Showing posts with label ddc. Show all posts
Showing posts with label ddc. Show all posts

Friday, May 28, 2021

Big storms; small storms

While there were a number of storms during the Central Plains severe weather outbreak on May 26th, one long-lived supercell takes the cake. It persisted for more than 8 hours, dropping giant hail (up to 4" in diameter) and several tornadoes from Hays to Salina, Kansas.

ProbTor version 3 (PTv3) gave much more consistent guidance than version 2, with fewer large fluctuations before tornadogenesis. At 19:32 UTC, about 25 minutes before the first tornado report, PTv3 was at 38% while PTv2 was 11%. At this time, the MRMS azimuthal shears and MESH, SPC significant tornado parameter (> 2), and the GOES intense convection probability (ICP) were leading contributors to the higher ProbTor probability. The ICP is a deep-learning model using GOES ABI + GLM input images. The ICP is a predictor in each PSv3 model. You can see the ICP plotted around this storm in Figure 3, along with ABI imagery and local storm reports. You can also interrogate time series for this storm, saved here

Figure 1: ProbSevere contours (outer contour is for ProbTor value), MRMS MergedRef, and NWS severe weather warnings for a supercell in central Kansas.  

Figure 2: Time series of PSv3 models for the storm in Figure 1. 


Figure 3: ICP contours and local storm reports for a storm in central Kansas.


Even though the big storms on the Plains usually get all of the attention, severe weather was ongoing elsewhere. In Akron, Ohio, for instance, a storm in a more marginal environment (30 kt eff. shear; 700 J/kg MUCAPE) downed numerous trees. At 17:06 UTC, about 30 minutes before the first reports of downed trees, PSv3 was at 62% while PSv2 was 24%. The strong mean wind 1-3 km AGL (33 kts), moderate ENI lightning density (0.66 fl/km^2/min), favorable 0-3 km lapse rate (8.2 C/km) and MRMS azimuthal shears were the highest contributors to PSv3 at this time. 

Figure 4: ProbSevere contours, MRMS MergedRef, and NWS severe weather warnings for a storm near Akron, Ohio.

Figure 5: Time series of PSv3 and PSv2 for the storm in Figure 4. 


And yesterday, a storm in far southern Illinois damaged mobile homes near Vienna. PSv3 was picking up on this storm much better than PSv2, with a probability of 46% about 15 minutes before the report (PSv2 was 3%). The MRMS VIL (27 kg/m^2), low-level lapse rate (7.9 C/km), ENI lightning density (0.34 fl/km^2/min), MRMS 3-6 km azimuthal shear (moderate), and satellite growth rate (moderate) were the top contributors. 

We hope these examples illustrate some of the improvements users can expect to see with PSv3.

Figure 6: ProbSevere contours and MRMS MergedRef for a storm in southern Illinois.

Figure 7: Time series of PSv3 and PSv2 for the storm in Figure 6.