Regional and Mesoscale Meteorology Branch

00:00:00:00 – 00:00:34:01
Unknown
Welcome everybody to today’s visit Satellite Chat. And today we’re very pleased to have Chad Gravel, leading our, chat session. He’s a goes-r satellite liaison affiliated with Sims and is onsite at the AWS Operations Proving Ground. So without further ado, I’ll turn it over to Chad. Okay. Thanks, Dan. So we’re going to try something, a little bit different, from the satellite chat, and, it’ll be about 20 minutes or so, maybe a tiny bit longer.

00:00:34:04 – 00:00:56:18
Unknown
But what I’m going to do is I’m going to jump back and forth between PowerPoint and my ellipse terminal. Just to kind of show the, the functionality of there. Now, the only thing that I’ll say, is that there’s, the quality of the, of the, the ellipse terminal is a little degraded. Not not too bad, but but it’s also degraded.

00:00:56:21 – 00:01:27:03
Unknown
But there’s ways around that. We just couldn’t implement those yet. So basically what I’m going to do today is introduce the convective RGB. The daytime convective RGB will, will end up being in your ellipse terminals. And the full disk probably the first week of May. There’s a clearly, a remapping issue. With your spoon feed on the 0.64.

00:01:27:03 – 00:01:54:14
Unknown
And this, this RGB uses that band. And because of that, it makes it unusable. Unfortunately, on the corners and mesoscale domains. However, we’re working to resolve that and hopefully by, by June, or July at the very latest. You’ll end up getting this convective RGB. So this is obviously just introducing it. And I’ll begin.

00:01:54:17 – 00:02:28:11
Unknown
So the case we’re going to look at is from February. It’s February 28th, 2017. There was a moderate risk, and, parts of Missouri, Illinois, Indiana. And, we’re going to look at two areas of convection. So we’re going to look at one area over, northern Illinois and in far eastern Iowa. And then we’re going to also look at another, supercell basically south of Saint Louis that was heading into the moderate risk, area.

00:02:28:14 – 00:03:05:18
Unknown
Okay. So what I will do, To set the stage is let’s take a look at, at the, at this case. Basically from Iowa and and Illinois. What I’ll end up doing is I’ll loop test. Okay. Well, that we’ll let all the imagery render there. And what you can see, and there was, convection developing through, basically an extensive area of stratus and mid-level, upper level cirrus, potentially.

00:03:05:21 – 00:03:35:08
Unknown
You can see storms developing first in Iowa and then some stronger production developing, over Illinois as well. So if I add on the, the rap surface dew points, you can see that, this convection basically fires initially in Iowa over, basically a warm front that extended from basically, Oklahoma, Kansas, through northwestern Missouri.

00:03:35:08 – 00:04:07:04
Unknown
And then up into, Iowa and then southern Wisconsin. But you could see the initial storms, were where were firing basically in Iowa. Okay. And if I, if I let this go, one thing that you’ll end up noticing in this imagery, by 22, the, or so you can see that stronger convection ended up forming, in, in in Illinois, northern Illinois.

00:04:07:11 – 00:04:28:02
Unknown
And you can see that, that there’s, there’s much, colder cloud tops associated with that. But that’s one thing, you know, to keep in mind as we move forward. Now, the next, the only other thing I’ll say is both of these areas of convection. So we have the or, lowest tilt of, reflectivity on the bottom, right.

00:04:28:05 – 00:04:48:18
Unknown
And if you all both of these areas of code, actually, even though I don’t have warnings displayed right now, I don’t think they’re on here now. They were always warned. So most of these had severe thunderstorm warnings out. Basically, shortly after, that convection formed. But if we go to the very last frame here.

00:04:48:20 – 00:05:13:22
Unknown
All of these storms were basically warmed in, in one shape or another. Okay. So that basically sets the scene. So we have 0.64 visible on the top left on the top right we have clean air. And then on the bottom bottom left we have low level water vapor. Okay. So let’s let’s take a look at this convective RGV.

00:05:13:23 – 00:05:41:15
Unknown
So I kind of I set the stage of that. But let’s take a look at that in a little more detail. So the state convective RGV was developed by the Europeans. And it was designed for the identification of convection with basically pretty strong updrafts. And those are associated at times with small ice crystals. So it’s really clear and, that this is a pretty complex RGV.

00:05:41:18 – 00:06:08:24
Unknown
I’ll show you the recipe in a couple of minutes. But, if you take a look at the interpretation guide, you know, there’s eight things that you can identify from this RGV. So it’s pretty complex. We’re only going to be focusing on the strong convection aspect of this. RGV so where our yellow pixels or yellow cores. Which are, you know, co-located with the updraft of convection usually.

00:06:08:26 – 00:06:35:22
Unknown
Where are they located? So here’s the recipe. You can see that, there’s some structural differences in each component. So the red component is a difference between the upper level and low level water vapor. And it’s a proxy for cloud height. The green component is the difference between the three nine and the clean air. The 10.4 band, which is a proxy for particle size.

00:06:35:24 – 00:07:00:10
Unknown
And then lastly, the blue channel is a difference between the 1.6 and 2.64. And that is that physically relates to cloud phase. We’re only going to be focused on, the red and green component. And the reason why is because that’s how you get a yellow pixel. So if you look at our color wheel over here, large component of red, large component of green ends up making a yellow pixel.

00:07:00:11 – 00:07:29:15
Unknown
So for the, you know, for the sake of time, that’s what we’re going to focus on for this RGB composite impact on for operations. The primary application application is convective and severe weather and identifies intense updrafts that indicate strong convection, strong convection. And as I said, ends up being bright yellow. And the reason why that occurs is we’re really picking one of the strengths of the three nine.

00:07:29:18 – 00:07:54:25
Unknown
So smaller ice particles that sometimes are associated with very strong convection at the top of the updraft are more reflective. So what ends up happening is, during the daytime there’s more reflected solar getting back to the satellite. And actually the satellite ended up thinking that that area of smaller ice crystals is actually much warmer than it really is.

00:07:54:27 – 00:08:22:05
Unknown
The clean air doesn’t suffer from reflected solar. So you can actually play the two off of each other. To really bring out that signal from very small ice ice crystals. So that’s basically what we’re doing. What we’re doing here, there’s some limitations. You know, it’s daytime only. Low sun angle may influence the character of the RGV.

00:08:22:07 – 00:08:47:23
Unknown
These are all things that, you know, we’ll have to get used to over the, you know, the next months and probably the next year or so as we start using this in operations potentially. So here’s a conceptual model of that three nine that small ice crystals. So if you imagine similar sized ice crystals at the bottom of an updraft, and a weak updraft are going to have more resonance time.

00:08:47:29 – 00:09:06:13
Unknown
So they’re going to be end up growing to be larger ice crystals. And then the strong updraft on the left, small scale ice crystals at the beginning, a strong updraft, you’re just going to get them to the top of the updraft much faster. And we’re not talking, it’s analogous to hail size, but we’re not talking large ice crystals here.

00:09:06:13 – 00:09:32:06
Unknown
We’re talking micro meter. So, it’s important to realize that. But this is basically, the conceptual model. So, now we’re going to basically break it down. Just to kind of like give a better understanding. So what we have here is a .64 visible on the left. On the right we have the daytime convective newbie. And I’m sampling not at the convective core because you can see where that is in yellow.

00:09:32:08 – 00:09:58:23
Unknown
But just to the basically up, downwind of that convective core. So we’re still at the top of the thunderstorm, but just maybe not with the updraft. Okay. So here’s the red component. And remember when I said the red component physically relates to cloud height. So at the top of a thunderstorm the point six or excuse me, the six two in the seven three the upper level and the low level.

00:09:58:23 – 00:10:23:00
Unknown
One two they are going to sample very similar values. And you can see that here. You know, the values only differ by basically a degree and a half of Celsius. So a small difference in the red component ends up being a large contribution. And you can see we’re at 91% 100% meaning you know, that component is completely saturated by that color.

00:10:23:03 – 00:10:41:19
Unknown
So we have a large component of red. Okay. If we take a look at the green component. So the three nine on the left and on the right, the two three, again, we’re not at the updraft, but we’re still at the top of the, of the storm. And you can see that what I have here is a small difference.

00:10:41:19 – 00:11:03:18
Unknown
Meaning the small contribution. Okay. Well, differences in these RGV are relative and it depends on that and the range of what you end up putting into the recipe. So here’s there’s a larger range. So even though it looks like a large difference of like oh I don’t know, 40 Celsius or so, that’s actually a small difference. And you’ll see why in a second.

00:11:03:20 – 00:11:24:21
Unknown
So if I move to the next slide now I’m going to be, sampling right on top of that updraft. So basically right on the yellow core. And you can see in the middle the red component is still very close or within a degree or two of Celsius. And the contribution of the red is 93%. So it’s pretty high.

00:11:24:23 – 00:11:50:07
Unknown
Now what you’ll end up seeing is because we’re at the top of that updraft where you have small ice crystals. The temperature increased quite a bit, almost by 30 Celsius. So now we have a much larger difference here between the three nine and the clean air, and that being a large contribution. And you can see that we went from basically 41% to 84%.

00:11:50:10 – 00:12:13:11
Unknown
And this is how we get those yellow pixels. So just you know for the cells that are out there breaking down, these are complex. Our GBS is very, very important to physically understand what’s going on. Okay. So let’s go back to let’s go back to our aqueous terminal now. Okay. I’m going to jump over to my next tab.

00:12:13:14 – 00:12:38:16
Unknown
And I want I want to zoom in basically on, one of these convective storms. Okay. So what you’ll end up noticing here is that, the top of this updraft, you know, we’re, the top left. We’re looking at, you know, 500 meter resolution imagery. So the top of this updraft, you can see it doesn’t look very crisp, does it?

00:12:38:19 – 00:13:00:01
Unknown
And if you ask forecasters and I’ve done this, what the top of an updraft or an overshooting top should look like. Most of us say it’s really crisp and clean, right? But that’s not always the case. And in fact, if you take a look at this updraft, you can see that, it’s kind of diffuse, right?

00:13:00:03 – 00:13:20:25
Unknown
So you can see downwind, there’s quite a bit of good texture associated, associated with the top of the storm, but right where that updraft is, you know, it’s kind of diffuse. And we’ll, we’ll take a look at why that occurs in a second. One of the things I wanted to point out, though quickly, is the parallax issue.

00:13:20:28 – 00:13:45:20
Unknown
Over the last 2 to 3 weeks, I’ve gotten numerous inquiries, from Susan, forecasters, about the parallax issue. Some forecasters think that the data is bad. It’s in the wrong spot. But there’s when you’re using this imagery, the satellite imagery for basically to monitor convection. You know, we’ve never been able to do that before because the satellite imagery hasn’t been timely or, you know, there’s not enough images.

00:13:45:20 – 00:14:06:11
Unknown
So we get an image every 15 minutes, but most of it has to do with latency. Now with basically one minute of latency, you can use the satellite imagery in real time. And what you end up seeing is, you know, hovering basically over the updraft on radar. We’ll just assume that it’s in this general area, but look at how far poleward the displacement is.

00:14:06:13 – 00:14:28:25
Unknown
So that displacement is caused by two things. Most likely, one being the parallax. So taller thunderstorms have more of a parallax, issue than and smaller than, lower in the atmosphere. Phenomena like fog and fire and things like that. And the other thing, the updrafts are tilted here. We know this is severe convection. The updraft is likely tilted downwind.

00:14:29:03 – 00:14:55:17
Unknown
So there’s a little bit of both going on. But, you know, and this is an isolated storm. So it’s easy to kind of see that this updraft is associated with this storm on radar. But I’m just going to throw it out there. That that is not always the case. There’s complex situations where it’s not as easy, and there’s going to be probably a little bit of comfort that is going to be needed to adjust for this parallax, because we’ve never used a symmetry in the same way.

00:14:55:19 – 00:15:22:07
Unknown
So but going back to my earlier, thing about the top of the updraft and the overshooting top, being diffuse looks, let’s potentially take a look. Why? So I’m going to go back to, our PowerPoint here. And, and the next slide, what is really going on, at least what the Europeans think. And, you know, it’s it’s hard to argue with them based on everything we’ve seen.

00:15:22:09 – 00:15:47:01
Unknown
And that, that one example I just showed an ellipse, is that they’re probably purely as clouds. So they form when a strong updraft locally lifts the moist layer above the overshooting top. And it doesn’t need to be really does like if you take a look at this high resolution, image I have in the background, you can see that the pillar of cloud just covers the dome with the overshooting top.

00:15:47:03 – 00:16:08:05
Unknown
And it puts like a very thin blanket on it. But this the satellite imagery is so sensitive that they can really pick up on these things. And the Europeans have done some, have written a couple of short papers and you can see the convective argb here is here with the yellow core. And they have, high resolution photography at that storm.

00:16:08:05 – 00:16:31:16
Unknown
And you can see that there’s a really is cloud above, that overshooting top. So I wanted to kind of explain physically, you know, what was going on. There. Okay. So let’s take a look, back at the Webb’s terminal, and I’m going to back out a tiny bit, and I’m going to loop this imagery for you.

00:16:31:18 – 00:16:35:15
Unknown
Okay.

00:16:35:18 – 00:17:01:15
Unknown
So here’s the imagery, basically looping and what you’ll end up seeing. As I said, there’s two areas of convection here okay. And now I have the warnings on. So there’s two areas. There’s one to the northwest and one in the southeast. And if you take a look at the convective RGV on the bottom left, you’ll notice that most of the signal of the yellow core convective course is to the south eastern, convection.

00:17:01:17 – 00:17:32:21
Unknown
Even though they’re all warned. You can see that the most in in the clean air in the top right. You can see that signal as well. You have colder cloud tops, associated with that convection. Even some really, really pretty strong, overshooting tops as well. So is there something going on there? So if we take a look at the, at the storm reports from those two areas of convection, you’ll kind of get the idea of what’s going on.

00:17:32:21 – 00:17:54:26
Unknown
So the Iowa storms, as I call them, to the northwest over that time period, there were 23 hail reports, 15 were some severe, eight had severe hail, but only one had pretty large hail. So 1.5in or greater. If you compare that to the Illinois storms to the southeast, there were only 16 hail reports, the same amount of severe.

00:17:55:01 – 00:18:23:10
Unknown
But what you end up noticing is that there was many, many more severe or strong or larger hail reports. So five, 1.2 or 1.5 inches or greater. And then there were three, that were two inches or greater hail reports. So the convective ought to be there at least with this one case is showing some promise distinguishing between very large hail and not so large hail.

00:18:23:10 – 00:18:50:29
Unknown
And remember, we’re kind of, you know, we’re, we’re taking a large scale look at this, but so some applied research really needed to be done and really taking a look at the store, individual storms. Okay. So let’s do that. Let’s take a look at an individual storm. We’re gonna jump back to, you know, my inbox terminal now, and we’re going to move to the south of Saint Louis.

00:18:51:01 – 00:19:10:22
Unknown
I’m going to loop the imagery just to kind of get everything rendered. Now we’re looking at one minute imagery. Before we were looking at five minute resolution imagery. And what you’ll notice is we have we’re going to focus on this one storm here from, south of Saint Louis. And that ends up going into, southwestern Illinois here.

00:19:10:24 – 00:19:42:03
Unknown
And what you want, I’m noticing, is that there’s a persistent overshooting top associated with the storm. Okay. A yellow core that pulses, almost feels like it tumbles, but but take a look at what happens there. So it’s very persistent. You know, we’re going forward here. It pulses every about 12 minutes or so. And then watch what happens as it hits the, the Missouri Illinois border and basically goes away.

00:19:42:08 – 00:20:13:17
Unknown
Okay. There’s really not a very strong single signal left. To, you know, to that thunderstorm. And what ends up happening is there’s no more hail reports associated with that storm. And, you know, it just basically, basically ends up dying. And if I go to the very last frame, this warning, basically is canceled.

00:20:13:19 – 00:20:43:11
Unknown
So the one thing I want to show you pretty quickly is and I’m going to basically really increase my sampling here, or my, you know, about the text size is this storm was was moving into an environment, that wasn’t as, supportive of, of large hail. So here it is. Here’s the environment basically. So my for example, my 50 degrees hail height, was about 25,000ft.

00:20:43:14 – 00:21:22:08
Unknown
But if I kind of, if I sample over in Illinois where that storm actually died, you should you can see that there’s a 50 deposit hail. Hell, high increase quite a bit. Other things change as well. So the held growth cape, for example, decreased, by about 200, joules per kilogram or so. So by using this near storm environment, basically, bundle that I have here, and I know that’s not, in a web yet, but the operational proving ground is going to evaluate that over the next couple of months.

00:21:22:08 – 00:21:44:05
Unknown
Spring forecasters. And you can see that it was moving into an environment potentially. So it just, you know, didn’t support large hail. And what ended up happening is as they move through this again, is that, they, you know, that storm basically ended up dying, but it was very persistent for a long period of time.

00:21:44:07 – 00:22:13:10
Unknown
And you can see the convective RGV did a great job at showing that signal. And really probably ended up giving some lead time here, of that storm potentially dying. So if I, you know, just to kind of summarize everything, let me go back to my, my, my PowerPoint screen. I showed this to to the to both our prep course is basically in the sixth and seventh class.

00:22:13:10 – 00:22:35:02
Unknown
And once we had goes 16 imagery, you know, and one of the things that I kept hearing was, how can we bottle up this experience, so that we can share it with forecasters at our local office like these? They appreciated everything that we ended up showing, in the hands on activity. But it was, you know, it was for one person and they wanted to know how we could do that.

00:22:35:02 – 00:23:06:21
Unknown
So myself, Kim, Matt Foster and Greg Mann, the two at Detroit basically had a brainstorming session and how we could accomplish this. It’s all a matter of the following. Forecasters at their local offices basically point to their point. They’re a web three client laptop to the OPG index server, where data for a case is stored. Now, we’ve had a request for change at the OPG, where we can actually open our index server to forecast officers out in the field.

00:23:06:23 – 00:23:38:00
Unknown
The subject matter expert runs an interactive remote session, basically just like I did here. And that display is transmitted via Google Hangout. Google hangout actually has better quality video. But one of the disadvantages is you can only have about 10 or 15, people logging into that Google Hangout at the same time. And then, the subject matter expert say it myself at the up at the Operations Proving Ground teaches the concept like I just did direct The forecaster.

00:23:38:01 – 00:24:17:25
Unknown
So to interrogate the same data. So imagine this. So I teach the concept of the, of the convective argb. And then I have them, the forecasters at their local office use a web thin client to interrogate the same data and think about why I’m getting a signal there. Right. A yellow convective core. And they have them interrogate the data and trying to figure it out, and then we’d all reconvene in 5 or 10 minutes, and we’d kind of brainstorm instead of me telling them the answer about the previous cloud, the group of us together in an interactive session, configure these concepts out, and, you know, you kind of can rinse and repeat with that

00:24:17:25 – 00:24:44:22
Unknown
type of thing. And the reason why this approach is just so powerful is that it provides the opportunity to actively explore the data at each office and make unique observations or discoveries with that subject matter. Expert and research indicates that adult professionals learn best with this approach when they are actively engaged in expanding the effort to solve job relevant problems under our system.

00:24:44:24 – 00:25:09:09
Unknown
And the last thing I’ll share is that the OPG will prototype this concept over the next month. I can tell you that we’ve tested all the components of it, but just like I’ve done here, you know, but we haven’t put everything together and we’re going to try to do that sometime in May. Just we can do it sooner, but my schedule just doesn’t, you know, is into cooperating with that, unfortunately until May.

00:25:09:17 – 00:25:27:01
Unknown
So, you know, with that, I’ll, you know, I’ll take any question we have, like, we used about 25 minutes and I want to keep this short and sweet, but I’d love to, answer any questions you guys have out in the field.

00:25:27:03 – 00:25:48:21
Unknown
Hey, Chad, the spokesman for the AG headquarters. Hey, Paul, did you, did you talk about the code for the smoothing? Overshooting tops? The beginning. Did you get you did you cover that again? I might have missed the explanation. Sure. Let me go back a few slides. I guess my first thought that was. Perhaps I’ll getting smoothed by the, you know, the synoptic scale winds at that level, just.

00:25:48:23 – 00:26:11:27
Unknown
Yeah, I think you’re right. There’s there’s there’s probably a few things going on. Right. You know, and I’m not sure they are, which we don’t know for sure if that’s Akhilleus code because they don’t have, you know, I don’t have high resolution photography of that storm. However, the Europeans suggest that this is probably happening more than we realize.

00:26:12:00 – 00:26:45:27
Unknown
You know, if I, if I go back to my ellipse term and on, I’m on that storm, you know, and we’re real, man. You know, you can you can see that, but that overshooting top is diffuse, right? And it kind of comes and goes. So here it’s a little more crisp. And, you know, at times the evolution of that overshooting top, ends up being, ends up devolving, into character changes.

00:26:45:27 – 00:27:08:19
Unknown
So, yeah, I think it’s probably cheating. And on, certain aspects, I don’t know if, you know, there’s a lot of work by Chris bad car about overshooting tops and one minute imagery and how they relate to severe production. Chris will probably end up looking at this, this RGB in time. But yeah, I’m sure that there’s upper level winds kind of bringing that downstream.

00:27:08:19 – 00:27:34:10
Unknown
And if I back out, you can see that there’s a yellow component here that’s kind of being thrown downstream. Stream. Those are above and below cirrus plumes that you can see there. And they have small ice crystals too. So yeah, I think there’s a lot going on. But it kind of it’s pretty interesting that you can kind of get the sensitivity of these bands this way.

00:27:34:13 – 00:27:56:08
Unknown
Yeah. Thanks. Appreciate that as good stuff. Yeah. This is Paul Phoenix. Hey, Paul, question for the regarding how it will get distributed, I guess. Will that be computed and then sent to us from a bigger computer than what I have here? Or when I load it up, will it have to load the six channels and then calculate it on the fly.

00:27:56:11 – 00:28:35:12
Unknown
Yeah. So basically everything that you saw me do in a web form is on the fly. And that’s how it will be on your system as well. So, you know, and you can see I’m on, a smaller domain if I back here, let me switch screens again. If I, if I back way out, you can see I’m on one of those DSS domains, you know, one of the recommended practices with this imagery, regardless if it’s hard to be or not, is to, you know, you don’t need the complex domain at times to load on the, the state scale.

00:28:35:12 – 00:29:00:22
Unknown
And that will minimize the amount of memory needed, to load these RG bs. But yeah, I mean, they will all be they will all be computed on the fly. As I said earlier, this RGB will be available first on the on the full disk domain only. And that’s due to a 0.64 projection issue with your data or remapping issue.

00:29:00:25 – 00:29:24:12
Unknown
So you don’t notice this right now. When you load 2.64. But if you do a difference between the .64 and the other band, what you’ll end up seeing is this checkerboard. Darren. And Salt Lake City, you know, saw this and, and was something else he was looking at, and he sent it to me and I explained that that was a remapping issue.

00:29:24:15 – 00:29:53:03
Unknown
That’s supposed to be resolved. One of the idea that you don’t need to have this data remapped anymore for a website way, way back there was, basically a requirement to remap it because a website couldn’t handle at the native resolution. However, my data I’m showing you right now is after native resolution, because in our building we have two feeds coming in, and I use that basically the Goes-r rebroadcast feed that he pulls.

00:29:53:03 – 00:30:19:28
Unknown
And so I, you know, proven that you don’t need to remap this, this imagery for Awacs reporting on the S-band. It adds up to one there’s latency associated with that. You’ll end up getting the imagery in five 10s quicker potentially if it’s not remapped. One more thing, is that, the file sizes are smaller, so it’ll save actually S-band bandwidth if you don’t remap it.

00:30:20:03 – 00:30:35:28
Unknown
So that’s the idea. It’s just not implemented yet. And, you know, you know, people at NWS headquarters and knows this will have to figure out, you know, what’s the best path. But that’s the idea right now. But going back to your original question, yes, everything will be done at the ellipse terminal. And that’s how it is for all.

00:30:35:28 – 00:31:01:28
Unknown
RGB is right now. And you’ll end up being you’ll end up getting a whole slew of additional RGB, in early May, for the field. And that’s something. Hey, Chad, this is Dan Lindsey. Very nice presentation. Just a quick comment on the interpretation of the small ice crystals. We did a study about 8 or 10 years ago where we looked at a climatology of the particle size.

00:31:01:28 – 00:31:25:03
Unknown
I don’t know if you looked at it, I. Yeah, I’ve read it. Yeah, yeah. So this is just a general warning is you will often get small crystals in the high plains, in the mountains that are not necessarily associated with stronger updrafts, simply due to high cloud bases or really cold cloud bases and dry environments. Yeah. I’m trying to find here’s an link sort of an example, right.

00:31:25:06 – 00:31:52:25
Unknown
If you look at my screen, see how there’s a lot of yellow in the RGB. And sometimes it’s way worse than that. Right. Like the red in the in the green components are completely saturated with like really high small ice crystals. Cloud. Yeah. So the climatology shows that it the smallest crystals occur really in like May, June, July places like eastern New Mexico, eastern Colorado, eastern Wyoming, sometimes western South Dakota.

00:31:52:27 – 00:32:13:06
Unknown
So I think that the best way to, to, I guess, teach this or whatever, it’s the relative particle size of two storms that are in relatively close proximity in the same near storm environment. And in that case, you can infer that one of them probably does have stronger address than the other. It’s not really the absolute particle size that’s the most important.

00:32:13:08 – 00:32:22:25
Unknown
Okay.

00:32:22:27 – 00:32:31:04
Unknown
Okay. Any more questions for Chad?

00:32:31:06 – 00:32:44:29
Unknown
Okay. Well, thanks very much, Chad. That was, a great presentation. And, you can find the recorded version of this on the visit web pages. By this afternoon. Thanks, everybody, and have a great day. Thanks, everyone.