How to Hodograph
This is an ever-evolving guide on advanced hodograph concepts.
New to hodographs and want the basics? Check out https://www.youtube.com/watch?v=PpsGMnoWaZk&list=PLnjboQ2ku8GDI9DGcqR8d9sr0sZKhH-qX&index=8
Want a parameter explained? Ctrl-F “critical angle”
Want a hodograph field guide? Ctrl-F “field guide”
Want this narrated? Check out…
What is storm behavior?
If you’re a storm chaser, you’ve probably sat outside some small town in western Kansas for hours, waiting on the low-level jet to kick in at sunset, since you know this can herald the arrival of “motherships” like this one:
You also probably know that unmistakeable “outbreak” look, the one storms give you when they’re gearing up to produce a strong, long-tracked tornado:
Or maybe you’ve got a special soft-spot for “cold core” days, where photogenic tornadoes drop out of dreamy cotton-candy cumulus, seemingly at random:
You probably also know how to tell a tornado-producer:
From one that may just leave a golfball-sized dent in your windshield:
If you’ve tracked enough on radar, you may even be able to tell a classic “cycler”:
From a frightening “long-tracker” with no plans to stop anytime soon:
How do we just know these things? Well, if you’ve ever heard the term “organized” convection, a supercell is just one type of organized storm, and can itself be organized into a myriad of possible structures and sizes. What does this “organizing”? The wind shear! So, for example, when you see the above supercell on radar, you’re not only seeing its stretched-out appearance, but also the intense low-level shear needed to make it that way.
Likewise, when you see a windswept “barberpole” like this one:
You’re not only seeing its tightly-wound, circular updraft, but also a large, looping hodograph.
How do we predict storm behavior?
Storm behavior is how a storm tends to be structured, and changes its structure, over time. Its “behavior” is thus a holistic, all-encompassing description of its structure, appearance, and hazards. The hodograph contains the “DNA”, so to speak, of how storms tend to behave. But where do we even begin?
Much of forecasting today is currently built around a parameter statistics paradigm to predict the probability of certain events. For example, there was a time when we knew very little about what distinguished between the environments of tornadic and non-tornadic storms. We created a few different ways to quantify the hodograph (including SRH and bulk wind difference) based on our understanding at the time, then plugged the numbers to figure out which of these, and what layers (low-level, mid-level, etc.), best correlated with the occurrence of tornadoes. Because they still do a good job and have theory to back them up, they’ve stood the test of time, and are still used today.
However, as we continue to work toward more and more nuanced forecast problems and deeper understanding, we find that these parameters we made may be a bit oversimplifying, and perhaps even lead us astray on occasion. We also find that these tools naturally can’t do everything for us. How do we predict tornado duration? What about hail potential? Mini-supercells? “Motherships”?
Let’s follow a logical progression:
- storm behavior is governed by storm-relative winds
- storm-relative winds are induced by storm motion
- storm motion is determined by the wind profile (and external forcing)
Storm behavior is technically governed not by the wind profile itself, but how the storm interacts with that wind profile. In other words, what storm-relative winds does it “feel” from that wind profile?
Fortunately, for storms free of external forcings that may influence their propagation (such as boundaries, fronts, cold pools, and neighboring cells), their motion is largely determined by the wind profile. So in this case, we can safely conclude that their behavior depends directly on the shear profile!
In other words, this means that storm structure depends on hodograph structure!
While parameters may be good for assessing the statistical probability of certain occurrences, we must remember their limitations. The effective bulk wind difference, for example, considers only two (2!) points out of the entire hodograph!
Bulk Wind Difference
Bulk wind difference (also, but less technically, known as “shear”) is the distance between two arbitrary points on the hodograph. In a general sense, and given the same hodograph shape, stronger shear leads to better updraft/downdraft separation, and larger, longer-lived, more severe storms. There’s plenty of statistics to back this up too. However, with different-shaped hodographs, this rule isn’t always true:
When assessing bulk shear, it’s often necessary to consider the boundary layer (say, 0–1-km) as well as the lower cloud-layer (say, 1–6-km). Since boundary layer shear has many different orientations, using a deep-layer shear such as 0–6-km (or “effective” shear) can lead us into the most trouble.
In the author’s experience, shear can be broken up into two main components:
- 0–1-km shear (important for hail/tornado production)
- 1–6-km shear (important for supercells/mesocyclones)
Wind shear is very important in organizing convective storms. But as we noted in our logical progression above, storm behavior depends on how the storm interacts with the shear. This interaction is determined by the storm’s motion.
For storms that are “free” to move with the environmental wind alone, predicting their motion isn’t actually too difficult. Initially, all updrafts move along with the mean wind in the cloud-bearing layer.
However, once they grow wider and acquire sufficient dynamic pressure perturbations (essentially, micro-scale low and high pressure centers induced by the updraft’s interaction with the shear), they will begin to deviate. Classically, this is seen as a “right” turn (in the northern hemisphere, as typically the cyclonically-rotating updraft is favored), such as in this case, where an eastward-moving supercell may turn sharply southward:
The Bunkers method of estimating storm motion is incredibly accurate in a statistical sense, such that when you’re using it to predict potential supercell motion, you’re rarely going to be noticeably off. That said, it also assumes every storm deviates exactly 7.5 m/s from the mean wind, which we know isn’t true on a case-by-case basis. This is a worthy trade-off, though, since it also allows us to calculate a variety of other useful tools (such as SRH and storm-relative wind) that wouldn’t be possible without it.
For classic supercells, this rightward deviation is usually pretty noticeable. However, given a fast enough storm motion, this deviation is hardly perceptible, as the storm changes course by only a few degrees:
This deviation can also be perceived by a sudden “stop”:
And, very rarely and paradoxically, even a “left” turn from its initial trajectory:
The width of the storm may actually have a lot to do with how much it deviates from the mean wind, like in the below example:
Tornadoes can also take on deviations of their own. These sudden turns had been generally thought of as “unpredictable”, but that was only until recent efforts on how to predict them!
On the other hand, storms that are “forced” by external forcing take on motions not predictable using the hodograph alone. Therefore, we can’t really estimate them as easily ahead of time!
For instance, take a storm that’s “latched” onto a boundary:
Here, we can watch a couple supercells on the upper right form, move with the mean wind, split, and deviate towards Bunkers Right. However, check out what that westernmost cell is doing! It begins by “anchoring” to a boundary, assuming its motion, rather than the mean wind’s. And once it establishes a strong enough cold pool, it even goes “zippering” down it to the southwest!
Now, what about convective systems? These are driven not only by the mean wind, but also by:
- Boundaries and fronts
- The low-level jet
- Their own cold pools!
As it turns out, MCS motions can be predicted ahead of time to some extent. That said, strong cold pools, and especially strongly-forced fronts, can push these systems elsewhere.
For all forced storms, the hodograph alone cannot predict their motion, thus it cannot predict their behavior. So, it’s not only best practice, but absolutely necessary, to always use observed storm motions!
Some common forecasting fallacies are that MCS strength can be predicted using bulk shear, or that mesovortices can be predicted using SRH. Instead, we need to know the motion (and orientation) of the system relative to that shear, and we can’t just use Bunkers Right SRH (a supercell parameter) on a QLCS!
The Storm-Relative Hodograph
Now that we know how to find our storm, let’s make a storm-relative hodograph.
First, start with the standard, ground-relative hodograph:
Now, subtract storm motion from every point along the hodograph:
Now, we have a powerful tool that normalizes all of the seemingly-infinite hodograph shapes into what the supercell actually experiences. And whereas no two ground-relative hodographs are alike, you’ll find that patterns may actually repeat themselves here! A supercell is an engine; here, every single turn and kink with height (or lack of segment altogether!) has a profound impact on the supercell, its appearance, behavior, and impacts.
The storm-relative wind can be broken up into two main components:
When forecasting with storm-relative wind, most of us (especially chasers) think of storm-relative outflow. Outflow regulates the ventilation of precipitation outward from an updraft.
Strong outflow, especially above around 6 km, pushes rain neatly away from the main updraft base, allowing you unobstructed views of the business-end of a storm. The author’s rule of thumb is that a deep layer of storm-relative outflow stronger than 40 kt above 6 km may give you a more “LP” (low-precipitation) storm:
On the other hand, a storm in weak outflow will be poorly ventilated, and tend to rain into its own updraft or very close by it, and at the very least hide the tornadic action from plain sight. The author’s rule of thumb is that a deep layer of storm-relative outflow weaker than 20 kt may give you “HP” (high-precipitation) storms that, unless you’re experienced, you probably shouldn’t be chasing:
That said, there seems to be an exception to this rule: mini-supercells! We’ll talk about how to forecast those soon.
The orientation of the mid- and upper-level storm-relative winds also has a lot to do with how safely we can spot storms. Storm-relative winds that veer around storm motion (such that blow outward in many different directions from the storm) can create heavily rain-wrapped mesocyclones and dangerous spotting situations that make you venture straight into “the notch”:
On the other hand, storm-relative winds that back away from storm motion (such that blow outward in primarily only one direction from the storm) can open up spectacular views of the updraft and make for some pretty easy spotting:
How does storm-relative inflow impact the storm? Quite intuitively, it regulates the mass flux into the storm — basically, how much air mass is flowing into the storm at once. Very recently, we’ve began to see that inflow has a huge impact on updraft width, and thus storm size!
Strong storm-relative inflow makes it a lot easier to make bigger supercells with all the moisture surging into them at once. The author’s rule of thumb is that a deep layer of 0–1-km storm-relative inflow stronger than 35 kt may help amass particularly “mega” supercells:
On the other hand, weak storm-relative inflow makes it much harder to sustain even a normal-sized supercell. The author’s rule of thumb is that if your hodograph features a deep layer of 0–1-km storm-relative inflow weaker than 25 kt, you’re probably dealing with mini-supercells!
Horizontal vorticity is the rolling motion induced by a change in wind with height. The vorticity vector points perpendicularly to the left of the shear vector per the right-hand rule:
In this sense, imaginary vorticity “rolls” (oriented in the direction of the vorticity vector) are always present in a sheared environment. But of course, what really matters is how the storm interacts with these vorticity rolls.
When the storm-relative wind blows through the vorticity rolls, the storm-relative wind is quite literally spinning. And when the storm-relative wind spins, so does the storm! The tilting of streamwise vorticity directly induces updraft rotation from the getgo:
In purely streamwise vorticity, you’re much more apt to get mesocyclones that are perfectly co-located with the updraft — in other words, the updraft is rounded and rotates as a whole. Remember our “mothership” supercell? This is a physical manifestation of a broad, purely-rotating updraft:
On the other hand, when the storm-relative wind blows across the vorticity rolls, the storm-relative wind has no spin. Although an updraft in this environment will not rotate initially, the tilting of this vorticity induces yield two counter-rotating vorticity maxima that straddle the flanks of the updraft, which, especially with straighter hodographs, may then mature into a splitting pair of right-mover and left-mover!
In purely crosswise vorticity, mesocyclones tend to be dislocated from the primary updraft, and confined to the flanking line. This can manifest itself as a more linear storm that may not appear to be rotating as a whole (or even at all). Make no mistake, though, supercells in even purely crosswise vorticity can be very long-lived and powerful, and produce all hazards just like their streamwise counterparts.
Though crosswise vorticity is still very important for supercell development and maintenance, we currently quantify only the streamwise component of vorticity, since it induces updraft rotation most quickly.
Streamwise vorticity can be quantified in two main ways:
- Streamwise vorticity — how much streamwise vorticity is there?
- Streamwiseness of vorticity — how streamwise is the vorticity?
The streamwise component of vorticity (typically just called “streamwise vorticity”) is the magnitude of vorticity that’s streamwise. This is directly related to how strongly an updraft will tend to rotate upon tilting and stretching it.
It’s important to understand that what matters for updraft rotation is the component of streamwise vorticity. So even if vorticity is not very streamwise, but there’s lots of it, the streamwise component adds up over time. This can be seen in the below case:
It’s also important to recognize that whenever there is extreme low-level shear, there will always be potentially extreme amounts of streamwise vorticity. In other words, even if forecasted storm motions don’t allow for much streamwise vorticity, it is always possible that a storm ends up acquiring a motion that supplies it with much more streamwise vorticity than forecast. The reverse is also true.
The magnitude of streamwise vorticity is traditionally estimated using storm-relative helicity.
Storm-relative helicity (SRH) is the product of both the streamwise component of vorticity and the storm-relative inflow, integrated over a layer. This ends up being graphically represented by the area under the hodograph that’s swept out between the storm-relative winds at the top and bottom of a layer:
It’s very important to remember that SRH is just an estimate, and not a direct measure of streamwise vorticity. In the author’s opinion, it’s interesting how we got to the point of using solely SRH in the first place, rather than streamwise vorticity itself. Regardless, it gets the job done, with plenty of statistical studies proving its correlation with supercell and tornado environments.
That said, because SRH is a product of both the streamwise vorticity and the storm-relative inflow (which we found has very different influences on the storm), this means that the relationship between SRH and streamwise vorticity isn’t exactly intuitive. Although most of us were taught that more SRH means more streamwise vorticity, this actually isn’t always true:
Remember, the SRH you see on most every model viewer gives you the potential energy that a robust, right-moving supercell would have available to it. It is not meant to be used to forecast supercell formation, since it’s not what’s available to a developing updraft. Though you may be tempted to remark that “supercells are likely today given all this SRH”, you’d be assuming a supercell already exists, which is technically a logical fallacy. Since you’d also be ignoring crosswise vorticity, the most abundant source of vorticity in most developing updrafts (which we’ll talk about soon), you’ll have much better luck just looking at a hodograph.
Streamwiseness of Vorticity
The streamwiseness of vorticity (typically just called “streamwiseness”) is the degree of streamwiseness of the vorticity. This is directly related to how purely an updraft will tend to rotate upon tilting and stretching it.
Be careful not to conflate this with streamwise vorticity (a magnitude). Folks may be driven to spot 90-degree critical angles or perfectly circular curvature and proclaim that there’s a lot of streamwise vorticity. Although there probably is, in this case, they are admiring how streamwise the vorticity is, not how much, so “streamwiseness” is the word of choice here.
Critical angle is the angle between the surface storm-relative inflow and the 0–0.5-km shear vector. It was found in a small sample of 65 supercells (only within Oklahoma) that significant tornadoes were associated with critical angles near 90 degrees:
It’s important to understand that critical angle does not measure streamwiseness, but rather the specific shape noted with significant tornado environments in Oklahoma. Because it compares only the surface storm-relative wind with the entire 0–0.5-km shear vector, it may not faithfully estimate the streamwiseness of the surface wind, or the streamwiseness of the 0–0.5-km layer. Once again, the author finds it interesting that critical angle, rather than streamwiseness itself, remains in mainstream use, especially as studies begin to show that contrary to its current use, the critical angles for significantly tornadic supercells are actually smaller than those for non-tornadic supercells (and farther from 90 degrees) on average across the U.S.
When forecasting supercells, most of us were taught that rotating storms need streamwise vorticity / SRH. However, in reality, supercells can be sustained with all of (or only):
- Streamwise vorticity
- Crosswise vorticity
- Vertical vorticity
This is to say that powerful supercells can still thrive in environments like this:
Or even in environments like this:
Vertical vorticity is vorticity with a vector that is already oriented vertically. An updraft atop vertical vorticity will rotate (especially from the ground-up), which is why vorticity-rich boundaries (such as the Denver Convergence Vorticity Zone) are so efficient at generating tornadoes. If we count upward motion as storm-relative wind, technically, vertical vorticity is streamwise vorticity!
With these other contributors, supercell “strength” (however you define this) is not necessarily related to streamwise vorticity and SRH. In this way, SRH is only half the picture.
What does “veer-back” do?
Veer-back has been oft-cited by chasers (and forecasters) as the bane of a supercell’s existence, and the kiss of death to any otherwise solid tornado event. Though these worries seem to be subsiding in recent years thanks to some mythbusting research, there’s still some curiosity as to what it really does to a rotating storm.
So what does veer-back do? Some folks may think it messes up a storm’s rotation by spinning it in the opposite direction aloft. This is absolutely not what happens. Others think it “suppresses” mesocyclones (and tornado potential). This is half correct at best.
What those of us who still fear this phrase need to understand is that a storm doesn’t care about veering and backing. All it cares about are the internal pressure perturbations (changes) induced by its interaction with the shear:
The linear dynamics term dictates that shear induces high pressure on the upshear side of a storm, and low pressure on the downshear side. In a straight hodograph, this does nothing to enhance or suppress the cyclonic (RM) and anticyclonic (LM) circulations which are on the flanks. In a hodograph that veers 180 degrees, however, this works to enhance the right-mover and suppress the left-mover:
So, taking the same concept but now for a shear profile which veers then *backs* 180 degrees, the backing would, in theory, work to suppress the right-mover’s updraft/mesocyclone above around 2 km:
But in this case, the backing is just less than 90 degrees, and associated with very weak shear, both of which will only negligibly suppress a mesocyclone:
Above all, it’s important to consider the relative impact of the linear dynamics term’s suppression on a right-mover. Even taking our first case, where there is clearly suppression, we also must consider the non-linear dynamics term, which states that an updraft that acquires rotation will ultimately induce rising motion that enhances it. We have tons of streamwise vorticity available to this right-mover, so especially if we have enough buoyancy, updraft rotation seems quite likely. And we even have studies that suggest that backing shear aloft may actually strengthen a supercell by re-orienting the downdraft to a position beside the storm (and not ahead of it), in a way that’s both less destructive and perhaps even more conducive to forward flank baroclinicity and the development of the SVC.
So it’s quite possible, then, that the suppression created by even the most wicked veer-back of this case pales in comparison to the enhancement of the supercell due to powerful streamwise vorticity, buoyancy, and even the backing aloft itself. Will we start saying “veer-back will enhance mesocyclones” in the future? Only time will tell.
Forecasting Hazard Type
Most of us reading this know that tornadoes are primarily a low-level shear problem. But that hail is also a low-level shear problem is a lot less common knowledge. Let’s explore the “inverse” relationship between the two.
Tornadoes, at least in the traditional sense, require a sustained, intense low-level mesocyclone. This typically requires near-surface streamwise vorticity (which is why we use near-surface SRH). As we talked about earlier, streamwise vorticity is provided by low-level shear. So, low-level shear is predominantly good for tornadoes:
Hail, on the other hand, requires a sufficient amount of embryos and a sufficient residence time within an updraft to grow. This residence time is both vertical (they must remain within the “hail growth zone” of ~-10 – -30C, which is actually often only centered at only around 6 km high), as well as horizontal (they must remain within the “embryo curtain”, a.k.a. the flanking line of the storm):
To maximize the number of embryos, we can never go wrong with a larger storm. This is one reason why mini-supercells are mostly harmless to your windshield, and another reason why behemoths like this one have cores that you absolutely positively do not want to go frolicking into:
To maximize vertical residence time within the hail growth zone, we ideally want a weaker updraft (yes, I know we were taught that 6000 CAPE is a good way to get Camri-sized hail, but that thinking isn’t holding up so well anymore). Intense mesocyclones might not be great for hail production either for this same reason:
To maximize horizontal residence time within the embryo curtain, we ideally want weak advections through the updraft:
The common denominator here? Low-level shear! Not only has low-level shear been noted to “blow” embryos out of the flanking line, but it also induces intense mesocyclones, which may loft hail up to the equilibrium level before giving it time to grow. What’s more, low-level shear even impacts the strength and depth of storm-relative inflow, a key contributor to updraft width as we explored earlier.
As a result, weak low-level shear is typically necessary for hail:
Is strong low-level shear necessarily bad for hail then? Well, not necessarily. Some simulations have shown the potential for sporadic giant hail production even with decreased overall hail efficiency in strong low-level shear, and there’s not a whole lot we know about how to anticipate this. That said, this seems to be the exception to the rule.
Almost exclusively, bona fide “gorrila” hail environments feature weaker low-level shear than that associated with tornadoes, and hail reports have routinely been noted to “shut off” as storms encounter stronger low-level shear and become more tornadic:
The end result is an “inverse” relationship between the environments that strongly favor tornadoes and the environments that strongly favor hail:
What about “elevated” storms? Most chasers know that once a storm crosses north of the boundary, it’s game over for tornado chances. But what does becoming elevated even mean?
Storms with access to a near-surface mixed layer and minimal convective inhibition are said to be “surface-based”, and are able to pull inflow from near the surface. But in the case of a stable layer or inversion, convective inhibition felt by a rising parcel in this layer may be so strong that even the strongest updrafts fail to pull inflow from near the surface. The layer from which storms can actually likely draw inflow is known as the effective inflow layer, and can be estimated ahead of time. So how does having an elevated effective inflow base affect hazard production?
An effective inflow base at the surface means that in all likelihood, a storm can pull inflow (and all of its characteristics) from near the surface. In this case, the storm would be accessing very strong low-level shear, encouraging tornado production while discouraging hail production:
On the contrary, an effective inflow base above the surface means that in all likelihood, a storm cannot pull inflow (or any of its characteristics) from near the surface. In this case, the storm would be accessing very weak low-level shear, discouraging even low-level mesocyclone production, but encouraging hail production!
Interestingly, for those chasers who know the “elevated hailer” all too well, this lends credence to the observation that in some shear environments, elevated storms are more likely to produce hail than surface-based storms.
The Map of Hodographs
Spatial maps of hodographs are becoming more common in the forecast process. Now that we know how hodographs can be useful to us, let’s see how some different renditions can help us out.
Storm Prediction Center
The SPC Mesoscale Analysis page features maps of ground-relative hodographs for the RAP model. Most prominently, they also feature the effective inflow layer — perfect for diagnosing the shear available to an elevated storm! It also features the Bunkers RM, LM, and MW storm motions, so you can make better assessment of the shear available to different common storm motions.
College of DuPage
The CoD NEXLAB Forecast page features maps of storm-relative hodographs for the RAP and NAM models for both floater sectors. Also included is an SBCAPE overlay to make life easier. With storm-relative hodographs, all the above concepts can be much more easily inferred, so whether your goal is predicting motherships or mini-supercells, you can do it here!
The Pivotal Weather models page features all the hodographs. From the long-range Euro to the CAMs, Pivotal has you covered. This makes assessing any small-scale hodograph variability quite a bit easier, but always be cautious withe using CAMs — as always, this variability may be convectively induced, and may (or may not) be realistic. What’s more, since all the hodographs are plotted, you’ll know which ones are coming even before the CAPE rolls in.
More on hodographs:
“Forecasting the Chase”:
“Storm Photogenic-ness and Spotting Hazards”:
Hodograph Field Guide
Here’s a few common hodograph shapes for supercell storms that you’ll likely see out in the wild. These are regular storm-relative hodographs, so they’ll look a bit more like you’re used to.
Though most are named by the region where they are most commonly found, it’s very important to recognize that these shapes can occur anywhere (video locations may reflect this).
Ohio Valley Outbreak
This type is found most often around the Ohio River Valley in the spring, especially from March-April (with a potential secondary peak around June), in organized severe weather outbreak scenarios, and is characterized by strong, mostly streamwise low-level shear and veering mid- to upper-level flow. Though lack of lower mid-level shear may make for some “grungier” and less organized storms at times, strong cloud-layer shear typically allows for longer-lived supercells with the potential for intense tornadoes and severe wind gusts.
This type is found most often in central OK and southern KS in the spring, especially around May (though similar shapes may filter into the Ohio River Valley, especially from March-April), and is characterized by moderate, mostly streamwise low-level shear and strong mid-level shear. These supercells are rather linear but can become very large, carrying the potential to produce large, long-lived, violent tornadoes, along with significant-severe hail and severe wind.
This type is found most often from the TX/OK Panhandles into central KS, especially from May-June, and is characterized by moderate, partly crosswise low-level shear and strong mid-level shear, with otherwise weak deep-layer shear. These supercells tend to be large with a circular front and deep rearward occlusions, and is rapidly cyclic, with the potential for highly deviant, significant tornadoes and significant-severe hail.
This type is found most often in central KS, especially from May-June, and is characterized by weak low-level shear and strong, purely streamwise mid-level shear. These supercells tend to be large, nearly perfectly circular, and often almost stationary, and carry the potential to produce significant-severe hail, as well as a couple weak tornadoes.
This type is found most often from W TX northward into E CO, especially from late May-July, and is characterized by weak low-level shear and moderate, purely streamwise mid-level shear. These supercells may be small at times, but may possess strong and tight mesocyclones with the potential to produce significant-severe hail, as well as weak tornadoes (especially given a surface boundary).
High Plains Magic
This type is found most often from E CO northward into E WY and SE MT, especially from late May-July, and is characterized by moderate low-level shear and strong, mostly streamwise mid-level shear. These supercells tend to be large, and may carry the potential to produce intense tornadoes (even in hostile thermodynamic environments) in slowly cyclic fashion, along with significant-severe hail.
High Plains Post-Frontal
This type is found most often from E CO into the TX/OK Panhandles (though may also appear almost anywhere up the High Plains), especially from June-July, and is characterized by weak low-level shear but very strong, mostly streamwise mid-level shear. These supercells tend to be very large, and persist well into barely hospitable thermodynamic environments, with the potential to produce long swaths of significant-severe hail and significant-severe wind.
Northern Plains Hailer
This type is found most often from North Dakota into Nebraska, especially from July-August (though similar shapes may be found from western OK into north-central TX especially around May), and is characterized by weak, largely crosswise low-level shear and very strong mid-level shear. These supercells tend to be very large and carry the potential to produce long swaths of significant-severe hail, and perhaps a couple weak tornadoes.
This type is found in a variety of locations, especially around the central US from W KS into C IL, at almost any time of the year, and is characterized by weak-to-moderate (at times largely crosswise) low-level shear, weak lower mid-level shear, and strong upper mid-level shear. These supercells tend to be small, but carry the potential to produce several weak-to-significant tornadoes, along with severe hail.
This type is found most often in a variety of locations east of the Mississippi River, particularly from the corn belt into the Ohio River Valley, especially from July-August, and is characterized by weak-to-moderate, purely streamwise low-level shear, and weak, streamwise mid-level shear. These “supershowers” may be very small, and carry the potential to produce several weak-to-significant tornadoes, but are usually otherwise non-severe (even failing to produce lightning).
This type is found in a variety of locations, especially around the south/central US from C OK/KS into the northern Ohio River Valley, especially bookending peak severe weather season from March-April and from October-December, and is characterized by strong, mostly streamwise low-level shear, and strong, crosswise mid-level shear. These supercells carry the potential to produce very long-lived, violent tornadoes, and severe hail.
This type is found most often in the Southeast U.S., especially from MS into GA and occasionally up to TN, especially from November-April, and is characterized by strong low-level shear and strongly veering upper mid-level shear. These supercells may possess large precipitation shields and produce copious amounts of rain, and carry the potential to produce long-lived, significant-to-violent tornadoes.
This type is most often found from the Southeast U.S. up to the Ohio River Valley, as well as occasionally into the Mid-Atlantic states, especially from March-April (though as early as December), and is characterized by very strong low-level shear, and weak mid-level shear. These supercells may be very compact and consist only of a large tornado cyclone, and carry the potential to produce violent tornadoes that are extremely long-lived, perhaps persisting indefinitely until the supercell runs into unfavorable thermodynamics or other cells. These supercells may struggle to remain organized and even dissipate when not producing a tornado. This hodograph is also frequently associated with Southeast / Mid-Atlantic QLCS tornadoes.
Special thanks to: Matt Wilson (UNL), Alex Schueth (TTU), and Will Wight (DTN)
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