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00:00:00:05 – 00:00:26:27
Speaker 1
Begin here. So, we’ll start off looking at, some synthetic imagery. And the way I want to introduce that is, with this particular slide right here, this is the recent, snow storm that affected Colorado, late, last week. And I’m going to run, slow loop, Buffalo, if you see any, problems or difficulties with my loops here, just, let me know.
00:00:27:00 – 00:00:56:27
Speaker 1
But, what we’re looking at here is the, ghost water vapor imagery on the right. And on the left we have the dynamic tropopause pressure, from the Nam. And the idea here is, looking for those higher pressures. In other words, a lower, tropopause height corresponding with where you see these, these large troughs that come through or sometimes, short waves, for example, there’s a weaker shortwave moving from Arizona eastward towards the Texas Panhandle.
00:00:56:27 – 00:01:24:00
Speaker 1
And you can see that in both the water vapor imagery and, the model output here. So the way I want to introduce this is one way of looking at, model output in comparison with, Go’s water vapor imagery. Another another way to do that here, I’m going to, the next slide and, and this particular slide, we have the same dynamic tropopause height, pressure.
00:01:24:00 – 00:01:51:24
Speaker 1
Excuse me. On the right. And then on the left, we have the synthetic imagery from the Nam nested operational, Nam model, that the models run or that the synthetic imagery is, run once a day at zero Z and it goes out to 60 hours. So it does go out longer than the synthetic imagery that we’ve been talking about for a while from the initial warfare, model that goes out 36 hours.
00:01:51:27 – 00:02:17:15
Speaker 1
One important thing to keep in mind is that the initial warfare, band is simulated for goes are. In other words, that’s at 6.95 microns. This particular, synthetic imagery is, for 6.5 microns, which is the same as the operational, go satellite. So you can make that comparison, that much more readily. Now, with this.
00:02:17:15 – 00:02:38:20
Speaker 1
And another thing to keep in mind is it will look somewhat different. And we’ll talk about that, a little bit later as well, in terms of the different micro physics package. But what I want to show here is that this is another way you can compare, between the synthetic imagery and some model output. What I want to show next here, I’ll really slow this loop down.
00:02:38:22 – 00:03:03:01
Speaker 1
This is the, RGB air mass products made from the go sounder. And some of the applications that are useful here is it shows you the different, air masses here over a fairly deep layer. It does have a nocturnal, signal with it, for the the channels that are, fairly low in, the atmosphere.
00:03:03:07 – 00:03:25:18
Speaker 1
But, one thing I wanted to point out is this is the same time period, essentially, that we were just looking at. So you can see this trough throughout the West here, indicated by this brownish or, rusty color or however you want to describe it, moving towards the southeast here. So again, another way of looking at the trough and short ways.
00:03:25:18 – 00:03:53:11
Speaker 1
And you can actually see that shortwave, starting over Arizona, moving towards the east and weakening in time here as well. So, finally with this particular, loop, let me slow it down. We have our Go’s imagery. On the right goes water vapor imagery on the, right here. And then on the left we have the synthetic, Nam nest model.
00:03:53:11 – 00:04:21:05
Speaker 1
So again, another way to, compare the model with the observed imagery. One of the things that I’ll go ahead and point out here is you can see a pretty significant difference at zero. You can see a pretty significant, significant difference here over Colorado in terms of the aerial coverage of the colder cloud tops. And we were getting, quite a bit of snow around this time and into the evening hours that you can see here.
00:04:21:05 – 00:04:41:16
Speaker 1
The, the model was slow to pick up on here. So finally, in terms of, a summary, like I said, for a number, for quite a while now, for a couple of years, we’ve had this nice little warfare, synthetic, imagery. Now we have this Nam nest imagery, and you can see they’re quite a bit different.
00:04:41:16 – 00:05:03:00
Speaker 1
These are the same, forecast times. These are different models, of course, but in terms of understanding why they look so much differently. Keep in mind, the band this is for goes are the from the missile. Worf, this is for the operational goes over here. It’s at 6.5 microns versus 6.95. So of course 6.95 is looking lower in the atmosphere.
00:05:03:00 – 00:05:26:20
Speaker 1
So that’s why one of the reasons you see this warm bias in the brightness temperatures, the forecast times, goes out further in the Nam. This goes out to 60 hours. After 36 hours it’s in 36. It’s in three hour increments. Before that, it’s in one hour increments. Micro physics packages are difference, which is another reason why these clouds are going to appear, differently.
00:05:26:22 – 00:05:58:12
Speaker 1
Both these products are available here. And this particular page right here. And if you scroll down to the synthetic imagery section, you’ll see right here. This is from the, the soil warfare model. And go to just below that and you’ll see, from the Nam nest. Any questions. That.
00:05:58:15 – 00:06:01:04
Speaker 1
Okay. No. Are you on yet?
00:06:01:06 – 00:06:08:21
Speaker 2
Okay, I’m here on the line, but I was talking to my essay. No, I haven’t been able to get it to update. Okay, I’ll be able to get it to come up.
00:06:08:23 – 00:06:13:27
Speaker 1
Okay. Well, what I’m going to do is, turn it over to Scott Lindstrom now.
00:06:13:29 – 00:06:21:17
Speaker 2
And I’m here. I’m showing my screen. Can everyone see it?
00:06:21:19 – 00:06:22:18
Speaker 1
Yes.
00:06:22:20 – 00:06:41:14
Speaker 2
Carried comes. Okay. Well, I want to talk. I wanted to talk a little bit about the return of Gulf moisture. And I’m going to say that this was really based on the GFS from a couple of days ago, that I had a huge storm coming out. It looked like a really nice potential severe weather outbreak for the Central Plains.
00:06:41:16 – 00:06:59:27
Speaker 2
But since then, it looks like the northern stream has reasserted itself in the GFS, and it doesn’t look like we’ll have a big storm coming up into the Midwest getting rid of all this cold air. It’s snow that’s on the ground. But of those. So what I was going to show one, one nice thing about this big cold air outbreak that has come down.
00:07:00:00 – 00:07:23:21
Speaker 2
I’m showing you the mode of sea surface temperature. So there are plenty of clear skies. So you see some really nice detail. For example, in the, loop current that’s in the central Gulf of Mexico. So the temperature, sea surface temperatures there are in the 70s. So it’s, once you get air moving across that maybe you’ve not from north to south, but more from an east southeast direction toward the Gulf Coast.
00:07:23:21 – 00:07:40:08
Speaker 2
And you can see that’s starting to happen. This is an image from Monday. But if you look at today, you’ll see there are clouds in the southwest Gulf of Mexico as moisture is starting to pull and it’s ready to come north. And I’m just showing you a couple of ways to find to see how that moisture is moving.
00:07:40:08 – 00:08:09:26
Speaker 2
And a big one is using the if it goes sounder. This back up here that’s available in a website. So just to show you what’s on here, these are the this is the imager water vapor in the upper right. So that’s at 6.5 microns. And then the others are the sounder water vapor at 6.5 microns. In the upper left a 7.0 micron sounder water vapor in the lower left and the 7.4 micron in the lower right.
00:08:09:26 – 00:08:37:04
Speaker 2
So the upper left is higher in the atmosphere, the lower left is intermediate and the upper right is and the lower, the lower right is the lowest in the atmosphere. So you can think of this one in the upper left around, oh 4 or 500 millibars. The one in the lower left is probably around 600 millibars, or in one of the lower right is closer to maybe 650 or 700.
00:08:37:04 – 00:09:00:07
Speaker 2
And of course, that changes with the atmosphere. And I’ll show you the weighting functions that really will let you pinpoint where things are. But I thought the interesting thing in this, in this animation, if you look at the lowest, if you look at the lowest part here, you see very warm temperatures. So the top of the moist layer is fairly low in the atmosphere, but you’re not seeing the east west motion at the end.
00:09:00:07 – 00:09:23:12
Speaker 2
Here you’re seeing motion from north to south and maybe a little bit to the south southwest. So this lowest layer and this goes sounder water vapor is showing that there’s potential for the start of the return flow into South Texas. And again you don’t see that a little bit higher in the atmosphere at seven microns or 6.5 microns.
00:09:23:12 – 00:09:43:23
Speaker 2
And one other thing of course, that this is Goes 13 on the right and goes 15 on the left. And especially at 6.5 microns, a little bit more noise in that particular sounder channel. So you have to, come to terms with that, I guess is a good way to put it. I told you I’d show you the weighting functions, and those are on this.
00:09:43:25 – 00:10:01:11
Speaker 2
You you do a Google search on goes weighting function. You’ll find this particular website here at Simms that you can look at the weighting functions for the different, different bands on the coast sounder and on the Coast Imager. So the sounder bands are here, you can turn them on and off. And I kind of like think that’s handy.
00:10:01:11 – 00:10:26:16
Speaker 2
So I’m turning on and off that goes imager. And you’ll see that black that black line even though it’s 6.5 microns. It does see a little bit farther down into the atmosphere than the sounder 6.5 microns, which is this blue. But for the sounder channels you do see a very nice, distinguishing between upper levels around 400 than around maybe 520 and then closer to maybe 600 millibars for the lowest level.
00:10:26:16 – 00:10:45:08
Speaker 2
So if you want to see the start of the return flow, you really want to look at the echo sounder. And this is available in, in, in a website. Just go to the satellite, and there sounder imagery there. And you do see the three different, water vapor channels there so you can load them up and look at the return flow.
00:10:45:10 – 00:11:14:14
Speaker 2
And if you look at the, this is the brightness temperature difference. You do see the incursion of the low clouds that are, heralding the return flow coming up from the Gulf of Mexico. I don’t know if there’s going to be much severe weather with this because of the the large scale is not, quite so to the large scale in the GFS now does not quite look quite so favorable for a return, for a severe weather outbreak early next week.
00:11:14:14 – 00:11:31:24
Speaker 2
But it does look like the moisture is starting to come back. And you look at the dew points down in South Texas. So not quite at 50 yet, but it is the start of the return flow. So that’s an important thing to think about. When you’re, you know, thinking about what’s going to be happening in the next couple of days in the Great Plains, where is the moisture coming from?
00:11:31:26 – 00:12:11:28
Speaker 2
And just some tools that you can have at your disposal that are readily available that you can use? That’s really all I would that’s really all I have to say. Yeah. Like a. Yep. Yeah. I don’t know if you saw my question a question, but no, I really, really enjoy this. I mean, this is tremendous. I don’t know if you can go back to the previous, four panel with, different, water vapor bands, because, even just last week and I think it also happened a few weeks earlier when I was the Eastern Region virtual workshop, and last week there and, Satellite Science Week, a lot of,
00:12:12:04 – 00:12:43:04
Speaker 2
reference and examples of, the, water vapor channels that will be available on API. And what I’ve been lamenting is and many of those, very little or sometimes no reference to the fact that, you do have and again, it would be a good thing to show maybe next time how close the API water vapor channels would be to some of the existing, go down or channel.
00:12:43:06 – 00:13:08:08
Speaker 2
But, I actually thought I heard it from one of the satellite liaison. I don’t think it’s any of the ones on the call today, so I think I can say it that they thought they could not get the current go sound or water vapor channels at one of the national centers. And I was kind of surprised to hear that, because as you’re showing here, it, it, they are available and it looks correct.
00:13:08:12 – 00:13:32:04
Speaker 2
They’re in a website. I’m not sure if they’re in all of the versions of any website, but, there might be some that I don’t know, Amanda. Or you’re there at Aviation Center. Maybe Amanda could follow up and find out just, Yeah, because there are differences between obviously it works and anywhere and but also hopefully able to we’ll continue to make these available.
00:13:32:04 – 00:13:52:15
Speaker 2
So anyway. Yeah, in general very, very nice presentation and very good connection to. Yeah. How this can help looking at the return flow from to go. Yeah, I really like the differential advection in the, in the sounder water vapor. You really can see that upper levels are still living from the west, but at the lowest level, things are starting to turn around already.
00:13:52:15 – 00:13:59:16
Speaker 2
So maybe tomorrow there’ll be a nice surge of moisture coming up to Texas.
00:13:59:19 – 00:14:11:15
Speaker 2
Okay. So do you have any questions? No, I have a question. Yeah. Or the end of your, talk today.
00:14:11:17 – 00:14:35:02
Speaker 2
But nothing on this sound or stuff. No. It’s interesting. Okay. Actually, I was just commenting that we never look at the sounder data because, well, the, the imagery has high resolution, but there’s an interesting case to show that, there is there is some utility in the summer data, and there are examples where the lowest level will show something that does not show up in the upper levels.
00:14:35:06 – 00:15:06:00
Speaker 2
So the imager will miss it, even though, I mean, it does have the better resolution. But, it doesn’t have the good vertical resolution that the sounder does. Yeah. I don’t know if I might be bold enough to say. And that starts panning out. Well, that might deserve a blog entry at some point. And in that entry, remind folks that there is training and, the fact that they’re already sounder, channels available on a was, that is a I mean, Tony.
00:15:06:03 – 00:15:12:19
Speaker 2
Okay. Well, I don’t I give it a shot anyway. Just.
00:15:12:21 – 00:15:27:02
Speaker 2
Okay, I’ll monitor this. I’ll monitor this for a couple of days and see what, see if it’s a I think it could be a good example. We’ll see what happens. Coming soon to a blog near you, Brad.
00:15:27:04 – 00:15:32:24
Speaker 1
Okay. At this point, I’m going to turn it over to Scott Meyer.
00:15:32:27 – 00:16:03:02
Speaker 2
Okay. I’m not sure. I really have a whole lot to add. I can talk a little bit more. About what, what the other, what we can see, the fears imagery in terms of, we are seeing some fog and stratus that are heading up into Texas, and you can see the edge of it here.
00:16:03:04 – 00:16:26:05
Speaker 2
Can bring it up. Let me get this out of the way. It’s all right. So hopefully you can see my whole or eight panel. Yeah. So if I toggle between, the.
00:16:26:07 – 00:16:34:08
Speaker 2
Borg product and the.
00:16:34:10 – 00:16:38:02
Speaker 2
Band.
00:16:38:04 – 00:16:57:26
Speaker 2
It’s amazing how the edge here is almost aligned. So it’s kind of. I, I think it’s very unusual to see an edge of it. That’s, that this,
00:16:57:28 – 00:17:28:24
Speaker 2
But but this allows you to, see a visible image in the evening. In essence, like, we have right now with a moon that offers a lot of illumination. And so, it it can see a lot more of the edges of the cloud and a lot of the cloud. And if I get there’s some holes here.
00:17:28:24 – 00:17:40:19
Speaker 2
I’m not sure if that’s from contrails. I believe it is, because it’s black on the.
00:17:40:22 – 00:18:16:28
Speaker 2
Borg Stratos, but, yeah, it it this is, you know, this is a new product that you can add in to a website, and it allows you, a high res, that you can compare to those and get a lot more accurate details on the actual actual areas of, of cloudiness. So that was really the only area that was possibly interesting, that, that it.
00:18:17:01 – 00:18:37:28
Speaker 2
I think I can actually add and let me just add in. Advertisement. There is a verse imagery in a pilot training, if you’re interested in the verse data and how to get it into your, a what’s machine and what you can what kind of data are are available, that’s available for sign up right now for you.
00:18:38:01 – 00:19:02:27
Speaker 2
That’s today precise. That’s one one quick question again. Well, that also include having an easy way to find out, what the time and a path is, you know, because obviously there’s a really good example, but the office may not even know when to look for one. And I pass to it. And some of you guys know I’m going to talk about that is in the, training.
00:19:02:27 – 00:19:24:12
Speaker 2
And the nice thing about, well, the unfortunate thing about beers is there’s only one satellite with it. The nice thing about that is you kind of know when it’s coming overhead. So it’s got about an, sometime between 6 and 8 for the East Coast. So there it also be at 12 hours so that 18 to 28, so and for the West Coast, it’s about two hours late after that.
00:19:24:12 – 00:19:47:17
Speaker 2
So how about for those, since they’re already, working with models, I don’t know what the time sequence is when you’re you’re also full notice. And this is very close to the Aqua Pass. Okay. So obviously you lose the day night, but you have all the other channels right, left, right. Yeah, but Pierce has, Sumi NPP has some advantages.
00:19:47:17 – 00:20:10:24
Speaker 2
It’s a wider swath. It has much better resolution at the edges compared to modus. All of this is talked about in the training, so. Right. And I think there may have been a blog about that too. Okay. Right. Well, gentlemen, there’s no. Yeah. When, when is the nearest training there? Okay. There is not one today. There are some on the calendar.
00:20:10:24 – 00:20:26:16
Speaker 2
I’ll check the calendar. Or you can just email me and we can set up a time of the calendar once or not. All right. I’ll check that. Okay. Yeah. I wanted to let you know kind of what was going on. What was happening is here is it’s kind of some of the security stuff, you know, we’re switching over to the cart.
00:20:26:18 – 00:20:46:05
Speaker 2
We’re what? What are these? Critical cat, the cat cart first. Yeah. And it was, it’s a matter of having administrative, privileges and so on. Whenever you do the go to meeting, if it doesn’t update it, you just type in your. Yeah. Then it it, when it downloads, then it can cause this kind of problem, right. Yeah.
00:20:46:05 – 00:20:53:04
Speaker 2
That’s just yourself. Anyway, just wanted to let you know what was going on.
00:20:53:06 – 00:21:15:04
Speaker 3
Okay. And Scott, this is Bernie, and it’s, since you have a whip, sir, and this is a follow up sort of question slash comment, to Scott Lindstrom, since you can probably display the TP, can we look at TP to see if what the return moisture signature looks like from that perspective?
00:21:15:07 – 00:21:32:29
Speaker 2
I can do that. I’m kind of curious to see how fast the load. Okay, so we go to the right product, and I assume you’re going to give me power to show this in a bit, or actually I could yeah.
00:21:32:29 – 00:21:35:22
Speaker 1
Scott B is, displaying it right now.
00:21:35:27 – 00:21:41:08
Speaker 2
So when I do that. So you want the blended.
00:21:41:11 – 00:21:49:13
Speaker 3
That’s sure. Okay.
00:21:49:15 – 00:22:26:04
Speaker 2
So there is a gradient, but the times, if, it’s really hard to tell the times of the blended also because it’s like, well, if certainly it doesn’t look like the gradient is, is equal to what we’re seeing on the actual cloud edge, I would say that Cloud Edge is a streamline limiting streamline, something that probably may not be related to the TP strictly, but you do see the tongue of warm air, warm, moist air.
00:22:26:12 – 00:22:56:11
Speaker 2
And it’s trying to, starting to come back up there. And although that’s only 1 or 2in, it’s the green 25 is. Yeah, the seven and a half maybe. So it’s barely an inch yet. So it’s still probably pretty far below normal. And this last airmass really scoured out the Gulf of Mexico. It’s it’s dry as a bone down there.
00:22:56:13 – 00:23:07:09
Speaker 2
So, this is valid. Eureka! I am seeing is. Well, you’re. Yeah, I got it resolved for me. Awesome. Okay, well, then.
00:23:07:11 – 00:23:14:01
Speaker 2
That’s good news. Yeah. And we will be using this as soon as I can. Okay. Are we going back to Dan now? Yeah.
00:23:14:03 – 00:23:39:09
Speaker 3
Yeah. And this is Bernie here. And I’m actually following up with Dan’s. We got snow last week, and so we’re still in snow season. I thought I’d show a couple RGB products to that. You can put in a waps right now. One is from Sierra here and one is from sport. And then the third one is actually one that’s from, well, from Sims.
00:23:39:09 – 00:23:45:04
Speaker 3
But I heard that that’s not going to be only available on iOS apps too. Is that correct? Scott.
00:23:45:07 – 00:23:46:24
Speaker 2
That is correct. Yeah. Okay.
00:23:46:26 – 00:24:09:01
Speaker 3
So this is just a visible shot of Colorado and our snow field. And from just looking at the texture of it, you could see that off to the east here you have low clouds. And up in here it’s sort of fibrous. So it’s high cloud. And then you could see our mountainous terrain, you could see snow areas.
00:24:09:01 – 00:24:35:11
Speaker 3
But as all of that snow and if we had the, the animation of it, we could probably guess quite a bit of it. But if we utilize some of our RGB, creations, this is derived from modus imagery that uses five different channels. And if you’re interested in finding that out, we can, go into that in a little bit more detail, but, we don’t need to for this.
00:24:35:13 – 00:25:01:28
Speaker 3
But essentially the snow is pictured here is white. Low clouds are yellowish, high clouds are pinkish, and then high. Clouds are an orangish. The ground is green and, various shades of green. And, this is not the best example of this product. And I think it’s, you know, getting later in the season where along the edges here, I think this is snow, when in fact it’s showing up as yellow.
00:25:01:28 – 00:25:24:16
Speaker 3
So, there needs to be a little bit more tuning of it. And I know this, algorithm actually gets pretty complicated. It has three different channels on each of the red, green and blue. But sometimes in the season, it does a really great job. And I think some of this actually has to do with because it includes a thermal band.
00:25:24:16 – 00:25:52:09
Speaker 3
And we’re, we’re seeing yellow along the edges of the snow. That’s not snow. It has to do more with, just the uniform temperature difference. Around 32 actually. So it might be more of an indicator of melting snow along the fringes. And so this is the one from sport where on the red, it has a point for micron on the green.
00:25:52:09 – 00:26:14:25
Speaker 3
It’s 1.6. And on the blue is 2.1 micron. So all visible channels, and here we see snow is like more of a bright red low clouds or white high clouds are pinkish. So sometimes there’s a little bit of a confusion in determining high clouds or separating that from snow. This is from modus imagery. So we don’t have a good animation.
00:26:14:25 – 00:26:33:03
Speaker 3
But in the future when we have goes-r this might we’d be better able to detect the motion of, cloud features. So that would be good. And then the one that would be from Sims, and these might not be exactly how they do in my it was just the way that I could get them. Here we see snow.
00:26:33:03 – 00:27:01:09
Speaker 3
It’s essentially it’s using a similar range of channels, where we have some channels where snow is highly reflective and another channel where it’s, not reflective at all. And so here we see the snow. Is this, aqua color. The low clouds are white. The background is reddish. And this actually has the, a vegetation component where the vegetation is more reflective.
00:27:01:09 – 00:27:24:12
Speaker 3
So we can see a distinction, particularly here in the mountainous area where it’s, greener. And so you could see where there’s forested region. And the last one is one that’s actually from the goes and it uses I forgot to put them down here. It uses a visible channel, the 3.9 and a 10.7. And it can be run an animation.
00:27:24:14 – 00:27:57:21
Speaker 3
We see the snow is more of a fuchsia. High clouds are this, magenta she color and then the ground is is grayish. Low clouds are a little bit whitish and I don’t I didn’t put the animation here. But, this can also be available on a website. So does anybody have any questions on that?
00:27:57:24 – 00:28:08:17
Speaker 3
Otherwise we can open the floor for questions. If any have come up, I think I heard Buffalo say they might have a question for near the end.
00:28:08:19 – 00:28:30:15
Speaker 2
I have a question. I hopefully it’s not too, political. There’s been a lot of talk over the past year or two about the utility of polar orbiter and, and the amount of data that they put into the models. I, I was always under the assumption it was the ghost data that was really contributing to, an improvement towards model data.
00:28:30:18 – 00:28:35:13
Speaker 2
What’s your thoughts on the polar orbiters versus or the quantity of data versus.
00:28:35:13 – 00:28:41:27
Unknown
The ghost data?
00:28:42:00 – 00:29:07:23
Speaker 2
Who do you want to start? Yeah, I’ll start from the perspective of Alaska. I know there’s a lot of data from Motus, or from the polar orbiters, including NOAA 17 about to be retired. That goes into when when the production at the poles, which has a big positive impact on models wanted to put in.
00:29:07:25 – 00:29:38:16
Speaker 2
It’s never clear to me when that model data, when those model data are used, though I know it’s all available. I know it can have a big positive impact on the model, especially at high latitudes. But I’m never sure what they’re being used. And I don’t know if there’s a good, online reference from NSF that says, okay, we are using these data, these data and these data in the models today, and this is the impact.
00:29:38:19 – 00:30:00:03
Speaker 2
So I think it’s I think polar orbiters, especially at high latitudes, give you great information. Much better than Gos does here in mid-latitudes. We’re kind of in that region where you get the great temporal resolution from goes, and you can fill in information at higher resolution from the polar orbiters as you get closer to the equator.
00:30:00:03 – 00:30:11:06
Speaker 2
So I think the polar orbiters really lose, their usefulness because the overpasses are so rare. So that’s my offsets.
00:30:11:09 – 00:30:22:07
Speaker 1
Anybody else and, expertise and more expertise than me on, data assimilation? I guess it’s more of a data assimilation. A question of the satellite data.
00:30:22:09 – 00:30:46:12
Speaker 2
Yeah. Than maybe this is something or. Scott, really that you could forward to. You have an expert there if I wanted. And obviously I spent a lot of his career working on exactly this problem. You know, the role of, various satellite system, regarding data assimilation and, and that has gone through some significant changes over the last few years.
00:30:46:15 – 00:31:07:27
Speaker 2
And really, I think when, when I’ve seen some fairly good presentations where, again, European Center seems to lead the way because they have people talk about the premier model, I think it really is based on the fact that they have the Premier data assimilation system, and they actually do this. They actually do break it out on a daily basis.
00:31:07:29 – 00:31:31:29
Speaker 2
The role of the multiple satellite systems. And really there are many, I think when we’re thinking about our NOAA polar orbiters, they’re just a small fraction of the overall polar orbit or fleet. You have to think about it. There’s a fleet of polar orbiting satellites up there now. And, again, I think the Europeans are leading the way in terms of, there are two parts, really, to the question.
00:31:31:29 – 00:31:58:18
Speaker 2
It’s really not where satellite system contributes more or less. It’s really that there is, a community of satellite systems that are contributing to the data simulation and any improvements we’re seeing in that. But then the second part is really what is the capability of your assimilation system? And I think this is where, Bob, you know, whether himself and it might be something that we put up for a visit next month or two.
00:31:58:21 – 00:32:23:03
Speaker 2
Dan, as Bob helped us out and, and really talk to this problem. And I think we we get a lot more participation in something that, is being dealt with by various modeling centers, even right here in the U.S. it’s macho stance. But the Joint Center for Satellite Data Assimilation is one of their big topic. But how do we actually get more of the satellite data into the system?
00:32:23:03 – 00:32:49:17
Speaker 2
Because what you find out when you look at some of the metrics is that and it doesn’t matter whether it’s Geo or Leo or some combination thereof. It really, especially in the US, the data simulation system is not keeping up, and they’re really only a small fraction of all of the observations are actually getting into the system because of all the complicating factors associated with, trying to bring in all that data.
00:32:49:19 – 00:33:10:10
Speaker 2
And I saying I think it’s changed somewhat in the last couple of years, but as little as 2 or 3 years ago, they were only using about 10% of the available satellite observations, just because there are so many of them. When you look at the entire fleet so, sorry I can’t give you more details on it, but but hopefully it’s something that we can look at.
00:33:10:10 – 00:33:40:16
Speaker 2
And, and also comment is working on this problem. They’re going to be putting together a module on the role of satellite data and and model, simulation systems and hoping to have that out later this calendar year. So Buffalo, I’ll look to see what I can find out. I recall one of the problems with, with Polar Orbiter data is its timeliness, getting it to the model in time for the assimilation.
00:33:40:18 – 00:33:46:09
Speaker 2
But I’ll, I’ll see what I can find out, and I’ll shoot you an email. Okay. Thanks for your comments.
00:33:46:12 – 00:34:06:28
Speaker 1
Yeah. And our next, satellite, session or satellite chat here is April 17th, and we’ll see if we can’t, get somebody that has expertise on this, to be on our next satellite chat or maybe, the one in May if he’s not available in April. So. So we’ll get somebody on the line here, for the future as well.
00:34:07:00 – 00:34:15:07
Speaker 1
Okay. Any other questions?
00:34:15:09 – 00:34:19:28
Speaker 1
Okay. Well, thanks, everybody, for your participation. And have a great day.
00:34:20:01 – 00:34:20:05
Speaker 2
I.