September storms near the Great Salt Lake

A number storms formed in the early afternoon of September 22nd in response to forcing associated with the North American Monsoon over the Intermountain West region of the U.S. The image below shows the accumulations of NWS severe weather warnings, storm reports from SPC, and the centroids of ProbSevere objects attaining 50%+, at each time. Each accumulation is over the timeframe of 12Z on 9/22 to 12Z on 9/23. You can get a quick-look at how the model performed using these accumulations (the previous day accumulations are here). On this day, the NOAA/CIMSS ProbSevere model performed reasonably well, with high probabilities corresponding to numerous wind, hail and tornado reports. There were a couple of false alarms to the south east of the Great Salt Lake and a couple wind reports missed to its west and south.

Figure 1: Accumulations of ProbSevere objects, reports, and NWS warnings for 9/22/2016.

The storm that produced hail, wind, and the one the tornado reported initiated well to the southwest of Salt Lake City. The time series below of its probability and constituent predictors in ProbSevere demonstrates its evolution.

The probability of severe is the thick red line, with the scale on the left. The six predictors in ProbSevere have varying scales on the right. The NWP predictors of effective bulk shear and MUCAPE are the dashed black and brown lines, respectively. The MESH is solid orange, and the total lightning flash rate is solid green. The lifetime max normalized satellite growth rate and glaciate rate are depicted by the solid blue and dashed cyan lines, respectively. Both satellite growth rates use the blue scale on the right with nominal 'Weak', 'Mod.' (moderate), and 'Strong' designations.

Figure 2: Time series of ProbSevere predictors and severe probability value for a long-lived storm affecting the Salt Lake City metro area.

We see that the normalized satellite growth rate from GOES-West was strong at 18:50Z, while the probability of severe jumped to 15%. The jump in MESH in a high shear environment also helped to jump the probability up to 50% at 19:12Z. Increasing MESH and flash rate helped the probability climb to over 90% by 19:50Z. The first severe thunderstorm warning was issued at 20:09Z. Golfball-sized hail was observed at the Antelope Island Marina at 21:37Z. The tornado in the city of Ogden was reported at 21:45Z, and left thousands without power.

Surprise Indiana tornadoes and total lightning in the ProbSevere model

A number of tornadoes spawned from storms in central and northern Indiana yesterday afternoon -- including strong ones -- in an area where tornadic activity was not expected. NOAA's Storm Prediction Center (SPC) forecasted a corridor of marginal to slight risk for general severe weather extending into Indiana, Ohio, and lower Michigan (Figure 1). However, the probability of a tornado within 25 miles of any given point was less than 2% in Indiana and Ohio (Figure 2).

Figure 1: SPC categorical outlook for August 24, 2016.

Figure 2: Tornado probability outlook for August 24, 2016.

Storms formed in the early afternoon in a juicy warm sector of an occluding system and put down multiple tornadoes, including an EF-3 tornado in Kokomo, Indiana, causing substantial damage to a shopping mall and leaving thousands without power.

Figure 3: SPC storm reports for August 25, 2016.

Though the NOAA/CIMSS ProbSevere model doesn't provide guidance to the type of severe weather, it could have given forecasters a heads up to some of the storms during this event. The animation below shows two storms developing in central Indiana (Figure 4). The first storm (near the Illinois border) had initially modest MESH (0.5-0.7"), but an excellent total lightning flash rate (50+ fl/min), before increasing to over 1" of MESH briefly. ProbSevere provided about 30 minutes of leadtime to the first severe thunderstorm warning from the 70% threshold. A tornado warning was issued at 18:37 UTC, and a damaging tornado reported at 18:55 UTC. One-inch hail was later reported in Indianapolis.

Further to the northeast, where MUCAPE was markedly less (~1600-1800 J/kg) but effective shear about the same (~45 kts), another storm formed west of the city of Kokomo, which produced the EF-3 tornado. This storm had low MESH (0.3-0.5"), but a rapid increase in flash rate (18->46->62 fl/min) in a well-sheared environment. This helped give the storm a probability of severe of 68% at 18:42 UTC, 8 minutes before a tornado warning was issued. The total lightning flash rate/effective shear predictor helped increase the probability of severe despite poor integrated radar reflectivity and satellite growth rates. A tornado emergency would later be issued for the community of Kokomo.

Figure 4: Two storms in central Indiana showcasing the utility of total lightning data in ProbSevere.

To show the effect of total lightning flash rate explicitly, ProbSevere was run with just radar, satellite and near-storm environment NWP data. As figure 5 shows, the probability of severe on the first storm only became elevated when the MESH neared or exceeded 1". In the Kokomo storm, the probability was 46% greater at the time of the initial tornado warning with lightning than without (70% vs 24%)! For both storms, the probability was generally 20-40% greater with the inclusion of total lightning data.

Figure 5: ProbSevere for the two storms in central Indiana, with total lightning data OMITTED from the probability computation.

The tornadic storm that traversed Kokomo traveled to the east side of Indiana, where it again re-intensified and became warned at 20:46 UTC. The probability of severe jumped up largely in response to an increasing flash rate. The storm would go on to produce numerous more tornado reports, beginning at 20:45 UTC.

This storm and another to it's north moved into Ohio, still producing tornadoes. However, the ProbSevere model only had low probabilities at this point for both storms, as the flash rates dropped into the single digits and MESH was largely below 0.33". So the flash rate did not contribute much with these two storms later on (see Figure 6). It is still uncertain what aspect of the environment in far northeastern Indiana modified the morphology of these storms.

Figure 6: Two storms in northeastern IN / northwestern OH that had poor ProbSevere values but produced tornadoes. These storms show that total lightning doesn't help every storm.

This event in Indiana and Ohio is interesting for a number reasons, including the unexpected number and severity of tornadoes, as well as the seemingly different morphologies of storms in reasonably close proximity. These examples highlight where total lightning flash rate improves ProbSevere probabilities, despite a meager reflectivity signature, as well as where total lightning doesn't contribute. I hope this case also shows the utility of an 'ingredients-based' approach to forecasting using observations (and near-storm environment data), where one data source may give insight to future storm severity when another is not, or when multiple observation sources may corroborate each other to enhance forecaster confidence and leadtime. This case also underscores NOAA/CIMSS's efforts to provide hazard specific guidance in future improvements to ProbSevere.

EDIT: This blog post by Jeff Frame gives a good post-mortem of the event. It appears the MCV in Illinois/Indiana played a key role, and that the environment itself was actually reasonably favorable for tornadoes, but that NWP guidance struggled depicting it as well as depicting the morphology of the storms.

2015 North American monsoonal storms

The NOAA/CIMSS ProbSevere model was reprocessed with total lightning data for several days in the fall of 2015 upon request from the National Weather Service. This post recaps a few of the interesting storms from these days.

October 18, 2015

A cluster of storms affected the Phoenix, AZ metro in the afternoon/evening of October 18, with one storm intensifying and producing severe weather in downtown Glendale. This storm only had weak satellite growth, but the good total lightning flash rate (up to 40 flashes/min) and strong MRMS MESH (1.08") generated a ProbSevere value of 51% at 22:48Z, despite rather weak effective bulk shear. The first wind report was at 22:50Z. So there wasn't much lead-time at all for this storm from the 50% threshold, but the ramp up in probabilities could have signaled to the forecaster that this was a storm to watch (3%-->11%-->17%-->38%-->41%-->51%), as well as how much higher the ProbSevere value was than neighboring storms. The storm produced multiple large hail (up to 1.25") and severe wind reports.

Figure 1: ProbSevere, MRMS composite reflectivity, and NWS warnings for storms near Phoenix, AZ.

Further southeast, northwest of Tucson, a very small storm produced big hail (1" diameter) at 21:04Z. A maximum MESH of 0.89", moderate satellite growth rate, and very low lightning (0-1 fl/min) combined for a max probability of only 21%, at the time of the first report. The very low lightning combined with modest effective bulk shear (~25 kts) certainly helped to keep the probability of severe low. This example shows that more training with western U.S. storms is necessary for the ProbSevere model, especially as far as total lightning is concerned.

Figure 2: ProbSevere and MRMS composite reflectivity for a small storm near Tucson. This storm had nearly zero observed lightning flashes (IC or CG). 

Strong storms also erupted in southeast California this day, with strong satellite growth rates, good total lightning flash rates, and strong MESH values, all combining to produce probabilities in excess of 90%. Only one storm was warned despite the high MESH values (as high as 1.45"), but no reports were recorded from these storms in the Mojave Desert region of California. The MESH might possibly have been biased due to rather sparse radar coverage in this region.

Figure 2: ProbSevere, MRMS composite reflectivity, and NWS warnings for storms in the Mojave Desert.

October 6, 2015

Numerous storms developed in southern Arizona in the early afternoon of October 6th. One storm stood out southwest of Phoenix, with a good flash rate (32 flashes/min), and good MESH (0.92"), but no satellite growth rates. The ProbSevere value ramped up from 17% to 66% in 10 min (from 18:58Z to 19:08Z). The probability then hovered in the 40-50% range before a tornado was reported at 19:34Z. Though ProbSevere doesn't have any predictors explicitly for tornadogenesis, this case demonstrates that it can highlight a strongly developing storm to the forecaster, which signals the need for him/her to further investigate it.

Figure 3: ProbSevere and MRMS composite reflectivity for a storm southwest of Phoenix, which produced a tornado. 

Further southeast in Tucson, a storm exhibited moderate glaciation and normalized satellite growth rates, modest lightning (< 20 fl/min), and modest MESH (lifetime max was 0.58"). The shear and MUCAPE were adequate (~35 kts and 1000 J/kg, respectively). The ProbSevere predictors all pointed to a garden variety thunderstorm (max probability was 24%), yet this warned storm went on to produce two 1" hail reports and a wind report in Tucson. The MESH may have been underestimated due to the storm being near the radar, and thus possibly partially in the "cone of silence". The next closest radar is in Phoenix, with it's lowest tilt being over 8,000 feet at the storm's location (possibly higher, depending on atmospheric conditions). It's also possible the storm may have been shallow, as well, with MESH not being as representative. The SPC mesoanalysis archive shows that the melting level was relatively low (~2500 m), which in the future might help correct the MESH in shallow storms.

Figure 4: A storm near Tucson, AZ, which produced severe hail and wind.

Finally, later in the afternoon, a storm quickly intensified (went from 10% at 21:50Z to 70% at 21:58Z), heading toward Casa Grande, AZ, and was promptly warned. The increasing MESH and total lightning caused the rapid increase in probability. The storm began producing golfball and silver dollar sized hail at 22:10Z.

Figure 5: A strong storm picked up by ProbSevere heading toward Casa Grande, AZ.

September 14, 2015

A couple of storms developed near the Phoenix, AZ metro area on the evening of Sept. 14th, with one storm producing multiple wind reports (e.g., trees and power poles down) in downtown Phoenix. The MUCAPE and effective bulk shear parameters for the wind-producing storm were good (~2200 J/kg and 30-35 kts, respectively). At 01:00Z, a moderate normalized satellite growth rate and MESH at 1.01" combined to generate a probability of 47% (the max in its lifetime). The flash rate was 7 flashes/min. About 10 min later, the storm diminished markedly, as the MESH went below 0.1" and flash rate below 5 fl/min. The ProbSevere values were in the single digits when the storm first began producing severe wind reports. So unless the radar operator was paying close attention to the probabilities nearly an hour prior, ProbSevere may not have helped much in this case. That being said, development is underway to incorporate other NWP and radar fields to better predict wet-microbursts. For instance, the low-level lapse rates were very good in this region (as shown by the SPC mesoanalysis archive), which helps in momentum transport. The ProbSevere developers will be investigating many fields, including low-level lapse rates to better predict severe wet-microbursts. The low ground-based total lightning also didn't help. It's not certain whether this is a detection efficiency or a meteorological cause, but it underscores the need for more training for western U.S. storms.

Figure 6: ProbSevere and MRMS composite reflectivity for a storm affecting the Phoenix metro.

These cases show that ProbSevere can help highlight storms for forecasters to watch and further interrogate, and that forecasters must also continue to bear in mind data problems (e.g., sparse radar coverage, possible low lightning detection efficiency), as well as environmental factors not captured in the ProbSevere model (e.g., shallow storms). We hope the ProbSevere model will constitute another piece of useful guidance to the forecaster and compliment the warning process.

June storms out west

Early to mid-June has supplied the western U.S. with several bouts of storms. On June 8th, storms developed in eastern Oregon and northern Idaho downstream from a 500mb trough with an embedded 60 kt jet, leading to an environment with excellent effective shear but only modest MUCAPE.

The first annotated storm in central Oregon only had weak satellite growth, but the ProbSevere value ramped up quickly an account of increasing MESH and the total lightning flash rate, in a very high shear environment. A brief tornado was reported at 20:22 UTC (probability > 90%) while golfball-sized hail was reported at 20:30 UTC.

Two other annotated storms in northern Idaho and far northeastern Oregon also had high probabilities. On both of these storms, the normalized satellite growth rate and glaciation rate were strong before the MESH became high, yielding 80%+ probabilities of severe. The flash rate also remained rather low until later in the lifecycle of the storms. The storm in Idaho had a report of 1" hail at 21:24 UTC, and later 2" hail at 21:45 UTC (a severe thunderstorm warning was issued at 21:12 UTC). The storm traveling from northeast Oregon to far southeast Washington report damaging 1.25" hail at 21:45 UTC (the hail dented vehicles).

Fig. 1: The OR-WA-ID tristate region, with ProbSevere contours, composite reflectivity, and NWS warnings.

On June 13th, a slow-moving storm brought hail to the Salt Lake City, Utah area in the early afternoon. Very strong satellite growth rates were observed at 17:45 UTC in an environment characterized by 1500 J/kg of MUCAPE and 25 kts of effective shear. A total flash rate of about 30 flashes/min and MESH close to 1" yielded a maximum probability of severe of 88% at 18:14 UTC. One-inch hail was reported at 18:20 UTC, and golfball-sized hail reported at 18:37 UTC.

Fig. 2: Storm near Salt Lake City, UT produces multiple large hail reports. ProbSevere contours are overlaid NWS warnings and composite reflectivity.

HWT 2016 GOES-R/JPSS Spring Experiment Complete!

The 4 week GOES-R/JPSS Spring Experiment in the HWT completed today, May 13.

Week 4 complete!

The fourth and final week of the HWT 2016 GOES-R/JPSS Spring Experiment is complete! After starting out very busy on Monday with severe weather, including tornadoes, in the Norman CWA, the week quieted down. However, we certainly still had enough severe convective weather across the CONUS Tues-Thurs to keep our participants plenty busy evaluating the satellite products.

Week 4 (9-13 May 2016) Summary and Feedback

The final week of the 2016 GOES-R/JPSS Spring Experiment concluded with our two pairs operating in the Nashville and Huntsville CWAs. Both were able to evaluate the PGLM product via the Huntsville LMA.

LAP
- Convection developed along the moisture and instability gradients in LAP.
- I liked seeing the model data where retrievals were unavailable. In addition to having a continuous field, it often allowed for quick comparisons of retrievals with nearby GFS.
- Our office does look at K-Index for flash flood situations.
- 30-min is a good temporal update frequency. Too frequent of updates would not be that useful, as such fields do not change so rapidly.
- Layer PW was my favorite LAP product as it was most unique, and added value to my analysis. It was particularly useful on days when we had strong low-level moisture advection, tracking the movement of moisture, and dry air aloft.

GOES-R CI
- When I had 1-min imagery, I did not need CI because I could identify areas of imminent CI in the imagery.
- In situations where you are expecting severe thunderstorm activity, you's look more at severe CI. Regular CI was not as useful for severe situations because you could see cb development in the 1-min data.
- When looking for general thunderstorms, I see CI being more helpful, including in the cool season. This would be valuable for DSS purposes.
- I found utility in having both CI products up. If severe CI was pinging on something in addition to regular CI, it helped to focus attention to particular areas of interest.
- It would be helpful to see probability trends for a particular cloud/area.
- We were fine with the display concept
- I like the current instantaneous visualization  over a smoothed probability field approach.

ProbSevere
- It would be nice to see a meteogram with a history of ProbSevere probs.
- Everyone is fine with the display and color-scale.
- Similar to VIL of the day, might be helpful to determine "ProbSevere Prob" of the day.
- I think it really well with discrete cells, but later would merge nearby cells.
- I would say this was my favorite product outside of the 10min imagery.
- I thought it performed great this week.
- We would all use this in operations.
- I've worked 5 or 6 severe events in the last month, and I've ProbSevere up for all of them. Usually I have storm relative velocity all tilts, regular velocity in the middle, and the third screen has different fields, including composite reflectivity with ProbSevere. I've also even started putting it on all-tilts. The display does not distract me. In my office, the threshold to warn depends on the day, but I've found with most of our events, especially with severe wind, we can get severe with a threshold of ~60%. Definitely not using it as a yes/no.

SRSOR
- All forecasters loved using it this week!
- 5-min is certainly bettern than 15. But when you are tracking low-end severe situations, subtle boundaries can make all the difference between something going up or not. We get better than 5-min radar data, but 1-min satellite data can fill gaps that we still have. 5-min will be useufl, but 1-min is optimal.
- I think it is certainly time to make the jump to 1-min satellite imagery. There is so much that can be seen, even outside of convection. Forecasters need to use satellite data more in day to day operations.  Generally, I think forecasters don't think satellite imagery is as useful as it is, and they have a hard time understanding exactly how much they will see in the 1-min imagery.
- It was helpful to view long loops of the 1-min imagery on the regional scale to get a big picture idea of how the system was evolving.
- It was really helpful for analyzing frontal structure and all the different boundaries.
- Satellite imagery is truly the only visual representation you have of a storm that you can't get with any other product.
- I found it useful to match 1-min lightning data with 1-min satellite data.

SRSOR Winds
- I liked the winds a lot. You could see the vertical structure of a front, and how winds changed with height from the surface. Seeing rapid change over a short vertical distance was intriguing. AMV's could be a big help with our TAFs.
- I felt that the low-level winds were more useful than the upper-level winds. They indicated areas of low-level convergence, moisture transport, veering of winds from the surface, potential for tornadoes.

Lightning Jump
- I liked it more as the week went on. I usually used it in tandem with ProbSevere and PGLM Flash Extent Density. I could see all of these being in a 4-panel and helping with situational awareness for severe operations. Especially on Thursday, I noticed the storms with the biggest LJ's were the ones that strengthened considerably thereafter.
- I'll be interested to use this during cool season events, as I am always looking for more information in these situations.
- I like the way it is now, though I can see others preferring a contoured look.
- I like a 4-panel layout with ProbSevere, lightning jump, Severe CI, Lightning, composite reflectivity, and satellite imagery.
- Forecasters are/will always change to their preferred color tables.
- There will always be a spot for a product like Lightning Jump in my display.

GLM Total Lightning
- The lightning data will be very helpful for DSS - events, fairs, etc. It will be very helpful to have this information updating every 1 minute.
- Especially for cool season events, we are always looking for more data. Lightning from satellite will be helpful.
- I can see this being helpful in EM's decisions to evacuate stadiums.
- This will be big for us during fire weather season in the NW US.
- In the future, with lightning in field offices, there must be very good training on all of this. There is/will be a lot of different lightning data. Generally, forecasters do not know the differences in lightning verbage.
- I will likely overlay it on radar or satellite.
- LMA-1 was the favorite among the group

NUCAPS
- The plan view and cross-section components were my favorite aspect of NUCAPS this week
- The lure is that it is an observation. I think it should remain observationally driven, even though we know there could be a source of error. If so, we know the source of the error. If you add in model data, you don't always know the source of the error.
- Pop-up skew-T will be good to use before and during an event with NUCAPS.
- Modification is not an issue for me. In our office we modify RAP soundings all the time. It takes some time, but it works. 
- NUCAPS has a lot of potential, but a lot of bust potential for captivating an office.
- I can't get anyone to look at it in my office in Portland.
- The lack of detail is a killer. That's why I think plan view and cross section displays are more valuable.
- People will use it if they see the value, and it is made clear that this is an observation.

General
- Participants felt that the start of week orientation/familiarization was great.
- It was the perfect amount of products to evaluate.
- It would be nice to have a DRT WES case for slow days.
- I suggest having a group briefing after the groups complete their mesoscale analysis but before CI.
- The broadcaster commented that this was a great experience, and it was wonderful to be able to work directly with NWS forecasters.
- Some of the training material should be put on the CLC so we can go back and look at it in the future.

SRSOR Sandwich

Below is a SRSOR 1-min-updating animation of visible imagery with transparent IR imagery overlaid. This imagery depicts the line of convection moving into the Southeast, through our area of operation today (Huntsville and Nashville). This image combination allows forecasters to view rapidly changing storm-top features with the detail of the higher-res visible imagery and ability to see/sample temperature from the IR imagery.

Using Pop-up Skew-T with NUCAPS

Pop-up skew-T is a feature in AWIPS that allows forecasters to quickly visualize temperature and moisture profiles on a skew-T diagram from model-derived or observed sources. The user has the ability to move their mouse over a field and see the profile change in space. This is of particular use for NUCAPS, allowing a forecaster to get a quick look at the profile before clicking it and interrogating it further. See instructions and images below to use pop-up skew-T in AWIPS-II with NUCAPS.

1) Load NUCAPS Sounding availability (so you know where the swath is).

2) Load pop-up skew-T (top of "Volume" menu)

3) Turn on Sampling

3) Right click and hold anywhere in the screen, hover mouse over "Sample Cloud heights/radar skew T" at top of menu, Select NUCAPS. (see image 1). A Skew T box will appear somewhere on you screen.

4) Move mouse into NUCAPS swath to see temp/mois profile change in space (see image 2).

Pop-up skew-T for AWIPS

The Pop-up skew-T feature in AWIPS works for NUCAPS. This feature allows forecasters to quickly view soundings from NUCAPS before interrogating them further in NSHARP.

Mobile, AL had a special 18z radiosande launch today (shown below). The profile reveals a moist layer below 700 mb, with a dry layer centered around 400 mb. SBCAPE in the sounding is about 2100 j/kg, while TPW is 1.5 inches.

A modified NUCAPS sounding was sampled over the same location. The sounding depicts a similar moist low-layer, with a dry layer around 400 mb. CAPE is about 2200 j/kg, and TPW is 1.36 in, both similar to that from the observed radiosande.