HR: 16:15h
AN: H24C-02    [Abstracts]
TI: Combined Radar-Radiometer Retrieval of Precipitation Structures
AU: * Munchak, S
EM: jmunchak@atmos.colostate.edu
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523- 1371, United States
AU: Kummerow, C
EM: kummerow@atmos.colostate.edu
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523- 1371, United States
AB: Satellite rainfall estimates from microwave radiometers (e.g., SSM/I, AMSR-E), and, more recently, spaceborne radar (TRMM, CloudSat) have provided the ability to measure precipitation globally. However, the remote sensing of rainfall requires assumptions in both radar and passive microwave radiometer algorithms that may not be uniformly applicable in all regions. These assumptions are required due to the limitations of the instrument and related to the wide variety of rainfall physical processes (e.g., convective vs. stratiform, warm vs. cold cloud). These processes lead to differences in the raindrop size distribution (DSD) and cloud profiles on a wide range of spatial and temporal scales. Radar algorithms are particularly sensitive to the DSD, whereas radiometers, while less sensitive to DSD, can only sense column-integrated liquid water over a large area, where rainfall is unlikely to be uniform. Combined retrievals incorporate the high-resolution radar profiles with the areally integrated constraint provided by the radiometer to produce a rainfall estimate that is consistent with both. However, the mismatch of resolution and field of view between radar and radiometer measurements complicates the formulation of combined algorithms. An optimal estimation methodology has been applied to adjust radar retrievals using radiometer-observed brightness temperatures, incorporating a priori knowledge about the spatial structure of raining systems in the retrieval. The adjustments made by this algorithm to radar-only retrievals are consistent with the known biases of the radar algorithm caused by DSD assumptions. The combined retrieval, therefore, has the potential to improve observations of the distribution of global rainfall and rainfall processes.
DE: 1836 Hydrological cycles and budgets (1218, 1655)
DE: 1855 Remote sensing (1640)
DE: 1895 Instruments and techniques: monitoring
SC: Hydrology [H]
MN: 2007 Fall Meeting