PHS Highlights Instability Axis – Elko, NV

PHS Highlights Instability Axis – Elko, NV

High resolution thermodynamic parameters from PHS appeared to be in line with meso-analyzed products from the RAP (SPC Mesoanalysis). The benefit with PHS is the 2km resolution output, highlighting terrain features in the CWA. Composite reflectivity product performed well with expected convection through the afternoon, and helped with the creation of a mock DSS graphic that included up to 3 hours of lead time for an airshow in Wells, NV.

 

PHS SB CAPE at 19Z prior to CI

PHS Comp Refl at 18Z

PHS Comp Refl at 20Z

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PHS PreStorm Environment

Looking at the pre-storm environment using PSH we can see higher MUCAPE in the eastern most portion of ABQ CWA. We also looked at the SHIPS model on the PHS website and saw high number also in the eastern region of the CWA. That indicated to use the best chance of storms would be in the eastern most half of New Mexico and the biggest threat would be hail. PHS did excellent in this event. We have been seeing a few good hail cores in the area of the highest CAPE while areas to the west of of higher CAPE has see a storm or two but nothing close to severe.   .-Thunderstruck

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PHS SBCAPE Data in NV

Here is what the PHS SBCAPE forecasted for 5/24, 20Z across NV.  (Some of the purple circles within the areas of blue hinted at ongoing convection).  This matches up well compared to the forecasted 20Z SPC Mesoscale Analysis SBCAPE.  How did it verify?

The 20Z SPC Mesoscale Analysis SBCAPE had an area that was 2,000 J/kg.  However, this appeared to be overdone as there  was widespread convection occurring across this area.

Remember, the PHS hinted at ongoing convection in some of these areas.

-Champion

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PHS Comp Refl Data in NV

Here is what the PHS Comp Refl was forecasting for 5/24, 22Z across NV.  How did it verify a few hours later?

MRMS 0.5 km Comp Refl at 22Z showed a broad area of convection over NV.  What’s interesting is how some of the individual storms were very, very close to the locations where the forecast hinted at there being individual storms.  Keep in mind, the radar coverage in this part of the country is not very dense.

-Champion

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Sectorizing Initiation Points and Greatest Severe Threats By Low Level Moisture Content

RGB Satellite Product Using Split Window Difference

The quality of boundary layer moisture will be important to the severe convective threat across the MAF CWA today. Using the late morning split window difference field (within the RGB shown below), the greater moisture field can be found over northeastern portions of the CWA with the subtly greener shade of color. This color shade in the northeast generally overlaps with surface observations showing >60 F dew points. The color shade is more blue in central portions of the CWA where dew points drop into the upper 40s. While dew points are still lower in the southwest, there is a color shade difference where higher terrain exists (as well as greener vegetation). In this area early morning orographic convection had developed. By the mid afternoon, convection had developed near the moisture gradient in the south central portion of the CWA as well as near the northern moisture gradient along a surface low over the southwest New Mexico border.

PHS Analysis

The PHS forecast product agreed with the overall moisture gradient, where greater dew points and lower LCL’s draped the northeast corner of the CWA. Subsequently, the PHS MUCAPE product showed greater instability within this corridor.

 

PHS Dew Point

PHS LCL

PHS MUCAPE

Even with these satellite based products analyzing the moisture content well before the convective threat later today, it lines up well with the forecast greatest severe threat from today’s SPC outlook (shown below), with the Slight risk favoring the northeast portion of the county.

– Joaq

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PHS as a SA Tool for Incoming/Developing Convection

Thunderstorms advecting (and developing) from the west appear to be moving into a better thermodynamic environment. SB CAPE parameters between 3k and 4k J/KG analyzed by PHS across the northeastern counties of the MAF CWA lead me to believe storms will strengthen in the next couple hours as they move into this region. SB CAPE values from 3,000 to 4,000 J/KG are analyzed by PHS at 23Z.

– Rain-Free Bass Guitar

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Satellite HWT Day 1 Analysis Carl

PHS Model Analysis

PHS model struggled to properly capture convective initiation within the Texas Panhandle on the day. While it did see a few cells possibly starting, overall coverage was significantly underdone with many of these storms reaching severe thresholds including numerous reports of hail over 1″. The overall output shared many of the same struggles as the HRRR model on the day. Unclear what the exact problem was, but dry line convergence may have been better than in models on this day.

Above: 15Z PHS model output forecast for 17Z to 22Z from 5/22 with MRMS Reflectivity overlaid.

Below: 15Z PHS model output for 17Z to 22Z from 5/22.

NUCAPS Forecast

As I was beginning to test out these products, this caught my eye as a forecaster on the east coast that regularly deals with Cold Air Damming along the Appalachians. Models regularly struggle with multiple aspects of the dam, including extent, depth, and actual temperature and strength. Additionally, one of the most common pathways for large winter storms in the southeast is when low pressure passes across the Gulf Coast and into the Atlantic while an Arctic high in the northeast helps drive cold air damming into the area. Models again struggle with the dam, but also with strength of the warm nose aloft. I would love to see how this system performs in these scenarios – I know it isn’t “convective”, but it still is an incredibly impactful event, where the strength of the warm nose can be the difference between a few inches of snow or half an inch or more of ice. We regularly attempt to send up special soundings to get the best sample we can, but since GSP does not do a sounding, we rarely get a meaningful sample of the cold air damming in the SE states.

Above: NUCAPS Forecast from morning pass over east coast showing CAD feature over the east coast.

Octane Speed and Direction

Above: Octane image around 22Z for storm just south of AMA.

The Octane product was extremely useful in seeing when updrafts were really “taking off” and hitting the tropopause, immediately highlighting storms which require quick attention. Another extremely useful feature is sampling the actual speed, which gave a potential proxy for storm top divergence. Noticed that the Octane product gave a value around half of what the radar was measuring on this storm – ~50 kts on the Octane product vs ~100-110 kts on the radar. I’m assuming the resolution combined with some of the smoothing within the algorithm may be playing a role here, but it would be interesting to see if there is a consistent way to match the two up, even if there is just a “rule of thumb” or something. This would be huge in areas of sparse radar coverage (portions of the west or the ocean, for example).

Below: Radar image of storm top divergence near 22Z from KAMA.

ProbSevere v3

Noticed an interesting time period where two close updrafts – one fading, one picking up, resulted in some jumping of the ProbSevere product as it would sometimes combine the objects and then sometimes track them separately. I think this shows the importance of pairing the algorithm with analysis – just looking at the time series of the product could lead to misinterpretation of what was happening.

-Carl Coriolis

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PHS Tornado Parameter

Unfortunately I didn’t look at this PHS Significant Tornado Parameter in real time when warnings were being issued, just completely spaced it.  But went back to see how it fared during the Tornado Warnings, it didn’t do too bad.  The comparison below is from 21z and even though the tornado warning was already issued before the PHS STP was available, it was a nice “confirmation” tool of the Tornado Warning.  The units of the STP were nearly 10 at the time of the strong couplet north of Clifton, WI and it was in the right location at the time of warning.

Figure 1: base reflectivity with ProbSevere Tor Model and warnings in effect.

Figure 2: base velocity animation of the strong couplet over Oakdale or just north of Clifton, WI.

Figure 3: PHS Significant Tornado Parameter at 21z on June 15, 2022. The circle over Clifton is a reference point for the velocity animation from Figure 2.

– PODIUM

Can PHS Improve Mesoanalysis and Near Term Convective Forecasts?

A large portion of the MKX CWA was included in a MDT severe risk, so by the start of the operational period, we had to assess the evolving severe threat spreading in from the west. Meanwhile, our DSS event was the Madison Jazz Festival, which entailed a focus specifically on south central Wisconsin. The PHS CAPE forecast appeared to be a noteworthy improvement from the CAPE fields on the SPC Mesoanalysis, along with the short-term forecast on that page.

Below are the 18z through 20z plots of MUCAPE, MUCIN and effective bulk shear from the SPC Mesoanalysis page.

Compare the above images with 4000 J/kg of uncapped MUCAPE to the PHS MUCAPE initialization at 18z and 2-hour forecasts (19z and 20z) below.

As you can see, while the SPC mesoanalysis was indicating 4,000 J/kg of uncapped MUCAPE, the PHS forecast showed CAPE decreasing across central and south central Wisconsin. This was an important and helpful piece of information for our DSS content for the Madison Jazz Festival.

The Day Cloud Phase RGB images below back up the PHS forecast vs the SPC mesoanalysis, as relatively flat Cu field over our area of interest actually dissipated between 20z and 22z.

Based on the PHS forecast combined with satellite analysis, we were able to focus the convective threat for the Madison area toward 6PM and onward, tied to the stronger forcing and better moisture arriving from the west where the ongoing convection resided closer to the cold front. It appears that the PHS sampling of moisture in the column applied to the near-term forecast strongly outperformed the SPC/RAP Mesoanalysis model background and OA algorithm.

Differences between the LightningCast (LC) CONUS and LC Mesos

Note below the CONUS scale (1st image) and Mesos (Meso Sector 2 on 6/15) had a different depiction of the lightning probability over northeast Iowa at 1911z 22Jun15. This was due to the time for a CONUS GOES-East scan to complete, vs. the much shorter time for a Meso sector, which in turn affects the LightningCast model. This is something to keep in mind when using the product.

ProbSevereV3 Trends for Severe Convection in Western/Southwestern Wisconsin

At 2106z, the ARX office had recently issued a Tornado Warning (2102z) for the northern cell with a high % on PSV3 and PTV3, per the noted superior calibration of the updated model vs. the V2. Could the PSV3 and PTV3 trend on this storm have assisted the radar operator in an increased lead time? As you can see below, starting at 2045z, there was a sharp upward trend in the ProbTor, to near 40% prior to 21z. At the least, this tool appears to be an excellent situational awareness tool, and may even be able to help lead time in some cases. It helped us in the MKX CWA regarding downstream warning issuances. In the event of an unexpected radar outage in a sparse radar coverage area, environmental analysis plus satellite interrogation with the utility of PSv3 could support successful radar warning ops in a less than ideal scenario.

– Hurricane84

Situational Awareness and Lead Time with LightningCast and ProbSevere/Tor

Today’s experience landed us in MKX monitoring convective development potential across the western portion of the CWA, with a line of storms ultimately moving in from the west, and some risk of discrete cells persisting even after we ceased the experiment.

I took the opportunity today to set up procedures overlaying PHSnABI indices (CAPE) with satellite imagery (e.g. Day/Cloud Phase or Viz), to see how well it corresponded with convective development. Unfortunately I didn’t grab a screenshot, but it was a nifty display that I hope to use again. PHSnABI suggested that CAPE in some areas of the CWA was not as high as the SPC mesoanalysis or RAP suggested. We tried to investigate this using a combination of NUCAPS and model soundings and RAOB, but couldn’t figure out a reason for the CAPE depression before incoming storms grabbed our attention. Notably, the indices derived only from GOES agreed with PHSnABI about this depression, though we couldn’t figure out if it was correct. It seems likely the GOES ABI was driving the PHSnABI result.

My main takeaway the rest of today is how useful ProbSever, ProbTor, and LightningCast can be with approaching/developing convection.

LightningCast, combined with GLM data, was useful for IDSS imagery to depict position and potential of lightning (example DSS slide using these graphics provided below).  Storms never made it to our decision point prior to leaving the experiment, but lightning threat was usefully communicated to the simulated JazzFest event.

As convection developed, we also practiced relying on probSevere and probTor for lead time in anticipating warnings. The following shows an example where the probTor trends corresponded well with ARX’s actual decision to issue a tornado warning.

SImilarly, intensification of the convective line appeared to be well detected. In fact, depending on what threshold of the probSevere parameters is relied on (probably depends on environment and other factors), the escalating value could have given useful lead time for a severe issuance decision.

Although the main mode appeared to be a line of convection, there were positions along the line where tornado risk seemed to increase (evidenced by radar velocity). It was reassuring to see probTor pick up on the gradually increasing risk of tornadoes as well.

And one final note… lightningCast is fairly impressive in how it produces calibrated estimates of lightning occurrence using only a single time step of satellite imagery (though it uses several bands of the ABI). Naturally lightningCast has difficulty where a developing tower is obscured by an anvil overhead, as we saw in this example. But it was neat to see lightningCast immediately respond with a broader swath of high lightning probabilities the very first time that a tower poked above the anvil that previously obscured it.  The fact that it was hidden probably means lightning could have been occurring below the anvil with lower than ideal lightningCast probabilities (though non-zero, to its credit), but it was neat to see the immediate adjustment to the probability contours with new imagery.

– Buzz Lightyear