Passive Microwave Precipitation Detection Biases: Relationship to Environment

Abstract:

Accurate satellite precipitation estimates are essential for understanding the long-term variability in the global hydrologic cycle and for constraining global climate models. Spaceborne precipitation estimates depend heavily on passive microwave remote sensors due to the large spatial coverage and long record of observations available from such sensors; however, light precipitation is frequently undetected or underestimated by passive microwave rainfall retrievals. Observations from the CloudSat Profiling Radar (CPR) and the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) provide a unique opportunity for long-term collocated precipitation measurements from passive microwave sensors and an active radar with sensitivity to very light precipitation that can be used to assess the precipitation detection biases. For this study, collocated measurements from AMSR-E and CloudSat during 2008 will be used to identify environments where AMSR-E underestimates precipitation. Environmental variables from the ECMWF Reanalysis (ERA-Interim) will be used to understand the characteristics of the large-scale and thermodynamic environments associated with AMSR-E precipitation biases. A preliminary comparison of CPR rain rates and AMSR-E Level-2B rain rates show a large fraction of rain missed by AMSR-E, with nearly 80% of missed light rain in regions with SSTs below 25°C. This is consistent with prior studies showing large detection biases in regions of large-scale subsidence. The relationship between precipitation biases and other factors such as 2 m air temperature, column water vapor, lower tropospheric stability, and vertical velocity will be explored.