KRAH: Using 4 Panel Lap Data in Mesoscale Analysis

I found creating a 4-panel of LAP data (below) useful to our mesoscale analysis. While the data was 2 hours old, we were still able to get a feel for the convective environment in the KRAX CWA. This will be a useful tool to supplement SPC mesoanalysis data since it utilizes observations from GOES-16 satellite rather than fully relying on a model. The updates are also a little more frequent than what is found on SPC. Including the data type helped to indicate some of the gradients and the reason for the pixelling of some of the data. This can give forecaster more confidence when its indicating clear or cloudy versus soley on the GFS, which could add uncertainty into the data. Other variables in LAP such as K Index and Showalter are not something I typically use, so I left these out of the 4-panel.

At first glance, the scale/labeling on the Data Type were confusing. One potential change would be to have wording such as partial cloudy (for cloudy retrieval) or something along those lines to better differentiate the categories.

Note: the time of the data was 2 hours old during analysis. 

-Ironman

KRAH: Initial Meso Thoughts.

CWA: KRH

Initial concern:

• SW-NE line of convection through the central CWA. 
• Big concern is with the northward propagating outflow boundary and its imminent convergence with the northern most band. (below) 
• Monitored initial ProbSevere numbers but feel this may be moot as the line is about to be modified by the outflow boundary.

Solely evaluating environment using satellite LAP data to get an idea of the the environment between the outflow and northern line. Only issue is the LAP data is almost 2 hours old and roughly evaluating the convective environment from it. 

The LAP 4 panel (below) reveals an environment with plenty of moisture and instability to promote further development and propagation for convective activity. 

• Ideally would have liked to overlay radar on the LAP output to see development along gradients, but not possible due to the old LAP data.
• This is a great SA tool to stay ahead of where you expect convective activity to continue or diminish.
• My take away from this analysis is: Atmosphere is primed to support long lived convection along the SW-NW swath through the RAH CWA. 
• Will now monitor radar trends, particularly interested to see if sharp trend start occurring in the ProbSevere. 

 --Forecaster: Tahoe

Dervived Motion Wind Issues

There are some inaccuracies with the derived motion winds when compared to surface observations. Here is an example with the 1000 mb wind speeds (near surface) and METARs:

Note the significant discrepancy in both speed and direction.

It also appears the clouds are moving southwest to northeast (opposite of the wind barbs).

In addition, I would suggest color-coding by pressure level rather than wind speed because wind barbs (by definition) already provide the wind speed information.

-Lost Met

EWP Week 1 Day 1 Operations

For the first day of the EWP Spring Experiment, participants are operating in the Boston and Raleigh CWA's.

HWT 2017 GOES-R/JPSS Spring Experiment Underway

The Hazardous Weather Testbed 2017 GOES-R/JPSS Spring Experiment is underway in Norman, OK. The experiment will last for four total weeks (June 19, June 26, July 10, July 17) and include three National Weather Service forecasters and one broadcast meteorologist each week. Participants will have the opportunity to evaluate imagery and derived products from the GOES-16 Advanced Baseline Imager which recently became available to forecasters in AWIPS. Additionally, HWT participants will be the first forecasters to evaluate the GLM lightning data in AWIPS. An updated ProbSevere Model will be demonstrated and include separate ProbWind, ProbTornado, and ProbHail probabilities. Finally, NUCAPS from JPSS will be demonstrated, including evaluation of the operational NUCAPS algorithm from Suomi-NPP, NUCAPS from MetOp A/B, and experimental NUCAPS product that is automatically modified in the low-levels.

Stay tuned to the blog for posts made by our participants and visiting scientists. Unfortunately, GLM data posts will not be available to the public due to the early testing stages of the data.

- Bill Line, NWS and Week 1 EWP Coordinator

Autumn storms on the Plains

An energetic, negatively-tilted shortwave trough traversed the middle of the country last week, bringing several bouts of severe weather to the Great Plains. By visualizing the accumulation of the ProbSevere output (storm centroids ≥ 50% [pink boxes]), the NWS warnings (orange and red polygons), and storm reports (blue, green, and red circles), we see that the ProbSevere model handled the first event on October 4th quite well, at least qualitatively.

Figure 1: A toggle between the 12Z 10/4 ->12Z 10/5 accumulation of NWS warnings and reports, with overlaid ProbSevere centroids greater than or equal to 50%.

A very long-lived storm that approached the Norman, OK area produced numerous hail reports. It was first identified at 23:47 UTC, with a probability exceeding 60%, due to high effective bulk shear, MUCAPE, and strong satellite growth rates. The MESH was 0.24" and total flash rate was only 1 fl/min. After quick jumps in the MESH (to ~0.5") and the flash rate (to almost 20 fl/min), the probability exceeded 80%, and was promptly warned at 23:52 UTC. We can see a time series of the ProbSevere probability (thick red line) and constituent predictors in the time series below. Note that the satellite growth rates were both 'Strong', and expired a little after 02:00Z. We can also see when NWS warnings were valid and when severe weather was reported in the lower subplot.

Figure 2: Time series of ProbSevere and its predictors (top), and NWS severe weather warnings and severe weather reports (bottom). The axes on the right are associated with the time series on the top subplot, while the legend in the lower right is associated with the bottom subplot.

The stunning time lapse of this storm was captured by Jim Ladue (NOAA/NWS/WDTD) as it approached from the west. The range of this video is from about 23:52 UTC (when the storm was first warned) to nearly 01:00 UTC.




A second short-wave ejected through the Plains on October 6-7 (as Hurricane Matthew threatened the southeastern seaboard), bringing with it another bout of storms, and this time, numerous tornadoes. ProbSevere again handled most storms quite well, with few false alarms and a couple of missed wind reports.

Figure 3: A toggle between the 12Z 10/6->12Z 10/7 accumulation of NWS warnings and reports, with overlaid ProbSevere centroids greater than or equal to 50%.

We can see the evolution of the storms and associated warnings below, over Kansas, Oklahoma, and far northern Texas. The animation is from 18:30UTC to 00:00UTC every 10 minutes. The pre-frontal storms and those close to the triple-point (in north central KS) remain discrete longer than those which are forced by the cold front. The red, orange, and green polygons denote NWS tornado, severe thunderstorm, and flash flood warnings.

Figure 4: Animation of ProbSevere contours, NWS polygons, and MRMS MergedReflectivity from 20161006-18:30Z to 20161007-00:00Z .

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.