The increased frequency of PMW passes over tropical cyclones, especially from higher-resolution sensors, has provided a recent and rich historical record. PMW identifies structural characteristics that are often hidden under the cirrus overcast seen on visual and infrared satellite imagery of more intense tropical cyclones. PMW reveals, to a certain resolution, the underlying precipitative framework of the tropical cyclone and indications of cloud structure. An understanding of the vertical structure is obtained by evaluating PMW at different frequencies in tandem with information from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). While PMW over any one tropical cyclone is infrequent compared to geostationary satellite imagery, the composite information provided by many PMW passes over many tropical cyclones provides a continuity of progressive formations.
Because the Dvorak technique of estimating current tropical cyclone intensity is based on a classification scheme of cloud structure based on visual and infrared satellite imagery, it is prudent to address whether a typed set of PMW could be similarly useful, either by yielding information on current intensity, or in identifying intensity changes and intensity trends of tropical cyclones. Future work will compare the set of microwave imagery, once typed, with available data such as recon observations, operational vs. best track intensities and best track fix files, to see if a range of intensities can be associated with the PMW tropical cyclone development model.
The study uses North Atlantic basin passive microwave imagery of tropical cyclones from 2003-2009 and specific examples from other basins, reviewing the 36-37, 85-92, and 150 GHz channels, drawing from an archive of PMW available and maintained online by the Naval Research Laboratory Monterey (NRLMRY). This includes PMW from the TRMM Microwave Imager (TMI), Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E), WindSat, and Special Sensor Microwave/Imagers (SSM/I and SSMI/S). In addition, the analysis uses imagery from the Univ. Of Utah TRMM Tropical Cyclone Precipitation Feature (TCPF) Database, including data from the TRMM PR.
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