Resolving SSM/I-ship radar rainfall discrepancies from AIP-3

The third algorithm intercomparison project (AIP-3) involved rain estimates from more than 50satellite rainfall algorithms and ground radar measurements within the Intensive Flux Array (IFA) over the equatorial western Pacific warm pool region during the Tropical Ocean Global Atmosphere coupled Ocean-Atmosphere Response Experiment (TOGA COARE). Early results indicated that there was a systematic bias between rainrates from satellite passive microwave and ground radar measurements. The mean rainrate from radar measurements is about 50% underestimated compared to that from passive microwave-based retrieval algorithms. This paper is designed to analyze rain patterns from the Florida State University rain retrieval algorithm and radar measurements to understand physically the rain discrepancies. Results show that there is a clear range-dependent bias associated with the radar measurements.However, this range-dependent systematical bias is almost eliminated with the corrected radar rainrates.Results suggest that the effects from radar attenuation correction, calibration and beam filling are the major sources of rain discrepancies. This study demonstrates that rain retrievals based on satellite measurements from passive microwave radiometers such as the Special Sensor of Microwave Imager (SSM/I)are reliable, while rain estimates from ground radar measurements are correctable.