Regional and Mesoscale Meteorology Branch

00:00:00:09 – 00:00:22:25
Speaker 1
We want to welcome a special guest today. Bill line, who is the satellite liaison with the hazardous weather testbed at, the SBC down in Norman, Oklahoma. And he’s going to talk about goes our proving ground, products that will be utilized in the spring experiment at the hazardous weather Testbed. So at this point, I’ll turn it over to Bill.

00:00:22:27 – 00:00:27:23
Speaker 2
Thanks, Dan.

00:00:27:26 – 00:00:53:23
Speaker 2
And so, to start, I just want to, quick give a brief highlight as to, the structure of the hazardous weather testbed. So the h w t in Norman, Oklahoma, in the National Weather Center is jointly managed by the NASA cell SPC and Norman WFO, and it’s, for the most part, split up into two main groups. The EFP experimental Forecast program and the Experimental Warning program.

00:00:53:29 – 00:01:39:05
Speaker 2
So while the RFP focuses more on the use of, convective allowing models and ensembles of guidance to the prediction of severe weather, from a few hours to a few days out, the group’s mission is to improve the nation’s hazardous warning activities by looking at new techniques of observing platforms, technologies, etc.. Now, the Goes-r Proving Ground has been a part of various exterior experiments within the team over the past few years, and the EPA and DWP, and the goal of these demonstrations are to provide a pre operational demonstration of new satellite based products and capabilities that will be available with the next generation Goes-r series of satellites.

00:01:39:08 – 00:02:12:06
Speaker 2
And this early exposure, really helps forecasters to become familiar with Goes-r capabilities and products prior to launch as and additionally, the feedback received from participants is very much utilized in the continued development of Goes-r and other satellite based products. And this free experiment is really a conglomeration of several experiments, during the height of the spring severe season, when scientists and forecasters can come together to, to look at these new products.

00:02:12:09 – 00:02:43:11
Speaker 2
So the 2014 spring experiment is made up of, several smaller experiments this year that will evaluate, their tools kind of separately with their own forecaster. And so in April, there will be an MRI mass experiment, in May, and the first and third week in May and first week in June, there will be a whole experiment, with its own forecasters, there will be a Earth network’s total lightning experiment in July and a hydro experiment in July as well.

00:02:43:16 – 00:03:05:20
Speaker 2
And then the big the main spray experiment in which Goes-r is involved will be the first three weeks in May and the first week in June, and then the experimental forecast program on the other side of the room will be, through May and the first week in June. So, key points about the big spring experiment this year.

00:03:05:22 – 00:03:28:28
Speaker 2
They said Goes-r will be a big role in it, as well as the, lightning jump algorithm, floating high resolution water and the ensemble labs. So there will be four participants per week, including three National Weather Service and one broadcast meteorologists. And, this is something new this year, and it’s part of the Proving Ground goal to get the broadcast community more involved.

00:03:29:01 – 00:04:14:01
Speaker 2
And, the Goes-r proving ground. This will be a simulated warning operational environment using Amos two training will be in the form of narrated PowerPoints articulated, to be sent to the forecaster prior to arrival, as well as a quick guide for the forecaster. Two years to reference during the experiment. Feedback will be in the form of surveys, live logging, discussion during UPS with scientists, and daily debrief and we’ll close out each week with eight tales from the test bed, which we’ve done, previous years, which is a webinar aired every Friday during the experiment where participants could discuss what they’ve, what the products they’ve looked at during the week and look at

00:04:14:01 – 00:04:44:09
Speaker 2
specific cases. And National Weather Service and product developer, attendees can call in to, hear about how the week went and provide their insight and expertise. So a typical day of woe. The forecaster will travel on Sunday. Get to Norman and Monday will be a 1 to 9 shift. Tuesday through Thursday will be also be eight hour shifts, where the forecaster will, will start and come in between 9 and 3 p.m..

00:04:44:12 – 00:05:07:21
Speaker 2
And we’re hoping this year that we’ll get started a few hours before convective initiation, because for the most part, many of the Goes-r products have their greatest use in the priority environment and increasingly in type two initial convective development. So starting early will definitely be key. And we’ll work with the EFP and, SPC outlook desk to decide when and where would be best to begin.

00:05:08:02 – 00:05:52:08
Speaker 2
Our experiment each day, developers and myself will be, in the sweep each day to answer questions that help participants with product interpretation. And at the end of each shift, the forecasters will take about 30 minutes. Usually to fill out online feedback surveys and then finally at the end of the day on Thursday, the participants will work with, WD is, with van der Bogart to put together some slides, and he’ll help them out with how best to, how best to present in a webinar, which they’ll present during the tails from the test bed Friday morning before heading home Friday afternoon.

00:05:52:10 – 00:06:18:00
Speaker 2
So now to get to the products that will be demonstrated in the GWP this year. There goes our products. First goes our synthetics, satellite imagery. This there are several advantages to evaluating this product in the experiment. For one, it’s a useful way for forecasters to check our model performance and compare it with actual imagery to know how well, at least the nascent wharf is performing.

00:06:18:06 – 00:06:47:27
Speaker 2
But also it gets, participants used to, the specific bands and band differences that will be available with the Goes-r API. So this year we plan to include the longwave air, three water vapor bands and the band difference. And so we’ll look at we’ll ask questions about how the forecasters are like looking at this imagery and help them to understand, what types of new information these different bands and band differences are giving.

00:06:48:18 – 00:07:16:11
Speaker 2
Next product is the near test system. This is a, quick, updated Lagrangian transport model that projects the under utilized satellite high return moisture retrieval data forward through space and time. Now it’s a nine hours into the future. The products can be computed that will, demonstrate this year our layer p.w and theta fields, as well as the safety difference field, which is a stability parameter.

00:07:16:14 – 00:07:54:06
Speaker 2
The observation based forecast provided by the near cash helps forecasters to identify where convection is more or less likely to occur in the near future. Very shortly after the actual observation themselves were made. And the goal sounder really observes moisture boundaries at extremes quite well, and these are preserved in the near task forecasts. We also want to see how forecasters like viewing groups of recent in the forecast analysis, in addition to the forecasters, because I found that they really help to tell the story of how we’ve arrived at the current through my data next state, which is very important in the Goes-r era.

00:07:54:09 – 00:08:26:08
Speaker 2
The Nircam system will utilize, goes our baseline products, legacy temperature and moisture profiles and improve from previous years. Now we have a full Conus near cast product by combining goes east and west soundings. But I’m also including the, goes East Atlantic and Gulf soundings as well as that goes West Pacific soundings to so we can see, get a broader view and we can start to see things such as moisture return from the Gulf in the near test system.

00:08:26:19 – 00:08:56:06
Speaker 2
Next, we’re also looking at the UAH convective initiation product. This product gives the probability that a cloud object will develop a greater than 35 zero at the minus ten C level, and typically gives the lead times to convective initiation of about 0 to 2 hours. If I using a, fried a of NWP and gross, static and temporal fields and it goes era, this product will certainly take advantage of the higher resolution.

00:08:56:08 – 00:09:46:03
Speaker 2
I think those are Abby. And this product demonstrated previous year has been improved each year based on forecaster feedback. And this year it’ll have, improved PSI detection under Penshurst as well as improved cumulus detection at night. And also they’ve increased the numbers in their validation database to improve hopefully psi probabilities, especially out west. Moving forward now to the time period after convection starts to, develop, whilst will be evaluating the new severe probabilities product, the Soviets first appearance in the testbed, and it is an observation driven statistical model that merges multiple data sets including NWP, Goldfields and, radar fields.

00:09:46:06 – 00:10:19:17
Speaker 2
And it gives the probability that a storm will become severe in the next 60 minutes for any given storm, and the probability is reference to a radar object. The display that we’ll be testing is a very unobtrusive overlay on their radar. So some of the questions will be asking is if they’re fine and if it doesn’t get if if they like having it, overlaid on the radar like that, this product will also take advantage of higher spatial, temporal and spectral resolution.

00:10:19:19 – 00:10:30:01
Speaker 2
But the goals are API. And over time, developers can continue to add more fields and, refine the product. So.

00:10:30:03 – 00:11:05:17
Speaker 2
We’ll also be bringing back the overshooting top detection algorithm. This has been demonstrated in the national centers for the past. Year. And we found that, it does have great use, not just at night and where radar coverage is limited, but also, where you have radar coverage. Forecasters have said that it really does help with, situational awareness sometimes basically just confirming what they already know, but helping to give them confidence in what other tools are showing, of course, where you have an overshooting top, that those areas often coincide with the occurrence of severe weather.

00:11:05:20 – 00:11:33:02
Speaker 2
And another thing the forecast is really like looking at with this product are trends and overshooting tops. So this is something we want to stress to the forecasters during the experiment as well. And moving on, we’ll also be looking at the total lightning and pseudo GLM product again this year. The GLM its greatest asset and demonstrating is it helps prepare forecasters for the gone overboard.

00:11:33:10 – 00:11:56:25
Speaker 2
Goes-r. And total lightning is near to May forecasters. So it really just helps some to get used to looking at, that new data set. And we see how much more information total lightning has, which is CG lightning data. You can’t see features that might show up the total lightning, such as lightning, just like you see in this example.

00:11:56:28 – 00:12:23:29
Speaker 2
We utilize, lightning mapping arrays across the country to demonstrate the PLM in. And this year we’ll have ten arrays, which will be really nice as they span, multiple regions across the country. And the final product that’ll be demonstrated, from Goes-r and the AWP will be the tracking tool also from sport. This tool has been developed and refined as a response to forecaster feedback.

00:12:24:01 – 00:12:45:22
Speaker 2
And what the forecaster can do is, manually track specific objects in it, and it generates a time series plot of, that field that the forecaster wants to track. Last year it was only able to track, lightning, total lightning. But this year they’ll be able to track fields from radar, satellite and models, which will be really great.

00:12:45:22 – 00:13:15:12
Speaker 2
And I’m really excited for, examples like looking at trends in brightness, temperature and reflectivity and comparing that to lightning, and see if there, any patterns show up during the experiment. In addition to getting feedback on, how, the forecasters thought the products worked and how useful they see them in operate and warning operations, we also want to get feedback on how what the best way to actually view these products is.

00:13:15:18 – 00:13:47:15
Speaker 2
And we want to demonstrate this Goes-r convective product procedure, which will bring many of the girls are convective products together into one display because for the most part, many of these products are valuable. And the couple of hours leading up to it during morning operations. So it’s valuable to have them in one holistic display because as the forecaster goes into warning mode, having one display will make it much easier for him to check back in with what his product is showing instead of having to toggle between multiple products.

00:13:47:28 – 00:14:10:26
Speaker 2
But the ultimate goal of being kind of trying to convey that information because there’s a lot of information being thrown at the forecaster. We all know that, and we want to just make it as easy as possible for them to deal with all of this valuable info. So we’ll be asking or really testing how can the forecaster most effectively and efficiently view these products?

00:14:11:03 – 00:14:39:22
Speaker 2
If you use them together and view them with other data sets in a A in an unobtrusive matter? So that’s pretty much all I have. So if anyone on the phone has any questions, I’ll take them.

00:14:39:25 – 00:14:40:28
Unknown
Hi, Bill and Brian.

00:14:41:11 – 00:14:47:13
Speaker 4
I think Bill Schober again, a question.

00:14:47:15 – 00:14:48:18
Speaker 2
Okay.

00:14:48:20 – 00:15:06:15
Speaker 5
Bill, are you there? So that was my question. Okay.

00:15:06:18 – 00:15:14:08
Speaker 4
What about Jeff? Anything in the, central region?

00:15:14:10 – 00:15:14:24
Speaker 4
Okay.

00:15:14:24 – 00:15:23:27
Unknown
How about Steve?

00:15:24:00 – 00:15:28:03
Speaker 2
There were a few more questions earlier.

00:15:28:06 – 00:15:43:27
Speaker 4
Well, I guess I have one, for the, for the slide. The up bill. Are those intentionally over different domains or is the thinking that maybe you think up?

00:15:45:20 – 00:15:58:23
Speaker 2
I don’t I’m assuming they’ll probably all be synced up. I guess it’s at the will of what to to can do. This is just an example. I mean.

00:15:58:25 – 00:16:05:18
Speaker 4
Okay. So the. Yeah, maybe like a four panel, display versus.

00:16:05:21 – 00:16:28:00
Speaker 2
Yeah, like a four panel display, maybe. And one query will have their test analyzes with maybe radar overlaid, and then we can have CII and another panel and overshooting tops and cloud top cooling would be another panel then lightning data and another just to keep it all together. Because they do often complement each other. But really look at this product.

00:16:28:02 – 00:16:41:27
Speaker 2
The that’s the way to get these products out there. I think we’ll be able to as if we can make them easy to view for the forecaster, because this is just new information for the forecaster, and we want to make it easy for him to look at.

00:16:42:00 – 00:16:45:28
Unknown
I know you’re concentrating on goes-r, but are there any,

00:16:46:00 – 00:16:52:05
Speaker 4
Sumi MGP polar products that are, available this year?

00:16:52:07 – 00:17:09:02
Speaker 2
No, not in spring experiment. If someone from the JP’s pro JFK’s program thinks there would be something that would help in warning operations, I’d definitely be interested to hear, for future experiments. But no, it’s come to me about that.

00:17:09:04 – 00:17:11:22
Speaker 5
So that’s all we need to do is come to you. Yeah.

00:17:11:22 – 00:17:17:24
Speaker 2
I always open anyone come to and say this that we should demonstrate this product and.

00:17:17:26 – 00:17:22:20
Speaker 5
Okay, Texas also has a s p also has a overshooting top.

00:17:22:20 – 00:17:29:02
Speaker 2
So, I guess it’s a matter of it’s not over the whole thing if it’s not, you know, timely.

00:17:29:02 – 00:17:36:28
Speaker 5
But it’s something that could be added. And maybe if there’s some product where we could.

00:17:36:28 – 00:17:45:11
Speaker 2
Have the Go’s overshooting tops, that whenever there is, polar pass, you could include them in that same product.

00:17:45:13 – 00:18:08:01
Speaker 5
Exactly. I mean, I would still have something like that, even for SPC to. Yeah. So let’s talk about this. I don’t want to derail your, you know, move forward on, your what you’re doing this year, but, Oh we should certainly the sports approach to having pros and cons together. Yeah. That we could we could look at some of these things.

00:18:08:03 – 00:18:08:14
Speaker 5
All right.

00:18:08:16 – 00:18:22:07
Speaker 2
I guess that’s that’s I just wanted to mention that’s something I’m still waiting to get from, sport. Is that hybrid imagery to demonstrate it. So my SPC forecasters,

00:18:22:09 – 00:18:24:29
Speaker 5
I know so that I know you’re waiting on them.

00:18:25:01 – 00:18:30:00
Speaker 2
Yeah, I brought it up several times, but I don’t really know what the problem is.

00:18:30:02 – 00:18:46:10
Speaker 5
Okay. So maybe I’ll, I’ll talk with, with the help share. Yeah. I answer might be helpful to when when, you might describe. How are you trying to define success for the spring experiments?

00:18:46:13 – 00:19:22:10
Speaker 2
I think success would be, that product developers actually take into account the forecaster comments and maybe implementing those into their products. And for us to receive feedback on how they want to view the data, so we kept moving forward, that this will be how we present the data to the forecasters. That’s just taking the feedback and actually listening to it, I think is a success in my opinion.

00:19:22:13 – 00:19:28:22
Speaker 1
Okay. Any other questions for Bill?

00:19:29:09 – 00:20:03:29
Speaker 4
Get Dennis. Brian. Oh, I guess I have a question about how you differentiate between the official Goes-r products, like the, convective initiation versus the, I guess, what you would call unofficial products, like the, overshooting, top detection cloud cooling. Are there an effort to sort of differentiate between the official goals our products?

00:20:04:01 – 00:20:06:03
Speaker 2
What do you mean by official goes-r?

00:20:06:09 – 00:20:16:08
Speaker 4
Oh, for instance, the UAH convective initiation algorithm was the algorithm chosen as the official Goes-r or convective initiation.

00:20:16:10 – 00:20:22:21
Unknown
Right? Yeah. So that that’s somewhat different than the overshooting.

00:20:22:21 – 00:20:26:25
Speaker 4
Top or the cloud top cooling products, which are not.

00:20:26:28 – 00:20:30:00
Unknown
Technically goes-r convective.

00:20:30:00 – 00:20:33:12
Speaker 4
System products. Yeah, I.

00:20:33:15 – 00:20:55:05
Speaker 2
I don’t know what I basically what I do is I know what products are available to me or that people say they want to demonstrate. And I rather write up my plan and the Stabenow accept it or don’t accept it. To me, it doesn’t matter where the funding comes from, but maybe to others it does. So did they approve.

00:20:55:05 – 00:20:58:02
Speaker 4
Essentially your list there or did it? I know.

00:20:58:02 – 00:21:03:11
Speaker 2
It. So that’s why I said this is a tentative plan. They still need to approve it.

00:21:03:13 – 00:21:06:08
Speaker 4
Right. So this is sort of your proposal.

00:21:06:10 – 00:21:07:21
Speaker 2
Yes.

00:21:07:24 – 00:21:11:17
Speaker 4
Going for it. But you know, they have the list of like.

00:21:11:18 – 00:21:13:11
Speaker 2

00:21:13:14 – 00:21:18:02
Speaker 4
Official Goes-r products, you know, for the API and the glam.

00:21:18:04 – 00:21:20:07
Speaker 2
Yeah, etc..

00:21:20:10 – 00:21:35:22
Speaker 4
So I think somewhere in that list, you know, there are some other things like, I guess total precipitable water is on the list. Have you given that in,

00:21:35:24 – 00:21:38:15
Speaker 2
You mean, from the,

00:21:38:18 – 00:21:39:21
Speaker 4
Well, there’s,

00:21:39:23 – 00:21:44:12
Speaker 2
The right from the the new or what is it, early P algorithm.

00:21:44:14 – 00:21:49:14
Speaker 4
There’s a blended one, but then there’s also a couple other flavors.

00:21:49:16 – 00:22:04:02
Speaker 2
A, legacy product, which would, be similar to the sounder product. That information is essentially going to be a near cash flow. Goes-r. So in a way, it is that is okay.

00:22:04:02 – 00:22:08:01
Speaker 4
So yeah, so is near cash. Consider that goes are.

00:22:08:03 – 00:22:18:12
Speaker 2
There cash will be utilizing it goes our baseline product. The legacy temperature and moisture profiles okay.

00:22:18:15 – 00:22:40:02
Speaker 4
So so I guess another like G.P.S. possibility might be in the ATM as vertical profiles, so-called new cap soundings. Those are going to become available, on a website, I think, this year. Is that right, Bill?

00:22:40:05 – 00:22:41:13
Speaker 4
Nope. Still there?

00:22:41:15 – 00:22:44:15
Speaker 5
Yeah. There, at the front, remember?

00:22:44:18 – 00:22:53:01
Speaker 4
All right. Now, according to the briefing, it’s science week. All right, you know, those are the next, to come online on.

00:22:53:04 – 00:23:01:26
Speaker 5
The, ellipse. That’s that’s correct. So for the last thing, I think as well.

00:23:01:28 – 00:23:11:24
Speaker 4
Right, I think, yeah. So those two things, Bill, you might put that on your list for next year. Next to me should be already flowing all those.

00:23:11:27 – 00:23:13:05
Speaker 2
Okay.

00:23:13:07 – 00:23:16:27
Speaker 4
And with to get, we least take a look at.

00:23:17:00 – 00:23:17:12
Speaker 2
Yeah.

00:23:17:19 – 00:23:18:20
Speaker 4

00:23:18:22 – 00:24:06:01
Speaker 5
So, a couple initiatives that we talked about at Science Week there where I was getting some cursory attention to, in the Pacific and the Alaska, work panels. I mean, not not work models. So, Yeah. Yeah. There there are, low points per models. And so maybe there is an opportunity to also, I don’t know how what kind of severe weather models, specialized models or like, we can put those in a slightly different scale, but.

00:24:06:03 – 00:24:09:08
Speaker 1
Okay. Any other questions for Bill?

00:24:09:10 – 00:24:16:29
Speaker 4
Sorry, Bill. One more question. Is there anything related to, qpf or precip?

00:24:17:21 – 00:24:33:26
Speaker 2
No, this this experiment is focused on, warning operations. But as I said, there’s going to be this hydro experiment in July that will coincide with WPC experiment. So that would be looking at that sort of stuff.

00:24:33:28 – 00:24:36:22
Speaker 4
So that like flash flood oriented.

00:24:36:25 – 00:24:47:23
Speaker 2
I think, I bet there hasn’t been many details about that. And up until recently they were very unsure as to whether it would happen, but it sounds like it’s going to happen.

00:24:47:25 – 00:24:50:13
Speaker 4
Who is the lead for that?

00:24:50:15 – 00:25:00:24
Unknown
Oh, Okay, okay.

00:25:01:18 – 00:25:06:00
Speaker 2
Looks like.

00:25:06:03 – 00:25:08:27
Speaker 2
I’m not sure. Gourley.

00:25:09:00 – 00:25:16:09
Speaker 4
Okay. It doesn’t. You know, if it involves WPC.

00:25:16:12 – 00:25:28:03
Speaker 2
I think they’re going to. WPC had their experiments and they’re going to be during the same time. And I think there might be some collaboration between the two, I don’t know. Yeah, that.

00:25:28:03 – 00:25:31:22
Speaker 4
Might be something to check with. Michael.

00:25:31:24 – 00:25:40:12
Speaker 2
Yeah, I know Michael during, their experiment is planning to, demonstrate some kind of goes-r products.

00:25:40:15 – 00:25:56:06
Speaker 4
Okay. Yeah, we’re still formulating the, total lightning stuff, for the summertime. So when that gets, better posed, you know, maybe we can have another, webinar and talk about that specifically.

00:25:56:09 – 00:25:58:15
Speaker 2
Yeah.

00:25:58:17 – 00:26:00:00
Speaker 4
Okay. Thanks.

00:26:00:02 – 00:26:01:04
Speaker 2
Thanks.

00:26:01:06 – 00:26:06:21
Speaker 1
Okay. Any other questions for Bill?

00:26:06:24 – 00:26:19:26
Speaker 1
All right. Well thank you everybody and have a great day. And we’ll we’ll announce our, satellite chat for April here pretty soon. In terms of the exact date, once we know it. But, thank you for participating and have a great day.