Guangxi province is selected as two researched area, localization experiments and its application research are done utilizing surface, sounding, other intensive data and several new generation Doppler radar observation data during 2008-2010. The following are the main conclusions and results:(1) NCEP reanalysis data which selected as background fields of LAPS system are improved through combining multi-source observation data into LAPS based on numerous schemes of data combination. Analysis field of multi-source data is better than single observation data. Comparing analysis field of wind by combining multi-source data into LAPS and NCEP reanalysis data, it's showed that LAPS analysis field of wind is better close to the wind field computed by radar reflectivity data observed by several Doppler radar.(2) The heavy rain process occurred at Guangdong and Guangxi province on May 17-19, 2008 is diagnosed and analyzed using LAPS system which combined multi-source observation data. Results showed that the heavy rain is produced by several mesoscale and microscale weather systems. Characteristics of strengthening and weakening of low-level jet stream is obvious during the heavy rain process. Characteristics of mesoscale and microscale weather systems during the heavy rain process is described through combing multi-source data into LAPS system.(3) By developing interface routines between GRAPES and LAPS systems, analysis field outputted by LAPS can be provided as the initial condition of GRAPES model directly.(4) Through analysis of 28 heavy rain cases during 2008-2010 and comparing initial field outputted by LAPS system, that produced by three-dimensional variational methods(3DVAR) in GRAPES model and observation data, the error between wind and temperature field outputted by LAPS and observation data is less than that of 3DVAR scheme, but the error of height field outputted by LAPS is large than that of 3DVAR scheme. The TS score of 24 hour precipitation forecasts from two initial field outputted by LAPS and 3DVAR scheme is compared. The results showed that TS score values of two initial field is almost equal. But score values of the initial field outputted by LAPS during moderate and heavy rain are higher than that of 3DVAR scheme. The improvement effects of moderate and heavy rain forecasts using initial field outputted by LAPS system is better than that of 3DVAR scheme in GRAPES model. The researched results showed that more variation information of mesoscale and microscale weather systems is included in the initial field outputted by LAPS, which combined multi-source observation data into the LAPS system.