Test beds have become an integral part of the weather enterprise, bridging research and forecast services by transitioning innovative tools and tested methods that impact forecasts and forecast users. O ver roughly the last decade, a variety of "test beds" have come into existence focused on high-impact weather and the core tools of meteorology-observations, models, and fundamental understanding of the underlying physical processes. They have entered the proverbial "valley of death" between research and forecast operations (NAS 2000), Develop and introduce new ideas, data, etc. Input Revise and iterate Experiment and demonstrate End testing Output Test and refine loop V Assess impacts and evaluate and have survived. This paper provides a brief background on how this happened; summarizes test bed origins, methods, and selected accomplishments; and provides a perspective on the future of test beds in our field. Dabbert et al. (2005) provides a useful description of test beds from early in their development and Fig.

The potential value of small unmanned aircraft systems (UAS) for monitoring the preconvective environment and providing useful information in real time to weather forecasters for evaluation at a National Weather Service (NWS) Forecast Office are addressed. The general goal was to demonstrate whether a combination of fixed-wing and rotary-wing UAS can provide detailed, accurate, and useful measurements of the boundary layer important for determining the potential for convection initiation (CI). Two field operations were held: a validation study in which the UAS data were compared with collocated measurements made by mobile rawinsondes and ground-based remote sensing systems and a real-time experiment held to evaluate the potential value of the UAS observations in an operationally relevant environment. Vertical profile measurements were made by the rotary-wing UAS at two mesonet sites every 30 min up to 763 m (2500 ft) AGL in coordination with fixed-wing UAS transects between the sites. The results showed the ability of the fixed-wing UAS to detect significant spatial gradients in temperature, moisture, and winds. Although neither of two different types of rotary-wing UAS measurements were able to strictly meet the requirements for sensor accuracy, one of the systems came very close to doing so. UAS sensor accuracy, methods for retrieving the winds, and challenges in assessing the representativeness of the observations are highlighted. Interesting mesoscale phenomena relevant to CI forecasting needs are revealed by the UAS. Issues needing to be overcome for UAS to ever become a NOAA operational observing system are discussed.

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To test the utility and added value of polarimetric radar products in an operational environment, data from the Norman, Oklahoma (KOUN), polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) were delivered to the National Weather Service Weather Forecast Office (WFO) in Norman as part of the Joint Polarization Experiment (JPOLE). KOUN polarimetric base data and algorithms were used at the WFO during the decision-making and forecasting processes for severe convection, flash floods, and winter storms. The delivery included conventional WSR-88D radar products, base polarimetric radar variables, a polarimetric hydrometeor classification algorithm, and experimental polarimetric quantitative precipitation estimation algorithms. The JPOLE data collection, delivery, and operational demonstration are described, with examples of several forecast and warning decision-making successes. Polarimetric data aided WFO forecasters during several periods of heavy rain, numerous large-hail-producing thunderstorms, tornadic and nontornadic supercell thunderstorms, and a major winter storm. Upcoming opportunities and challenges associated with the emergence of polarimetric radar data in the operational community are also described.

Tornadic vortex signatures (TVSs) of 52 tornadoes were identified and analyzed, then characterized as either descending or nondescending. This characterization refers to a known tendency of radar-observed tornadic vortices, namely, that of their initial detection aloft and then of their subsequent descent leading to tornadogenesis. Only 52% of the sampled TVSs descended according to this archetypal model. The remaining 48% were detected first near the ground and grew upward or appeared nearly simultaneously over a several kilometer depth; these represent primary modes of tornado development that have been explained theoretically. The descendingnondescending TVSs were stratified according to attributes of the tornado and TVS. Significantly, tornadoes within quasi-linear convective systems tended to be associated with nondescending TVSs, identification of which provided a mean tornado lead time of 5 min. Two case studies are presented for illustrative purposes. On 1 July 1997 in southern Minnesota, nondescending TVSs and associated tornadogenesis were revealed in the leading edge of a squall line, with a squall linesupercell merger, and later during that day, with the cyclonic bookend vortex of a bow echo. On 22 June 1995 in southern Colorado, a low-topped supercell storm produced a tornado that was associated with a descending TVS.