Microphysical and kinematic analysis algorithms for a network of x-band radars (Formerly P8A.6)

The network of polarimetric X-band radars designed for the Integrated Project 1 (IP1) of the NSF Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) provide unprecedented observations of the lowest levels of the atmosphere, which are often problematic for the current NEXRAD network of S-band radars due to earth curvature effects at longer range. The dataset collected by the CASA radars affords the opportunity to study microphysical and kinematic properties of the lowest levels of the atmosphere, such as hydrometeor flux at the Earth's surface and wind features such as mesocyclones, convergence lines, and downdrafts. In-depth study of these types of features is expected to contribute to our understanding of storm initiation and development. Although there are many algorithms currently available to extract microphysical and dynamic information from radar data, the unique configuration and data collection methodology of the CASA radars, as well as the short wavelength, require modifications to these algorithms when adapting them from longer wavelengths for use with the CASA data. Adaptation of algorithms for multiple-Doppler wind synthesis and hydrometeor identification are described and applied to a set of case studies from the CASA network. The utility of hydrometeor identification algorithms, based on information provided by polarimetric variables, has been illustrated by numerous authors. However, X-band radars are highly susceptible to attenuation and Mie scattering affects, making direct application of S-band algorithms to X-band data difficult, if not impossible. Furthermore, the specific differential phase (Kdp) becomes much larger at X-band due to wavelength scaling. Theoretical simulations were performed to determine the scattering properties of rain, drizzle, snow and graupel (hail is excluded in our study due to complicating Mie affects at X-band). The results are used to form the basis for the Membership Beta Functions for a X-band fuzzy logic hydrometeor identification algorithm. Although the locations of the CASA radars are ideal for maximizing dual-Doppler and multiple-Doppler coverage, the restriction of data collection to the lowest levels of the atmosphere also limits accurate retrieval of the vertical component of the wind field using traditional multiple-Doppler wind synthesis techniques. The lack of data at the upper boundary condition complicate the integration of the continuity equation to estimate the vertical wind. Methodologies for overcoming this challenge are presented. One of the objectives of CASA is to utilize the unique network of high-resolution X-band polarimetric radar data to perform case studies that will enhance scientific understanding of storm microphysics. The above algorithms are applied to several case studies collected by the CASA IP1 network during the spring of 2007 to achieve this goal. Data are compared to local S-band radars, including the polarimetric KOUN radar.