• Evaluate the technical design for polarization diversity (i.e., evaluate the simultaneous transmission scheme without high-power switch).
• Demonstrate the accuracy of KOUN reflectivity, velocity, and spectrum width measurements through comparisons with conventional WSR-88D radar data.
• Demonstrate the accuracy of KOUN polarimetric measurements through comparisons with high-quality research polarimetric radar data.
• Demonstrate the improvement in KOUN polarimetric precipitation estimation and hydrometeor classification products over those generated with conventional WSR-88D radar data.
• Demonstrate that polarimetric precipitation estimation and hydrometeor classification products can be collected with acceptable antenna rotation rates (all previous research results were obtained with relatively slow scan strategies).
• Perform tests to ensure minimal degradation in VCP times, and no degradation in ground clutter filtering, anomalous propagation filtering, and velocity dealiasing.
• Demonstrate the polarimetric WSR-88D radar improvement in rainfall estimation:
• Estimate the accuracy for small scale area rainfall estimation (e.g., for one- hour/one-gage accumulations)
• Estimate the accuracy for areal average rainfall estimation (e.g., for typical watershed accumulations)
• Examine the relative performance of polarimetric and conventional rainfall estimators as a function of range.
• Demonstrate the polarimetric WSR-88D radar?s ability to classify different types of meteorological and non-meteorological echoes.
• Rain/hail
• Rain/snow (for cold season)
• AP
• Birds versus insects
• Snow / water in non-precipitating clouds - icing
• Demonstrate how improvements in polarimetric radar QPE can be used to improve operational hydrologic forecast products (especially for intense flash flood events).

Science Project Goals:
 

• Improve physical understanding of polarimetric signatures.
• Conduct verification and comparison studies of radar rainfall products. Compare conventional and polarimetric radar rainfall estimates.
• Collect data that can be used to evaluate the accuracy of operational precipitation and hydrometeor identification algorithms.
• Investigate the effect of natural drop size distribution variability on conventional and polarimetric rainfall estimators.
• Investigate the effect of drop oscillations and canting angles on conventional and polarimetric rainfall estimators.
• Examine the accuracy of hydrometeor classification schemes through detailed comparisons with verification data sets.
• Use verification data sets to develop hydrometeor quantification schemes.
• Investigate how microphysical information derived from polarimetric radar measurements can be used in cloud resolving models.
• Examine the microphysical basis for drop size distribution variability in both cold and warm season precipitation events.
• Investigate source of typical overestimation of extreme ?cold-process? rain and underestimation of extreme ?warm-process? rain.
• Investigate how improved precipitation estimates from polarimetric rainfall measurements can be used to initialize hydrologic models.
• Measure streamflow and runoff and conduct hydrologic modeling studies. Investigate how input data uncertainties influence flood prediction, the maximum time/space scales required to accurately simulate a flash flood, and the basin characteristics that are most important in transforming rainfall into runoff.
• Conduct polarimetric S-band radar intercomparison studies with polarimetric Ka- and X-band radars.
• Assess how Ka-band (hydrometeor identification) and X-band (precipitation) measurements can be used to improve interpretation of polarimetric S-band radar data.

• Can we decide on special mode of operation involving measurement of depolarization variables (LDR and co-cross-polar correlation coefficients)?
• What types of real-time, operational products are required? What types of displays need to be developed? Who will do the work?
• Rainfall and classification algorithms will need to be selected for real-time delivery. Do we deliver multiple products or try to reach a consensus on which products to deliver? Or is it left to the discretion of the NSSL?
• How do we document, archive, and disseminate the results of the experiment? How do we format the data? Web, CD-ROM, netCDF, etc.? Who will do the work? Can CHILL and/or SPOL technicians assist with the development of this capability?
• Can we plan a multi-seasonal experiment with a) a cold season stage for the observation of rain/snow, b) a February - March stage for non-precipitating clouds with Ka-band radar and aircraft measurements, and c) a April -June stage with major focus on rain measurements, rain/hail discrimination, bird nocturnal migration, and AP detection?
• Which facilities can we realistically expect to deploy for the field phase of the experiment? Radar? Aircraft? Surface measurements?
• What kind of hydrological component is anticipated?
• Since the NSSL Cimarron radar can only be depended on as a back-up radar, where do we deploy CHILL/SPOL radars (as well as possibly the ETL Ka-band radar and the University of Iowa vertically pointing X-band radar)?
• What kind of radar scanning strategies are required to achieve the operational and science goals of the experiment?
• What kind of radar scanning strategies are required to support aircraft operations?
• Since the NSSL 2D-video-disdrometer is located close to the KOUN radar (and can therefore not be used for comparisons with KOUN data), where do we deploy other 2D-video- disdrometer that might be included in the experiment?
• For rainfall measurements, should we restrict ourselves to the ARS raingage micronetwork or consider alternatives (e.g., Oklahoma mesonet, EVAC piconet)?
• What other ground-based verification data sets are needed? For example, should we make plans to collect ground-truth hail measurements?
• How do we fund research facility deployment? What are the deadlines?