| The GPS data from GPS networks in Yangtze delta is explored to investigate the improvement of MM5 simulation on rainfall event occurred over Meiyu period in 2002 with the aid of initial humidity fields reanalysis and assimulation. The results show:1, GPS is a valuable tool of observing water vapor in atmosphere consecutively. GPS observation which is about 2km far away from radiosonde site is comparable to radiosonde with a absolute bias of 2.13mm on precipitable water (PW) observation and 1.28cm on zenith total delay (ZTD). The variation of ZTD is mainly caused by the zenith wet delay (ZWD). zenith hydrostatic delay (ZHD) and ZWD from different GPS sites exhibit individual features that ZHD has a obvious periodic change and ZWD is related to weather. Accuracy of PW retrieved from GPS observation can be improved by using the average vertical temperature calculated from MM5 outputs.2. The reanalysis fields of MM5 can reveal the distribution of ZHD as a whole and has larger bias on ZWD and PW than ZTD. 12h-simulation of MM5 can show the daily change tendency of ZTD, ZHD, ZWD and PW with a bias in depicting their hourly change. MM5 has a ability of simulating ZWD on the whole with a bias larger than ZHD's, which manipulates the bias of ZTD simulation. The increase of MM5 resolution can improve the ability of simulating and depicting ZHD, ZWD and PW distribution.KF, BM and Grell parametric schemes have a close ability of simulating PW at the beginning of 10-11h integration of MM5 model, and then the prediction bias of PW increases obviously after 20-21h integration. Grell scheme can simulate PW more accurate than others for coarse grid of MM5 and PW simulation of BM scheme is less accurate than others for fine grid of MM5.3, The initial humidity fields reanalyzed by using GPS PW can obviously improve its capability in revealing the water vapor distribution, which can result in restraining PW prediction bias during the earlier period of model integration so as to improve PW prediction. Nudging assimulation of PW can improve prediction slightly, and increasing nudging gain coefficient play a little role in improving prediction. It'salso found that the reanalysis influences the results of 6h accumulated precipitation through changing the non-convective precipitation prediction mainly, while results improved by the nudging assimulation are substantially associated with convective precipitation change. On the whole, better results are obtained by the reanalysis than by the nudging assimulation.4, Background errors (BE) play a key role in three dimensional variation assimulation (3dvar). The BE calculated by NMC technique reach the true BE more closely than that provided by MM5-3dvar system. The horizontal scalelength of model variables (u. v. T, p and q) is closely related to the average time of NMC technique and convective parameteric scheme of MM5 which affect the 12h and 24h outputs of MM5 integration. The scalelength of model variables is different for each other, which value is associated with the vertical height of the variable on the MM5 level.5, GPS PW data can be assimulated into MM5 by using 3dvar technique. After GPS PW data assimulation, the initial humidity field can be reanalyzed while the initial temperature, pressure and wind fields also being modified. Although MM5 with the Cressman objective analysis predicts the first 6h accumulated precipitation more accurately than 3dvar of GPS PW data, vice versa for 6-18 h accumulated precipitation. On the whole, GPS PW data assimulation will improve precipitation prediction.6, GPS ZWD assimulation ingests atmospheric information observed by GPS into MM5 initial fields more easily than GPS PW assimulation so that the initial fields of humidity, temperature, pressure and wind can be modified in a greater degree. In general, 6h accumulated rainfall prediction of MM5 is improved by 3dvar of GPS ZWD data more significantly than GPS PW data although the former improvement is related to the rainfall amount.
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