The 45 WS is testing a new dual-polarimetric C-band Doppler radar to improve the prediction of lightning initiation and cessation, convective wind, hail, tornadoes, heavy rain, and general weather. Generally speaking, the new radar should improve assessments of launch weather and attendant launch availability. More specifically, the new radar should also improve the evaluation of the Lightning Launch Commit Criteria--the weather rules to avoid natural and rocket triggered lightning strikes to in-flight space launch vehicles--and eventually might improve the actual Lightning Launch Commit Criteria themselves. The lightning watches and warnings are the most frequently-issued advisories from 45 WS and are arguably the 45 WS service with the most impact on space launch operations from CCAFS/KSC. This paper will focus on efforts to improve the forecast of lightning initiation for 45 WS.
Dual-polarimetric radar observations provided by the new C-band radar such as differential reflectivity (Zdr), specific differential phase (Kdp) and the correlation coefficient (ρHV) provide detailed information regarding precipitation sizes, shapes, orientations and thermodynamic states (e.g., liquid vs. ice) in the radar resolution volume, particularly when used in combination with horizontal reflectivity (Zh) and each other. By applying these variables as inputs, along with environmental temperature, into a fuzzy logic based particle identification (PID) system, the precipitation type (e.g., rain vs. hail) can be inferred.
Previous research has shown that lightning initiation in vigorous warm based convective clouds (like those often present over Florida) is typically preceded by the lofting and subsequent freezing of millimeter-sized supercooled raindrops. This process is well captured by polarimetric radar. Lofting of supercooled raindrops to sub-freezing temperatures (0°C to -10°C) is clearly identified by so-called Zdr and Kdp columns. Freezing of the raindrops is often associated with a local reduction in ρHV associated with a mixture of rain and partially frozen drops. Rapid riming of the frozen drops in the updraft results in efficient hail production. Non-inductive hail-ice crystal collisional-charging occurring during vertical extension and glaciation of the associated cloud subsequently causes the first flash.
Despite this rich research history, few studies have addressed the specific issue of translating these dual-polarimetric radar signatures (Zdr columns) and capabilities (PID) to an operational algorithm for first flash forecasting. The specific goal of this study is to develop and test operational polarimetric techniques that enhance the performance of current operational radar reflectivity based first flash algorithms, including reflectivity vs. temperature/depth/duration/width thresholds and temperature layered VIL thresholds. For development and testing, we leverage research instrumentation and processing capability at UAH and NASA MSFC, especially the UAH Advanced Radar for Meteorological and Operational Research (ARMOR; C-band dual-polarimetric) and the NASA Lightning Mapping Array (LMA). The summer weather over northern Alabama is similar enough to the summer weather over CCAFS/KSC that the techniques developed should require minimal adaptation, especially if the studies are restricted to pulse thunderstorms. Through the analysis of case studies, lightning initiation forecast techniques are being developed and tested. The hypothesis is that the additional dual-polarimetric information could potentially reduce probability of false alarms while maintaining high probability of detection with high skill, and also will increase lead-time for the prediction of the first lightning flash relative to reflectivity-only based techniques. To test the hypothesis, various techniques using polarimetric variables and/or PID will be benchmarked against the 45WS operational reflectivity-only based approaches to find the best compromise between forecast performance and lead-time. Since the lighting watches and warnings issued by 45 WS are so important to personnel safety, a nonstandard statistical metric giving more weight to probability of detection may be used to optimize the forecast tool.