Our previous study showed that assimilation of GOES imager radiance with conventional observations could lead to a significant improvement in the quantitative precipitation forecasts (QPFs) near Gulf of Mexico (Zou et al., 2011). In our continual studies, impacts of GOES imager radiances on coastal QPFs are examined in the presence of other satellite observations (e.g., AMSU-A, AIRS, HIRS3/4, MHS, GOES Sounder etc.) which have been assimilated in Gridded Statistical Interpolation (GSI) system. Numerical experiments show that direct assimilation of GOES imager radiances in clear-sky conditions can result in a large positive impact on QPFs, compared to all other types of observations. It is also shown that the impact of the AMSU-A data on this coastal QPF ranks the highest among all the experiments while that of the GOES imager radiance is the second. It is clearly demonstrated that adding MHS and/or GOES sounder data to the AMSU-A experiment significantly degraded the forecast skill and the GOES imager radiances can further improve the forecast skill. The reasons that MHS and GOES sounder radiances produce such a negative impact are still not very clear. Perhaps, the quality control and bias correction schemes of MHS and GOES sounder data in GSI are poor and need to be further optimized.