cc  >> Cathy Vrentas: Hi, everyone.  Welcome to Wednesday Nite at  the Lab, here at the UW-Madison  Biotechnology Center.  Tonight's speaker will be Wayne  Feltz, from the UW-Madison  Cooperative Institute for  Meteorological Satellite  Studies.  He got his undergraduate degree  in Ashland, at Northland  College, and his graduate degree  here at UW-Madison,  in Atmospheric and Oceanic  Sciences.  Currently, he's the leader of  the Satellite Nowcasting  Aviation Applications team, as  well as part of the NASA funded  Advance Satellite Aviation  Weather Product Effort at the  Center for Meteorological  Satellite Studies.  He'll be talking about this  research today.  But briefly, his work directs  research to use satellite  products to improve the  forecasting of aviation weather  hazards.  So please join me in welcoming  him to Wednesday Nite at the  Lab.  (applause)  >> Wayne Feltz: Thank you.  It's always a nice opportunity  to actually come out to the  public and discuss how your  taxpayer money is being spent in  the area of taking satellite  data and trying to help out  aviation weather, and actually  predicting and nowcasting  hazardous weather for pilots,  commercial or general aviation. 

 We've been specifically focusing  on thunderstorms, turbulence and  volcanic ash, here at the  University of Wisconsin.  There are several other  universities that are working  with us.  The University of  Alabama-Huntsville, MIT Lincoln  Lab is actually working with us  along with the National Center  for Atmospheric Research out in  Colorado.  So what I want to do is overview  what our team has been working  on the last seven years now, and  where we're actually taking  satellite data, turning it  around into decision support  product and making traction in  helping out the aviation  community with the nowcasting  problem and forecasting aviation  hazards, meteorological hazards  primarily.  So, what I want to focus on  first is outlining the  National Aviation Transportation  System now and into the future.  Can everyone hear me okay?  No? Louder? Okay.  The National Aviation  Transportation System currently,  and into the future, where we're  going, where the FAA is going  with the Transportation System.  What are some aviation hazards  that are encountered.  How can satellites help out with  detecting thunderstorms,  turbulence and volcanic ash, and  a summary of this work.  So who am I?  I'm a weather geek,  aka weather-weenie. 

 I knew I wanted to be a  meteorologist since I was three  years old.  Somehow, I found employment  doing that.  It's rare and I never take it  for granted.  I moved to Brownsville, Texas,  from Stevens Point, Wisconsin,  when I was ten years old.  And I still have pictures of  myself plotting Hurricane Allen  coming into the Gulf of Mexico  and heading toward the Texas  coast when I was ten.  I have my weather scrapbook.  And actually, just before  landfall, we left our home to  escape its path.  I went to undergraduate school  at Northland College in Ashland,  Wisconsin, and moved back from  Texas back to Wisconsin.  I came here to graduate school  in 1991 and found a way of  staying.  I currently work at the Space  Science Engineering Center, on  the second floor. 

 And currently, I'm an Assistant  Scientist, principal  investigator, working in this  area.  I have some past weather  hobbies.  Now that I have small children,  I don't storm chase as much, but  I am a cooperative weather  observer.  Why are we worried about using  satellite data for the zero-six  hour time range when it's  helping out aviation?  The aviation community demands  high time and spatial  resolution.  Past satellite data didn't have  that.  Even 20 years ago, it wasn't  looked at.  It was an afterthought.  It's only been in the last ten  years that satellite data has  been used and thought about  being used for aviation weather  nowcasting and trying to help  out with getting aircraft from  point A to point B.  Aviation weather hazard  information is relevant only on  very short time scales.  Geostationary, which are our  current GOES satellites, which  you see on the weather channel  and local forecasts, the visible  and infrared imagery, provide  high time resolution, but do not  provide data at high latitudes  where great circle commercial  aviation routes are common. 

 So the polar routes are not  covered by geostationary.  There are polar orbiting  satellites also.  They do not provide the time  resolution, but they provide  higher spatial resolution, and  also cover the polar areas which  have a lot of volcanic ash  issues.  Finally, satellite data provide  the primary information over  data sparse oceanic arctic and  high terrain regions.  The current system is not  performing adequately.  If you look at the newspaper,  especially during the summer,  there are a lot of delays.  If you've flown on a commercial  airline, you've probably been  delayed.  Demand is already high in  congested markets, and the air  transportation system does not  utilize current available  technology to support aviation's  role in a national economy, or  address aviation's environmental  impact.  In fact, if we go and look at--  wanted to know on the NASA--  what's your cost benefit  analysis.  If you're doing  research, how much money are you  saving now. 

 It wasn't like that before, but  now it's really part of the  proposal process in a lot of  ways.  Aviation accounts for 11 million  aviation-related jobs,  1.2 trillion in the economic  activity, and then  2.5% contribution  of Gross Domestic Product.  It also adds $61 billion  to the US Trade Balance,  to put it in perspective.  This is a new concept that was  introduced about three years ago  now.  This system is called Next  Generation Air Traffic Control  System, or Aviation  Transportation System.  And it's not just weather.  It's trying to impact aviation  from the way that aircraft fly  from point A to point B, trying  to mitigate issues at airports,  not just due to weather, but  even the surface landing  conditions, moving baggage  through the airports, and that  sort of thing.  And the only part we're involved  in is this little satellite  circle up here.  These are all the agencies  involved, it's about every  federal agency in the federal  government, all working together  to improve the air  transportation system.  And the idea is, we're right  here. 

 Here's basically, the air  traffic management efficiency,  which is in red and green here.  This is the expected result if  we just do the business as  usual, how we're working today,  versus figuring out better goals  to keep efficiency high.  That's sort of-- These are some  high-level overview slides.  I'm kind of setting the stage  for talking about why we're  going to be using satellite  data.  The idea then is to improve  efficiency and capacity.  Today's National Airspace  Transportation System is  basically super highways of  aviation instead of point to  point transportation.  That is, you want to go from  Atlanta to Chicago, in the  future, you'd go directly there,  you wouldn't take a designated  route or highway.  That's only going to come  through a lot of coordination.  Safety is always the number one  issue.  The transition to this next-gen  philosophy has already begun. 

 This is a huge endeavor.  I'm really involved in a small  piece.  There's actually a Web site you  can go to.  If you type NextGen into Google,  you can get into these slides  and take a look at what they're  looking at.  The area we're interested in is  the weather arena.  So, you've got a plane that  takes off on an airport.  You have to worry about arrival,  alternate forecast weather or  flight winds.  When they're about to take off,  thunderstorms, lightning, cross  winds, wind shears, freezing  precipitation, visibility,  icing.  While they're in route, they  have to worry about  thunderstorms, where's the jet  stream or the highest winds,  volcanic ash, turbulence, icing,  winds and mountain waves.  I'll explain what some of these  terms are and how we view them  from satellite. 

 Again, landing is another--  listed issues to worry about.  Then, post-flight observed  weather-- are actually a part of  this.  We're worried about the point to  point.  The pilot isn't so much worried  about what type of weather, but  is his route blocked.  What's his chances of his route  being blocked due to anything.  They don't really want to know  the weather side, they just want  to know, can I get to point B,  what's the risk.  And that's sort of the future.  So what are the primary aviation  weather hazards.  Number one is actually  convective weather and strong  storms.  It's the number one cause of  delays and cancellations. 

 Huge loss of money.  Turbulence is number two.  It's the number one safety  hazard at cruise altitudes.  It's probably the highest amount  of money for litigation,  commercial airliners being sued,  flight attendants hurting  themselves walking up and down  the aisle, or people just not  really buckled in, say you have  a long flight and they're  sleeping across three seats and  over the ocean, and they get a  terrible bout of turbulence,  they can be thrown about the  cockpit, they actually get hurt.  It's not so much fatality  driven, but just hurt.  Icing is on ground and in  flight.  There's even some hazards, of  course, you've heard about some  terrible icing accidents, where  the wings build up with ice and  the airplane cannot fly.  Visibility is an issue.  And finally, volcanic ash  and gas.  It's rare, but potentially  catastrophic. 

 There's been some very, I'd say  a handful of near misses, where  a commercial airliner has almost  gone down due to volcanic ash  and gas, and losing their engine  power.  So, aviation weather has real  implications.  This is actually, maybe, I don't  know how easily you can see this  from the back, but this is ice  accretion on the windshield and  on the nose of an aircraft.  This is an aircraft that was too  close to a volcano in Italy, and  actually volcanic ash was  deposited on it before they  could take off.  It pretty much crippled the  aircraft.  And this is an issue where  something is wrong with this  picture.  And it's due to turbulence.  The aircraft had lost part of  its wing and an engine.  So the first phenomenon I want  to talk about is thunderstorms.  I've got to try to stay away  from the acronyms, convection,  convective initiation. 

 I'm trying to back off on the  terminology.  I try to anti-acronym these  slides as much as possible.  Let's see.  So, aviation summertime delays.  If you go look at the months,  January, this is through  December, and I think this-- Oh,  these are off, actually four  different years.  You see a natural peak in delays  in the summertime.  That's all driven by aviation.  It's not so much aviation across  the United States, it's aviation  particularly up and down the  east coast and the northeast.  It can mess up the routes all  the way to the west.  I'll show you an example of that  through an animation in a little  while. 

 But basically, you can shut down  Laguardia due to thunderstorms,  you can have delays  in San Diego.  They call them convective  delays.  And it may not mean that that  aircraft that takes off from San  Diego or Chicago is actually  going to encounter  thunderstorms, but it means that  the airplane that was supposed  to go from Chicago to Laguardia  is delayed.  So they can't get in.  The airlines can still call that  a convective delay in San Diego.  They have very loose terms for  what they call a convective  delay.  And that's how they bend them.  So it really has implications  for the whole transportation  system.  § §  So a little bit of humor  with music.  This is Aerosmith. 

 But this is an example of FedEx  in Memphis, and what happens  when thunderstorms impact the  Memphis airport.  I'll play it.  You pretty much see these FedEx  flights flying in.  What happens is, at night the  airport shuts down and FedEx  owns it, and all the planes go  into Memphis.  And that's what's happening  here.  They rearrange their packages  and they take off again.  UPS' hub is Louisville.  They do the same thing there.  But when you have a thunderstorm  complex come in like this, you  see the planes can't get into  the airport.  And every time one lands, it's a  million dollars a piece to the  company, whenever it lands at a  different airport. 

 So you can start counting the  money that that impact has, just  for one night, with  thunderstorms over Memphis.  § §  So examples of aviation delays,  for instance, in 2007.  These are the top 15 delays in  2007.  And what we have here is January  '07 through the summertime here,  and again into the wintertime.  And you see the cluster of  delays in the summertime here.  And what do the radars look like  on those days?  Here's the northeast corridor.  I'm not sure if everyone can see  that, but those are  thunderstorms there, the  northeast thunderstorms.  The northeast thunderstorms.  The northeast thunderstorms.  It's again, the delays that are  encountered up here in these  airports have huge implications  across the whole air  transportation system. 

 Another animation, without  music.  This one, again, is showing  Laguardia with radar.  I'm not sure that is Laguardia,  in fact.  It's basically showing-- I think  that is.  The radar coming in with the  thunderstorms.  You see what happens to the  flights all the way off to the  west.  They're forced to circle,  because of thunderstorms over  Laguardia.  This will continue.  You see another line come in  here.  The same thing happens. 

 In fact, you can actually see  some of these aircraft which  were meant to come into  Laguardia have to go over  Wisconsin and circle over  Madison, for instance.  Eventually, some of them will be  low on fuel, so they'll have to  land in Chicago.  That was real data.  That was real aircraft.  It wasn't just a video game.  Overshooting tops.  What if we look at from the  satellite to help out with this  issue and this problem?  One of the things we can look  at, and we can see from space,  are overshooting tops.  And I'll explain.  That's basically a domelike  protrusion above a cumulus  nimbus anvil, representing an  intrusion of updraft.  What it is, is a big  thunderstorm. 

 You've got an updraft coming up  through that thunderstorm, and  you basically have a higher  cloud that looks like this.  And you've see this, probably.  Some of you probably have seen  huge thunderstorms, and you see  a bevel of a cloud on top of the  anvil, if the storm's far enough  away.  That's called an overshooting  top.  So, it's an isolated cold spot  on top of a very severe or heavy  thunderstorm.  What can you do with that  information?  Well, if you know where an  overshooting top is occurring,  it tells you that you do not  want to fly underneath that  overshooting top, because  there's a strong updraft.  It also tells you that you're  very likely to get cloud to  ground lightning.  So if you're under that  overshooting top, and you're on,  say a golf course, you might  want to be inside.  And it's an inference of  turbulence.  An overshooting top means  there's probably turbulence  generating, emanating away. 

 And I'll show you why I'm saying  all this, with some supporting  data, after this slide.  It probably also means that if  you see an enhanced V signature,  which I'll show you later, there  could be severe weather  conditions at the surface,  affecting people.  So, I'm not sure how well this  is showing it, but this red area  here, is basically temperature.  Red being cold.  And as you head to blue, it's  warmer.  It's kind of the opposite of  what you'd think for the scale.  But what we're trying to  demonstrate here, this is a  visible image, like you'd see on  a local TV channel, with an  infrared image, which also they  show on the local channels,  mapped on top of each other.  So basically, you get the idea  of the reflection from sunlight  with the cold temperatures of  the thunderstorm mapped on top.  And what this allows you to see  is this red V-like structure  here, which looks very vivid on  my screen, but I'm not sure how  vivid it looks there.  That's called an enhanced V. 

 These signatures have been seen  for a long time.  I think the first papers I saw  on these things were in the late  1970s.  This isolated red dot right here  is the overshooting top.  Usually associated with these  overshooting tops enhanced Vs is  a warming in the top of the  thunderstorm.  >> What does that mean?  >> Feltz: It means that  basically you've got an anvil,  which is this big flat cloud  here.  And you see an isolated cloud or  bump on top of that anvil.  That's the overshooting top.  It's, again, this bump.  Here's the anvil from the  thunderstorm.  And it's this bump that's  overshooting. 

 It's basically overshooting the  top of the thunderstorm, which  is usually the anvil of the  thunderstorm.  And I'll show you some more  examples of that.  I'm not going to go into the  details of an algorithm.  We have an objective way of  determining where these isolated  cold spots on top of these  anvils, or these large  thunderstorm complexes.  If we know a location from  satellite data-- And one thing I  want to also emphasize before I  jump to that is, the  overshooting tops are showing up  as these dots in the visible  imagery.  Basically, we're looking down  from space, and we're looking at  the reflection of sunlight  coming back up.  And overshooting tops are  updrafts, are forcing the clouds  higher than the anvil.  Updrafts are these large columns  of air being forced upward due  to the thunderstorm, and the way  the thunderstorm is working.  These measurements right here  are actually United Airline 757  aircraft, a commercial aircraft,  real passenger airline data.  But it's objective turbulence  reports. 

 It's a way that we can actually  now, instead of just listing  pilot reports, we actually are  getting objective turbulence  reports from United Airline  aircraft.  We have five years' worth now.  That's helping us with the  satellite data.  Now we know exactly where the  turbulence is occurring, and we  can actually look at some  relationships between where the  turbulence is occurring and  where we see lightning data, and  where we know the overshooting  top is.  There's some figures I'll show  you next.  It's really beautiful data.  Without this, it's the key  thing, it's our treasure chest.  Without this, I don't think we'd  be where we're at with what we  can do with satellite data and  overshooting top, and looking at  the dangers of these bigger  thunderstorms.  Here's an example, again, of an  overshooting top in the visible  imagery.  This is actually from the  International Space Station. 

 That's a picture taken from the  Space Station.  High resolution, visible  imagery.  Now, if we look at a satellite  of this same thunderstorm, this  is basically the temperatures at  the top of the thunderstorm.  And that coldest dot right there  is the overshooting top.  It's the coldest spot on the top  of the anvil.  Again, this is what it looks  like from the weather satellite  versus the International Space  Station.  You see the difference in how  that same thunderstorm looks.  So if you know where an  overshooting top is, an isolated  cold spot, meaning that there's  a strong, that's probably the  strongest area of that  thunderstorm, from space, you  can basically look at that  overshoot, which is the distance  from the overshoot to the  frequency of lightning.  We actually have lightning  detection arrays across the  nation now, so we know where the  cloud to ground lightning is  occurring.  So we have these arrays actually  in certain areas of the United  States. 

 But if you see an overshoot,  what's your chance of getting a  cloud to ground lightning  strike?  If you see an overshoot, the  solid lines are, as you get  closer to that overshoot, your  likelihood to experience a cloud  to ground lightning strike.  And the blue to green to red is  a temperature of between, the  blue is 205 or 210 Kelvin, so  that's the temperature of that  overshoot.  As you get colder, that  overshoot actually shows a  higher likelihood of producing a  cloud to ground lightning  strike.  So if we know where the  overshoot is and we know the  temperature of the overshoot, we  can infer anywhere on a  satellite image, all the way to  South America and the ocean,  what the likelihood of a cloud  to ground lightning strike is.  Very important information when  you don't have radar, when  you're not in the middle of the  United States where we have  radar and we've got this dense  network.  Most of the world doesn't have  that.  And what we've learned from our  dense network of data over the  United States, we can then infer  on satellite imagery across the  whole image, at 15-minute  resolution, which is the time  resolution in the satellite.  In turbulence land, if we look  at how close we are to the  overshoot, this is zero  kilometers, out to 100  kilometers.  And this red line shows the  likelihood of experiencing  turbulence as you get closer to  an overshooting top.  You see that there's almost a  40% chance of experiencing light  or greater turbulence. 

 In turbulence land, 40% is a  very, very high chance for  turbulence.  It doesn't act the same way as  say, your chance for  precipitation or something.  You can have a very, very high  chance of getting turbulence in  an area, but the turbulence that  you experience has to relate to  the size of the aircraft.  So it has to be a small  disturbance in the atmosphere.  And we're trying to infer from  satellite data that's four  kilometer pixels, or one  kilometer pixels.  So we can only give what's the  chance for turbulence being in  this area.  Let's see.  The other thing we're looking at  is convective initiation, or  rapid thunderstorm development.  What we're trying to do is  monitor how fast the cloud tops  are cooling by looking at  infrared imagery from image to  image.  If we can do that, plus monitor  the cloud top water phase  transitions, we can actually  retrieve the top of cloud water  phase state. 

 Is it warm water or mixed phase,  supercooled water or ice  glaciation cloud?  We look at the time change from  warm water to mixed phase to  glaciation, and also look at how  fast that thunderstorm is  cooling to infer, are we seeing  a rapidly growing thunderstorm  in this cumulus cloud that isn't  occurring in the next cumulus  cloud.  And what's the goal?  Well, it's a pre-radar nowcast  of imminent convection or  imminent thunderstorm formation.  Before we even see it on the  radar, we're getting up to 45  minutes of lead time from the  satellite data.  It's an important gap though for  aviation, because they want to  know routing aircraft into  airports, where those  thunderstorms are going to form,  and get as much lead time as  possible to figure out other  possible routes, so it doesn't  impact the transportation  system.  So, what are we doing when we're  talking about convective  initiation?  Essentially, what we're doing is  looking at how rapidly, for  instance, clouds are cooling  here or here.  This is actually degrees Kelvin  in 15 minutes.  So, another way, if you go from  blue to yellow to red, that's  faster cooling in 15 minutes.  This one probably right there is  cooling the fastest.  There's a little bit of red  there.  What we do is make a decision. 

 Is it going to imminently turn  into a thunderstorm, which is  green, or is it just likely, or  is it just possible.  So we do have a condition on  here.  And what this image is saying,  and we actually went to the  storm prediction center, and  they're looking at this product  now in real time, what is this,  for instance, this green that  says there should already be a  thunderstorm there on the radar.  The red is that it's likely to  occur.  And if you go look at radar for  that same time, there's nothing  on the radar on the Texas  panhandle, even though there's  an indication from satellite  that something should occur.  So, in essence, what we're  trying to do, at the time of the  nowcast from the satellite, you  see the radar fill in with  thunderstorms.  I think this is 21-UTC.  So this is time up here,  2018-UTC, don't worry about the  timescale if you're not familiar  with UTC.  But basically, this is a 2015  time step at the solid image.  This is a little time after,  actually, the satellite  prediction from the radar. 

 And you see the thunderstorms  form in the area that the  satellite stated it would form.  So we're actually applying this  in real time, and sending this  data to the local National  Weather Service in Sullivan, and  also to the Storm Prediction  Center down in Oklahoma.  This is a future--  This actually was just developed  in the last year,  this algorithm.  And it's really taken on  traction.  This is the sort of aviation  products we're working on, and  cutting edge research, and  trying to figure out what we can  do, even with our current  satellite, but also figuring out  what we're going to do with the  future satellite which will be  launched in 2016.  I should slow down here.  Is there any questions?  It's supposed to be interactive.  (laughs)  (inaudible)  No, actually because the data we  have is only cloud to ground  over the whole United States, we  only know that statistic.  There are four ways in the  United States that do cloud to  cloud.  One is located in Huntsville,  Alabama. 

 One is in Florida at the Space  Flight Center.  One is over Washington, DC.  And the third is in Oklahoma.  But these are small, maybe 3-D  lightning detection, and they  can go cloud to cloud.  But they're very limited in  spatial coverage, so it's hard  to make the relationships I just  showed you here, over a lot of  cases, to come up with  statistics we trust.  So this is just cloud to ground  at this point.  (inaudible)  Actually, mainly for tarmac  evacuation, like for FedEx and  UPS, getting people off the  tarmac, they want to know up to  30 minutes ahead of time if  there's any cloud to ground  lightning strikes.  But not so much for the  aircraft.  Aircraft are pretty immune.  I mean, there was this one case  off of South America, on a  Brazilian flight that went down  that they haven't found the  black box for. 

 And the first thing that was in  the paper was that it might have  been struck by lightning.  But aircraft get struck by  lightning, commercial airliners,  all the time.  They're pretty insulated now, in  the engineering, to protect the  fuel, and all that.  And actually, in what they  found, they don't think it was  lightning now.  It was other issues.  They still haven't quite figured  out the mystery.  It's pretty much a whole long  list of bad things went wrong at  the wrong time.  Anyway, so cloud to cloud is  probably more important for  aviation, but even with that,  most of the aircraft are pretty  immune to lightning strikes, at  least the commercial airliners.  I'm not talking about smaller  general aviation.  (inaudible)  Um, yeah, that's true. 

 We haven't related the lightning  to turbulence.  We've just been relating the  overshooting top to turbulence  or the overshooting top to  lightning.  Two separate, but we've never  cross correlated the turbulence  to the lightning.  So that's an interesting thing  to look at.  This is another case where we  had indication of imminent  thunderstorm development.  And at the time, there was  nothing on radar.  In fact, in this case, there was  a 33 minute lead time before  there was indication on the  radar of a precipitation array.  In fact, this cell grew into a  supercell and dropped a huge  tornado in Kansas and Nebraska.  (inaudible)  I think mainly because of the  time and money spent by the  commercial airline industry in  making them immune.  There's a lot more fuel on those  commercial airliners, and are  probably more likely to have a  catastrophic failure due to a  lightning strike. 

 They threw a lot of money in  that early, because I know in  the 1950s, that was a huge  issue, lightning strikes.  In fact, I had done some reading  in the past.  Basically, the lightning strikes  then did cause problems.  And they spent a lot engineering  money on trying to neutralize  that as a problem for the big  commercial airliners.  There's so many different types  of general aviation aircraft, I  don't know if there's a  one-size-fits-all sort of  solution to protecting all the  GAs, so I can't really speak  about that.  I just know the commercial  airliners are relatively safe  when they get struck by  lightning.  In fact, I've never been on  airlines, I've done a lot of  flying, but I've never been on  an airliner that has been  struck.  But I know lots of people I've  talked to that have been on  airlines and know they've been  struck, but nothing happened to  the aircraft.  And I'm not an aeronautical  engineer, so I'm out of my  league.  Well, when we're passing this  convective initiation of  thunderstorm product out,  forecasters were looking at it. 

 I was going to do a little  animation here.  But what they see, in real time,  they would be getting the most  recent image.  They would see an indication  such as the red flag there.  Then you see the thunderstorm  form.  When that red flag appears, that  red spot-- And I can't really  stop this video.  I wish I could.  That's 33 minutes before radar  detected the precipitation.  That's the key.  It's adding a gap.  The weather service office  really wouldn't care about this,  probably, if they've already got  radar and it wasn't adding  anything. 

 But this is adding something to  the lead time on the forecast of  convection.  So, 33 minutes is pretty  significant.  And pictorially, here's what  we're seeing from the satellite,  is this small cumulus cloud  growing rapidly.  That's this infrared cooling,  which the infrared imagery, most  people see every day, again, on  the local TV channel, for the  nighttime imagery.  That's infrared imagery.  Before precipitation starts to  occur, before you actually get  the rain process going in a  thunderstorm, you actually are  seeing rapid growth by  satellite.  And that information then is  being passed into a decision  support algorithm.  Basically, it's an algorithm  that brings in radar, that  brings in satellite, that brings  in anything that can help the  terminal forecasters with  knowing if thunderstorms are  going to develop or not.  So when you add satellite data  into this sort of system, so  without having satellite data,   what's the precipitation  forecast in this system, here's  what the field looks like.  Here's basically the real time. 

 So radar at the time the  forecast is made looks like  this.  Here is the forecast without  satellite.  When you add the satellite  information and the cooling rate  and the convective initiation,  you actually add in a lot of  what the radars are showing, by  actually the GOES information  into this.  So, basically, this is what they  use for decision support on  forecasting thunderstorms up to  an hour in advance, so they can  redirect traffic routes at say,  O'Hare Airport, for instance.  And again, we're just one piece.  Weather radar is included in  this lightning.  Satellite is sitting over here.  What we're trying to do is use a  piece.  A lot of these pieces have been  used for some time and have some  heritage.  Satellite has been a relatively  new thing to look at, to go help  in this problem, and that's  basically what we've been  working on. 

 All right, so now I talked about  convection.  What about turbulence?  How many people have experienced  turbulence on a flight?  Okay, how many people think that  when the pilot gets on and they  say, "Everyone buckle your  seatbelt, we're probably going  to encounter turbulence," that's  coming from a forecast model?  Good.  That's actually information  coming from pilots that have  just flown through turbulence  ahead of them.  And that shouldn't be the way  the system works.  But that's the way it works  right now.  So, the aircraft themselves are  the in situ observation of the  phenomenon they're trying to get  out of the way of.  So that's not a good situation  at this point, but that's all  they have.  The forecasts aren't very  reliable for turbulence.  And so, the way turbulences are  being forecast now are just by  using numeric weather prediction  models.  The idea is to us that, plus  satellite data, plus radar data,  plus this new objective  turbulence data from aircraft  that are already up there--  although again, that means that  they're flying through it-- to  improve the turbulence nowcast. 

 What's the one-hour forecast for  turbulence?  And let's get that information  to the cockpit so the pilot can  see there's turbulence, through  some graphical means, ahead of  them, and they can route around  it.  Yes?  (inaudible)  That was a commercial claim,  but I'm not sure about the type  of plane.  Maybe there's someone here from  aviation weather?  Okay.  (inaudible)  It is an older picture, yeah.  (inaudible)  I don't know.  It did, but I don't know.  I wouldn't have wanted  to be on the plane.  (inaudible)  There you go, aerodynamic.  (laughs)  Turbulence is a really tough  problem.  And it's not low hanging fruit. 

 The problem is there are  multiple sources that generate  turbulence.  Many people, probably in the  paper, have heard of clear air  turbulence, where turbulence is  encountered and there's no  cloudiness.  It's just encountered.  Well, that can be generated from  thunderstorms, which I described  before, these overshooting tops  and updrafts.  That core of a thunderstorm can  generate turbulence.  There's in-cloud turbulence just  from the updrafts themselves.  There's mountain wave  turbulence, which is just the  wind blowing over mountains.  And I'll show you illustrations  of that from the satellite  imagery.  There's convective.  There's boundary layer  turbulence. 

 There's terrain induced  turbulence.  But the idea is, how do you take  a satellite data that, at its  maximum spatial resolution, is  four kilometer resolution, and  infer something that's the size  of an aircraft, a disturbance  the size of an aircraft?  And the answer is you really  can't.  You can't say that the  turbulence will be there and the  aircraft will fly through it  from satellite.  But we can at least indicate  that we have higher confidence  that turbulence will occur in  this area of the image than in  another area of the image.  And that's really about the best  we can do from satellite, at  this point, with the spatial  resolution we have.  There are some military assets  up there that have much higher  resolutions that we don't have  access to.  They're probably forging the way  ahead in helping us, but all we  have right now are the civilian  assets, which are the GOES and  polar satellites right now.  This is an example of empirical  turbulence data, also known as  EDR, eddy dissipation rate.  What this is, is that United  Airlines 757 aircraft are  sending their navigation system  information to the National  Center for Atmospheric Research,  who's applying an algorithm to  calculate what turbulence  they're experiencing in every  minute.  Even when there is no  turbulence, they're actually  figuring that out. 

 What we're getting is a very,  very useful data set to help  take satellite data navigated  over this data and figure out  some relationships and what we  can do with satellite data.  And actually, I think Southwest  Airlines is on board now.  Delta has bought into this, too.  So three airlines will actually  be providing their navigation  data to NCAR for them to go and  calculate turbulence with this  eddy dissipation rate.  It's very valuable.  The pilot reports, by the time  they report that they've gone  through turbulence, they're  worried about their passengers  first.  So they're calling back, making  sure everyone's all right.  By the time they report it,  they're 100 kilometers upstream.  Then you've got a report here,  you're trying to look at  satellite data over here, and it  just doesn't work very well.  We're trying to understand what  we're seeing in the satellite  data. 

 This has actually been a  treasure chest for us.  We now have five years worth of  this data from 757s.  Delta, again, just came on  board.  Here's some Delta information.  And now that Northwest and Delta  have merged, it's going to be  pretty much covering most of the  southeast and central part of  the United States.  There's even a new type of data  coming that's Continental  flights.  And I think, yeah, they're on  board.  I don't understand this data  quite as much, and I don't have  access to it, but there are  other empirical or objectively  measured turbulence data sets  that are coming out now, too.  (inaudible)  That's part of the problem, and  why it's not low hanging fruit.  Even if we say there's a high  probability of turbulence in  this location, and an aircraft  is going through it, it depends  on the scale of the disturbance  in the atmosphere. 

 Usually, turbulence is kind of a  roll.  If that roll is big enough, that  plane may just go through like  this, and it's not a problem.  But if that roll ends up being  the size of the aircraft, it  could disturb it in quite a  harsh way.  And a lot of times, these things  last probably, maybe a couple  seconds, maybe ten seconds at  the most.  So really, just a turnover in  the atmosphere, and the timing  is, the aircraft size has to be  about the right size to be  disturbed.  So it's a tough one.  It's not something that even  radar may be able to tackle down  to a point where you can say  point A, and location, and say,  you know, the pilot is going to  fly through there, they almost  need a sensor on the front of  that aircraft to see what's in  front of them.  You have to be able to react to  it on a very small time scale.  But what can we do from the  satellite?  When I first walked into NCAR  five years ago, we showed  satellite data, and they said,  we're not even going to talk to  you.  There's no way a satellite is  going to help turbulence. 

 It's a scale argument.  You've got four kilometer  imagery, how are you supposed to  detect something the size of an  aircraft in a clear sky?  We said we took a shot at it,  and here's where we're at right  now.  And they're actually working  with us right now, and I'll  explain the history as we go  along.  But this image up here is a  satellite image from MODIS.  It's a research satellite from  NASA, a very high spatial  resolution.  I think this image is 500 meter  resolution, spatial resolution.  This is the water vapor image  for this same scene.  If you look in the visible, you  see a few clouds over the Rocky  Mountains.  This is Colorado.  But if you look in the water  vapor, you see this very  disturbed area. 

 And that's actually an effect  due to mountain wave generation.  So, what can we do when we see  these ripples, these wave-like?  In the water vapor imagery, you  see these wave like features.  The first thing we did was we  relate it to the actual  turbulence reports.  In this case, it was pilot  reported turbulence, because we  didn't have access to EDR data  at the time we were doing this  research.  And basically, pilots report  turbulence on a scale of 1-8.  I've never seen an eight.  I've seen 1-7.  Anything between four and five,  you probably don't want to be in  the aircraft.  You see these fours here.  That means they've experienced  moderate to, you know, heading  toward the severe side of  turbulence. 

 There's a three.  Over here, there's a six here.  It's kind of hard to tell on  this imagery.  The red circles are the severe  reports.  So this is basically stating,  using pilot reports, that when  we see these wave-like features,  we're seeing a lot of  turbulence.  When these white features  disappear, the turbulence  reports drop.  And that's the relationship,  very crude, very qualitative  to start, but it gave us a lead.  Maybe there's something in this  water vapor imagery, and this  pattern, that could help us.  So then we used MODIS water  vapor imagery to identify  mountain waves.  Again, that's these ripples. 

 The clear sky doesn't really  show you.  You really need the water vapor  imagery.  And we found that mountain wave  signatures were observed in  water vapor imagery over the  central Rockies for 68% of MODIS  overpasses.  When the mountain waves were  both apparent in MODIS and GOES,  which is our current operational  imagery over the eastern United  States, which has four kilometer  resolution, so one kilometer of  spatial resolution, so it's a  tougher thing.  The spatial resolution isn't  quite the match to the waves.  But if you see them in both of  those, you're basically light or  greater EDR turbulence is either  1.5 or 2.4 times more likely  to occur than on days without  waves.  So this is basically stating  that if you see these waves  on an image, and you're on an GA  aircraft, or general aviation,  and you're going to take off  from an airport and you're going  to fly over the Rockies, if you  see these waves on a satellite  image, you can pretty much  expect that you have a high  likelihood of encountering  mountain wave turbulence, just  by looking at the satellite  image.  I've actually gone to some  aviation clubs and talked about  it more generically.  They're not worried about the  science side and the algorithm  side, but it's just looking at,  can you interpret the features  and come up with a good idea of  what you'd expect to encounter,  just by looking at satellite  imagery.  Here's an example, again. 

 These waves don't quite show up  the best here.  But these are the Rockies again,  and these are all the pilot  reports, let me make sure.  No, this is EDR, the objective  United Airline reports of  turbulence, whenever the waves  that occur on these two days.  And you'll--  (inaudible)  Eddy dissipation rate.  So this is the algorithm that's  run on the navigation system of  these 757 aircraft to determine  objectively, is there turbulence  report, is there no turbulence  report, is it a light turbulence  report, a moderate or a severe.  So on these two days, you see  that relationship again.  We even get these mountain waves  over the Appalachians.  So it's not just what you see  over the Rockies.  You see these features there,  also.  And we've done some work and  research on now trying to build  pattern recognition algorithms,  so that when we see these  ripples, we can basically mask  out an area on the solid imagery  that says we're at a higher risk  of turbulence on this day than  on the day before. 

 And actually, this information  is being fed into the graphical  turbulence guidance product,  which is a forecasting product  that the aviation weather center  has for pilots to use, that  right now, the numeric weather  predictions is being put in  there.  But satellite data is one of the  things that will be put into  this.  I'll show you an example.  That's what that interference  pattern looks like close up,  that generate the mountain wave  and water vapor imagery.  If you take this objective  turbulence data from United  Airlines, and basically plot all  the turbulence reports, this is  an example I think from  November, 2005, for one month.  This is longitude at the bottom.  And this is the latitude of  Denver.  So basically, Denver Airport is  right here.  What you're seeing, this color,  all the descents and ascents of  the Denver Airport.  The United aircraft 757  turbulence data is cutoff at  about 20,000 feet in altitude,  mainly because they get too many  false alarms when they start to  go in circles and get in the  boundary of down low. 

 They really only want to look at  upper level turbulence.  But you do see a maximum of  turbulence reports, especially  black or severe reports, on the  foothills, rather than over the  plains.  And we're thinking when we look  at the satellite imagery, is  this is a phenomenon called  downslope.  Mountain waves are generated  over the mountains, like this,  and you get rapid downslope  winds.  And it just so happens that the  Denver Airport was located right  outside of Denver, actually to  the east of Denver.  And on the days when we see  these downslope winds, we gets  lots of reports of severe  turbulence.  There's probably some  information in a way we can  objectively, from water vapor  imagery, help with the downslope  issue and the warning of the  downslopes.  So that's another piece of  research we're looking at right  now.  This is triple pause folding.  It's very technical. 

 It's another source of  turbulence.  It basically means the upper  part of the atmosphere turns  over.  It's another thing we can detect  from satellite, is what are the  zones or locations where we get  these triple pause folds or  upper air mass transitions.  It's way high up in the  atmosphere.  But they've been known to cause  lots of turbulence.  And we can actually look at  water vapor imagery, again, and  detect where the zones of likely  turbulence will occur.  So again, turbulence is  generated by mountain waves, by  upper level features, where the  atmosphere is turning over, and  thunderstorms.  And we're looking at different  ways we can take satellite data  and infer the possibility of  turbulence.  Another thing we're looking at,  and I think I'm not going to get  real into this slide too much,  but it's rapidly expanding  thunderstorm tops or anvils.  This is time. 

 So as this thunderstorm, which  is in red here, it's a very cold  top of a thunderstorm, as you  move forward in time, you see  this anvil get bigger and bigger  and bigger.  And what we're seeing in the  imagery are these little  striations called transverse  bands.  So around these huge  thunderstorms, we get these  striations of thin cirrus, or  high level clouds.  The correlation between that and  aircraft flying through them is  pretty obvious.  You know, no turbulence, the  white are no reports; and then  turbulence, turbulence,  turbulence, turbulence,  turbulence.  The same thing here.  Turbulence.  You get through those bands,  nulls.  And again right here.  There's a 90% chance, if you're  an airline going through these  features around a thunderstorm,  these real thin bands, there's a  90% chance of experiencing  light, moderate or greater  turbulence. 

 That's another relationship  we've found, a quantitative  relationship, by relating what  we're getting from United  aircraft to satellite imagery.  Very important for even general  aviation, if they see these  features, you can see them even  out your cockpit window.  If you're flying high enough,  you're going to run into this.  This is the statistic again of  when we looked at transverse  bands and what was the chance of  a pilot experiencing turbulence  by going through that feature.  So, what's the flow chart for  this?  We're developing all these great  satellite products, but we'll  also model data.  And the in situ is the objective  turbulence data.  All these satellite diagnostics,  or satellite indications of  turbulence will actually be fed  in and integrated together, and  put in this global graphical  turbulence guidance.  We already have this Graphical  Turbulence Guidance product at  the Aviation Weather Center.  They want to fold in satellite  data and radar data.  This is not a stand alone  product the satellite is  producing. 

 We want to help figure out the  problem, fill the gaps.  And eventually, what happens  from the National Center for  Atmospheric Research is that  product goes and gets  disseminated out to pilots, to  terminal forecasters via the  World Wide Web, and even to the  cockpit.  I had to put that little  airplane in there.  And basically, the idea in the  future is that that gets fed  into this NextGen data cube,  which is this weather cube for  the future.  Basically, everyone is going to  go to this, all the agencies,  including the National Weather  Service, will go to this weather  cube of data, which will have  the most recent up-to-date  turbulence reports, a nowcast or  analysis, along with icing and a  lot of the other aviation  weather hazards.  And the future is possibly  taking things, this is an  example of cloud top height, but  you can imagine your chance for  turbulence being mapped into  here.  And then you basically, if you  had a flight path, an aircraft  going through there, you'd have  the pilot getting an ascii text  readout of what's your,  hopefully this will change too,  but this is what they still get  in the cockpit, are the old  ascii text, because they don't  have a lot of bandwidth yet.  It's kind of funny, we walk  around with iPhones and things  like that.  The pilots are still very  limited in what they can  actually disseminate, because it  costs money, and there are still  a lot of old systems out there.  But this is what they get, for  instance, if they want to look  at the cloud top, and what  they're going to encounter in  the next 15 minutes. 

 The idea is that you could  actually have current position  in your cockpits, and the  turbulence would be out in front  of them, and they could avoid  the higher likelihood of  turbulence with a product like  this.  This goes for thunderstorms.  This goes for cloud top height,  or whatever they need.  Yes?  (inaudible)  Can they fly, or do they?  Well, in general, when  commercial airliners fly in one  direction, I think it's east,  from west to east, they fly  lower I think than from east to  west.  But one flight level is around  39,000 feet and the other is  like 45,000 feet.  They actually keep them  separated by a certain altitude,  depending on if they're going  west or east.  That's when they're going west  or east.  So around that flight range,  39,000 feet to 45,000 feet.  It's sometimes lower than that.  Yep?  (inaudible)  Feet is the international  metric for altitude. 

 Feet, believe it or not.  International.  There's a lot of countries that  don't like that, but that was  adopted a long time ago, and  really never has changed, which  I always thought odd, too.  You'd think it'd be meters.  (inaudible)  (no audio)  (inaudible)  >> It depends on how high the  atmospheric weather is.  If the top of where the weather  occurs is higher or lower.  And during the summertime, you  get a rapid thunderstorm, the  triple fold will stabilize the  top of the weather.  That actually causes the  atmosphere to become quite  disturbed.  So you can easily still  encounter turbulence at that  level.  But you're right, there's less  molecules, so you'd think it  wouldn't be as terrible. 

 But it's still an issue.  Volcanic ash and gas.  It's not so much an issue, I  guess, if you're in Wisconsin,  and on the ground here.  You don't see a lot of this.  It doesn't happen very often.  But for a lot of places around  the world, it's a huge aviation  hazard, including Alaska and  Japan.  Here's an example, for instance.  Right now, they have these  volcanic ash advisory centers  around the world.  Their sole responsibility is to  warn about volcanic ash and  gases.  This is an example from  Washington, DC, actually. 

 We have received a report from  Navy aviation in the area  indicating an eruption of Santa  Ana to FL460, 46,000 feet.  The eruption cannot be seen in  the 1515Z image, possibly  because of weather clouds.  That actually is the ash cloud,  but it looks just like  thunderstorms.  So remarks.  The eruption is now believed to  have started at 14,000, and an  area previously thought to be a  thunderstorm is now identified  as thick ash.  A forecast will be issued soon.  This is a problem.  There's been new algorithms that  have been developed.  And by indication, ash at 1415,  at the time right there, of  volcanic eruption, we can  actually separate the ash cloud  from another cloud.  This is a new algorithm that's  really been developed in the  last three years, and being  implemented now in operations. 

 It's a huge step forward,  because the problem with  volcanic ash, it's basically  bits of glass.  And when you have that, it's not  a good thing.  It melts and you lose your lift  and engines stall, especially  commercial airliners.  I've only read about five  incidents where this has  happened.  But when it does happen, pilots  at high altitudes have dropped  20,000 feet before they could  get an engine restarted.  So it's very sparsely populated  areas, over oceanic areas, over  the arctic.  These ash clouds are a threat.  It's a matter of time before  something serious happens.  But satellites can provide,  probably the answer, because a  lot of these places don't have  any other observations, just  satellites.  Volcanoes are in pretty remote  areas in general. 

 So basically, we're working on  trying to monitor the ash, and  trying to find out cloud height.  And we're actually pretty  successful at building an  algorithm to do that.  In a lot of these cases, they're  over Africa, Madagascar.  The other issue is--  (inaudible)  It's SO2, besides ash,  you have SO2, which is a gas.  They can separate.  Gases are lighter.