Passive microwave precipitation detection biases: Relationship to cloud morphology

Abstract:

Accurate measurement of the Earth’s hydrologic cycle requires a more precise understanding of precipitation accumulation and intensity on a global scale. While there is a long record of passive microwave satellite measurements, passive microwave rainfall retrievals often fail to detect light precipitation or have light rain intensity biases because they cannot differentiate between emission from cloud and rain water. Previous studies have shown that AMSR-E significantly underestimates rainfall occurrence and volume compared to CloudSat. This underestimation totals just below 0.6 mm/day quasi-globally (60S-60N), but there are larger regional variations related to the dominant cloud regime. This study aims to use Moderate Resolution Imaging Spectroradiometer (MODIS) and the 94-GHz CloudSat Cloud Profiling Radar (CPR), which has a high sensitivity to light rain, with the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) observations, to help better characterize the properties of clouds that lead to passive microwave rainfall detection biases. CPR cloud and precipitation retrievals. AMSR-E Level-2B Goddard Profiling 2010 Algorithm (GPROF 2010) rainfall retrievals, and MODIS cloud properties were collocated and analyzed for 2008. Results are consistent with past studies and show large passive microwave precipitation detection biases compared to CloudSat in stratocumulus and shallow cumulus regimes. A preliminary examination of cases where AMSR-E failed to detect precipitation detected by CloudSat shows that over 50% of missed warm precipitation occurs in clouds with top heights below 2 km. MODIS cloud microphysical and macrophysical properties, such as optical thickness, particle effective radius, and liquid water path will be analyzed when precipitation is detected by CloudSat and missed by AMSR-E. The overall goal is to understand how cloud morphology relates to detection biases.