Typically, in studies involving both polarimetric radar and total lightning data, emphasis has been placed on a case study approach, borne largely out of necessity, as historically these datasets have been large and unwieldy given computational limitations. The case-study approach has yielded valuable scientific results and insight. However, there is a fundamental weakness, as all case studies ultimately suffer from lack of statistical significance in their results, and from sampling issues that make it difficult to generalize findings.

Computational capabilities, along with objective analysis algorithms, have progressed to the point that true objective statistical analysis of polarimetric radar and total lightning information is now possible. Moreover, statistical analyses will become necessary given technological improvements in observing platforms. In the near future there are plans for polarimetric upgrades to existing NEXRAD radars, as well as a lightning sensor on a GOES satellite and the ability to retrieve lightning information from the GPS satellite constellation. Coupled with the growing number of permanent ground-based three-dimensional lightning mapping arrays in various regions of the United States (including portions of Florida, Oklahoma, Texas, Alabama, and New Mexico), it is becoming imperative to be able to deal with these large radar and lightning datasets in an objective, statistical manner. We believe that new insights into the relationships between storm dynamics, microphysics, and electrification can be gained from such an analysis (over various climatological regimes). Furthermore, we envision that these results will be particularly valuable for validating numerical simulations of convection.

In this paper, we will present a prototype of an objective statistical analysis framework that will be able to incorporate full three-dimensional polarimetric radar and lightning mapping data. Using this framework, we can objectively calculate and compare information on storm microphysical structure (including the location and type of hydrometeors, derived from polarimetric radar observations), degree of organization, intra-cloud (IC) and cloud-to-ground (CG) lightning flash rates, lightning-inferred charge structures, and many other parameters on a storm-by-storm basis over a wide variety of meteorological regimes. This framework also will have the ability to incorporate environmental information from soundings or operational forecast models, as well as satellite-derived information on aerosols.

We will demonstrate the performance of the framework via the re-analysis of previously completed case studies, such as from the STEPS project, and will discuss planned future improvements and additions. Plans for the analysis of large datasets, from entire field projects or observing seasons in various locations, will be detailed. Applications of the statistical framework for addressing outstanding operational meteorological issues involving lightning also will be discussed.