This paper presents an evaluation of over-land rain-rate estimates by both the Global Satellite Mapping of Precipitation (GSMaP) algorithm and the standard (GPROF) algorithm for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), by comparing them with estimates by the standard algorithm for TRMM Precipitation Radar (PR). This study has the following advantages over previous studies: (1) the errors in rain-rate estimates are decomposed into those caused by rain/no-rain classification and those caused by rain-rate retrieval, (2) the quantitative effects of bright band height (BBH) and land surface physical temperature on retrieval are evaluated; and (3) the role of lower frequency channels (37.0 GHz and lower) for retrieval is investigated. GSMaP yields monthly average and zonal mean rain-rate estimates close to those estimated by the standard algorithm for PR, as it refers to a database produced with PR data. However, GSMaP and GPROF overestimate (underestimate) rain rates for tall (shallow), stratiform (convective), and evening (morning) rainfall. Dependence on storm height (SH) is unavoidable as long as the algorithm relies on the scattering signal caused by solid precipitation for higher frequency channels (85.5 GHz). Lower frequency channels are secondarily used in some algorithms to mitigate the above bias characteristics to some degree. In GSMaP Version 4.7, the severe overestimation seen in GSMaP Version 4.5 when SH is higher than 10 km is mitigated by using 37.0 GHz observations as a scattering signal. The following are indicated for stratiform rainfall with a bright band (SRBB). While the rain-rate estimates are negatively dependent on BBH in GSMaP, the use of 21.3 GHz and 10.7 GHz observations resulted in the cancellation of the dependence on the BBH in GPROF. Although lower-frequency observations are subject to variation in land surface physical temperature, no significant effects of land surface physical temperature on the rain-rate estimates were observed in this study. To improve over-land rain-rate estimates, it is important to make the most effective use of lower-frequency observations.