Monday, 7 January 2013
Exhibit Hall 3 (Austin Convention Center)
Handout (11.7 MB)
Satellite remote sensing offers new and unique insights for the study of cloud and precipitation systems. A contemporary instrument for cloud mapping is the Cloud Profiling Radar (CPR), which is the first spaceborne cloud radar onboard NASA's CloudSat satellite (http://cloudsat.atmos.colostate.edu/). CPR operates at W-band (94 GHz) and provides good sensitivity for measuring the vertical structure of cloud liquid/solid water distribution. On the ground, the Next-Generation Radar (NEXRAD) network has proven its value for nation-wide weather observations. An advanced quantitative precipitation estimation (QPE) system based on NEXRAD is NOAA's National Mosaic and Multisensor QPE system (NMQ, http://nmq.ou.edu). Since June 2006, NMQ has been generating high-resolution, national 3-D reflectivity mosaics (31 vertical levels) and a suite of severe weather and QPE products at a 1-km horizontal resolution and 5-min update cycle. The polarimetric NMQ will be available in 2013. These products are being merged with CPR observations to yield better depictions of storm structures and microphysical processes. Mixed-phase clouds account for the majority of convective precipitation and concomitant severe weather over continental regions. The understanding of icing conditions in the mixed-phase clouds is important to estimate and forecast icing hazards with radar observations. This issue is especially critical for aviation and ground transportation. The current study investigates the potential of detection and identification of supercooled liquid drops (SLD)/freezing drizzle (FZ), which are believed to be responsible for hazardous aircraft icing, using observations from spaceborne and ground-based radars. Scattering characteristics of SLW/FZ, ice crystals, and graupel/snow at W-band (94 GHz) and S-band (2.8 GHz) frequencies are studied according to the scattering theory. Research products from the CloudSat mission and NMQ, including vertical profiles of reflectivity, liquid water content, characteristic size, temperature, cloud type and phase, are utilized to assist with the discrimination of SLD/FZ from other hydrometeors. The combination of CloudSat and NMQ demonstrates the potential in enhancing the hydrometeor classification in the sub-freezing region.
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