The high frequency channel of satellite passive microwave (PMW) imagers is a suitable choice for monitoring tropical storm (TC) movement and intensity because of its relatively high spatial resolution and ability to penetrate raining clouds, thus providing key TC structure, intensity, and location details. By using multiple satellite PMW imagers, we are able to globally track the life cycles of TCs in terms of location, intensity, structure, and rapid intensification. However, there is a key issue with this approach, i.e., the high frequency channel of every PMW imager is different from each other, which leads to varying brightness temperatures (TB) from different sensors monitoring the same TC at similar times. Thus, incorrect TC intensities could be derived due to confusion by satellite TC analysts world-wide. In order to overcome this problem, we develop a united scheme to calibrate all satellite PMW imager high frequency channel to a common 89 GHz so that their TBs will be consistent to allow a globally united view. The selection of 89 GHz channel is arbitrary, but based on the fact that this high frequency channel will be utilized in most future PMW sensors such as NASA Global Precipitation Measurement (GPM) microwave imager (GMI), JAXA Global Change Observation Mission (GCOM), and Advanced Microwave Scanning Radiometer-2 (AMSR-2). This calibration scheme is developed with the MM5 simulated TB s of a squall line system over the west Pacific coast and hurricane Bonnie over the Atlantic Ocean for different PMW sensors. Four different cloud conditions of clear sky, cloudy, rainy, and light rain are considered in the calibration process. In addition to the simulated TB, four matched TC cases between TMI 85 GHz and AMSR-E 89 GHz channels are analyzed. Results demonstrate a consistent TB calibration from 85 GHz to 89 GHz frequency with a maximum bias up to 10 K for heavy rain situations and -5 K for cloud free situations, respectively. By same token from two matched TC cases between SSMIS 91 GHz and AMSR-E 89 GHz channels, there are TB biases up to -3 K for rainy clouds and 1.5 K for cloud free conditions, respectively. With this new calibration scheme, the maximum TB bias between different PMW sensors is reduced from 10K into 1 K. This study demonstrates the importance of TB calibrations between PMW sensors in order to systematically monitor the global TC life cycles in terms of intensity, track and life span. A physics-based calibration scheme on TC's TB corrections developed in this study is able to significantly reduce the biases between different PMW sensors.