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Deciphering Storm Interactions with Cameron Nixon

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[00:00:47] Howdy folks, and welcome back to another episode of the Chaser Chat Podcast. I am Gabriel Harber, and as you probably have already discerned from the title, today is going to be an absolutely fantastic episode. About a month or so ago, Cameron nudged me with a text message to ask me about recording again soon, and we decided to merge our schedules together and find an appropriate date, which then led to this year’s collision on the podcast.

[00:01:19] I had to go with that, man. I was planning that out for a long time.

[00:01:23] So Cameron, how are you doing, man? (Cameron) I am good. I’m really glad that we have this, this merging of the minds happening right now. I appreciate that, but I don’t know that people are particularly interested in hearing what my mind has to say. So you flatter me. (Gabriel) Now you and I spoke last year and during our last conversation, you illuminated all of the listeners as to the things that we had been missing when it comes to forecasting severe hail.

[00:01:52] Just wanted to see, follow up. How’s that research been going? Has it been playing out now that you have a couple of chase seasons in the books to actually see how the things you’ve studied and researched and put out there for people, how they’ve performed. (Cameron) Yeah, definitely. So that’s actually a really good question because what so the, the, this whole cell mergers thing, this is a little bit kind of outside what I’m doing right now at my, my new job at the SPC.

[00:02:17] And what I, what I am doing right now is a continuation of that kind of parameter based research. Both for hail and, you know, I, I try my darndest to get into tornadoes as much as I can. So that’ll be included in there too. And I, I think one of I’m actually working from this guy from Poland too. He’s researching at the NWC this year, and we’re basically trying to perform in what one of the most robust parameter based studies that we, we can with the data that we have we have data from the US we have data from Canada. We have data from Europe and Australia. And I think we’re adding South Africa in there too, that there’s a lot of data.

[00:03:01] And we’re basically trying to find like. You know, not just in the US and our very specific regimes, but what parameters are correlated with tornado and hail potential around the world. And we’re finding some interesting things, really nothing new on the hail front. Honestly, maybe a little bit new on the tornado front.

[00:03:22] A lot of the parameters that we use to distinguish between, say, weak and significant tornadoes. They might have actually varying skills. Maybe some parameters work better distinguishing between TOR and non TOR. And then other parameters work better at distinguishing between SIGTOR and violent TOR.

[00:03:41] So I think that’s kind of where we’re, we’re going with this. (Gabriel) That’s really interesting, particularly because one of the things that has really stood out to me over the years in chatting with you is how the parameters that we use, it’s, it’s sort of like that phrase, the map isn’t the territory. And how a lot of times we can get stuck on these conceptual parameters that maybe don’t tell the whole story when you’re actually looking at how things are lined up.

[00:04:11] I think one of the ones that sticks out in my mind right now is from your research about significant hail and how it’s not particularly how much CAPE there is. It’s where that CAPE is located and what its relation is to things like the freezing level and the LFC. (Cameron) Exactly. And so one of the biggest things that my, my buddy from Poland is most excited about in this study is the whole lapse rate problem in hail.

[00:04:34] Because in the US we love our lapse rates or whatever, 700 to 500 millibar lapse rates. If it’s steep or if it’s, it’s above like eight, then it’s a hail sounding. But interestingly, if you look at hail soundings across the world, the US Great Plains are the only location that actually gets these steep lapse rate hail soundings.

[00:04:56] So it’s very evidently not necessary for hail. But like you said, it’s just the distribution of CAPE. But we’re sitting here in the US. and the majority of our hail falls in the Great Plains. So all we have in our statistics is these lapse rates and that’s really evident. We’re kind of blinded to the fact that there is more.

[00:05:18] So it seems almost like a pretty cool example of correlation, not equaling causation. (Cameron) Bingo. Yeah. (Gabriel) Interesting stuff. So do you have any plans for publishing any more research with that in the near future? Or are you still in the phase where you’re getting all the ducks in a row? Yeah, so my buddy’s name is and he’s the Polish guy. And this study He’s just about to submit it. So it’ll probably be, you know, a few months to half a year or so before it gets out. I just played a very small part in this. But this this project as a whole is kind of inspiring me to like do similar research here at the SPC because we sorely need it.

[00:05:59] So that’s, that’s kind of where we’re going with this. So maybe I’ll publish some kind of like small spinoff paper, but otherwise I’m just kind of considering this a teamwork effort with him. (Gabriel) So if you had to summarize then what you think the major problems still are when it comes to severe hail forecasting because, you know, you just said that you would really like to translate some of that research that you’re doing from a global perspective into a more US-centric perspective. What would you, what would you say those big challenges are that still exist? (Cameron) Well, the thing is I, I think this whole study on storm interactions puts the biggest fork in environmental analysis of severe storms. And the, the reason why I went into this whole storm interactions thing is because I saw how, how little my returns were by looking at the environmental parameter space alone in the prediction of hail.

[00:07:03] And like, of course, like there’s some, there’s some correlations, there’s some, you know, like CAPE distribution, storm depth, whatever. They’re definitely there, but they’re just not super robust. Particularly as compared to tornadoes. So, that’s kind of what inspired me to go, Okay, well, we know that the same Great Plains environment occurs, you know, X amount of days a year, and only a couple of them get massive hail.

[00:07:30] So, what’s so special about these cases that we actually do realize this environment in this way? So that’s kind of where this whole cell mergers thing starts, and I think the biggest challenge is that Regardless of the environment, these storms on a 15 minute, you know, time window or, or microscopic mesoscale are experiencing a completely different environment than the skew-t and hodograph would suggest.

[00:08:01] So that’s the problem. (Gabriel) You know, what it reminds me of is this really cool. presentation I heard about tarot cards and stay with me for a second because I promise I’m going to bring this all I’m going to bring this full circle. So a lot of people have an idea that tarot cards are this super mystical thing that they’re like reading the future and they have some sort of supernatural power.

[00:08:25] But one of the arguments that I’ve heard made is that it’s not the cards themselves. It’s the actual method of utilizing them that causes creative thinking that you wouldn’t have actually utilized otherwise. And you get so often stuck into a box. Yeah, I’ve experienced this. And so, yeah, what, what you just described makes perfect sense to me in that context, because if you’re sort of stuck just in the old ways or the conventional ways of thinking about something like what causes significant hail, like you just mentioned earlier, we love our lapse rates.

[00:09:00] It has to be lapse rates, right? Or at least that has to be a significant part of the equation, but by kind of broadening your scope and looking at things that don’t even necessarily include significant hail as something you would think being part of the equation, it kind of gives you those ideas. Like gets you out of it, thinking outside the box, thinking creatively in a way you wouldn’t have otherwise.

[00:09:18] And then all of a sudden you have that Eureka moment where you’re like, Hey, wait a second. And then it connects back everything. Especially in dynamic fields like meteorology where everything is constantly in flux, it just seems like it’s all more connected than a lot of people have realized. (Cameron) Yeah. And to sum up this entire storm interactions thing, because I know this is where we’re going in this talk, but basically regardless of the environment, right?

[00:09:43] The environment can be anything it wants to be. Regardless of the environment, we, we seem to have these, these very repeated patterns in storm morphology that precede tornadoes and big hail. So how important actually is the environment? I think some parts may be more important than others, but it seems like this, the storm scale condition may or may not even be more important than the environment itself in some cases.

[00:10:16] That makes perfect sense too, because how often do we see an event underperform and everybody’s left scratching their heads? Well, this looked exactly like this other day that did this massive crazy thing. And today didn’t do anything right? We, we got a couple of, you know, crapvection supercells that went up and super quickly formed into a giant MCS and, and that was it, everything was done for.

[00:10:39] And people are kind of left wondering. And I actually think that sort of day is exciting. And I know that might seem counterintuitive because people are out there chasing and maybe the forecasters feel a little down on themselves because the forecasters feel down on themselves. Cause like, man, I definitely, it seems like I might’ve missed on that forecast, but I think it’s super exciting because it tells us like, hey, there’s so much left to be solved in this field that we, we can’t account for yet.

[00:11:04] It’s just like, it’s rife with possibilities. (Cameron) I agree. Yeah. That, that you’ve just described. You know, three quarters of my chase days this year. I think living in Oklahoma gives you like an even better, like appreciation for failure modes because we can do it so spectacularly. (Gabriel) Failing spectacularly. I like that.

[00:11:27] So as we get into this portion of the discussion of talking about storm interactions, I just want to share with you and the listeners, the thing that has stuck out to me the most, it’s, it’s like the Matrix in a certain sense, because once you see it, you can’t unsee it. I had never thought about storm interactions before, other than like, Oh, you know, it looks like the inflow might be getting cut off from this storm.

[00:11:49] So maybe we go to a different storm, but now after I’ve seen you and many other people who have picked up that sort of research and started integrating it into their forecasting, into their storm chasing themselves, I can’t unsee it. I look at a radar now, I look at satellite imagery now, and it’s like, I’m trying to connect the dots almost as second nature, whereas it wasn’t even something I thought of previously.

[00:12:11] And I think that to me has been the biggest thing is like, it’s causing me to reconceptualize how I view storms when they’re occurring. (Cameron) It’s exactly one of the most common I guess, comments I’ve gotten from my presentation, like in the NWS because those people are literally looking at radar as, as much as your average high school and high schooler is, if not more.

[00:12:34] But they’ve seen it all. They’ve, they’ve seen all the storm morphologies preceding tornadoes, and they’re like, you know what, Cameron, you didn’t tell me anything new. And I’m like, yep, that’s the, that was the goal. Like I’m basically just, just showing them that this pattern exists, validating what they have been seeing and they feel good about that and now they have potentially a rhyme or a reason behind what they see so that now they can actually train their brain to like, you know, when is this pattern going to happen? What, what can it do? Whatever. (Gabriel) So looking at your research, I’ve noticed that, and I’m sure there’s like a lot of bleed over so that like nudgers can be like semi-colliders and all this other stuff, but I see like three like subclassifications when it comes to storm interactions.

[00:13:23] So I actually want to start with mergers. Just because that is the thing that we are most used to. And that is the blob merges into blob and they become one larger blob.

[00:13:37] Very articulate, by the way, you’re going to put that in your research paper, right? (Cameron) Yes, it’s something similar in there. But no, like that is what we have been used to training our brains to think about that. If we have a storm and another storm physically merges into that storm. Then, you know, we, we have, we have problems or we have, you know, fun stuff.

[00:13:57] So nudgers now are, and this, we, we went through several names for these trial and error, like I, being a member of the chaser community, like I did want to make something that was, you know, some kind of new and definitive term that like people wouldn’t know what, what it is when they heard it kind of thing.

[00:14:19] Yeah. And like, unfortunately, I, you know, I kind of predicted this, but like, it’s been a little bit misused and abused . Not every storm is a nudger. Yeah. But, and, and like you said that there’s such a, a, you know, wide array and, and spectrum of interactions that it’s hard to just put a name on it.

[00:14:38] But basically anything, any storm that was nearby the supercell or any, any little cell or reflectivity blip. That was nearby a supercell, you know, within 10 kilometers or so. I just called that a nudger. It was sitting there near the storm, nudging its near storm environment, so to speak. And the reason why these things, in my opinion, are so important for us to understand and to see is because they are very subtle. And you know, like, because most of us are trained to look at the two blobs coming together, but when it comes to nudgers, most people are just trained on the supercell itself and are completely ignoring anything outside of it and how it could potentially impact it. (Gabriel) An example that sticks out in my mind, and I’m not sure if this is a nudger or not, but it’s when you see a supercell and you have the hook echo and you see like that little blob of convection, like down to the South, maybe even like the Southwest or even due West sometimes.

[00:15:41] And it almost gets like, it’s almost like a vacuum effect where it gets sucked into the RFD and you see that intensification occur. Is that a pretty common instance of a nudger right there? (Cameron) Yeah, so I think you’ve just described basically . If I understand what you’re saying I think what you’re seeing is the nudger actually going full speed ahead into the RFD and accelerating the RFD.

[00:16:09] So in essence, it’s, it’s a chicken and the egg problem, but in this case, the egg comes before the chicken. The, the nudger is basically what ignites the RFD or what, what initiates the RFD And you can see this El Reno is, is the most common example. If you look up a radar loop of that storm your supercell is pretty stationary until this, the series of, of nudging cells behind it forms just rear of the hook echo.

[00:16:40] And that’s when you see your hook echo, just accelerate forward. You get your, you know, 50 mile per hour tornado motion and all that deviance. And that’s ostensibly because of those nudgers.

[00:16:51] () Now in a situation like that, if and obviously hindsight being 2020, so I’m not second guessing anyone’s chasing decisions on a day like El Reno, but now with this knowledge that we have, would you say that if you were in a situation like that, and you were positioned, let’s say, due east of the storm, and you’re thinking to yourself, Hey, I’m okay.

[00:17:09] Cause this thing’s like mostly stationary, maybe moving a little, even to the Southeast or whatever. And then you see some of those cells start to feed in off of the rear of the RFD. You’re like, okay, maybe I need to actually put a little more distance between myself and the storm because we might see some unforeseen acceleration about to occur.

[00:17:26] Yes.

[00:17:26] I tweeted earlier this, this spring, a picture of a this, this two cell configuration, right? With a supercell and like another supercell along its rear flank. And I’m like, I just, I want this image like stapled into people’s minds. Like when you have two storms next to each other, that’s when you have problems.

[00:17:45] And I think that’s what I really wanna focus on for consequent kind of chaser community education, because it’s not just the supercell you’re on, right? It’s the super, it’s the storms around your super cell. And my, like, my rule of thumb in the field is that as soon as you add one more bit of chaos, be it like a whole nother supercell or just like a little, you know, little preset blob in the rear flank, you’re gonna get misbehaving storms.

[00:18:18] If you don’t have these, these nudgers or mergers, that’s when you just have your, your cute little like LP steady state supercells. But as soon as you start feeding it more storms, that’s when the chaos starts happening. And I think like what I feel most passionately about is that when you’re out chasing, you do pay attention to your surroundings or your storm surroundings.

[00:18:44] Yeah. Situational awareness is obviously key. I think Skip Talbot. did a lot to advance that idea with some of his analysis that he’s done with both El Reno and the Lawrence, Kansas tornadoes. And I also think you’re doing a great service to the chaser community for that as well, because I actually can, can point to some examples where last year during chasing season, after you’d put out your deviant tornado motion research, people were talking about how it was actually helping them to avoid getting hit by these tornadoes because they actually would know beforehand what was about to occur.

[00:19:19] And so this, this research on storm interaction strikes me in the same way as like now people in real time are going to be able to actually take evasive measures before it’s too late. (Cameron) That’s exactly the goal.

[00:19:31] Okay. So nudgers, I think we got a pretty solid handle on that. And by the way, I should have mentioned this at the onset, but if people want to learn more about all this stuff, you’ve got, I think you have a blog post on your website, right? And then you’ve also got a video where you talk about some of it on your YouTube channel.

[00:19:47] Yeah, I’m kind of slacking on the blog post. if you search Cameron Nixon storm interactions, there’s a College of DuPage lecture on there that you’ll find (Gabriel) You’ve also done a couple of good tweet threads on it I’m not sure how robust the Twitter search feature is but if you if you play around with that and try some different inputs and put in Cameron’s Twitter handle You’ll probably be able to find some stuff about that as well.

[00:20:09] Yeah Thanks for reminding me though. I need to, I need to update that website. (Gabriel) Okay. So we started off with, with mergers and then we talked about nudgers. There’s another class though, which is collisions. What about those? How, how do those influence people’s chasing actions out in the field? What are they?

[00:20:26] Yeah, those are so I, I reserve collisions for storms that impact the supercell that are not a right moving mesocyclone , basically. Yeah. So things like a left mover that impacts a supercell or like a QLCS that impacts a supercell. Something that, that has a, a very differential motion and kind of smacks it, into oblivion.

[00:20:54] And so like the, the most common example is that you’ll see like supercells that get rammed from behind by like a QLCS. Interestingly, left movers and ostensible left splits were actually quite common in cases of tornadoes that we looked at. So, and I know earlier this year there was a couple days in a row down in Texas where supercells produced tornadoes as soon as these left movers hit them.

[00:21:21] And I, I think the, the collision and the angle of the collision and the speed of the collision there, there’s a lot of randomness there and not every, you know, colliding right and left moving pair are going to produce a tornado, but it’s just something else to keep an eye on. (Gabriel) Yeah, no, and that makes a lot of sense.

[00:21:37] The, you know, the inherent chaos and all of this, but I think the main takeaway still remains right? Which is if you see the storm about to eat something And you know, you should probably take a step back because it’s going to be unpredictable, at least for a certain amount of time. (Cameron) Yeah, exactly. (Gabriel) As far as the left movers ramming into the right movers, is that still like the same idea that it is creating just like a more dynamic wind field in the area of the RFD for a potential mesocyclone to feed on or

[00:22:09] does that have to do with boundaries or how does that work? (Cameron) No, but you, you essentially had it like basically the, the theory that we’re operating under is one that actually a former chase buddy of mine back at Texas Tech when I went to school there he and his professor

[00:22:28] they came out with a simulation study. So they, they simulated these storms and progressively stronger and stronger storm relative inflow. And so I know that’s, that’s kind of been a buzzword lately and there’s, there’s been some misuse and abuse, including by myself. There there’s, there’s still a lot of research that has yet to be done on why storm relative inflow influences supercell behavior.

[00:22:55] But one of the things that this group found was that basically, and man, it’s hard to show this without doing physical demonstrations, but imagine that you have, you know, like a vacuum cleaner and you’re holding it up above your table. And you’re, you’re simultaneously you’re, you’re trying to pick up some, some piece of dust on that table and you’re simultaneously blowing horizontally at 40 miles per hour.

[00:23:19] That vacuum is not going to be able to suck up that dust because that dust is just going to flow across that table. So God, this is an awful. (Gabriel) No, no, this is premiere podcasting right here. (Cameron) I’m trying. But so now let’s say you stop blowing and you know, yeah, that piece of dust under your vacuums is going to go straight up into your vacuum.

[00:23:40] So the, the, the moral of the story is that. If you have excessive horizontal motion underneath your vacuum, it’s going to be pretty hard for that, that updraft to consolidate that vorticity. That’s essentially what we’re talking about. If you have too strong of storm relative inflow, your vorticity kind of just slides right down past your updraft and doesn’t kind of play in it and, and conglomerate and amplify.

[00:24:07] So the reason why these, these nudgers, mergers, flank collisions, anything the reason why these seem to be important is that they decelerate that storm relative inflow. So maybe you have an inflow of 40 knots and they provide an outflow of 40 knots. So that 40 knots and that 40 knots, especially if they’re, they’re directly in opposition, they’ll cancel each other out and then you get convergence underneath that updraft and then you can start the whole process.

[00:24:36] That makes a lot of sense because I, I, I believe it’s your Hail Forecasting 101 video where you go in depth into the delicate balance between horizontal and vertical momentum and how they really need to be in sort of a, a really harmonious balance with one another in order for you to actually get those hail embryos in the hail growth zone for the appropriate amount of time.

[00:24:58] And so just from that research, which by the way, everybody listening, search Hail Forecasting 101 on YouTube. You’ll get Cameron’s video on that, that’s what I’m referring to here, but that makes a lot of sense that even for the tornadic side of things, you would get a more, a better chance at a more prolific tornado if you are getting that perfect balance between the two.

[00:25:17] So now it’s just ingesting a lot more, and I’m guessing a lot of this also leads into John Peters’ research about entrainment cape as well. (Cameron) Yeah, that’s a little bit adjunct, but essentially the storm relative wind part. Yeah. Yeah, very similar. One thing that I learned in this process, and I think that Yannick Fisher actually told me was that, you know, we, we all know that hail is a residence time problem, right?

[00:25:42] Like how long does that hailstone spend within your storm? Tornadoes are also a residence time problem. How long does your vortex underneath your updraft? Because if it only spends a couple minutes. You’re not going to be able to amplify. And you know, like as a chaser, you’ve seen vortices that, you know, start out on the forward flank and kind of just slide past or updraft and occlude and don’t do anything.

[00:26:06] But when you get the right balance between your RFD and your storm relative inflow, that’s when these vortices stop sliding. And that’s when they start kind of sitting there. (Gabriel) Interesting that, okay. You just kind of blew my mind with that, the idea of that vortex residence time. Okay I have to ask. (Cameron) The vacuum cleaner metaphor metaphor didn’t do it.

[00:26:27] You drew me in with that. You look like, yeah, you had my curiosity and then the residence vortex time that got my attention. All right. Well, that sounds like a pretty good place to leave the podcast here. I think everybody has definitely been given a taste of storm interactions and what they’re capable of, what sort of things they need to be looking for.

[00:26:46] And I, again, just encourage everybody to head over to your YouTube channel to check out that information. And then now that you have been put on the spot they’ll be looking for that blog post as well. So I’m sure that’ll come sometime within the next six to 12 months. (Cameron) Yeah. Emphasis on the 12.

[00:27:03] Emphasis on the 12. All right, Cameron, tell them where they can find you on social media. I’m pretty sure everybody listening to this podcast already follows you, but in case you know, the person who lives under a rock and happens to listen to Chaser Chat is listening right now. Where can they find you?

[00:27:17] I’m at CameronJNixon on Twitter. And then I believe I just moved my website to CameronJNixon.com or just just search Cameron Nixon and it’s a WordPress site. You’ll find it. (Gabriel) Sounds good, man. Thanks again for joining me here today. (Cameron) Yeah thank you.