While the weather in the local area started out rather quiet, it ultimately picked later in the week allowing us to view PAR and CASA radar data in real time. In the early part of the week we also had the opportunity to view archived data and issue real-time probabilistic forecasts for thunderstorms in the central plains.

For both the real-time and archived cases where we made probabilistic forecasts for thunderstorms, the process seemed to work reasonably well. The fact that many of the storms were discrete probably made the task relatively manageable. It would be interesting to experiment with cases of widespread strong/severe thunderstorm development including a few high-end storms such as supercells. Managing the boxology and frequency of updates could be a challenge.

I can envision the additional value that the probabilistic forecasts could provide to some customers especially for values below some “threshold” that might trigger a warning. For example, tornado probability trends for a supercell could give an EM or TV weather person some insight on the likelihood that a storm may subsequently have a tornado warning issued on it.

The strength of the PAR data was clearly its capability to perform rapid volume scans. Storm evolutions seemed to be easier to follow and also allowed the detection of features a little sooner than you might with the 88-D. The archive data of a developing microburst nicely demonstrated the advantage of having more frequent volume scans available.

While the range of the CASA radars was limited, they did provide additional information about the near surface wind speeds in storms than could be detected using the 88-D which was located farther away from the storms.

Although only available for a few volume scans, live radar data from a SMART radar was available for display on a workstation. To be able to view a remotely transmitted dataset in real time was impressive.

In the back of my mind, as I explored many of these datasets, I was trying to visualize how a warning forecaster could incorporate all of this information during warning operations. The long term solution may be short-term storm-scale forecast models that incorporate all available datasets. However, in the interim, it might be worthwhile to also explore the development of tools that would allow all available radar data sources to be combined into a seamless dataset for interrogation by the forecaster. This would also include developing robust 3D and 4D visualization tools.

Chris Sohl (NWS Norman OK – Week 6 Participant)