Verification

One of the many struggles with forecasting is verification, especially of "rare" events. In the severe storms world, we have storm reports. It has been shown that there are serious flaws with this database over time. They are conditional upon hitting something or someone; population density or highways. There are many areas un-accessible that may have had things like hail or high wind but yet there are no observations nearby. In the Plains this is a big challenge.

Over the course of the HWT EFP, we have debated over the so-called practically perfect methodology. At is core it is a Kernel Density Estimation (KDE) technique using a gaussian smoother (120 km) and a radius of influence technique (40 km) to map individual storm reports to a grid and produce probabilities of severe.

Given that storm reports are not the most ideal, independent, non-biased dataset out there we look to other more unbiased data. So what are the alternatives? Can we use severe storm warnings? How about data specifically from the radars like Max Estimated Hail Size or Rotation tracks? How about satellite derived data about vegetation?

Just about all of these data sets have their own problems. For the radars, we are observing rotation or hail aloft, not necessarily at the ground. This is still valuable information. But how do we switch from spotty storm reports to continuous tracks? Will the same KDE smoothing approaches be necessary?

For the warnings, it is clear that meteorology alone is not driving them. If there is a chance a storm could be severe over a highly populated area at a critical time, the edge goes to issuing warnings as opposed to not. This is not all that bad, since we would all like to err on the side of safety. Better to be safe than sorry.

Using  radar data we still have to verify that what the radar detects is actually occurring at the ground and that phenomena is as strong/large as indicated aloft. And that requires doing verification on the observations. The SHAVE folks at NSSL-OU are trying to do exactly that as are some other NWS associated folks, though at the moment their name escapes me.

Satellite data also offers some advantages on tracks of severe storms provided there is damage say from large hail stripping vegetation bare or tornadoes doing damage.  Collecting more fine resolution data is going to take a dedicated effort but in the end it helps build more complete knowledge about storms, more understanding about the successes and failures of the forecasts, and quite possibly will end up making better forecasts.

Thanks to TAMU for soundings

One of the observation components of this years EFP has been an intercomparison between the Vaisala RS92 and InterMet radiosondes to help verify the Microwave Radiometer that we (Dave Turner at NSSL) have on the roof of the National Weather Center. We were lucky to have Don Conley from Texas A & M bring his observations class on the road and visit the HWT conduct some local and mobile radiosonde intercomparisons. They did two mobile deployments: one in Concordia, KS on Wednesday and Altus, OK on Friday for helping to verify the models we are using for convection initiation.

They drove from Norman to Concordia and were able to make 3 launches (4 really), and 2 trips to Walmart (for helium and then to return said helium). Many thanks to the City of Concordia and the airport manager for allowing them to use a hangar for these balloon launches in very strong winds (which caused the failure of the very 1st balloon launch). They got to a great spot just east of 2 very long and robust Horizontal Convective Rolls both of which produced CI along the front-HCR intersection.

I haven't heard the stories from today, but I do know they got to Altus after lunch at Meers (for the Meers burger, obviously) and got off two launches again in an environment characterized by HCRs. These are great tests of the instruments, great experiences for the students, and excellent learning opportunities for the rest of us.

They (and you) should know that these soundings make their way to the SPC (something that is usually done upon request at TAMU) and prove valuable. These types of partnerships, sometimes ad hoc, but almost always mutually beneficial are what make the HWT a vibrant place for forecasting, research, research forecasting and forecasting research; and now with observations!

You can find the mobile and local soundings here.

Again, Thanks Don, Mike D., Mike C. and the whole Observations Class (Send me your names and we can make you famous* write them on here!).

*Fame not guaranteed.