GLM
Lightning definitely behaved differently in some of the different environments, particularly in west
Texas where the storms seemed to be less electrified
Texas where the storms seemed to be less electrified
Good at identifying the intense storms in South Dakota yesterday, seemed to ramp up when storms
were just starting to go severe
were just starting to go severe
The 2 minutes update product seemed to be a pretty good compromise for viewing the data
The parallax shift was more noticeable up in South Dakota than in other areas from throughout the
week.
week.
Had a hard time picking out any features in the core using the GLM products while it was good for
finding the large flashes out in the anvil
finding the large flashes out in the anvil
The smaller flashes were more difficult to pick out and interpret
ProbSevere
Continue to try to find a way to discriminate the storms better, even at the expense of longer lag time
Did seem to be a lot better calibrated and didn’t overdue probabilities as much as I’m used to
See the use in having the option to have the individual probability contours
ProbTor especially needs to be kept separate to pick out the relative increases
NUCAPS
Better than the sounding that we never get
The modified seemed to be very situation dependent on how much modification took place
Did underdo the lapse rates yesterday quite a bit even in the mid to upper levels
There were definitely some discrepancies between the direct broadcast and the operational
Focus training on the “gotchas”
The awareness is the main point to focus on to get others to use it
The availability of the soundings can help fill a lot of holes
Having some best practice starting procedures would be useful particularly for sending out the
gridded data
gridded data
All-Sky LAP and CI
CI was still just not very useful and frustrating to put much confidence in
Did reasonably well in the times when it wasn’t really needed, times that it was expected
Didn’t do well at times when it would be most needed
Interested to see some improvement with the GOES-16 training data
There was nothing yesterday in South Dakota leading up to initiation time
LAP did pretty well yesterday, and the GFS fill in areas seemed to do a lot better yesterday than the
day before
day before
Echo the fact that getting a higher resolution or faster updating model would still be ideal
There was a more smooth transition between the clear and cloudy regions than previous days
Values also seemed to be better than the baseline GOES data
Good to be aware of which data type is filling in the retrieval at that point
The PW products seemed to make terrain features stand out in certain cases
The Layered PWAT color tables should probably be adjusted to pick out the smaller scale gradients
easier
easier
General
It was good to be immersed in the science and learn the new tools in a familiar setting
Turn the data on and use it
Getting into the nuts and bolts has been invigorating
Very helpful having experts here for explanation and question answering
-Michael
-Michael