Abstract
The beam filling error is a significant problem in rain rate retrieval from passive microwave radiometer measurements from space. Rain will not be uniformly distributed throughout footprints of the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). This inhomogeneous rainfall distribution within the field of view (FOV) and non-linear relationship of rain rates and brightness temperature (R-T) produces errors. This error can be reduced if we have some information on rain/no-rain at a higher spatial resolution. The Visible IR Scanner (VIRS) on the TRMM observatory will provide cloud coverage, type and cloud top temperature at high resolution (2 km at nadir). In this study, we have examined how good the rain/no-rain criteria should be from VIRS in order to improve TMI rain retrievals using a simple passive microwave rain retrieval algorithm. It is found that the improvement in rain retrieval using VIRS rain/no-rain information depends on the intensity of rain rates. Generally, it is better to overestimate raining fractions of moderate and heavy rain within a footprint than underestimate them. On the other hand, it is better to underestimate raining fractions of light rain than overestimate them. We can have improvements of rain retrievals by the TMI in heavy rainfall (r > 20 mm hr-1) with the aid of VIRS measurements when scattering effects are considered.
