Regional and Mesoscale Meteorology Branch

00:00:00:25 – 00:00:20:07
Speaker 1
Welcome to today’s, the Visit satellite chat, and we have a few highlights to show from our recent blog entries that we’ve been working on. But before we show that, we just want to ask everybody on the line, since the go 16 imagery is new, if there’s any questions or comments or anything interesting you want to share with us.

00:00:20:13 – 00:00:31:10
Speaker 1
Before we, talk about some blog entries we’ve been working on.

00:00:31:13 – 00:00:31:29
Unknown
Then I’ll just.

00:00:31:29 – 00:00:33:15
Speaker 3
Mention a couple of comments.

00:00:33:15 – 00:00:34:15
Speaker 1
Okay. This is.

00:00:34:15 – 00:00:38:26
Speaker 3
Scott. The you may have noticed that the resolution at.

00:00:38:26 – 00:00:40:17
Speaker 4
The Kona scale for the visible.

00:00:40:18 – 00:01:02:24
Speaker 3
Was not full resolution. That has changed, effective yesterday. So you should be seeing better resolution there. And the, issue of the black dots at high reflectivity in the visible imagery, there has been a nastiest meeting on that. So the changes are starting at nastiest. And once those are done there, the change, they’ll have.

00:01:02:24 – 00:01:05:15
Speaker 4
To make a little change in a website too, but that that.

00:01:05:18 – 00:01:11:26
Speaker 3
Difficulty is being worked on too. So that’s mostly a high sun problem. So.

00:01:11:29 – 00:01:16:05
Speaker 1
Okay. Any questions or comments from the field before we begin in.

00:01:16:07 – 00:01:17:00
Speaker 4
The.

00:01:17:03 – 00:01:34:01
Speaker 3
Sea at the end of that? Maybe I’ll just ask, have you anybody. I don’t I’m not sure who all is out there, but have there been any problems with apes, in terms of storing stuff or slowing it down or anything?

00:01:34:03 – 00:01:49:05
Speaker 4
Fell fellow. Any anytime we try to put it in names that are beyond like 240, it definitely starts to slow down the system. And if we try to be more than a couple of, panels or that it sometimes crashes out.

00:01:49:07 – 00:02:01:07
Speaker 3
Okay. That’s that’s good to know. Do you happen to know by any chance, how many, how many hours you’re storing?

00:02:01:09 – 00:02:04:10
Speaker 3
A good day’s worth or.

00:02:04:21 – 00:02:10:09
Speaker 4
I think right now here at NWS Amarillo, we’re still on the four hour, but I’ll get back to you on that after that visit. Yeah.

00:02:10:15 – 00:02:27:04
Speaker 3
Okay. Okay. Yeah, I know that Dave up at the Boulder office was was storing just six hours, but he made it 36 yesterday. I’m not totally sure how that’s going, but I, I think he didn’t think there’d be any problem at that right now. But thanks.

00:02:27:07 – 00:02:31:05
Speaker 1
Okay. Any other questions?

00:02:31:27 – 00:02:34:23
Speaker 4
This is Greg at El Paso. Has been noticing,

00:02:34:25 – 00:02:37:23
Speaker 3
A lot of alerts on our workstations.

00:02:37:23 – 00:02:43:06
Speaker 4
About high memory usage on these satellite images. There seem to be consuming considerable resources, probably with a.

00:02:43:06 – 00:02:43:14
Speaker 3
Large.

00:02:43:14 – 00:02:55:18
Speaker 4
Size. That really is a function of how many loads. So it is kind of placing, a performance issue in it on the, on the workstations itself.

00:02:55:20 – 00:03:03:14
Speaker 3
Okay. So you’re getting the notification, do you actually see any, any kind of slowdown, do you think as well, or.

00:03:03:17 – 00:03:15:28
Speaker 4
I don’t see a real big slowdown, but I don’t know a lot. I haven’t really tried working with radar data. And yeah, ultimately we’ve been relatively quiet here weather wise. Okay. Help us out.

00:03:16:00 – 00:03:19:28
Speaker 3
All right. Thank you.

00:03:20:01 – 00:03:30:24
Speaker 3
I might mention that, you know, a couple of these to Dave and, maybe you guys know data, but. See what he thinks. Thanks.

00:03:30:27 – 00:03:33:11
Speaker 1
Okay. Any other questions or comments?

00:03:33:13 – 00:04:01:05
Speaker 4
Hey, Dan, this is Chad Gravel. I the only other thing that I want, I there’s there’s two suggestions I have for, for those those folks just said those comments. Number one. There’s some things that you really don’t need the Conus view for. So I would recommend, you know, using your, your full regional view that cuts out a tremendous amount of the satellite tiles.

00:04:01:07 – 00:04:24:24
Speaker 4
Only those satellite tiles that are needed will be loaded there. So that’s one suggestion you may want to do. Another thing, is you can, for each cave session, if you have three cave sessions going the video texture cache under preferences should be set at two gigabytes. There’s a you’ve had the hardware refresh. You’re actually waiting.

00:04:24:26 – 00:04:57:15
Speaker 4
You’re letting memory not be utilized. If you use three cave sessions by default it’s set at one, one gigabyte, but you can really bump that up to two as long as you use three caves. I personally only use one cave, but I’m not in operations of mine set at four gigabytes. So, I would that’s another suggestion I would have, but if you use three caves, two gigabytes of video texture cache, and, that can be set with every user, you know, in the, in the preferences in cave.

00:04:57:27 – 00:05:06:21
Speaker 4
So that and then do a regional view and that’ll speed up the processing tremendously.

00:05:06:24 – 00:05:11:01
Speaker 4
Thanks. That’s very helpful.

00:05:11:03 – 00:05:17:18
Speaker 1
Any questions or comments for Chad or anybody?

00:05:17:21 – 00:05:19:25
Speaker 4
I do have this Greg in El Paso do have a question.

00:05:19:26 – 00:05:22:17
Speaker 3
On some of the difference products.

00:05:23:05 – 00:05:27:03
Speaker 4
Aside from the perks being somewhat defaulted and.

00:05:27:12 – 00:05:28:04
Speaker 3
There are some.

00:05:28:06 – 00:05:37:15
Speaker 4
Articles or some interesting info on the usefulness of some of the curves. We’ve a couple of forecasters, you’re curious about, like the moisture, one on the.

00:05:37:15 – 00:05:38:12
Speaker 3
Difference.

00:05:38:14 – 00:05:49:25
Speaker 4
Difference products and what their what they were hoping to target with, I didn’t see any info on that. That’s why I asked.

00:05:49:27 – 00:06:00:03
Speaker 3
So you’re talking about the ten -11 and that, I mean, the the default color curve looks to me just like a, you know, the default grade color curve.

00:06:00:06 – 00:06:00:14
Speaker 1
Yeah.

00:06:00:14 – 00:06:02:00
Speaker 3
And it really cries out to be changed.

00:06:02:00 – 00:06:30:04
Speaker 1
To be something more useful. Yeah. Those don’t do need to be worked on. I know Dan Lindsay here at Sierra is, working on that. And, one of the applications we’re looking at is, for signals of moisture convergence, for convective initiation. There’s a number of other uses, but, yeah, the default color table is not good where we’re looking into, better, much better color pairs for that.

00:06:30:07 – 00:06:35:06
Speaker 4
Okay. Thanks.

00:06:35:08 – 00:06:41:19
Speaker 1
Okay. Any other questions?

00:06:41:21 – 00:07:08:15
Speaker 1
Okay. Hearing none, I’ll just discuss some recent blog entries. We’ve been working on, reminder on the visit page, which you’re looking at here. You go to blog sites and you’ll see the visit blog and the Sam satellite blog up here at the top. So if you click on the visit blog, you’ll see a recent entry that’s very much a team effort highlighting, the names, everybody, that is involved in this on this call now.

00:07:08:17 – 00:07:38:18
Speaker 1
And we’re looking at a case from, Monday. That was very interesting. If we start with the, water vapor imagery, we have the, the three different water vapor bands, 7.3 for the lower level and the upper left, 6.95 microns. The mid-level in the upper right. And then in the lower left, we have the upper level water vapor and surface ups in the lower right and in the 7.34 micron band in the upper left.

00:07:38:18 – 00:08:05:24
Speaker 1
Here you can see a large area of warmer brightness temperatures early in the loop. And, really spread its way eastward, to much of the day. We do have a fair amount of cloud cover over here to the east as well. And one of the things that we’ve been, looking at quite a bit and looking at this particular channel because, where its weighting function is situated, is quite well suited for analysis of the elevated mixed layer.

00:08:05:26 – 00:08:30:00
Speaker 1
And what you would do is just confirm first that this region of warmer brightness temperatures is indeed associated with the elevated mix layer or if we go to soundings for, that particular morning, here’s the Omaha sounding. And it was indeed associated with the elevated mix layer. Remember the weighting function for that channel is around 600 to 700 millibars or so.

00:08:30:02 – 00:08:57:05
Speaker 1
And that’s where the elevated mix layer usually is. It’s drier. It’s above this capping inversion. And as we know that’s an important one of the important ingredients for severe weather. It leads to a number of factors that are favorable for severe storms. If we look at a larger scale view of, the 7.34 micron channel, you can see what I mean in terms of how far eastward, the elevated mix layer extended.

00:08:57:05 – 00:09:19:21
Speaker 1
It was actually these warmer, right, as temperatures well, to the east. Like I said, you do want to confirm it’s actually elevated mix there because, just general synoptic scale subsidence will lead to this signaling in addition to a number of other things. So so confirm it’s associated with the elevated mix layer. Unfortunately, in this particular case, the eastern edge of it is hard to track because we have quite a bit of cloud cover.

00:09:19:24 – 00:09:45:04
Speaker 1
So Cloud Apps is is going to be an issue with tracking this. But what I want to do next is, go down a little bit further in the blog here. And I want to highlight by this, this yellow removal that I have in this annotated image right here, this line of warmer brightness temperatures, this is 16 Z.

00:09:45:07 – 00:10:17:16
Speaker 1
And now I’m going to go back to the animation that we have stop at right around 16 Z and trace this line that I, that I just highlighted. All right. At this particular time over eastern Nebraska, extending into Kansas, a region of warmer brightness temperatures. And note, as we go through the day and we only see it for a few hours here before it comes in much more subtle.

00:10:17:19 – 00:10:45:28
Speaker 1
And then by later in the afternoon hours, it’s it’s generally in this region, but it’s very hard to pick out. It becomes, very subtle. We see storms, break out along the cold front and then curiously, we see some storms, break out ahead of the cold front as well. So, one of the things that we’ve also been looking at is with this particular channel, it’s also good due to its weighting function profile where it typically exists.

00:10:46:00 – 00:11:14:09
Speaker 1
And it for analyzing elevated cold fronts. So we were supposing is this an elevated cold front that we’re looking up as before. We look at other data sets to confirm we have an elevated cold front. And I’ll go ahead and bring up a cross-section. This is from, Denver to Saint Louis. Denver on the west, Saint Louis on the east, the right hand side here looking at theta E, along with relative humidity.

00:11:14:12 – 00:11:37:21
Speaker 1
And on the left, I’ve annotated the surface cold front position at this particular time. This is at 16, the, from the wrap and you can see the temperature gradient and then the ice and troops sloping, like so here towards, off in this direction. And then the nose of the sloping ice and drops, coming out over here, we have this elevated cold front.

00:11:37:21 – 00:12:09:12
Speaker 1
So this is, additional confirmation that you have a elevated cold front in place. Another way to look at this, another way I like to, look at this as well as, similar cross-section. About the same, line that we just looked at. Only here we’re looking at temperature advection, which is shaded. So this cold advection, first I’ll just point out the, relative deep cold advection that we have over this region, these, cooler colors.

00:12:09:14 – 00:12:37:15
Speaker 1
And then just out ahead of that, we have this region of cold advection, around 600 to 800 millibars, sloping, like so. So this is the elevated cold front ahead of the dry line. And the surface cold front is, the other thing to point out here is notice the contours. These cyan contours are specific humidity. So with that cold advection we have a drier air mass associated with that.

00:12:37:17 – 00:13:00:21
Speaker 1
Think back to the line of warmer brightness temperatures that we pointed out earlier. Why was the leading edge of that warm? Well, if we have a drier air mass above this here, we would be able to see a little further down into the atmosphere and thus be warmer. So again, it’s gets gets back to the weighting function profile, understanding what you’re looking at in the vertical.

00:13:00:23 – 00:13:39:14
Speaker 1
And the only caveat with this, like I said, even though it showed up, fairly well early in the day, it became more subtle, by later in the day. And if we simply, extrapolate, extrapolate along, in terms of where we expected it to be, looking at this and going back and forth here, here, we’re expecting it to be approximately in this position where we see these storms go up where my cursor is ahead of this, surface, cold front where we see convection a little bit further to the west.

00:13:39:17 – 00:14:07:01
Speaker 1
If you look at the meters, there’s no real, well pronounced surface convergence where these storms are going up like we have very well, defined surface convergence further to the west where these storms are so and so if we go ahead and, go a little bit further down in our, blog here, here, this yellow, oval here that’s indicating the, storms of interest that I’m talking about ahead of the cold front.

00:14:07:04 – 00:14:28:09
Speaker 1
And, one of the studies that looked into this here in terms of, these convergence and divergence patterns that set up at the leading edge of the cold, the upper cold front, you can have this convergence where storms get going. And I believe that’s what happened in this particular case. If we look at the, radar, go ahead and bring in the radar.

00:14:28:24 – 00:14:52:17
Speaker 1
Here’s the storms of interest just out ahead of the line. And these storms were severe. We could see the severe warnings here. And, just had hail up to, golf ball size with, with some of these storms before eventually merging with a line. And I think what happened is the surface cold front, caught up with the elevated cold front as these storms, progressed to the east here.

00:14:52:19 – 00:15:14:04
Speaker 1
So let me pause here and, ask any questions or comments, particularly if we have anybody. That was maybe, within this area, Iowa or maybe eastern Nebraska. They noticed this. Any questions or comments?

00:15:14:06 – 00:15:31:00
Speaker 1
Okay. If not, let me, turn it over to Chris Citro, who is, one of my, coauthors on this. And, I know you were, talking to me, yesterday, talking how busy you were here, just maybe a few comments and, and your perspective here in terms of what we put together here.

00:15:31:03 – 00:15:59:10
Speaker 3
Yeah, this is something that, I started looking at, when I was still a forecaster up in New York because, there were a couple papers published by, people across from, the Burlington weather office about, elevated cold fronts and their significance for northeastern, a large northeastern U.S severe weather events. And, I think it’s an under utilized and underappreciated triggering mechanism, if you will, for convection.

00:15:59:12 – 00:16:17:06
Speaker 3
And it’s often overlooked. I, I don’t see a whole lot of discussion in, in day one outlooks or anything like that. So, now that we have this available to us again with the Goes-r, you know, I’m hoping that, we start to latch on to it because there is one paper that I referenced the other night.

00:16:17:10 – 00:16:40:10
Speaker 3
I sent this out to my staff here at the Pleasant Hill office, and I think, from the like of tell me at all back, like 2002 or 2003, they estimated that 48% of the cyclones that are east of the Rockies have elevated are having, elevated cold front of some sort associated with them. So know that’s a pretty significant, forcing mechanism.

00:16:40:10 – 00:17:10:12
Speaker 3
And just talking with one of my colleagues here, he’s an avid storm chaser. He’s been out on hundreds of storms. He says this could be the reason why get pre-positioning. And then all of a sudden notice wide notice that, convection developing east of them. So, you know, this is just something that, with the goes-r and all that, we had this or go 16, I should say, this data set available to us again, you know, this is something that we can maybe start looking at a little bit more and have a little bit more deeper appreciation for it.

00:17:10:15 – 00:17:34:06
Speaker 3
But in terms of this severe weather event, I think we’re casually calling this probably the biggest severe weather event in about ten years. Here at the Pleasant Hill office. We were swamped from the from the minute convection started working into our forecast area as it slid down southeast from Omaha, Omaha area. And we started the day with, no tornado warnings issued for the year.

00:17:34:14 – 00:17:54:16
Speaker 3
We ended the day as it exited our area with 19. So we should 19 tornado warnings that day. And, so far I think our verification scores have been fairly decent. We actually had an EF three tornado that probably, that made national news and I’m sure many you’ve already heard. So in Oak or Oak Grove, just east of the Kansas City metro.

00:17:54:16 – 00:17:58:23
Speaker 3
So definitely a pretty significant severe weather event from our perspective.

00:17:58:25 – 00:18:00:08
Speaker 4
Chris, this is Chad.

00:18:00:10 – 00:18:00:22
Speaker 3
Okay.

00:18:00:25 – 00:18:23:27
Speaker 4
Hey, I was wondering if you could give an indication that you were swamped. Okay, okay. And, I was wondering if you could give an indication on if, you know, the go 16 imagery was utilized during the event if you had, like, if and if it was, who did that? Was it the warning forecast or did you have an MSL analyst like.

00:18:24:00 – 00:18:46:15
Speaker 3
Yeah, we had a muzzle and analyst I would say I was probably looking at the go 16 imagery, in between warnings, a little bit more than anybody else because, the images that I sent to you guys, I was trying to grab like every 15 minutes as opposed to every five minutes, just from a data, standpoint, because I, I had a feeling a day in advance this was going to be an elevated cold front flash.

00:18:46:15 – 00:19:05:00
Speaker 3
And I think I sent you guys an email on it, you and Dan, that this was a possibility, you know, so I really look at this event from a, our very mixed layers flash cold front, a lot of perspective. I honestly, Chet, I was looking at it, I was grabbing screenshots because I figured, you know, this was going to potentially lead to something.

00:19:05:03 – 00:19:21:18
Speaker 3
We were so busy with warnings, though. I don’t know how many other forecasters within the office were actually looking at it. As much as I was, I was really interested in it because I knew what was probably causing the event. And, you know, having the three water vapor channels available to us was was something neat to watch.

00:19:21:18 – 00:19:25:13
Speaker 3
And in my perspective, because I knew what we were going to be dealing with.

00:19:25:15 – 00:19:56:29
Speaker 4
Sure. So, you know, the only reason I asked is because obviously, you know, there’s been a lot of suggestion that, you know, forecaster during these events, this data should be utilized for the warning decision making process. Sure, if it’s the morning forecast or if it’s a muzzle analyst, but, you know, over the next, whoever shoes or forecasters are on this call, you know, as we get into the convective season, really think about how you can utilize this.

00:19:57:01 – 00:20:10:21
Speaker 4
You know, this imagery is useful and you’re getting it in real time. So how can you incorporate it into the decision making process? Because that’s going to take a while for everybody to get a good grasp on. And I just want to plant that seed with everybody.

00:20:10:25 – 00:20:30:24
Speaker 3
Oh, I’ll just, add a comment real quick, said one of the comments that I made. Before the event really got underway. I came in, I think, at 3:00 that afternoon, and, I knew probably by 6:00 we’re going to be issuing warnings or shortly thereafter. So I came in and I immediately started doing screen captures of the of what you see moving in front of you right now.

00:20:30:24 – 00:20:49:09
Speaker 3
I was like I said, I was trying to get them like every 15 minutes. And I made the casual comment to a couple of my fellow forecasters. This is this is a a neat problem to have. This is the first time with satellite imagery. I’ve actually got to skip frames, because I just cannot manually get all the screenshots that I want, because we’ve just got so much data available to us now.

00:20:49:09 – 00:21:00:21
Speaker 3
So I said, this is a neat problem to have. I usually had that problem with radar, but now we have that problem with satellites. So I think they, I framed and then probably.

00:21:00:23 – 00:21:05:21
Speaker 1
Thinking around have questions for, Chris or Chad.

00:21:05:23 – 00:21:10:25
Speaker 3
I go ahead and repeat that right now.

00:21:10:27 – 00:21:13:24
Speaker 1
Does anybody have any questions or comments? I mean.

00:21:13:26 – 00:21:36:21
Speaker 3
It’s that everybody’s there on the road. Hey, this is Dan Baumgarten, lacrosse. I guess I have a question. If you could maybe stop the loop and point out where you maybe see the elevated cold front in that, lowest level water vapor imagery. Is it just a subtle radiation there in the, in the reds? I guess can you point it out a little bit more clearly?

00:21:36:23 – 00:21:55:00
Speaker 1
Yes. That’s a very good point. And I want to emphasize that here you can settle. This is me and Chris have been looking at this for a while, and we’ve seen better examples that you can follow along further. And we’ll certainly be looking for more examples when we get a greater sample size of the events. Here we go to 16.

00:21:55:03 – 00:22:19:26
Speaker 1
So I’ll go ahead and point out with my mouse here, it pretty much eastern Nebraska extending into Kansas. It’s a gradient in these warmer brightness temperatures that we see right here. And, and just a little bit after this, I, move forward in time. It becomes quite subtle. By this time, I would say it’s very hard to make out.

00:22:19:26 – 00:22:43:05
Speaker 1
So, like I said, as we go along in time here, hopefully we’ll find more examples where this just becomes more clear cut. When we see if we get a greater sample size. But, that was one of the frustrating aspects of this case was, we we definitely had an elevated cold front as you can see, by the supporting evidence that showed up early on.

00:22:43:07 – 00:23:02:08
Speaker 1
But it became more subtle in time. And I should ask you, do you see that, in the early imagery right around here? Yeah.

00:23:02:11 – 00:23:15:15
Speaker 3
Yeah, I can see that. I mean, that’s pretty subtle. Yeah, I guess the linearity of it. Is that what your eyes pick up on in that diagnosis?

00:23:15:18 – 00:23:44:14
Speaker 1
Yeah, it’s that it’s going to be warmer brightness, temperatures and, a line of warmer brightness temperatures. And, the, the examples that we’ve seen me and Chris have seen in the past, particularly in the northeast, is you’ll see this line in the at this particular channel advance, to the eastward typically and, and you’ll see convection, where you can see convection, initiate at the leading edge of these lines here along these edges.

00:23:44:19 – 00:23:56:21
Speaker 1
So that’s really the signal to, be watching for. And at times it may be very subtle. Chris, does that sound, all good to you in terms of the discussion?

00:23:56:21 – 00:24:18:10
Speaker 3
Yeah, that Dan like like Dan, Dan said. And this was definitely not the most classic example we’ve ever seen. Know, I’ve looked at many of these cases now, and in many times it’s much more distinct and much easier to track eastward with time. And I’ve seen several events up in the northeast that were, you know, very well defined.

00:24:18:10 – 00:24:36:06
Speaker 3
And I’ve seen several events down here in the Plains as well that have been fairly well defined as well. Dan, one thing I thought was pretty interesting that we talked about yesterday was looking at a couple of the other water vapor channels as well, specifically the higher one, because we were able to actually even track the position of the actual trailing cold front and the dew point.

00:24:36:06 – 00:24:39:24
Speaker 3
I don’t know, I think that was like at 1602 Zulu. I don’t know if you could pull that up.

00:24:39:27 – 00:24:48:12
Speaker 1
Yeah. We have a, the we we have a animate annotated image on the go back here.

00:24:49:07 – 00:24:54:18
Unknown
See? That’s.

00:24:54:21 – 00:25:00:28
Speaker 1
And this is the one at 16.

00:25:01:00 – 00:25:02:27
Speaker 1
Or did you want the latter one at 21?

00:25:03:02 – 00:25:08:12
Speaker 3
Chris I again I think a 101 actually. Dan. Sorry.

00:25:08:14 – 00:25:10:17
Speaker 1
The 21 okay.

00:25:10:19 – 00:25:21:00
Speaker 3
Yeah. Okay.

00:25:21:02 – 00:25:36:15
Speaker 3
Okay. There it is. Yeah. Right there. You can you can actually look in the bottom left here Pat left hand panel. You could actually see the position of the the dry line in the actual trailing cold front. You can actually kind of see them converging up there in southeastern Nebraska. But it crossed the county line. That’s what I told you.

00:25:36:18 – 00:25:38:10
Speaker 3
So we’re back to across.

00:25:38:12 – 00:26:05:07
Speaker 1
Yeah. The, the the feature I’m pointing at right now is believe is the dry line. And then this feature, it’s further to the west is the surface cold front. And if you follow that northeastward, it does in the dry line up here where you had storms going in, Nebraska at this time. And the surface cold front very soon afterwards did surge southeastward and catch up with the dry line, in the looping imagery just a little bit after this time.

00:26:05:10 – 00:26:13:16
Speaker 3
Although then I still would bring up I’m not. Why is the dry line of seemingly cooler brightness? That’s what we were trying to figure out yesterday.

00:26:13:17 – 00:26:27:07
Speaker 1
Yeah. That’s something, we were asking a lot of questions about. And, to help hopefully answer that question. We’re working on, getting a weighting function profile from goes 16, to hopefully answer those questions. Yeah.

00:26:27:09 – 00:26:31:09
Speaker 3
Or it could be just it could be something else in this case.

00:26:31:09 – 00:26:48:24
Speaker 1
I guess it could be something over the top of it as well. Yeah, it could be related to the elevated cold front. There’s, there’s or maybe just there’s also make sure that. Yeah, you know, there’s a lot of dust and smoke in the air. There were a lot of fires here. So it’s it’s possible we’re looking at the tops of those, the brightness temperatures of the tops of, smoke.

00:26:48:24 – 00:27:03:12
Speaker 1
And so there’s a lot of hypotheses we have, but we’re not quite sure. And, and maybe the, weighting function profile will help, glean some more information on this.

00:27:03:15 – 00:27:28:23
Speaker 3
Dan, would you think maybe in those three supporting water vapor images, you think potentially you see that convection going up over western Iowa? You notice that darkening, especially in the upper right hand panel, just directly off to the east, to the east of the, convection that’s developing in far western Iowa and far eastern Nebraska. Do you think that might be evidence of that, upper level cold front to or that mid-level cold front?

00:27:28:23 – 00:27:29:15
Speaker 3
Cold front aloft?

00:27:29:20 – 00:27:49:13
Speaker 1
Yeah, it’s definitely possible. Like like. Well, we’ve been saying it’s it’s very subtle. And I almost go from an extrapolation when I was looking at this where I expected it to be, rather than definitely being able to see it from a continuity perspective, just because I, I kind of lost it as it went along. But this is where I would have expected it to be just purest.

00:27:49:14 – 00:27:59:29
Speaker 1
And it seems that it was moving up.

00:28:00:01 – 00:28:10:11
Speaker 1
Okay. Any other questions or comments?

00:28:10:14 – 00:28:15:18
Speaker 1
Okay. And I believe we’re just about out of time. I’ll just quickly.

00:28:15:20 – 00:28:25:17
Speaker 3
I would if I show one thing that is the line on the line. If he’s not, I’d like to show something that he made. And then we can end with that if you’d like.

00:28:25:24 – 00:28:33:01
Speaker 1
Okay. You want me to just pointed out here this this is the, I just went back to our list of blogs, and I went to the goes our Proving Ground blog.

00:28:33:03 – 00:28:33:29
Speaker 3
Okay.

00:28:34:01 – 00:28:37:13
Speaker 1
And, I can simply show this here for you.

00:28:37:13 – 00:28:41:12
Speaker 3
And I know it’d be actually on Bill’s blog. I’ve got.

00:28:41:12 – 00:28:45:23
Speaker 1
It. Or you. I have to, I have to pass it over to you here. Okay.

00:28:45:26 – 00:28:47:17
Speaker 3
Or. Okay. Sure.

00:28:48:03 – 00:29:04:06
Speaker 1
Let’s see here. I will make you the presenter.

00:29:04:08 – 00:29:08:16
Speaker 3
Okay. I thought this was kind of. Can you see that? No.

00:29:08:16 – 00:29:10:06
Speaker 1
Do I see your screen?

00:29:10:08 – 00:29:33:19
Speaker 3
What I thought was kind of nice of Bill. Bill has some really nice blogs that he’s been billing. Is, was this satellite liaison at SPC? He’s an intern now at Pueblo. And, there were there were a ton of fires that broke out in between, far eastern Colorado, the Oklahoma Panhandle, western Kansas on Monday and have continued up and on.

00:29:33:19 – 00:29:56:10
Speaker 3
But, what he did was put the 3.9 combined with the channel one, and it shows the smoke pretty nicely. Now what I’m wondering about and maybe, Scott might answer this. We do. You know, Scott, is this a mercatus colored table or. We were not able to do this on finance on trips unless he created his own version that looks like a mercatus V display.

00:29:56:10 – 00:30:02:17
Speaker 3
Yeah, yeah. Okay, so this color table hopefully will be available. You think? Scott, at some point.

00:30:02:20 – 00:30:06:26
Speaker 4
I would think someone would be able to create it if,

00:30:06:28 – 00:30:27:03
Speaker 3
Okay. So yeah, we’re not taking advantage right now with the, you know, this is all going to be at the Boulder office. We were just getting black for the fires. But, as somebody pointed out, we get a lot warmer temperatures now since with the with the instruments. So yeah, I noticed I was looking at Florida today in the 3.9 and it’s really very black.

00:30:27:03 – 00:30:54:18
Speaker 3
And I had to change the enhancement. So I think I just tweaked the, the bounds of the, of the color bar. So. Okay. Okay. Better. Yeah. All right. I didn’t know if there was something out there on the lab or something that could be downloaded or. And I wasn’t aware of it, but but I thought this was a nice combined image that he had created a.

00:30:54:20 – 00:30:57:03
Speaker 3
And that’s probably not, I guess, DNA.

00:30:57:06 – 00:31:08:16
Speaker 1
Okay, well, let’s go into wrap up mode here. Just, before we end, does anybody have any final questions or comments?

00:31:08:19 – 00:31:12:02
Speaker 1
Okay. Well thank you everybody. Thanks for attending and have a great day.