Comments for CIMMSE

Comment on Potential New Interpolation Method in TCMWindTool by Jonathan Blaes @ WFO RAH

Jonathan Blaes @ WFO RAH — Mon, 20 May 2013 15:48:41 +0000

Bryce,

Thanks for sharing the summary. This is very encouraging work. I plan on reviewing the radail and four planel plots shortly.

Comment on Keith Sherburn Completes his Forecasting HSLC Thesis Defense by gerapetritis

gerapetritis — Wed, 15 May 2013 07:07:06 +0000

I notice that the very latest formulation of SHERB is a little different from the most recent GFE smart tool version. I have updated the GFE SHERB smart tool on the Software Collaboration Portal to account for the latest coefficient adjustments. (https://collaborate.nws.noaa.gov/trac/nwsscp/wiki/Gfe/Smarttools/Sherb)
Harry G.

Comment on Wind Gust Climatology for Southeast Georgia and Southern South Carolina by Jonathan Lamb

Jonathan Lamb — Thu, 09 May 2013 17:59:30 +0000

Brian,
Thanks so much for the information. I hadn’t heard about the peak wind gust sampling changing with the IFWS install. The explanation on the site you linked was quite interesting. I just corrected my original post.

Regards,
Jonathan

Comment on Wind Gust Climatology for Southeast Georgia and Southern South Carolina by Brian Miretzky

Brian Miretzky — Wed, 08 May 2013 19:03:36 +0000

Hi Jonathan,

Very nice work. One comment. Jonathan Blaes also recently asked about the different gust definitions and I wanted to let you know that ASOS now is in line with WMO standards and NDFD wind gust definition by taking the highest 3 second wind average and recording it every 5 seconds. As for AWOS it still seems to be the highest 5 second wind average recorded every 5 seconds.

Here is a link to the ASOS site – http://www.nws.noaa.gov/ops2/Surface/asosimplementation.htm, which details the ice free wind sensor install dates and a comparison between the old and new wind sensor. It seems like it may have some effect on the study since the installs were done in the 2007-2009 time frame in your area and the different sensors recording different wind gusts for the reasons mentioned above.

Just thought I would send the heads up,

-Brian

Comment on A Wind Gust Factor Database from 10 Tropical Cyclones for Use with GFE Tool Development by Wind, Wind Gusts, and Gust Factors Observed Over Marine Locations with Hurricane Irene | CIMMSE

Thu, 25 Apr 2013 13:29:55 +0000

[...] note that a previous blog post, “A Wind Gust Factor Database from 10 Tropical Cyclones for Use with GFE Tool Development”, highlighted the examination of 14,938 gust factors at locations over land for ten tropical [...]

Comment on Notes on the Effective Use of High-resolution Models including CAMs by Jake GSP

Jake GSP — Wed, 24 Apr 2013 01:17:02 +0000

Nice summary! Also, I had not seen that feature of the RAH website before… I will keep it handy for future use at the office!

Comment on Update on HSLC Environmental Climatology WAF Article by Keith Sherburn

Keith Sherburn — Mon, 15 Apr 2013 16:03:20 +0000

Justin,

Good points. You’re right–most of the QLCS mesovortex work cites crosswise, rather than streamwise, vorticity as the primary contributor. Also, I’ve heard a lot about the Bunkers method of storm motion being inaccurate at times. I look forward to seeing your case study comparisons.

Comment on Update on HSLC Environmental Climatology WAF Article by justingsp

justingsp — Sun, 14 Apr 2013 19:24:49 +0000

One thing I forgot to mention: another thing that I’ll be showing in BOTH of my case studies is that the Bunker’s method was not the best means of estimating storm motion. The old 30/75 rule actually did a better (not perfect, but better) job of estimating the observed storm motion in both cases. This resulted in not-insignificant differences between SRH from my modified soundings and the SPC mesoanalysis.

Comment on Update on HSLC Environmental Climatology WAF Article by justingsp

justingsp — Sun, 14 Apr 2013 13:48:50 +0000

JB/Keith, the fact that SRH isn’t as skillful as shear magnitude in terms of identifying significant HSLC environments is certainly consistent as far as the QLCS end of the spectrum is concerned. Trapp and Wesiman (2003) and Atkins and St. Laurent (2009) described different processes for mesovortex genesis within QLCSs, and neither of them had much to do with tilting of streamwise vorticity. One of our case studies (largely a broken-S/QLCS event) will show that environmental SRH was barely (if at all) favorable for tornadoes, especially considering the weak instability, yet multiple tornadoes occurred. (Granted, they were all quite weak).

Comment on Update on HSLC Environmental Climatology WAF Article by Keith Sherburn

Keith Sherburn — Fri, 05 Apr 2013 18:48:38 +0000

JB,

Thanks for the comment. I’ll address all of your comments/questions in turn.

Yes, in terms of the development dataset, both the SHERB6 and the SHERBS6 show remarkable skill. I think this corresponds to the large number of cool season significant wind events in the development dataset, which is where the deep-layer shear parameters really show substantial skill. Note that the SHERBC (using the mean cloud-bearing layer wind; in general, also a deep layer) also does quite well in these events. The SHERBE and SHERBS3 are both skillful when examining just tornado cases, and the SHERBE especially stands out with hail cases.

The normalization value for the LLLR is 5.2 K/km.

The SRH struggles are an interesting topic. The formulations with the SRH struggled primarily in our development dataset compared to the verification dataset; in fact, on the nationwide scale, the SRH versions do quite well (particularly outside of the winter months). They are among the best performing composite parameters during the spring and for high-based (i.e., LCL > 1000 m) cases. So why do they struggle in our development dataset? I suppose it is important to recall that SRH is based off of some estimate of storm motion assuming a right-moving supercell. As Jason’s work has shown, though the majority of HSLC tornadoes in our development dataset occurred with some sort of supercell (discrete or embedded within lines/clusters), a substantial fraction are from non-supercells. Perhaps in these non-supercell cases (or even some of the supercell cases, given the non-uniformity of right-movers’ motions), the SRH is not a useful metric. However, I am interested in hearing some other impressions of this decreased skill.

I’m not sure I completely understand your next question, but I think you’re asking, “How much does the skill of the SHERB depend on which wind/shear parameter you use?” I would say that, depending on the situation, it could vary a lot. A product of the lapse rates themselves, without using any shear/wind parameters, is quite skillful (maximum TSS of 0.462 in the development dataset). But depending on the regime, season, region, etc., several of the wind parameters, when combined with these lapse rates, can further augment the skill. Based on the nationwide verification dataset and their increased performance in tornado cases, we chose to suggest the use of the 0-3 km shear magnitude and effective shear magnitude in the article. I think that the wind or shear component used could “make or break” the SHERB, depending on the situation. It may require further testing to really gauge which situations require which wind/shear parameter. Let me know if this wasn’t the question you were trying to ask…

I agree; I look forward to the case study results. It appears that even marginal lapse rates, when coupled with just the right amount of shear, can mean the difference between a significant severe and non-severe event. Hopefully we begin to understand this dependency a little better once the case studies are completed.