The primary objective of this study is to assess the accuracy of satellite derived estimates of rainfall data for strong hurricanes. Seven satellite-based rainfall retrieval algorithms have been selected to be evaluated against NEXRAD Stage-IV and rain gauge observations for six very strong hurricanes after landfall. These algorithms are four high resolution (hourly, 4km x 4km) satellite infrared-based rainfall data: Hydro-Estimator (HE), GMSRA, and SCaMPR from NOAA-NESDIS and PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), two TRMM 3-hourly, 4km x 4km products: 3B40RT (microwave product) and 3B42RT (blended passive microwave and IR), and the IR and microwave based NOAA CPC Morphing Technique (CMORPH) at 3-hourly, 8km x 8km resolution. Three strong hurricanes: Charley, Jeanne, and Frances that caused devastating damages over Florida in the summer 2004 and also three very strong hurricanes: Katrina, Wilma, and Rita from summer 2005 have been considered to be investigated. Preliminary results reveal that the estimates and the observations show different spatial distributions of rainfall and also the estimates tend to underestimate the total volume and peak values of rainfall. This study also demonstrates that there is little agreement between time variability of spatially averaged of estimates and NEXRAD Stage IV radar, particularly for intense rainfall.