Determination of Winter Precipitation Types.

摘要

Parallel to the observational efforts, work has continued to develop an improved hydrometeor classification algorithm that combines polarimetric radar observations with thermodynamic information from numerical models. In addition to providing more information to aid in the interpretation of polarimetric signatures, the thermodynamic information provides a mechanism to produce surface-based classification results at distant ranges from the radar, where low-level layers of warm/cold air that fall well below the lowest available radar data might result in microphysical processes that would otherwise remain undiagnosed. The benefit of adding the thermodynamic data is therefore twofold: (1) to enhance classification capabilities in regions where polarimetric radar data are available, and (2) to extend classification capabilities to regions where it is not. The project also seeks to provide an algorithm framework that allows ongoing observational work, as listed above, to be easily incorporated into future algorithm development with the long term goals of improving automated precipitation type classification at both the surface and aloft, including the capability to remotely diagnose conditions favorable for liquid water generation.