Satellites equipped with microwave radiometers have provided meteorological data for weather forecasting, climate studies, and global climate models since the late 1970s. In recent years, these satellites have greatly improved their latitudinal extent and continue to deploy more refined sensors. The Defense Meteorological Satellite Program (DMSP) deploys the SSM/I microwave radiometer from 50N to 50S and has been collecting cloud top brightness temperatures as indirect measures of precipitation rates in ocean environments since 1987.

A long-standing concern in satellite data processing is the lack of "ground truth", which aids in the calibration of sensors in remote regions like the open oceans. It has already been established through comparisons with other satellite systems that the SSM /I sensor underestimates precipitation due to a beam filling problem associated with the radiometer's design and that the indices by which brightness temperatures are classified may assign a precipitation event to cirrus cloud formations that do not ordinarily contain precipitable moisture.

Fifty years of ship-borne data are compared with data derived from the SSM / I for correlations of precipitation events over the open oceans. Results from this study examine daily weather observations, sea surface pressure, and precipitation amounts with the indices classifying the SSM / I data. Biases found include sensor design, indexing, and equatorial crossing times that may influence the precipitation classifications in the SSM / I dataset.