Hi everyone, I am Swaroop I am currently working at Fidelity Investments. So, I will be talking about recommended systems. So, I mean just for an idea sake I mean can you just raise your hands if you are aware of recommended systems.  So, I will be the agenda being I will talk what recommended systems are the most popular algorithms collaborative filtering content based and matrix factorization I mean with few tweaks and then finally few use cases from my experience. So, imagine yourself being on a e-commerce website. So, most of the e-commerce website these days have millions of products on their catalog. So, the company has to recommend a few relevant products from their existing millions of items to you. So, it would help the company to drive their sales because he is recommending the relevant products to you and it also help the user because less time on the website I mean go get the relevant products come out I mean lots of increased user satisfaction. So, what's the challenge here? So, you have millions of users millions of products and everyone each one of us have our own unique taste and the products even the products have a huge number of varieties. So, at the given scale I mean you can't try solving this problem using maybe a regression problem with a regression for every particular product in your catalog or even manually. So, at the given so if you want to apply any of the machine learning techniques to solve this particular problem at hand. So, that falls under recommended systems. So, if you mathematically represent the problem. So, this is how it would be you have users on one side of the matrix and you have products on the other side of the matrix. So, I mean here we have considered maybe a 10 by 7 matrix but usually you have millions of users and millions of products. So, and the user might have purchased a very few items maybe 3, 5, 10. So, for the company to recommend items from their catalog to the user they should know what his ratings would be for all the other items in the catalog. So, the company would want to know the million products in the catalog minus the purchased few items maybe 5 or 10. Then they can sort the predicted ratings in the descending order and then maybe send out a few customized marketing messages or how they want to do it maybe through sidebar messages or whatever it is. So, it's all about predicting million minus few rated items. Yeah, as I said I mean you can't solve this using regression and definitely can't solve when you have the sparse data. But you have the advantage because in if you solve it through regression you can interpret the coefficients which you get whereas here it might be tough because you're just it's a mathematical problem. You have a sparse matrix you're getting another matrix which is completely filled which is a huge matrix but so manually interpreting it might be really tough here. So, coming to the most popular recommender systems you have a collaborative filtering and content based recommender systems. So, collaborative filtering is all about similarity, user similarity. So, if you take a user based collaborative filtering it's all about clustering users who are similar to the other users. So, you cluster users and if I did not buy any product which the other users in my cluster have bought. So, it's all about recommending that product to me likewise item based. So, you cluster all the items and if I purchased a good number of items in the cluster. So, it's all about recommending other items in the cluster which are not bought by the customer. So, I mean it's all about you could see groceries I mean usually they they're very common in nature. So, if you miss out a few items from the which are purchased by other households you can very well recommend them whereas here it's like bed sheet and pillow I mean they go together. Coming to the content based recommendation systems here you consider the metadata of the items. So, if you consider books it could be the publisher the other the year in which it has been published the genre the number of pages stuff like that. So, you consider the metadata of the items in coming up with recommendations. So, now I mean we'll solve a simple collaborative filtering problem. So, let's assume you have users and products and these are the ratings assume that the ratings are in this range of one to five. So, I purchased few items and I've rated items in the scale of one to five. So, you'd want to know what item you'd want to recommend to maybe a user one because you don't know what his rating is for the item two maybe item four item five. So, if you're doing a item based collaborative filtering what you do is you construct this item item similarity metrics where what you calculate is the similarity of item one to all the each item to every other corresponding item in the catalog. That's what you compute here you can't compute because for the item two if you take the item two which is product two that is this row second and third columns there are no intersections as you could see you have three there and there is no rating for the no rating here likewise no rating here likewise you have no rating here. So, it could also be a cold start problem I mean if very few purchases are made ideally this would not be the case. So, I made the matrix really small. So, if that's the case you never know how similar item one is to item two you also don't know how similar and as you could see this is a diagonally symmetric matrix. So, all the values on the bottom are similar to the values at the top. So, once you compute this and for similarity you could use maybe a cosine similarity Euclidean distance PSN you could use any metric as it's your choice. So, once you have the similarity score computed you can calculate the final values for all the sparse values. So, you could compute all the sparse values I mean based on these. So, user one has purchased item I mean product one and product three. So, you know how product one is similar to other products you could see these values and then compute what these recommendations would be for the other items in the catalog. Likewise, it would be the same thing for the user based collaborative filtering you compute the user user similarity how similar am I to all the other users in the database. So, you could see you could see there are a few null values because there is no matching you couldn't compute it. So, that's a cold start problem. Likewise, there could be few popularity bias I mean few people have very unique taste and it's really tough to match them I mean every other user in the system rates it really low this guy rates it higher I mean can't help it. So, I mean unless there is another similar guy exactly who is mimicking his behavior. So, coming to the content based recommendations as I said you consider the metadata of the items. So, like here you could see the you consider all the publisher book release of the year and each user is nothing but so the user is nothing but the profile of the item. So, if I'm rating all the books by rolling very high. So, in a way my profile could be said as something as I'm more of a rolling fan. So, in a way it's as simple as any other new release of rolling maybe you could be recommended of it. So, the user profile is composed of the item properties. So, here since you have a item profile. So, given any new item coming into the system you could compute a simpler cosine distance or any other similarity metric between these two things and find out his affinity towards the new item which is coming into the system. So, there is no kind of cold problem per se and we can also provide a good meaningful explanation because. So, if I'm recommending something to this guy I know why I'm recommending him because I rated all the rolling books very high. So, that's the reason why I'm recommending him another newly rolling book which has been published and the coin being getting the metadata it's not as easy to get the metadata as we think is in the e-commerce I mean sometimes it's the metadata is really not so easy to get I mean we could see the talk on index I mean the things they have been doing to get the metadata maybe extract the image features. So, I mean as we know the higher the features I mean better it is and till now we've considered either user user similarities item item similarities what if we consider the interactions between users and items both at a time. So, let's assume had this matrix not been sparse let's assume every user has bought every item in the catalog and every item has been bought. So, in that case maybe you could have used in SVD and we could explain the direction I mean the interactions which have have been happening between the users and the items since the matrix has been sparse. So, you use a alternating least squares approach to solve this particular problem. So, simply put alternating what you do in alternating least squares is you initialize two random matrices and you optimize the objective function the objective function being the known ratings minus the ratings which are there in the compute randomly generated matrix. So, this is the error which you have. So, you know few ratings you generated a completely full matrix. So, you compute the root mean square error I mean this rating minus this rating whole square it's all about minimizing that particular error with a so, you do solve it maybe using a stochastic gradient descent by with choosing a particular alpha rate and approaching reaching the optimum value. One simple assumption being the interactions between users and items can never cross the number of items or the number of users in the system because you are creating. So, if the sparse matrix is of size m by n. So, you would create m cross k and k cross n. So, the k should always be less than m and n both. So, this is how you would solve it and to make it more complex you could also consider the user by us. So, let's assume if I am a Rajnikanth fan irrespective of how good or bad the movie being the content of the movie I tend to rate Rajnikanth movies higher. So, I have a particular bias towards Rajnikanth movies. Likewise, you could have an item bias. Let's assume a particular product has been hit in the market. So, the immediate product in the market usually tends to get high ratings. So, that could be the item bias. So, you would want to eliminate these from the ratings or else you could have a time varying impact. I mean if you could see if you go into the IMDB all the newly released movies are very high ratings as soon as they are released. But with time the rating decays. I mean they tend to fall. So, I mean this could be called SVD plus plus and right now Netflix is using an ensemble of SVD plus plus and restricted Boltzmann machines. So, this kind of does really well with the accuracies. I mean now that we have talked about four types of recommended systems I mean when would you want to use what? Let's assume if your item catalog is really huge even though you don't want to go for the matrix factorization because the computations are really high. As soon as a new item gets into the matrix you would want to do the entire matrix computation again. You want to do the matrix factorization which might take good amount of time. In the real world you obviously have millions of users and millions of items. So, maybe it's better to stick to collaborative filtering. When you have metadata of the items which is really rare in the real world maybe definitely use it. Go for the content based collaborative filtering. Content based recommendation systems and if accuracies are the key maybe matrix factorization. For cold start problem let's assume a new product has entered your catalog. No guy has brought it. So, what would you do? So, you can cluster all your existing items and maybe just give it the same attribute the same value what the other items have or combining methods to ensembles. I mean we know I mean you could very well boost the accuracies with ensembles even though the accuracies are nearly low the ensemble model will definitely have a higher accuracy and data processing. I mean maybe removing the average like I mean you could see people usually complain saying a particular instructor always scores all the students low a particular instructor is even though you do fairly okay he rates higher. So, maybe you want to remove the average from all the ratings. As I said earlier I mean Netflix is using an ensemble of SVD++ and RBMs and from my observation I've noticed that it's very simple to produce reasonable recommendations but it takes a really good effort to improve them. I mean to increase the recommendation to make the recommendations great or I mean maybe I've worked on a so while I was I've done a consulting project where a particular company he's hosting a meet with all its executives and at the tables are arranged in such a manner where and they wanted to figure out who would be sitting in the table I mean which kind of users gel together maybe if you make a I mean I don't know I mean they might might have thought that people from diverse backgrounds may not gel well that might might have been their assumption whatever something might have been going in their mind and they want to have the best seating arrangement for them and the data which you got from the firm was just the employee first name last name and the company he belongs to so we solve this problem by scraping the skill set data from the LinkedIn so usually most of the top executives they maintain a LinkedIn profile page updated so we scraped the skill set and the problem with the skill set is we could have clustered users had this matrix not been sparse I mean I have all the attributes I know all the skills I mean I could have easily clustered them but this matrix is sparse I mean a but he a particular guy knows Julia sass are high SQL and there are only two users so a guy knows high and DB DB meaning database the other guy said I know high SQL and database so it's very intuitive that even he knows SQL so we want this pass matrix to be filled so that would be a one and maybe since this guy doesn't know sass so the other values would be zero so using the matrix factorization we filled the entire matrix and then we went for a hierarchical clustering and that's how we got the seating arrangement fixed and maybe you could recommend our packages based on the packages you have already installed or in a financial domain usually people have multiple maintain multiple credit cards and they use each credit card for a particular category so the numbers are the dollar values U1 U2 are the users and flight food are the particular categories in which they spend money so the values are a bit normalized not normalized actually hidden actually so those are the dollar values so you so for the company credit card company to cross sell they should identify how much he is spending in the other category that's when I get to know I can cross sell to him so let's assume if you solve by matrix factorization so you the first time you see are the random values the values generated in the range of three to five and then you keep minimizing the root mean square error so after these are the iterations for a particular value of alpha and at the end you reach a stage where the random matrix values which are the values in the flight and user two will tend to three actually usually it's four yeah it's three and it's six so this has reached that final stage where the root mean square error is almost nearer to zero so now you know the what he's actually spending in the other categories now the credit card company can go hit that guy who is spending really high in the other categories because now I know based on his similarity to other users you consider the interactions and maybe you can generate the marketing list and then maybe assume a 10 percent lift and yeah that's it yeah thanks guys


What is going on guys welcome back to the channel critical overload here so we're talking about screen six in this video here again today talking about Sydney Prescott and Just how the movie can still factor her in in some Significance to set up screen seven which I know is something that many people were speculating on in the past something that many people Myself included thought could play a factor into the upcoming movie But after the test screenings have come and gone for the upcoming six movie We now know officially so far anyway because they're still I will say a chance But as of now officially as I am on the bandwagon of thinking she is not going to be in the movie She will not appear Neve Campbell Unfortunately, yes did not manage to ink a secret deal to appear at Sydney Prescott in this upcoming movie However, we know that Sydney Prescott or we expect at least to have Sydney Prescott referenced in some capacity So what they could do is use this reference and take it a step further into a cliffhanger of The movie and how it ends to set up her return in screen seven so instead of actually physically seeing her Something can go down with ghost face I do want to say that this has nothing to do with her appearing This has nothing to do with Sydney's house appearing This has nothing to do with ghost face going to Sydney's house It has nothing to do with any of the stuff you might have heard in the past as a rumor This is just simply something I could see them doing that might actually be in line with what they wanted to do originally at the end of screen too So in screen six, we know that the Carpenter sisters again will be the focus of this upcoming ghost face free Sam and Tara Tara's away at college. We're in New York Sam is going with Tara and her friends Chad and Mindy And of course, we'll have our new players get get involved in all of this Now it's safe to assume that by the end of it all after ghost face is done running a muck in New York The last two people standing plus a few others will definitely include the characters of Sam and Tara Carpenter So we know that there is an aged mask that's being used by ghost face into in this upcoming movie this aged Mask not only do we have that we have an iteration of the mask that we saw in the teaser That looks different than the aged mask that we saw in the image that was shared after the teaser dropped And then we also got a new image from USA today That looks like it is a completely different mask than the other two masks that we've seen in the past Previously so that is giving an indication of people that we have three killers that will populate in or that will appear in some capacity In this movie. So here's what I would like to see. Let's say you get Tolled and just shown out upfront that yes, there are three killers But then the movie could end in a way that reveals that there weren't just three killers at play There were four, but they only revealed three the fourth person got away And they are going to take us into the events of scream 7 now in my mind if you've seen some of my videos I would love to see scream 7 wrap up this series wrap up the Carpenter story Wrap up the Prescott story with the character of Leslie Mocker have someone brought in to tie up any loose ends address some of the stuff regarding the exploitation that's been happening since the very first film and Target Sydney target gale target any of the other survivors in any loose ends that always seem to spawn and you go space Killingsbury and just have Leslie Mocker herself Commentate on how the mockers have suffered ever since that first movie how no one seems to really care about them How everybody seems to just blame them when stew is actually just responsible for his own actions Leslie could be upset about her own son's death blaming Sam for that blaming Sydney for Billy and all the other antics that led to stew getting tied up in that which ultimately destroyed their family and their Reputation in the town of Woodsboro, but I digress so I want to get back to what I want to get into This fourth killer and an ending of how Sydney Prescott can factor into it. I would love to see a situation occur where We have the film end in a manner in which Sam and Tara share a sweet moment and let's say that Sam is maybe Holding on to something from one Holding on to something from the very last final battle with the killer She decides to drop this item on the ground to end the movie and walks off into The future or the unknown future as it stands right now in another happy ending sequence with Tara as they both decide to leave New York, they're gonna get out of town. They're gonna move somewhere else They don't need to be in New York the same way. They don't need to be in Woodsboro They're just gonna pack up and move once again So when she decides to walk away from whatever this item is you can then also tie in Another individual walking up into the frame. We don't see who this person is But it's someone who has who has the aged ghost face mask in their hand. Now. Here's where the here's where the tricky thing comes in People will be forgetting that during the finale They never saw the age ghost face mask appear, but they did see three killers appear and get revealed So ultimately people will just assume at that time even though the aged mask was never shown They'll assume that one of those three killers was also the person wearing the aged mask earlier But they weren't again the minute Sam walks out of her frame and you think that the movie is over someone else I would say wearing wearing black pants and black boots is what we'll see Walks into the frame and they are holding the aged mask in their hand. That is all we see from them They pull out their cell phone after walking away into like an alley We still don't see who this person is but again in my mind. This is Leslie mocker She's walking away into an alley after Sam and Tara have left She pulls out her cell phone and she's and she phones to call Sydney Prescott. We hear Sydney Prescott's voice. This could be something they either pull from Neff Campbell or something that they have Had Neff Campbell come in and do like some voice work in some capacity This is just how I would have it still tie into Sydney Sydney could be called You could have Sydney answer the phone or even this like I said before Sydney doesn't have to appear. You don't even have to hear Sydney She can just simply call Sydney Prescott and then the movie ends on a cliffhanger like that to let you know as a Viewer that going into scream 7 Sydney Prescott will be very important to whatever they have planned for screen 7 now again In my mind this individual who remains anonymous at the end of the movie is Leslie mocker People that are in attendance won't know who it is. I of course won't know who it is But I already have it said in my mind that this is Leslie mocker This is who I would prefer to see wrap up the series This is who I would prefer to see target Sydney target Sam target Tara in screen 7 And that is how I would like to see this wrapped up so that in the movie For scream 6 in a way that ties in the scream 7 and establishes that Sydney will be very important have a final Individual walk into a frame after it after it appears the movie is about the end after Sam walks out of the frame They appear always sees black pants black boots and the aged mask in their hand Revealing that they were a fourth killer The ultimate the ultimate confirmation that they were a fourth killer will be the fact that when they are going to Call Sydney they pull out the phone and there is blood on their hands They just call Sydney Prescott and the movie ends with Sydney not answering the phone That is how it can be done And that is another exciting way to get people on the edge of their seat and a way to have them look forward to the Events of scream 7 would you like to see something like this in scream 6? Why why not let me know down in the comment section below if you haven't already of course and make sure you Go ahead and subscribe turn on post notifications that you never miss a video in the description I will have links to my social media accounts. I'm on Facebook Twitter and Instagram You can message me there of course to let me know if there are any movies news or reviews You let me to cover in the future and with all that in mind guys. I will see you in the next video


Look outside. Do you believe this is Seattle? I forgot the sky was blue since I got here. It's sunny out in Seattle. How about that? We are about to walk out that door to go to Vlogger Man. I'm actually gonna be there an hour before everyone else, or I get let in an hour before everyone else, along with the other vloggers, just because we have a breakfast and a little, uh, I guess a get-together before the fair. Probably gonna be to prep everybody and tell everybody what's gonna happen, where to be, and when and whatnot. For me, I'm sort of just gonna be wandering the floor, trying to meet some of you guys that came out. I'll be tweeting on the Twitter. What not? So if you guys did come out, that's where you would have been able to find me. Oh, I didn't sleep so well this night. I'm gonna be tired. You would not believe the noise that Seattle makes in this particular neighborhood at one in the morning. On a Friday night. Probably the same as any other city. I remember Winnipeg was really noisy when the bars let out too. That was one of the biggest reasons why I moved to the country. Quiet. Oh my, there was like a marching band outside, and people yelling and fighting and everything, and they came in the hallways here. I guess some of them were staying in the hotel and just yelling in the hallway. Anyways, party people. It was okay. I did get to sleep, and everything quieted down. And I think I got a reasonable rest. I've also been very excited, so we're gonna go to Vlogger Fair right now. I know I've shown you this park like a dozen times already, but isn't it nice? The sun is out in Seattle. You have to get that on camera. So we got lost for like the 100th time trying to find the Seattle Center. I already went and tried to find it yesterday, so I knew where it was today. Apparently that did no good because I still don't know where I'm going. But I'm pretty sure we go this way. Oh yeah, there's a whole crowd of people there already. Oh dear, a long lineup. Okay, here we go. This is what it looks like before everything starts. The crazy lineup outside already. It's just absolutely crazy.  I guess this is lineups to all there'll be like meet and greets over there for the big vloggers. Whoops, I am photobombing. Am I in the background of that one? Solid promotion. This is Chris Peril, the host of everything. Cheers, everything. The life universe and everything. I am the host, not with the most though. I have like half. I'm the host with the half. Can I get away with saying that? I think I just did. I think so. This was Liz. She was the one who helped me coordinate. Yes, I love Canadians. I am Canadian, so. She is from Montreal originally from Nova Scotia. She's an East Coast Canadian. We still like her. Okay, there's a whole rivalry going on. I just say things like car and far and... Is that my head? That sounds normal. My ear, my entering ear. So we're just getting everything set up here. All the lights are going off. What's that mean? It's going to be dark. I don't know if anybody told you, but we don't have electricity. Yeah, I hope you brought your flashlights, guys. So we're getting everything set up here. Oh, it's Brian and Ollie. Hi, guys. Hi. Waiting for his fangirls. This is the main stage here. Oh, VIP seating. I hope you guys got your VIP tickets. Look at this, look at this. So this is what it would look like for you guys. Very exciting, very exciting. So they're going to let everybody in here very soon. I can see them all lined up at the doors over there already. They're just going to line up around the block of people. Mingling. Waiting for everything to start. They're about to open the doors. This is apparently where everybody's hiding. Oh, awesome. Shane Collette and Brotard. Hey, guys. What's up, guys? Hey, guys. Canadians right here, fellow Canadians. And some more people hiding all the way up in the back here. Hey, guys. Hey, guys. Hey, Carl here. We're backstage at Waterfair about to go in. There's thousands of people lined up outside. And Trucker Josh is just telling me how he misses his doggy. I do. Diesel would have loved to meet Zeke. I should have brought Zeke. We could have brought our dogs. I brought a baby and a wife instead. Chris Perl is talking about maybe a docker fair. A docker. Okay, guys. They just opened the doors here. A lot of people. I think Shay went this way and that's why the whole crowd is over here. So it's even when it came out for him behind the stage. Oh, man. It was just like a swarm. It was funny. Winnipeg. Winnipeg, Manitoba. Yeah, in Canada. I'm in the United States a lot more than I am in Canada. Yeah. Okay. Yeah. So we go wherever there's a road. That's where we go. Colorado? Oh, yeah. We've been there. You're from Colorado and you're from North Carolina, right? Yeah. Black Mellow is coming out to be exact. Wow. You guys took travel a bit to get out here. Exactly. Oh, it's good to meet you guys. Oh, pants. Shay just got on stage. Can you tell? Hi, everybody. Welcome to the second annual vlogger's fair in Seattle. And we can meet some pictures and book rubs all kinds of stuff.  Mom's stage, my big buddy, Austin. No. This stage now talking about 3D printing. Check it out. That was 3D printed. Sitting here talking trucks and whatnot. He came out. He lives in the... Go check him out on YouTube. It's time off, y'all. No time off, right? Yeah. If you have headphones on, take him out. Yes. In the loud. Warning. Tyler Oakley's about to come on stage. What are people having now? Everybody is very excited to see him here. Well, Tyler Oakley is still making all the little girls scream. Oh, of course he is. Yes. And... What's his name? What's his name? What's your name? Project Launching. He's got a good name. It's all in. So he appears here. Conversation, but Tyler Oakley keeps interrupting us. So am I. So am I. Everybody's really excited, everybody. I mean, like every teen girl here is self-excited to see Tyler Oakley. Tyler Oakley is just floating right now. Is it? Tyler Oakley in the back. He's actually a really nice guy. Yeah. He talks to him and even talks to me about my vlog and stuff. He's very curious about how I find Wi-Fi. I'm reading lots of new vloggers. I want to introduce you to a couple of new friends. We got R.C. R.C. Vlogs, right? R.C. Vlogs. Yep. R.C. Vlogs. Right on. Yeah. We'll go check them out. I got some more friends here that are family vloggers. You can see by their shirts. And they believe in staying debt-free. That's right. Living life on a budget. And that's a lot of what I've been talking about.  But sometimes it's a necessary evil, but in moderation. Especially when it's war on and debt is war on. You don't have to do it. Yeah. So here's a couple of friends that I met that you guys will check out. And I'll put a link to their channels in the description for you. I'm tired. I am used to sitting all day. I just stood for like 10 hours. Little breaks here and there sitting down. But that was a lot of fun. I met a lot of awesome YouTubers. Made some good connections and whatnot. And a few of you did show up there to say hi to me. Some of you have gone on camera. Some of you I didn't. But thanks to all of you who came out and said hi to me. Really appreciate that. And it was great to see you. I'm really tired right now. I've had very little sleep in the last couple of days. So I think I'm just going to hit the sack there for a little bit. We've got a supper later on tonight yet that we're going to enjoy together as vloggers.  Well, this is the real world. But this isn't my real world. This is West Coast. Real world. Fly back to the prairies. And then I'll go on one or two more trips. And then I got to move. And then I'm going to really have to get my button gear. Quite literally. And drive that truck hard so that I can make some money. That's the plan. So let's take a little break. A little breather here now. And we'll see you in a bit. The weekend is over. It is over guys. It was so much fun. So much fun. I'm just going to stand here in front of the air conditioner because it's hot. Seattle. You're awesome. Had a lot of fun here. It was great to be here. Chris Perillo. Don't know if you watch this or not. Maybe not. But hey, shout out to you. Thank you for setting up Vlogger Fair. You did a great job. Thank you to Liz who was the coordinator who helped me get everything in order. Make sure I knew what I was doing. She's from Montreal. She's a fellow Canadian. And thanks to everyone else who helped set up Vlogger Fair. I'm just getting responses to some tweets here. I was just tweeting out how awesome it was to make new friends. So cool to meet so many of the YouTubers that were here. It was really cool to hang out with them and form friendships with them. I want to stay in contact so that maybe we can meet up again. I know VidCon's coming up next year and I want to be able to see them again there. Hopefully I get to see them again before that. But other than that, my day, my weekend was amazing. So we're going to fly home tomorrow. And after that, it'll be back on the road for a week. We'll be trucking like we've been trucking before. And then everybody's still tweeting like crazy. Vlogger Fair was awesome. Oh, somebody's tweeting me. Anyways, then after a week of trucking, we get back, we're going to move. I'm going to show you all my new house after I move. I know a lot of you are excited about that. No one's more excited than me, trust me. And after that, it's back to the regular grind on the road. Got to pay for everything. Taking time off isn't free. But it's definitely worth it for the sake of Vlogger Fair. Okay guys, we'll see you tomorrow. 4 a.m. Central time. Just like every other single day. You guys should know that, right? Do I really have to say it? 4 a.m. tomorrow. I'll be right here. I'll see you then.


Thank you. Thank you for this wonderful introduction and thank you for coming tonight to the MESA lab For this talk the last talk in the explorers series Thank you to all those of you who might be following us via live stream for tuning in tonight This is a talk about the phenomena here atmospheric phenomena that affects us all on the front range through shaping our natural environment and Intern shaping our lives and Whether you like the down slope winds or not Whether you are a fearless liar or a skittish one. I Hope you will enjoy this evening with me tonight Mountain clouds mountain wave clouds among the most beautiful clouds that form in the Earth's atmosphere How many of you have seen clouds like these? I Thought so quite a few What was it here on the front range or somewhere else? Only here on the front range Okay Well, they do form Worldwide and and this cloud which is called technically Lenticular cloud or the latin name altocumulus lenticularis As actually formed in the lee of Mauna care on on the big island of Hawaii Alto indicates the height cumulus indicates the shape and Lenticularis comes from lentil as a matter of fact The latin and describing the lens shape which exactly this cloud has And if you look more carefully at this cloud it actually has several layers to it a layers five layers little stack Caps on top of each each other that indicates the layering of moisture moisture in the atmosphere These clouds actually related to mountain waves. They are generated by mountain waves and thus they are also called wave wave clouds They can be quite spectacular they can be spectacular in both shape and in color especially at sunrise and and sunset and And They are quite mysterious They have a aura of mystery to them because the shape can be quite intricate Even more intricate than this one and they also persist in in a given location for hours So sometimes they are mistaken for UFOs and trust me. They have nothing to do with that But they equally have inspired scientists and artists alike and they continue to do so and Whenever I look at a lenticular cloud such as this one in particular Einstein's Statement comes to mind and he said the most beautiful thing we can experience is the mysterious It is the source of all true art and science He to whom this emotion is a stranger who can no longer pause to wonder and stand wrapped in all is as good as dead His eyes are closed So I invite you to keep your eyes open And join me on this journey through mountain waves winds and clouds So how do they look here on the front range? How do these clouds look? Here is a very nice clean example And a photo taken by my colleague senior scientist Bill Randall from from Enkar This is a northwest view from the Enkar Mesa lab and As I'm looking at these clouds as a scientist. I'm immediately analyzing. What do I see? I see clouds at many different levels I see that I can draw a phase line a line connecting the same positions of the on on the wave shape Think of a simple sinusoidal shape and the phase line is the line that is connecting the same point of the updraft on a longer phase or along the wave front What I know as a scientist is that that phase line is actually perpendicular to the flow And so I can draw the wind direction. There is a wind direction Approaching the mountains and this gives me information I didn't quite do the analysis of this photo photogrammatic analysis to tell you what exactly the direction But I know from the climatology This westerly winds and and sometimes slightly north of westerly that give rise to the winds winds here on the front range The waves that gave rise to these beautiful clouds are not generated by the front range By by the flat irons They are generated by the mountains further to the west and oftentimes they're generated by by the continental divide themselves Itself which which is oriented in the north-south direction here So it is actually we get a very clean clean nice looking waves when the westerly flow and it's westerly flow Approaching the colorado rocus So what else do we see I mentioned several layers of clouds In the middle column if you look at the middle column, there are three layers of clouds And altocumulus our friend altocumulus lenticularis is here There's a lower layer and there is also an upper layer And the lower one is called the stratocumulus Allenticularis and the upper one is serocumulus for you affectionados cloud affectionados in the audience Okay, the flow through these clouds. It's smooth extremely smooth Anyone who has flown through them being close to them knows that they they are smooth any glider pilots here in the audience Okay, very good So the glider pilots will recognize this diagram which comes from the osteve publication Osteve is an international scientific technical soaring organization and the glider pilots Have to know about the waves and and they know about the waves they get quite educated about them From the publications, but also from just flying through them Before I describe How and why the mountain waves form let me spend some time describing on this diagram itself On the left side the two yellow lines curves Describe the profiles of the temperature and moisture in the atmosphere represented here as a dew point The vertical coordinate is the altitude expressed either as pressure Or as the altitude in thousands of feet or kilometers the wind barbs Which is a standard meteorological symbol for the wind shows the direction points to the direction from which the wind is coming from and the little Flags on barbs indicate the strength of that wind The full one is 10 knots The short one is five knots and the flag is 50 So this wind is increasing from 25 knots at 850 hectopascal to all the way to 75 at 300 hectopascal, which is at some 30 000 feet Now why the waves form in the atmosphere? Atmosphere is a fluid. It's a gas. It's a compressible gas And it is a stable fluid Stable means that any that atmosphere on average will resist vertical motion And as the air parcels are pushed up the mountain The buoyancy force will bring them down They will find themselves warmer than their sorry colder than their environment and buoyancy will bring them down As they pass over the mountain But they will not stop at their equilibrium level level where they come from They will overshoot and go further down find themselves warmer than the environment and be pushed up So this restoring force for this way motion is buoyancy, which all of you are familiar with You know if you try to push the balloon in the water the buoyancy will push it up And similar as the pendulum, which if you take it out of its equilibrium position And let go will go back to its position But it will overshoot it because of the inertia And it will go back and will continue doings back and forth back and forth until friction eventually Slows down the motion and kills the motion The same happens with these buoyancy driven waves in the atmosphere They will keep going until eventually the energy somehow dissipates Now We don't want to fly yet Okay, the the solid lines the white solid lines What we call streamlines and if the flow is steady it doesn't change these streamlines actually represent the flow lines So think of them as the flow lines because these waves can be steady. They can stay the same for quite a long time The clouds the waves themselves are invisible to a human eye And we can detect their presence only when there are clouds that form at levels where the atmosphere becomes saturated with respect to water vapor And any lifting of the air will read the deformation of clouds Clouds in this situation typically form a top two wave crests and evaporate as the flow goes down And then they might reappear again for the downwind You see our friends altocumulus lenticularis. You see the cirrus cloud up here And there are two more types of clouds that I have not mentioned yet The one is fern wall cloud And the other one is a rotor cloud fern wall cloud has to do with this if the air stream That's coming from the upstream Is fairly moist clouds will form on the upward side of the mounting Mountain they will rain out the snow out and some of them will actually spill over on the other side And evaporate because again atmospheric compressible warms warms up and the clouds evaporate The rotor cloud marks the top of the zone that's quite turbulent and it's indicated with these carrots Here that is quite turbulent. All your glider pilots know all about it In between the two the the fern cloud and the rotor cloud. There's a gap. It's called fern gap It's called wave opening. It goes under many different names And there's a reason why it's really nice beautiful and sunny and warm here In these situations here here in balder Again, I keep mentioning glider pilots for reason because they've Learned they learn early and repeat often that these wave clouds are beautiful beautiful for soaring And if they position their craft with a nose to the wind And in the right position here on the upright of this wave That wave will carry them to a very very high altitude They actually have to be careful if their craft is unpressurized that they don't exceed the altitude At which there is a reasonable concentration of oxygen Because bad things might happen, right The world records in gliding for those of you who are not gliders the world records in both distance Flying and in altitude have been achieved in these situations that are called trapped lee waves or lee waves Where the energy of the waves is confined to lower levels of the atmosphere And all the waves propagate to very large distances downwind So the the world distance record from 2006, I believe is slightly over 3000 kilometers And the world altitude record was again pushed this year in in seventh september this year It was pushed to nearly 16 kilometers, which is even outside of this my my diagram By by a pilot with a pressurized glider clearly Flying down in the lee of the Andes in Argentina Okay, aside from striving to to push the world records The glider pilots and I admire you all I do quite quite their devilish things Such as intentionally flying through the rotor zone To measure how bad the turbulence is how strong the updrafts and downdrafts are and how How how strong the intensity of that how strong intensity of that turbulence is The photo comes from charlie martin Who is not only an excellent software engineer and has been a long-term member of my laboratory But also is an avid glider pilot And he teamed up with the scientist role hurtenstein who is my colleague also And really a glider pilot and they use the two-seater schwarzer Which was actually at the anchor glider at one point no longer in our in our suite They instrumented it with with good instrumentation for measuring air motion and and and some turbulence they tried And they flew it on purpose In in these situations with nice rotor and wave clouds so you can you're looking west There you can see the the rain mountain range You can see the rotor cloud the wave cloud the loft and the pilot The tow plane is in front and it is Pulling the the glider to position it on the upwind side of the rotor cloud and then let go Once there once they go through the One they get into this wonderful position On the upwind side now i've i've changed the rotation You are looking north-northwest from above the flat irons and Here is the firm wall cloud evaporating gap the rotor cloud the Alentecular is above and I've indicated A part of the flight pattern of what they repeated several times in these situations So they would come from the west underneath the rotor cloud. They have to fly the visual So they flew visual underneath in the rotor zone, but underneath the cloud Then After the worst they would come in the gap opening They would go north and up Above the lenticular and then fly in the smooth smooth smooth there All the way to the to the east end and descend And go south and repeat repeat repeat probably until their bodies were Sufficiently beaten And here is a trace of of that measurement. So if you look this is a time series And this is a vertical velocity on the on the On the y axis and I marked plus minus 10 meters per second So keep your eyes focused on that region west What's labeled west are those sections of the flight path where they are flying underneath the rotor cloud So as you can see as they are coming from the east there is a Largest scale structure. There is a down draft and then up draft But within that there are really really severe gusts And that is producing the acceleration They change the vertical velocity with that is leading to to the acceleration and that acceleration can exceed Several g is plus and minus several g's So this this is this is quite a bit of beating both on the glider and the pilots inside. I deeply deeply admire them So let's take a deep breath After all these after after all that turbulence And I will take you Back to to the other continent to the old continent Back in time a couple of centuries to explore routes of wave and rotor research And lo and behold, they actually go back to my old country to to the Croatian coast to northern coast Where a fellow Scientist called Andrija Mojorović, which you might know actually recognize his name from the moho layer The seismologists who discovered this continuity between the earth crust and mantle He was a physicist by training train in Prague with Ernst Mach and his first job was here in the naval academy On the northern Croatian coast. He got a job and he became professor of meteorology And he loved clouds He was he was an avid observer keen observer and he seemed to have a special relationship with the clouds And he said clouds are strange fellows and you must catch them when they appear And not when would you like to But one cloud seemed to persevere and and or stay in place was quite stationary What Mojorović noticed as the Bora wind, which is a northeasterly wind that comes over this dynamic Alps range When it's just breaking out, which is just starting He noticed that there is a stationary cloud that is parallel to the coastal range And he concluded with very little data that in order for that cloud to persist in that location Um, there has to be a circulation That would support it and updrafted the leading edge down dropped further down And he connected with dots by having a few surface observations that were in the opposite direction than the wind And lo and behold His conceptual model was more or less right So this the year is 1889. He published it in the leading atmospheric journal of the time The observations of lower mountains continued in the in that part of the world in the 1930s and 40s And uh, here is a series of works documenting the perturbations created by the Atlas mountain in Algeria Riesengebirge in Germany Poland Crossfell range in northern pennines the eastern Alps and then Czechoslovakia And all but two used just surface observations those two in red Actually used instrumented gliders In addition to surface observations The first aerial study of lee waves of these mountain waves that I that we looked at in the in the o steve diagram Was done by the gentleman called Joachim Kutner Who was a meteorologist student phd student at the university of Helsinki And um, he was from the region of the Riesengebirge And he persuaded his colleagues glider pilots That they should all team up to do the study of these strange Claws which are labeled. It's a local name matzagotl Which is essentially appeared whenever there was a warm wind on the lee side of the mountains And so they did They had more than 10 gliders glider pilots who teamed up to to work with joach and The diagram here is from his phd dissertation from 1930s late 1930s And the structure that I showed you that the steve diagram, which has many more details hence quite more sophisticated That the special structure is here so They did At that time actually they didn't know that the oxygen decreases with height and then And so joach told me That he once he was here in this updraft He kept going and going and going up until he noticed that his fingernails turned blue And he started seeing double suns And he has sufficient faculty with him still To realize that whatever that is he needs to get out of that as soon as possible And so he did and and he landed somewhere far far downstream in poland But what he what he achieved is he he had some instruments on board primarily barometers And they they provided this wonderful wonderful documentation Vela stands for wave matzagotl is this local cloud And he wrote labeled something else He actually said there's this terrible turbulent region down Underneath the wave crests and he called them rotors.  So another flight over the atlantic We can do it quickly here So here's a digital relief map of the western western us There is lots of lots of terrain here complex terrain here That's just to orient you the four corners is here california nevada And most of the mountain ranges here are oriented north south except perhaps for the sierra nevada Which has a southwest northeast orientation? the junta mountains stand out in that group as as being oriented east west But the rest is pretty much north south. What are there? Why there's rocky mountains or they're narrow as the wassage or the grand tithons that depends also on their geological age so Few of the regions here have been studied extensively The first one is our colorado front range The second one is the further to the north. Um, it is medicine bow mountains and larimi range So think of them as essentially the northern extension of the rock is And the reason why they have been studied a lot Perhaps because there are two research aviation facilities right there On on the lee slope or maybe it's the vice versa The research aviation facilities are here because there is a lots of lots of atmospheric phenomena that the mountains generate One is our own here is anchor and our research aviation facility. The other one is university of Wyoming in up in larimi But I want to draw your attention to the third region here and that is down here in the sierra sierra sudden sierra nevada And this what looks like a narrow Opening um in between sierra nevada and the inyo white inyo range It's actually a wide long valley called owens valley And that's the third region that has been studied extensively Where mountain waves and and clouds and all the phenomena i've been talking about have been studied extensively So here's the sudden sierra nevada I blew it up and you can now start to make out different features here in this valley The range sierra nevada range itself Has a gentle upwind slope and a rather steep downslope downslope Which is 30 the slope there is 30 percent boat on the sierra nevada side As well as on the white inyo mountains that slope there is also Approximately 30 degrees The valley itself is Wide as the valleys go I keep having discussions with my european colleagues for whom that is sort of is this a valley and i said yes It is a valley It's just wider than what you are used to um at the bottom of the uh The floor of the valley it is approximately 10 miles 15 kilometers and it's double that ridge to ridge And mount whitney the tallest peak in the lower 4080s is right there The valley Is revered by glider pilots But it's also admired by scientists and and um who Investigated what happens dynamically happens in in that valley for for quite Wow in in several field campaigns and one of those the first one of those was in the 1950s It was called the sierra wave project The glider pilot the gliders instrumented gliders With the primary platform. They had some rudimentary surface observations And also in the later stage of that project. They had instrumented aircraft some b29s and War surplus that the only instrumentation they really had were radars to look look at the terrain Underneath the aircraft so they were not well instrumented But the glider Gliders were instrumented and the pilots were quite skillful and among those pilots Was the gentleman So by that time he he was here on the uh, not in american continent And he was the program manager at the air force research laboratory And not only was he project manager, but he was also a scientist And he flew as as a mission pilot in these missions So what they documented Were primarily the waves they were they were interested in mountain waves in the waves that the sierra sierra generates But since they used gliders they had to go through the rotor and they documented that zone as well So in the left portion of the diagram you see what they labeled A lee wave rotor. So when there is a nice lee wave situation such as I showed you in the diagram The rotor the rotor cloud is there the right there Right above the center of the valley as the photo shows sierra navada is here to the left The inyosa to the right the floor is from left to right and you see in that diagram down there The full lines against stream lines and the rotor circulation is indicated as being present The flow to the right was altogether something else They labeled it a rotor because it was extremely turbulent and rotors have that reputation. So Let's call it the rotor as well. But indeed the flow had a quite a different character There were no indication of the waves at low levels and our understanding today Is that this is a hydraulic jump? It's something a feature called a hydraulic jump that indeed is very turbulent and we could call it That respect it's okay to label it a hydraulic jump rotor Underneath probably you've already read this text Is an account from the chief pilot sierra wave project chief pilot John Robinson in flying through this through this beast And he said that the turbulence in this was far in excess of anything He had ever found in thunderstorms which he had been deliberately soaring for many years And accelerations he they they had accelerometers on on board the gliders And so it was plus five minus four g's accelerations So you either get pushed against the seat Or you are pushed and and flying against the Ceiling of the of your cabin, of course, where you're but belts but a lot but a lot In 2000s we came back in that same area and the The experiment was the terrain induced rotor experiment And we brought in our mother of the instrumentation compared to what the sierra wave project had We we were well well equipped to to unresolve any mysteries any remaining mysteries If only the atmosphere cooperated fully The outline the diagram in the background is actually comes from the sierra wave report And it is a west east cross section across the sierra navada in your ranges and some of the ranges in the great basin Fresno, you can see fresno indicated here Those are the slopes i talked about And um Here are the three aircraft that we used in these missions The galf stream i'll start from the top our nsf n car galf stream five which is our premier platform and this was this Maiden voyage scientific voyage of that aircraft the first field full full flash field campaign that it supported We kept it out of the turbulence We didn't want that there At the middle one is the one from the uk BA 146 from the met office and and the consortium of the universities And the aircraft the lowest aircraft is the university of ayam in king air The horizontal lines indicate the flight tracks these aircraft flew and range of these flight tracks and you can see that the king air The parenthesis includes these lines down in the valley And so what we did with that aircraft We actually did plunge down into the valley and did the box patterns within the valley The aircraft carried in-situ instrumentation, but also carried specialized instrumentation such as the two higher ones drop the drop zones Which are the instrumentation packages that carry sensors for pressure temperature And wind and relative humidity and perhaps you have seen seen one here in our part of our exhibit This is the n car technology This and used widely by many research aviation facilities around the world And the lower the lowest aircraft carried a cloud radar This is a specialized radar That actually seizes not the precipitating part of the cloud But seizes inside the cloud and the reflectors is cloud ice and cloud drops Those those that are too small yet to fall out. So they are they actually form the body of the cloud That is a Doppler radar Which allowed us also to retrieve the velocities inside the cloud and so Here we are Flying our box pattern in the valley You are looking north along Owens valley Um date is 25th of march 2006 And the mission scientist is one the Grubbyshech She is sitting in a co-pilot seat She's not a pilot Pilot is in command But in in that aircraft It's a relatively small aircraft and the mission scientist sits in in the co-pilot seat right next to the pilot And as we emerged we flew part of our box. So here's our part of our pattern We are flying west and we emerged underneath the the rotor cloud and I see this beautiful gap And i'm apt in wrong I'm off of this is beautiful grabbing for my camera And taking the picture of the fun cloud evaporating of the rotor cloud forming And then i'm rudely awakened by the autopilot Saying terrain terrain pull up And My turn I look at the mountains and then I'm mesmerized by the beauty of the east and sierra slopes They're as beautiful as it gets But I realized that the aircraft is moving at 200 220 miles per hour and we are heading straight into the slopes And I look at my pilot and he's calm He's calmly ignoring the terrain terrain pull up warnings and heading for the waypoint For our western waypoint At which he makes a skillful right turn And now we are flying along the slopes of the sierra in exceedingly silky smooth air It's a downdraft, but it's very very smooth And then we reach our northern waypoint He makes another right turn and off we go Completing our box now we are flying toward the inos and facing another of these moments terrain terrain pull up And then repeat repeat We repeated that that several several different altitudes, but we were also we had to fly visual as well And so we could not fly through through the rotor clouds. We had to fly around them So this is a photo from another mission And uh, you see the the uh fern cloud I call it a cloud fall. It looks like it's coming over the mountain waterfall cloud fall And then there is a rotor cloud here, which you can see down here in this diagram This is a cross section valley cross section And the altitude and the solid lines are the Think of them as flow lines the indication following the flow those stream lines And uh, there's a gap in here because we had to fly with the aircraft around that We continued down into the valley And you can contrast the smoothness of these lines would show a nice wave pattern With a crest over the valley another crest over the inos and the jumble of these lines down down in the valley The color scheme indicates the intensity of the turbulence That the aircraft encountered so the warmer could the color it is the more intense that turbulence was I mentioned the cloud radar. So what cloud radar allowed us is is really to don't do those dare devilish things But to actually fly above or below and look at the cloud And what i'm showing here in the inside is is the back scatter From the from the clouds from the cloud over the sierra ridge and the rotor cloud A big unknown before the project was whether we would actually find any ice in that rotor cloud It was april already, but there was some ice in in that cloud which actually was beneficial for us to do the full analysis And to do to reconstruct the flow field through these clouds. So now this is a strip I enlarge this And what you are looking is a vertical velocity recovered From from the back scatter data from the radar and shows a nice Down draft up draft down draft and then up draft again Which mimics the what i've showed you here from the in situ data and we can also Get the horizontal velocity through that wave And both of these are remarkable in their values. So the vertical velocity is minus eight to plus eight meters per second You can notice that part is smooth, but the parts closer to the terrain and Underneath the rotor is is is rather turbulent small-scale structures You can also notice that the horizontal velocity changes Dramatically from somewhere zero is between here green and yellow Two reds and magenta's and 25 meters per second And then there are even patches where the flow is in the opposite direction The boundary layer turbulence is tremendous But that turbulence also in the rotor zone is there with small-scale structures with little rolls and vortices being there This data was great. This was exhilarating. This was the first fantastic data But the nature there were not enough scatterers to actually connect all the dots So we went to Wyoming in winter Where it's called there's ice clouds everywhere And this actually allowed us to reconstruct the flow Over a somewhat smaller mountain, but it's more stable there and and and the wind can be cooperating And and so here you see a cross section across that medicine bow mountain You see the aircraft is here. That's a flight track of the aircraft And the radar is looking down and allowing us to reconstruct the flow field And you can see how the boundary layer is turbulent and the rotor zone even more so What we did with that data is actually to derive the quantitative measure of turbulence Which is the characteristic of the flow and that those turbulent processing and the cascade of energy from larger scale to smaller scale And we got the numbers here. This is so-called edit dissipation rate which is a quantitative measure of the intensity of turbulence and And That turbulence was severe So now I should say that the the the edit dissipation rate is an objective measure It's a quantitative measure and it characterizes the atmospheric flow How is it? How is it felt by the aircraft by the structure of the aircraft and then people on board? Depends on the size of the aircraft So what I labeled as low medium and severe It refers to that size of the aircraft such as the king air, which is somewhere small to medium size In any case it you can see that the wave the turbulence is undetectable. It's smooth Whereas the turbulence zone underneath the rotor Underneath the rotor cloud is severe turbulence. So no aircraft No, no matter how dare devilish the pilot is Should be there But what about those downslope windstorms? I mentioned downslope windstorm didn't I and I even showed you this photo now. It's flipped So this year is is on the right side. This is that hydraulic jump Um flow is from right to left Here's the sweeping flow down the Owens valley and these are meter dust Some sources of off of dust or aerosol or this And it is being carried by the flow at the bottom of the valley and then suddenly it gets picked up and goes A slanted vertical and reaches the base of that cloud that looks awfully similar To a hydraulic jump in a river stream Now there's a different fluids the atmosphere is a compressible fluid. This is Incompressible fluid water. It has a free surface, but there's a remarkable similarity. So there's a construction Construction here on the river the flow gets accelerated over flows over over some bump here Which was intentionally put in place and it gets strongly accelerated as it flows over it and Then it goes through a hydraulic jump where there is a tremendous energy dissipation And emerges on the other side as a slower again subcritical flow. So this is called Hydraulic transition for all of you hydraulic engineers here in the audience So what is this? Why is the atmosphere behaving? apparently as as a hydraulic layer Not all waves that are generated by flow over mountains have the form of those nice trapped lee waves that I showed you um Originally at the beginning of the talk sometimes depending on the upstream wind and more profiles stability The waves actually can take the form where the energy propagates vertically all the energy wave energy is going up And if the mountain is tall enough or conditions as such to to support large amplitudes waves These waves can steepen And you can use the the image of ocean waves Growing and breaking and and then leading to to turbulence their dissipation again This is what we called way breaking region Waves break and this region is now starting to to act as a separator the atmospheric flow Underneath it plunges down the mountain generating very strong winds That cannot actually persist for thousands of kilometers downwind But rather than flow that's behaving like a hydraulic layer Has to go through an adjustment and that adjustment is that jump Which we label hydraulic jump and there is something similar to to a rotor so Here we we live here on the on the lee side of the rocky mountains and this does happen With with the good good frequency here on the front range And you don't want your airport to be right here, right? No, and this is actually where Stapleton sort of was And so it is a good thing that we all have to drive farther to the east to the kansas international as I affectionately call it To get out of of the rotor zone Wow We did capture one of those in the medicine bows as well And we documented it with a cloud radar and we were able to quantify that turbulence In that jump So here's another case of flying over the medicine bows the aircraft is here at a relatively safe altitude The waves are breaking and I can tell you because we also did numerical simulations And and and we I can we were able to reconstruct fully what what happened And so there is a way breaking here the floor is plunging here on the lee side respectable 78 miles per hour And then recovering through a jump and that is now turbulence is expressed slightly differently But it is a severe it is a severe turbulence For you who know what the adr Edr is it was point seven zero Okay So it can get this extreme and This is about one minute long Or a case Where the gusts were official record of 140 miles per hour Again, this is a coastal range mount coastal range. So from the mountains all to the sea And there was a low over the genoa bay of genoa and the anti cyclone high pressure area I mean central europe which created a tremendous pressure gradient and pushed the air over that coastal mountain range The coastal mountain range Is is fairly low um And uh, but nevertheless the the this actually has nice We lost our sound It's it's fairly low coastal mountain range is only about one kilometer Nevertheless, this flow the ebora can be extremely extremely severe This persistence for two days And the average wind speed was 60 miles per hour This is what means being dedicated to measurements Uh Actually the human no matter how heavy and strong cannot sustain when such does gets blown away. So Here you are not looking at the coastal range You are looking at the islands downwinds and you will notice that there is no vegetation. There is no soil They have been all swept away Years and years being beaten by boars Also, you don't want to find yourself down in the seafoag because if you don't die from other reasons you might actually suffocate because This there is a lots of sea spray and it's very very hard to breathe. So No sailing on the borough conditions, especially extreme ones Damage was significant all ferry traffic in the Adriatic was was halted and the economic damage Was tremendous there Boulder is no strangers to strong winds extreme winds and here at the mesa lab in tower a We've had an thermometer for for a very long time at the mast and This is the trace from january 1982 This case is one of the most One of the costliest wind wind storms here in boulder The the economic damage from this wind storm was 20 million dollars And 40 percent of the structures in boulder have been damaged And I guess builders have improved There they they stick to better codes since then But two gusts here in this side was a five and a half hour event time is going from bottom to top And this is continuing. So the where this stops this one starts And you can see the gusts of the borough. I've indicated with the red lines indicate hundred hundred twenty hundred forty miles per hour And there are two gusts here of 137 miles per hour And numerous ones above 120 miles per hour And it is those gusts actually that that do the damage to to the structures Climatology of wind storms in boulder you all live in this town. You've lived here for a while It is not an unknown to you that they peak actually in the cold part of the year January is when there is most of them 30 of the days have something what these label can be labeled as a as a wind storm Are they Ubiquitous is this this phenomenon ubiquitous or is this only a few locations I picked up for you to scare you If you look at the distribution of the global mean wind speed at 80 meters Um, you can start making out some of the mountain ranges the one I talked about cholera rockies El Sierra Nevada The Alps and the Daeneric Alps The New Zealand the Andes. They clearly are the windy places. So it's greenland and for that matter Antarctica as well There are other areas that are not windy clear and here there's a blue area Which means low average wind speed and order to understand why is that you look at the global distribution of the winds And the blue area is the area of intertropical convergence zone Where the surface winds which are marked here in red Actually meet so there's a northeasterly trade winds in the northern hemisphere And the counterpart in the southern hemisphere they meet and all the wind is vertical And goes up and creates tremendous cumulus clouds lots of precipitation, etc But in middle latitudes and in high latitudes the winds come from the west And they they are perpendicular whether it's sometimes from the west something from the east because the weather systems determine What direction and when the winds are perpendicular to the mountain ranges This is when we can expect the phenomena that I talk to you about So if you look we look at the earth topographic map Here the shows where the orography significant orography on the earth is And the our rocky mountains actually is the whole cordillera on the northern american continent continuing down south The greenland both the greenland and Antarctica are very tall Because of the layer of ice on top of the solid rock there and there are beautiful places to study Phenomena orographic phenomena So is Iceland up here? So those of you who visited island or who are planning to visit Iceland or have been there You you be be prepared It gets it gets windy there So to show you that actually the phenomena are quite ubiquitous. I've chosen a spot down here Which is called the elephant island It's the continuation of the Antarctic peninsula And this photo comes from a recent Our nsf anchor Gulfstream 5 mission over the southern ocean The wind is blowing out the screen You are looking in south southwest Toward the elephant island And the elephant island is like a ridge and it's elongated and it's creating beautiful wave clouds And the rotor clouds underneath this was taken from the during the mission photo Looking at the window of the Gulfstream 5 Should you be afraid of flying after all in this talk? Are you afraid of flying? Well, you should not be Unless you are a general aviation pilot In which case you already know quite a bit about this and then you can always learn more And my advice is to be careful Don't show hubris because atmosphere might surprise you no matter how well you know And how good the pilots you are be careful Sailor glider pilots. I know you are there devilish, but you are well trained. So If you are like me who fly commercial airliners most of the time Don't be afraid And there are a number of reasons why not to be afraid the bigger the aircraft The less of an impact on the aircraft's structure From the turbulence all pilots Have meteorological training and well trained to avoid avoid the areas of turbulence Whether it's mountain generated or it's cloud generated turbulence And also The federal aviation administration has invested significant funding over the years In research to make our flying safer to make the skies safer And quite a bit of that research has been done here at anchor in the research applications laboratory Where over in the over the recent decades, they've been working on quantifying the turbulence Getting the information out of the models numerical weather prediction models and getting the quantitative information on turbulence And translating this into the charts For the for the pilots So here the uc this is called gtg graphical turbulence I don't know what the other g stands for And I plotted the chart last evening For a heavy aircraft you can choose the size of the aircraft here And whether you want a mountain wave turbulence or what your cloud turbulence or a mixture of the two For a given forecast time I've got the chart which shows where the regions of turbulence are and most of that turbulence if you look at Down at the chart is labeled as Low turbulence greenish, maybe some some yellows Which it's it's not a problem If pilots detect see areas of stronger turbulence, they of course work on rerouting Flying around that to avoid avoid the worst Also, they fly at approximately 30 000 feet and which gives them quite a bit of altitude to work with in between the flight level and the ground So feel safe, but be curious. Thank you


The majority of studies on high entropy alloys are focused on their phase, microstructure, and mechanical properties. However, the physical properties of these materials are also encouraging. This paper provides a brief overview of the physical properties of high entropy alloys. Emphasis is laid on magnetic, electrical, and thermal properties. This article was authored by Meng Hong Cai.