Comparison of warm rain detection and quantification from spaceborne passive microwave and radar sensors

We present a recently developed warm rain climatology from CloudSat and explore the sensitivity of that climatology to algorithm parameter assumptions. The CloudSat climatology is compared with coincident observations from the GPROF-2010 algorithm applied to AMSR-E and an analogous warm rain climatology from the TRMM Precipitation Radar (PR) with an eye towards identifying potential areas for improvement ahead of the launch of the Global Precipitation Measurement (GPM) mission. GPROF-2010 is found to frequently misclassify lightly raining scenes as non-precipitating. The rate of misclassification is found to decrease with increasing rain rate and length scale of precipitating systems suggesting a pathway for refinement of the passive microwave algorithm through the cloud and rain water partitioning inherent in the GPROF database. It is found that the PR and CloudSat produce similar spatial distributions of warm rain with the PR underestimating the CloudSat accumulations. CloudSat data are used to simulate both PR and Dual-frequency Precipitation Radar (DPR) reflectivities. These simulations suggest that the PR may miss light warm rain due to both sensitivity and resolution limitations and that the DPR will substantially improve warm rain detection.