Good morning everybody, welcome back to another vlog. Today is Thursday and I'm actually headed to my friend Lyra's house. We are going on our little walk-in chat.  I get to see her baby, I just love him. He's so freaking cute and he's almost a year old now, which is crazy. Lyra is one of my friends from high school back in Tennessee but she's lived here for the last few years and she's just the best. So we're gonna spend some time together and then for the rest of the day today, I'm not entirely sure what I'm gonna get up to. I have like a couple errands that I need to run and depending on how much walking we do, I might try to do some sort of like workout. I kind of hurt my shoulder the other night. I genuinely think it's cause I slept on it weird. So I've just been trying to like take it easy and just like walk mostly but it's feeling a lot better today. So I think I'll be able to do like some sort of a workout, like a light workout. And then we will see what we get up to for the rest of the day, but it's a beautiful sunny day. Oh, it's yellow light. And we're gonna start it off with one of my favorite things. Drew and I usually do this on the weekend but I'm doing it on a weekday and that is a walk and a treat. Those are the two most important things, a walk and a treat. So let's do it. It's much later now. It's like noon and oh my God, am I sweaty, but that was so nice. We walked her probably like three miles or so and I actually did some damage at Lulu Lemon. Surprisingly, if you watch my main channel, I tried some of their stuff in like a fitting room trial and video and it was miserable. But a lot of people said to give them another shot and like maybe try to order some stuff online which like they're basically sold out of everything in my size online as well that I wanted anyway.  So I got some stuff for a main channel video. So I'm not gonna show you now. I'll show, you know, in a main channel video soon, I'll try everything on and everything and kind of figure out my sizing but like giving them a second chance. You know what I mean? So that's fun. That was like sort of an impromptu thing and got to have lots of good chats and see beautiful scenery and I loved it. And now I'm heading home and I'm gonna make some lunch. I really need to shower now because I am profusely sweating and I'm not gonna do a workout because I just walked like three, four miles or something. And I'm feeling great. The endorphins are kicking. One of those like, what do you call them? Celebrity tour buses is going by. I wonder if you'll be able to see it. There they go. All right, I started this at a light but now I'm driving, so we'll talk later. We'll catch up later. Home now, making lunch. I'm basically heating up some leftovers. We had like chicken, rice and veggies last night but we actually bought way too many veggies. So I'm air frying some zucchini right now and then I've got some chicken and rice in here and then I'll just make like a little rice bowl that Drew was doing this thing that we saw on TikTok where if you haven't tried the Trader Joe's chili crunchy onion or something like that.  Here's what it looks like. So far, it's looking pretty good. Do you flip it too? No, I'm just gonna let it stay in there. Oh, okay. Dang. That looks really good. Sexual. Okay, it's hard to tell because I put Parmesan cheese and balsamic glaze on it but we got some zucchini, some chicken and some rice and gotta have my favorite golden kiwi on the side, obviously. And then the spicy water of the day is aha, blueberry pomegranate. I actually like this one, Drew said he hates it but I really like it. I think it's delish. And he said his sandwich is good and that he would try that technique again. So in case you're curious, it turned out pretty good. Just got out of the shower. That was fantastic and amazing. Trying to go one more day without washing my hair because I need to test out a hair tool for a main channel video tomorrow but I put on my old navy set that I showed in a couple of blogs ago, I think and I ended up ordering like exchanging it for the right size and it's so cute. So here's what it looks like.  They also had like a shorts version but I don't know, like with fall and winter coming I thought pants would be cute. So I'm actually, it's very echoey in here, hold on. I'm actually going to start, I'm coming in my room to get this book but I think I might like sit on the couch and read for a little while because I'm a little bit ahead on some work. So I'm going to take advantage of it. And I finished Evelyn Hugo, what is it called? Seven Husbands of Evelyn Hugo last night and it was good. I wasn't like as crazy. I think it got way over hyped. It was a really good book. I really enjoyed it and I would highly recommend it. I won't give any spoilers. I just realized I just listed off a bunch of spoilers but I did enjoy it. I really did enjoy it but like, I don't know. I wasn't like blown away but my friend Laura gave me this book or she let me borrow it. The last time I was at her house it's another book by the same author. It's called Malibu Rising. So I'm going to try it out. I'm going to start this. This is how you know you're getting old. I mean, you're just like, I'm just going to tuck into a nice book but I'm really enjoying getting back into reading and also I'm trying to read. I think I mentioned this like all of my physical books that I have. I have this one. I have It Happened One Summer that I haven't started yet but I will after this. And then I've got like a few more and then I think I'm going to go back to my Kindle or maybe I'll like interchange with the Kindle in between because it's just so much easier, especially at night. I read like every single night before going to bed and it's just like part of my nightly routine. I like fill out my little journal and then I read and it's so peaceful and it's just so much easier laying in bed reading the Kindle but I don't know, we'll see. But for now, we're going to have some reading time. It's like one PM. So hi, it's the next day. I'm actually getting ready to do some filming. It's my first like filming day since being in this new setup. I love it so much and everything has held up so far with the command strips and all that but I'm actually doing an impromptu main channel video. It was what I showed you yesterday, all the Lululemon stuff I got. And then I think I might do a fitting room video today. I don't know. It's going to depend on how much time I have because I actually have dinner plans tonight. I'm going to meet up with some friends that I've been friends with online for like a few years but I haven't met in person except I've met one of them in person but I haven't met the other in person. So that'll be really fun to we're going to get like some drinks and some dinner. It's at one of my favorite places. It's out near like West Hollywood and it's called Grassie's Modray. It's like a vegan place but it's so good. It'll be really fun to catch up and kind of like hang and have some girl time but in the meantime I have a lot of work to do so let's get to it. And also this, ugh. I did book a hair appointment today with a new hairstylist here in LA that I have never used before. She was recommended on Instagram. So hopefully she can help me fix my baby bangs situation. All right, it's a little while later. I've changed and I actually am wearing my cute little handmade shirt that I got from the Melrose Trading Post if you saw it like a couple of vlogs ago. It's so cute. I am just wearing like a normal brown color bra underneath it. I don't really care. And the reason I change is because I am going to do a fitting room video today. I'm going to head out and do that right now. Like it's the afternoon though so it's going to be kind of busy. We'll see. But we're going to ignore that and this is what I decided to pair it with. These pants are from ASOS I think, I would say, and they're like probably my favorite pants. And then my yellow Converse and that's the fit. Let's go to the fitting room. My goodness. That was an experience, that's for sure. It was one of those experiences where like nothing is going your way. First of all, sweating profusely. It was super busy in there. Not to mention it just wasn't the most fantastic selection or my size if you feel what I'm saying. But overall it was fine. Like I feel fine, I don't feel like sad. Sometimes I feel like crap after leaving fitting rooms but I actually feel fine. So now I'm going to head home. I have about two hours until I have to leave again because I'm going out for drinks like I said, or dinner. I don't know why I keep saying drinks. It's literally dinner. Apparently I'm excited to have a drink. I'm probably just going to Uber there.  So let's do it. Ignore my hair. I was just laying down on the couch. I think I dozed off for a second but I'm getting ready now or I'm going to start getting ready now. And I'm trying to decide what I'm going to wear to dinner tonight because it's definitely like, LA is funny because it'll be like super hot during the day and then it cools off at night. So I'm like, do I need to wear something more like long sleeve? Honestly no, because it's like 80 degrees outside but this is what I came up with so far. I will be cleaning this room later but not right now. So I have this like one shoulder top. I actually showed this in a main channel video. This one shoulder top and then this thrifted midi skirt go kind of cute together. And then I was thinking maybe like some cowboy boots. I don't know if that's too dressed up but honestly this place can go either way. Like it can be really dressy or it can be like pretty cash. And it is like a Friday night. So I'm thinking maybe a little more dressy might be the vibe. I've got to like fix my hair and touch up my makeup but otherwise my only other option, where is it? The other one that I was kind of thinking is this brown dress. I've worn it before. I wore it when we came and visited here back in April before we moved back. And it's like kind of a more body con type of thing. This is totally out of focus. Okay, great. But I feel like it might be a little too warm out right now for that to happen. And our reservations are at 7.30. The sun sets at like eight. I'm literally gonna sit outside and see like how warm it is. Oh yeah, it's fine. It'll be fine. Anyway, okay, enough of that. Just had to make sure, my house is frigid. I just like to keep my AC very, very, very cold. So I'll grab my cowboy boots. And then I will actually go ahead and grab this cute little purse that I thrifted recently. It's from Thread Up. And it's like a handmade in Italy cutie little purse like this. Do I wanna wear something else? Oh God, I do this all the time. Ah, I can't decide the vibe. Can you tell I don't get out much? I'm just gonna stick with it. I'm gonna own it. Okay, let's touch up our hair and makeup and then get some dinner.


I didn't think so. The answer we were looking for was what's two times faster. Clearly, you had no idea what that means, so I'll explain. You had two drinks. The lady's on either side of you had one drink. All of them tabled us out of all that about the same rate. Heather, it's your turn. I'll take drug majors for $400. I'm your answer. This is the most common bugger. And then we spaced ourselves, and I remember wiping the blood off and the tears and everything. And I said, I'm so sorry somebody's hurt you. Do I know you? Why are you apologizing to me? She said, you don't recognize me. I said, I'm sorry. I don't. She said, I was one of your students in your self-defense class.  I kicked and I punched. And I did everything you taught me to do. She said, and I failed you. See, she was in shock. She felt she had betrayed me in the reality of April 12, 1973, approximately 260.


For you, let me get in this camera, right? My name is Ken Walsh. I'm an engineer for everything else. My bachelor's in electrical engineering, my master's in ocean engineering. I worked at the Navy Lab for 43 years. And when I retired in 2002, I went back to school and studied history and economics. And I got a PhD. So I spent two years looking at Newport's history, particularly from an economics standpoint, which turned out to be very interesting. Had a thriving international economy. Turns out that the farms on this island and the adjacent, Hog Island, Gold Island, like that, were very productive. Twice as productive as any of the farms on a mainland, mainly because the predators couldn't get to these farms. And if a wolf or another predator managed to get to the island, you got hunted down and gotten rid of. So the island farms were twice as productive as the mainland. That gave them something to sell. They started selling up and down the coast and down to the Caribbean. It turned out that there were three major ports at the beginning of the American Revolution, Halifax in Canada, Newport, and New York. The problem with New York was that the water was too shallow to get in there with major warships. The British, in order to shut down the trade, occupied Newport from 76 to 79. And the prevailing opinion was that this action by the British, which did depress the economy here severely, put a permanent crimp in Newport economy and it never recovered. It turned out to be not so. Let's say I'm an engineer. If I went in and said you've got to have more samples on a set of data because of the Nyquist criteria, everybody would say, huh, not good. So what I did is I put this quote in and now most people recognized Arthur Conan Doyle, a studying scholar at the first of the Holmes novels. And he has Holmes saying it is a capital mistake to theorize before one has data. It biases the judgment. A lot of the contemporary literature, they didn't bother checking. So we went in and we checked. We used the local records. We go to Historical Society in Newport, what you'll find is the tax records going back all the way to 1772.  There was an industrial revolution in Providence in the late 1770s. Slater Mill started it and then went on from there. And then what that did, it produced a phenomenon called creative destruction. What happens is that some new product comes along off a buyer's shift from the old product to the new product. People who were making the old product go out of business. And what happened was that Newport had to shift from a mercantile economy to a tourist industry and basically to what we've got now. The colony was founded in 1639 and Newport was set up the following year. We got a charter. Rhode Island was the only non-secular state in the world when that charter was passed. It was signed by the king. The only place you could go where you couldn't, the legal structure could not make laws regarding religion. And because of that, all the non-conformists ended up in Rhode Island because they were thrown out of every place else. A couple of examples. Aaron Lopez was a refugee from Portugal. He came with his family about, and then Tom Robinson was a quaker, neither of which were very welcome any place else. When Lopez went to, his family went to New York from Portugal because they had relatives in New York City. Founding fathers of New York said, we don't want you guys here, right? They said, go to Newport. They'll take anybody, right? So they went to Newport. Aaron Lopez became the richest guy in Newport in 1775. Excellent merchant. Newport became the major commercial center for the East Coast by 1760. They were trading with England for manufactured goods. They were trading and would produce, take the manufactured goods and trade them, trade down to the Caribbean for sugar, molasses, make rum, trade that to Africa back to the Caribbean and then back up here for more rum. In terms of religious freedom, in 1659 two quakers, well three quakers from here went up to Boston and two of them were men, one woman, Mary Dyer. The two men were tried and hung. Mary Dyer came back to Newport following years she would back up to Boston and they tried her and hung her too. It was very dangerous outside this colony for anybody who didn't total line on whatever the state religion happened to be. Colonial merchants traded with England due to economics and advantages. When it was profitable, they bypassed the British law. British law said that if you trade with a foreign country, like a Dutch or a French or Italians, you had to stop in England before you came home and pay your taxes. The problem was that it was too costly for the British Navy to effectively stop the trade. The result was a general disrespect for the English law and customs service. Charles II named Edward Randolph as a surveyor of taxes. They sent him over to see what was going on. Randolph, the courts, the governor in all the inhabitants obstructed the British customs collectors and supported the smugglers. Randolph's comment was the need of law in the government in Newport. The city had become a major port where there was much illegal trade. In Newport, the courts were used to harass the government customs officials. In many cases, a smuggler was caught. Before they could bring him to trial, the evidence disappeared. The witnesses disappeared and the guy who was found not guilty. If a customs inspector crossed the line, he was tried and convicted immediately. Speedy justice. Documentary evidence was sent through the British Custom Service to England describing the infamous practices of the colonials. The use of bribery and fraudulent papers and the highly effective way of evading the English law. Up until 1760, Newport's economy was unconstrained. Nobody could keep track of it. In fact, the Navigation Acts but before 1763, the Navigation Acts provided a workable system. If it was profitable, they'd go to England. If it wasn't, they'd just bypass England and not worry about them. The shipping events were set up in tables. The way you could find out what the shipping events were is you go to the newspaper and the Custom House posted which ships came in which ships would go out and where they were coming and going from. You can see the sloops and the destinations. One of the things you gotta watch out for when you're reading these old newspapers, the first letter that looks like an F, it's really an S. If you look in this list, you get Turk Island and Newcastle and this is right here. That's an S. Not an F. Now, here are the destinations of the shipping between 1762 and 1763. If you look at this, you can see that most of the commerce was local. You had 494 ships in local trade. To the Caribbean, you had 133 ships trading back and forth to the Caribbean. In the whaling, you had four. Nova Scotia had 15. What they were doing in Nova Scotia, the Brits would ship manufactured goods to Nova Scotia. These guys would go to Nova Scotia and pick up those trade goods. They were going to Africa. The only reason they were going to Africa was in the slave trade. Out of some 600 ships coming and going, only 12 were in the slave trade. This is some of the routes. In the slave trade, they would go this way. They were trading not only for slaves but for gold. This is the gold coast. They came back around through the Caribbean and back and forth to England, back and forth this way. The ships used, most of the ships were sloops of Briggs. Some of them were a little larger. They would trade fish, grain, meat, lumber, whale oil, and ships, tobacco. They would trade with the West Indies with slaves, fish, trade goods, lumber, livestock. The King of England forbade the export of horses from England because he was afraid he wouldn't have enough horses for his cattle rig. When he did that, all the Newport people who were raising horses started trading quick with the Caribbean because the price went up. This gives you a list of things that were advertised for sale in the Newport people. The colony of Sunam is a Dutch colony on the North Coast. They also hunt their wheels in the Falcons. This is a picture that was painted of a tavern scene by John Greenwood. You've got Cook, you've got Ezra Hopkins, Stefan Hopkins, and Joseph Wanton. Nobody liked him. There's a guy going to put a punch on his head and he's passed out from drinking too much, and this guy's throwing up in his pocket. It turned out that he's a Tory, and when the Newport was occupied by the British, they made him the Chief High Sheriff. He was not well liked. This picture, by the way, you can get off the web at St. Louis Op Museum as it posted. The price of molasses on the French islands in the Caribbean was half the price it was on the British islands. There's a big advantage of trading with the French islands, right? One of the techniques for justifying trade with the islands under flag of truce, what they would do is they would take one Frenchman and a shipload of cargo and go down and trade with the French islands. The other method they would do is they would sail into one of the Spanish islands, put a Spanish crew on the boat, and then into the French island and do the trading. At one point the little town of Monte Cristo was on the north coast of Espanola. It was right next to the border of what is now Haiti, the French colony, and they would go to that port and meet the French ship there and they would trade. They wouldn't even take the stuff as short. Aaron Lopez, Richard's man on Newport in 1775. He had a farm in Portsmouth. He purchased the farm in 1758 on the corner of Bremen's Lane and it's on Wapping Road that goes down to the winery if you want to go look for it a lot. He had a farm house in a barn and easy access to the second it. The claim to fame for this farm was that you could bring boats into the second it, unload on the beach above the farm, haul the stuff up the road, store it in the farm, and take it into Newport as if it came from Boston. Lopez did on at least one occasion because we sort of let him. He wrote a letter to the Dutch merchants. Had the Dutch merchants ship their order to the Dutch colony on South America. No taxes. He was in a sloop down, picked the stuff up, bring it back up into the river, load it in the farm and then down into Newport. Bremen's Lane is the Wapping. This is the road going down to the beach. This is such well known to the British that when Lieutenant Fage drew his map they named the bay Lopez Bay and they actually took over his farm house and made a fortress out of it. Now, George III took over after George II died in his water closet. He was 77 years old. He died sitting on his throne in his water closet and his grandson took it over. George III. Now, the seven years war in Europe was a French and Indian war here. It was basically that turned out to be the root cause of the American Revolution if you believe that. William Pitt fighting the French doubled the English national debt. Right? When he died in his water closet his grandson, George III, took it over. George III wasn't interested in the war. He didn't like Pitt either. And he replaced the illibute above him. George III negotiated an easy settlement of the Seven Years War with the French and left them in an economic condition where they could provide financial and military aid to the colonies. The enemy of your enemy is your friend. Right? So, anyway, the success of Britain in the Seven Years War made them overconfident. Pitt's expenditures during the Seven Years War, they doubled the British national debt. The objectives of the British government after the Seven Years War was get the Canadians under control. Now they got Canada from the French. France didn't want Canada. Canada was a money sink. Right? And they were trying to get the Canadians under control. They wanted to get the colonies to cooperate. Right? And the colonies to pay the cost of the defense. Right? Right here the revolution started. When they started to try to make the colonies pay the English national debt. Newport was under control of a group of major merchants. The merchants controlled the international trade and the local trade. They corrupted the British government officials and performed a prodigious amount of smuggling. Right? The customs office's salary was 100 pounds a year. It was about 480 Spanish dollars. Right? Now customs official was making over 6,000 Spanish dollars a year under the table from the merchants. So you can guess who the size he was on. Right? The major merchants formed the backbone of the Newport economy. Members in this group in 1775 paid about $10 each in taxes and had about 70-70% of the wealth. These people fit the description of barbarians they were aggressive traders. They really had a clear idea of what they wanted to do. They wanted to make money profit. Right? And that drove the whole setup. Now taxes on a basis for this I think was done in 1772. All right? Merchants paid $24 Spanish dollars. Farmer was 16. Distiller was 11. Comptroller and like that down the line. And until you get to a ship captain he didn't have any property. These are property taxes. He may have had a house on a postage stamp lot in Newport so he didn't pay much. Farmer's Merchants and Distillers paid the most of their taxes. They accumulated most of the wealth and property and they paid most of the taxes. The Newport tax base was pretty stable between 1772 and 1775. You can see them sort of overlay. The taxes were property tax. Whenever they had a project they had to do they would figure out how much it was going to cost and then they would divide it up proportionally among all of Newport citizens. Most of everybody in Newport paid taxes. The mean value of in Newport of the town was about a little over a million Spanish dollars. And plus or minus about 200,000. That's an important number it turns out because that's the number we use to see whether or not Newport recovered after the revolution. Washington was closed Bunker Hill was fought 1775 2,000 people out of 5,000 were smart enough to leave Newport the only people they left behind were the Tories. They were the guy that was getting punch on his head in his pocket. Lopez moved up to a small town in Massachusetts Joseph Anthony moved to Pennsylvania and there's 2,000 people left with better places. Port of Boston was closed in the wake of the Boston Tea Party. Guess where all those merchants went they went to Newport and went to Newport. By the way when the British tried to take Bunker Hill they learned a hard lesson right? They lost 47% 48% of their troops trying to take Bunker Hill and the reason for it was the Colonials hid behind the stone walls and didn't stand up straight and they just shot these guys as they killed. The second thing they did was that they shot the officers first right? In the British Army the troops of cannon fodder they were from the low class that don't count for anything the officers from the noble class usually and they provided all the direction once the officer was dead these guys just milled around right? Bunker Hill, General Sullivan the only reason they didn't lose more was that Sullivan ran out of ammunition In an article published in the Newport Mercury in August of 1775 it was a letter it was sent from Britain to the Brethren quotes Quakers and it said the large fleet in Army that was being ready to sail against them that was one of the things that prompted the 2,000 people to leave Newport right? the Rose Swan and the Kingfisher made preparations to cannonade Newport but they never did they went to Jamestown and burned a bunch of buildings between the East and West Ferry the Rose and another armed schooner attacked Prudence Island but there wasn't anybody there I think they wrecked a windmill and Prudence Island had already been evacuated now of the three ports Halifax the British had Newport they occupied they shut down the port and then New York they had that picture was taken on siege day in 1978 but British arrived 6,000 regulars half British, half Hessian closed the port martial law, no civil government military courts were used for everything people who spoke up against the British were thrown in the prison ship no freedom of speech British collected all the firearms no right to bear arms now when you look at the bill of rights you can tell who is lobbying we had personal experience in Newport as to what happens when you get an army in there to suppress you these are forts along the top of Portsmouth the ferry is out here going out to Tividon Bristol ferry is here Lopez Farm was made into a fortress the Elms was made into a fortress what they would do is take the house and they would raise a dirt wall around it and the dirt wall would be thick enough and high enough to protect them from small arms fire and some light cannon right now Benjamin Franklin negotiated a treaty with the French for mutual aid the first item under the treaty the king of France sent Admiral de Stang and the Toulon fleet here to help out he went down to Sandy Hook to try to attack the British fleet that was down there under Admiral Howell turned out that his ships had a 25 foot draft big ships, lots of guns the water was only 15 feet deep so he couldn't get at them eventually he and Washington were going back and forth Washington said go to Newport Deepwater Port and help General Sullivan so he comes up to Newport talks to General Sullivan and the plan was he was going to land his troops on the west coast near Dyer Island Sullivan was going to attack across from Fargo and Fury and they were going to make a pencil movement and cut off the troops in the north part of the island well he was creating Newport had made a decision that if the French got into the bay he was going to pull all his troops back down to Newport and leave nobody up on the north end of the island so what happened was that's what he did he pulled all his troops back and he got this defensive line this is the internal line he had built and then he pulled all his troops back he built this line while the Colonial troops were trying to get the way down the island this is Cod's Redoubt this is where the Colonials were up on Honeyman Hill eventually they came around this way seized a little damage to Newport most of it action took place up on Valley Road in Middletown and there was a rear garden in Portsmouth that covered withdrawal into August the French fleet came into the bay and as they came into the bay they had a gunfire can dual with the short batteries the British had set up the British didn't do any damage apparently the the French didn't do much damage either again English forts this is Greenland going out this is the Colonials coming down this is Valley Road now 1979 the British hike behind in New York decides that all these guys sitting up in Newport aren't doing any good to anybody except they're making a target of themselves so they recall them in 1779 they recalled all the British out of Newport down to New York and they were going to use them in campaigns in the southern colonies now the British weren't really interested in New England New England was basically a competitor to England right but they were interested in the southern colonies because that's where they got their cotton for the cotton industry so they were going to pull them out and work them down there so what happened in 1780 Russia on boat comes with another French fleet land and they come and buy Newport no English so they pulled into Newport and set up they had quite a few sick because of the scurvy and they had to have them here let them recover this is a map drawn for Russian boat showing the French and the interesting part about that is that it tells you here which ones are which and all numbered turned out the French built three new forts and then rebuilt the English forts that were made in this exterior defense line that we were looking at and so the other thing they did goes to show you what we were just doing and Compton Rushamble was in charge of the Army Brendan houses where he had his headquarters when he was here you can see you can look at the plaque on the wall these are on Washington street and they were locations where the French military had the sub headquarters the French and the local militia built up all these forts they positioned the French warships in a harbor to defend Newport against a British counter attack Rushamble left the detachment of French military which combined with the colonial militia defended Newport for the rest of the war Rushamble brought money right the French government had given Rushamble a large quantity of silver that he could spend to buy troops and like that the most important thing for Newport's economy was that the ships brought money and customers you can look at the Newport newspaper in this time era advertisements written in French trying to sell stuff that are French soldiers right anyway Rushamble was one of the merchants that left Newport but he didn't go very far he went over to Narragansett and stayed out of the way when the English left he came back and he got between the French military and the local farmers because he knew everybody right and he started making money he used his money to purchase a ship and he got into the far eastern Baltic trade John Gibbs and Walter Channing came back and they reestablished their trading firms and Gibbs and Channing merged their businesses in 1793 and by 1800 they owned seven 300 ton ships one 600 ton ship three brigs and one schooner so Newport's reestablishing its status as a merchant community now what's the worth of Newport based on the tax returns 1775 we figured places worth a million and some it lost half its value when the 2000 people left the British ruined whatever was left and by the time the French arrived the value of the material in the town was like half of what it was before 1782 the economy is growing like a weed right 15% per year and you get down in here 1796 the town is worth more than it was here 1801 it's worth this and when you look at the growth rate this is about where it would be if there had been no war and it was growing at a nominal 1% to 2% now I work for the federal government for 43 years I know what it's like it wasn't good to these folks between 1801 and 1812 there were 4 groups with 4 different agendas the French under Napoleon was trying to take all of Europe the English were trying to stop the French the United States wanted the British out of the Americas 1803 we bought the Louisiana Purchase the British are selling guns to the Indians in ammunition through Canada they wanted them out of there and so the people in the congress were predominantly southern large land owners ok and southern politicians and they wanted to expand westward their states and so anyway the merchants in Newport were doing a good business because they were neutrals stuff to everybody and having a good time the British were impressing seamen right now a British seamen was making something like $7.50 a month ok a US merchant seamen at the time was making $18 a month you can guess where those British sailors wanted to go work now so the British would stop a ship and say hey that guy looks like he's in English and grab him so you had a crew of 5 you had a crew of 4 they would make port and they would hire a seamen who was probably a British deserter coming back to work for the merchants the British Royal Navy had 600 cruising warships 175 ships of the line they needed a lot of people and it was not a job they could easily recruit to Nelson wiped out the French Navy basically he beat the French in Egypt he crushed the Danish fleet and then he went to Trafalgar and got rid of the Napoleon's remaining forces so after that date the British controlled the ocean Americans were making a lot of money it was stealing the British commerce right and British were involved in this war but the Americans would come in and trade with it whatever by 1811 the merchant marine fleet expanded from half a million tons to almost a million tons double they needed sailors for their ship they recruited from all countries they were paying $16 $18 a month of able body compared to the British who paid $7 the British claimed that at least 20,000 British subjects deserted the Navy to serve the merchant marine the American estimate was about 9,000 the justification for the war of 1812 for the US government was that this enslavement of white American seamen on British ships right the driving motivation however was the intended expansion westward into the Louisiana Purchase and the British was selling guns to the Indians true objective of the war of 1812 was to attack Canada and remove the British from the Americas not the Navy or not the ships but that and Congress tried to stop US goods from reaching Britain embargo act of 1807 and the non intercost act of 1809 disaster for Newport shut it down we couldn't trade reform ports there goes our merchant the British weren't injured at all they obtained their food by trading with South America they found new markets for their manufacture goods in South America British ships took over the maritime trade that the American ships had been stopped in addition the United States discharged the British born sailors they could no longer employ they all went back to work for the British it was a windfall for the British and it ruined the American trade the other thing was that normally the goods from the Midwest would come through like to Newport and Newport would trade them out to the Europeans well Newport couldn't ship so what they did is they moved the goods to the Canadian border the American merchants had a field day the American exports and imports dropped from 114 million and 8 to 20 million down by a factor of 5 government revenue dropped to 13 million from 13 million to 6 million even though the tax rate was doubled the senior merchants in Newport were reaching the end of their lifespan what had happened Slater Mill in Pataka was started up you started to have an industrial revolution happening in Providence area so the merchants in the Providence area didn't have to go to England to get their manufacturing goods they got them right there they could trade them at savings compared to the Newport merchants and they competed very aggressively the other thing what's happening is there's no new investment in Newport shipping it's being invested up in Providence George Gibbs died in 1803 and at the time Gibbs was the highest taxpayer George Gibbs look at these dates these are the major Newport taxpayers in 1801 and look at when they're dying so by 1820 there's one major taxpayer left alive everybody else is dead and their businesses are coming apart Channing announced that he was going to take over the partnership of Gibbs and Channing he continued to operate after George Gibbs died and dissolved that day and became also Channing and cooperated top 10 taxpayers in 1793 9 had died before the end of the war in 1812 the 10th was James Robinson died in 1817 at the age of 79 so you can see the whole mercantile structure of Newport is collapsing by 1820 of the 9 that survived 3 more died 5 minor merchants and 1 major merchant Thomas Dennis to rebuild Newport and what happened if you look at Samuel Whitehorn his house is down on Thames Street he and his brother were partners in the distillery he was a junior partner in the distillery he imported molasses and sold some of that at retail and still likely in the slave trade is likely that he was taking rum to Africa and slaves to some of the islands in the Caribbean and then coming back up with molasses he went bankrupt he lost a couple of ships and he went bankrupt in 1844 that's the house he built on Thames Street up until about 1807 they were still operating at a profit even in the adverse trading environment mainly because the costs were up so high 1815 after the war of 1812 the harbor was wrecked by a hurricane and the porcelain and bridge was wiped out had there been no more changes Newport might have recovered however the industrial revolution in Rhode Island centered in Providence brought big changes after 1815 this is what's going on here's Providence here's Newport you can see building up 1780 this is where the British occupied it dropped it down and it starts building up again now right about here steam engine in the US takes off Providence takes off Newport continues on at the same growth rate okay this increase in here in railroad and steam ships Providence became a big manufacturing center for steam engines you're building railroad engines all kinds of things and during the Civil War the woolens manufacturers in the northern part of the state made a fletchum they produced most of the woolen uniforms for the United States Army and they were doing quite well we ended up with four mills in Newport two woolen, two cotton the woolen mills burned down the cotton mills are still there this is Perry Mill which is on a corner by the post office downtown and that's Quidditch Mill which is for the down Thames street on the right hand side 1836 Newport had mills and both cotton and woolen cloth it's Warwick in Newport you can see 1809 it's 6, 12, 11 15, 29 we had four in 1840 and the reason for that by the way is that we don't have any rivers on the island none that are with anything I grew up in Winsocket the Blackstone River coming down to power the mills and to provide water for washing the cloth and all the northern part of the state is growing like a weed banking capital it's Newport going along look at this is in millions 15, 208 million dollars in banking capital what's happening to the slave trade what did you build up then the last guy we know that was in the slave trade was Whitehorn and he was at a very low level the slavery you know, out in Newport and all the slavers went to Bristol and after that Bristol for a while the economics of the slave trade are interesting because what would happen is that they would take the rum and other goods from here trade it to Africa pick up the slaves in Africa take them to the Caribbean in that loop gave them a factor of 10 increase in value so the slavers in that loop made a lot of money they increased their profits by a factor of 10 but most of the the economy the slave trade per se trading goods back and forth up and down the coast and like that there were 22 distillers down on Washington street down in that area and I read a report from one of the town council meetings in Newport that said that these people were complaining because a woman of good virtue could not walk down Washington street without getting drunk from the distiller fumes and they were complaining because of the air pollution so but the the slave trade became very consequential after this time but he was up in Bristol they kicked all the slave traders out of Newport oh shoot this was before the war of 1812 I forget exactly when they outlawed the slave trade in Newport I didn't stop Whitehorn was trading up until 1844 but from what I understand he was the only one left and he was doing it because they needed molasses for their distillery by the way most of the rum from the distilleries in Newport were trading up and down the coast I think they said two thirds of the rum was drunk in the colonies and a third of it was used in the trade alright yes the thing that put the finish to the Newport trading was the railroad they built a railroad coming up from New York along the coast up through Providence, up to Boston and the coastal trade out of Newport depended on picking up produce along the way and selling it in New York and back when the train was there train does 30 miles an hour what does the sailboat do train arrives on time the sailboat's stuck with the wind or whatever as long as the sailboat was the only mode of transportation Newport was doing pretty good when the train came along to compete with them it ruined the coastal trade Newport basically 1811 when Channing retired it folded up cloth mills established in here railroad and shipyard the Newport shipyards were making wooden ships for the coastal trade when the coastal trade went away they got in a lot of trouble they did some whaling farming and fishing there was an international depression in 1857 which hurt a lot of these businesses it's the same map the same basically we saw the war of 1812 we can see the expansion tourist industry now the farmers in the southern colonies in the southern states would come up with their families and spend their time in the summer in Newport at the same time the Newport merchants would be making deals with them for either transporting their cotton or bringing it up here to be manufactured into cloth they were getting in the order 500 visitors per week during the tourist season social life was informal and the technology helped the Newport tourism industry because the steam ships and the railroads made it easier to connect from Charleston and Savannah to New York and Newport and the Fall River line was bringing people up from New York up through to Newport they would get on the train they would end up going up to Boston the problem we're now these people they're from the south they're running cotton they're growing cotton Civil War wiped that out now Bellevue Avenue in 1850 was a dirt road and you could buy land on Bellevue Avenue at $300 an acre land speculators moved in they bought it for $300 to $400 per acre and 1853 they were selling it for $2,000 to $5,000 an acre right now this come out of the city documents so it's reasonably good up until the Civil War was a mixed population of upper middle class both the south and the north many cases the heads of the family would be in business with each other they opened a hotel Bellevue hotel opened on St. Catherine Street landing hotel opened on Bellevue what about clipper ships going to China say again clipper ships going to China they had some they were doing that before the war of 1812 that's where they were making their China runs and the Baltic runs during the war of 1812 the British ran a blockade on Newport and caught those ships coming back that trade more or less collapsed that's the fishing and ocean house now conclusions the occupation by the British 1776 to 79 stopped the trade chased away a lot of prominent merchants but it didn't do any major damage to the town's infrastructure oh it did do sorry it did not change the trading environment as long as everybody was using wooden ships and there was no overland transportation things were pretty good for Newport Newport recovered and was back in the international trading business by 1801 wasn't Newport sort of a center of piracy to Newport was a center of pretty much anything there were people running ships in Newport that were considered privateers depending on which side of the war you were on and pirates if you weren't and some of them decided they were still going to be privateers even though the war was over which made them pirates by everybody's you know what happened basically is the people from from Providence had significant advantage in the way they were manufacturing goods there and the merchants traded it out and they just put Newport out of the trading business the personally coined this thing Joseph Schrumper he was a professor of economics at Harvard but basically it's the new thing comes in all the customers desert the old thing for the new thing the people were doing the old thing go out of business capitalistic systems get changed from the inside new goods, new market methods Slater Mill was the start of Newport's problem once Slater Mill in the northern part of Rhode Island started in its industrial revolution Newport was in bad trouble the difficulty with Newport is you can't get to it once you get away from travel by ship you got you got if you got somebody coming down from Providence he's got to come across the Mount Hope or you got to come across from Tividen and then he's got to come down the island then he's got to go over to Jamestown on the ferry and then from Jamestown to now against it on the ferry whereas somebody in Providence who wants to go to New York he gets on a train and goes down the coast so it's a very high place to get to second there's no water resources no water power on the island so they were limited until they started getting steam engines which were manufactured in Providence by the way steam engines they couldn't run their factories and then they had to bring the coal in you notice all the factories they were making either cotton or woolen cloth were down on Thames Street and the reason for it was that they had to run on coal the only way to get coal to them is to bring them by ship so they were at a competitive disadvantage because you go up to Providence you got water power not to bring coal you don't have to ship it so it was a problem the Providence merchants just competed them out of business Nupa just couldn't change because he didn't have the resources so when did they get into the the tourist business I mean look at the houses New Yorkers coming when did all that start basically after the war of 1812 in that timeframe what was happening is that the rich people in the southern states where they were a matter of fact or growing cotton and other things where they had trading relationships with the merchants in Newport they bring their families up here in the spring go through the summer and in the fall they go back south and this is a nice place to sit out the hot summer in Savannah like that that's basically how it started the Civil War put an end to that because those people no longer had any money and then the people from New York who were making all their money on railroads and whatever started keeping an eye on Newport Newport is a nice place it's not crowded it's not hot it's relatively cool in the summer compared to this place and so they decided this is a nice place to have their summer homes and moved their people out of New York and wherever else they were it turns out that the people from New York came up into Newport and built their houses out of stone the people in Philadelphia who were rich moved up to Jamestown and built their houses out of wood there are very few wooden houses left in Jamestown there's a lot of stone structures left over at Newport the beneficiary right now of a lot of that stone structure is South Virginia University most of their big buildings are left over mansions donated to them and converted over to the school anyway more of 1812 and it's aftermath really put a finishing touch to Newport British occupation did not finish Newport that's the revolution around and finish Newport


Okay, we'll get started. This is Craig talking about defending VoIP. Hi everyone, I'm Craig Asking, so I work for a couple of companies. One of them is NetSIP, who's a VoIP provider, so we have a bit of practical experience in this particular arena. Yes, they really are out to get you all day, all the time. Why are they after you? Money. Pure and simple. It's either they're selling Globestar Satellite or mobile phone access in various African countries, or more commonly these days it's some kind of premium number overseas where they actually get a kickback of the revenue. It is large amounts of money now. There was a group late last year in Eastern Europe that was caught who'd done about 11 million euro worth of premium number calling, of which they were getting about a 10% kickback. They were going so well they actually set up a franchise system where they were leasing out access to these numbers to people who had hacked your system. More profitable than McDonald's I guess. Okay, here is some of the things, basically the logged attacks against some of our systems. As you can see there's a distinct spike on Mondays. It's actually early Monday which is the weekend on Sunday in the US. The reason they do this is they want to do these attacks when you're not there. They want to get a good couple of hours in where they can smash your systems. Go hard, 30 channels, 60 channels, 100 channels, simultaneous calls all up, going to these premium numbers. Some of them can be dollars per minute. All going to your phone bill. Okay, do you really need to be on the internet for your SIP? Is it just a couple of phones in your office? If so, get behind the firewall. Don't let 5060 UDP through. Don't let TCP 5060 UDP through. If you do have roaming people put them behind a VPN. VPN access only. There are some hard phones these days that can connect to open VPN. Back to your call. Most mobile devices that do SIP can also do SIP tunnels. Seriously don't get on the internet unless you really need to be there. And if you are there try and whitelist certain IPs and block everything else. So if you can do that, problem solved. If you can't, this is the rest of the story. First thing, defense in depth. Use strong passwords. Don't use 1, 2, 3, 4, 5, 6. Don't use extension 100 with a password of 100. That will be attempt number 2 in the SIP thing. SIP attacks. Generally we see attack rates of about 1 to 2 megabits a second. That's about anywhere between 500 to 1,000 registration attempts a second against your system. They'll start at Anthony and work their way down to Z and extension 100 all the way through to 999. They'll just keep going. Use fail to ban or something like that. Fail to ban or watch your asterisk logs for these attempts. And once someone's tried 3 or 4 or 5 times, whatever you configure it will do an action of your choice. Generally the default ones that they've got, which are quite good, is it will add an IP tables rule to firewall it and then send you off an email saying the following IP address has been banned. Make sure you whitelist your office network. I've seen it done. I've done it to myself. It will stop the attacks against your asterisk box. It'll also free up the resources. While you're under attack under a heavy attack, you will actually have your fellow staff members complaining that they can't make calls because the asterisk box is down trying to do MD5 sums for all the authentication requests. This will stop the attack from actually penetrating your system. You'll still be using several megabits a second of your traffic. So it'll protect your box. You'll still be consuming data. There's also an IP tables rate limiting script. Go to the URL. I won't explain it in too much depth. What it actually does is it uses what's called hash limit where it runs a couple of source and destination IP address. So even if you've got one person actually hammering you or everyone else won't be directly affected by the rate limit. If you're really good at good IP tables set up just grab the relevant bits out of the script at that URL and just insert them in. It works quite well for anything really. You can use it for SSH. Just change the port numbers. Limit the number of simultaneous calls on your trunks. Once you're compromised, if you've got an office of five people do you really need 30 simultaneous calls to your upstream supply? Do you need 100? I've seen a two person office get owned and they were doing 60 calls simultaneous. If you don't really need it dial it back. You've already been owned. This gives you more time to as far as your wallet's concerned while you're dealing with the situation. Ask your telco to block international calls. Also get it in writing or an email so when they forget you've got that to fall back on when you go to the telecommunications omission about the size of your bill. This actually happened to a client two shops down from me. So we had a wholesale customer who asked them. One of their clients asked our whole customer to block international calls. They said, yeah, we've done it. They hadn't. They got smashed. Thankfully for the wholesale customer we had our own systems in place so they were limited to $600 in about 20 minutes. Which of course comes to the next step. Choose a paranoid supplier. That there is an itemised bill for 60 channels used day in, day out. That's actually a legitimate bill from our rapport accounts department had a slight heart attack when they turned up. For some reason our supplier thought it was a good idea to give us a paper itemised bill but yes, if you have a whole month of SIP traffic going, that's what your accounts department will get from Telstra or however your supplier is. That's the basic part of the talk. I will cover something else that's not official. When you get hit by these systems they're all generally a variant of what's called a tool written by a bloke with SIP fishes. It doesn't maintain state in the application. It inserts the state of the request in the UDP packet that's sent to you and then comes back. That means it can go fast. It can go hard and doesn't particularly care if it doesn't get a response back.  Amazon EC2 isn't unusual. Rackspace cloud servers are not unusual. They will be having at you for days at a time. Now this particular server was actually written as a load testing tool. It wasn't designed to be a cracking tool. It just got turned into that way. So he wrote an updated version of the software. The newer version, if it doesn't get a response for about 15 minutes or so it'll just shut down. The older version that's still in the wild actually has a processing bug in the unpacking of the information that comes back. So he wrote a tool called SV Crack. This is why it's not in the talk. It will send a packet back, especially crafted that will crash the software. I don't recommend you use it have at least once. Somewhere else on the internet just on the off chance that they decided they really didn't like me for doing that. But yes if you're sitting there on a 1.5 mega ADSL it will be flat lined. Day in, day out you will get shaped because you went over your quota. So there is that as well. Any questions? Implementation details. Excellent. One other thing as the gentleman mentioned, Asterix is the common particular target and if they find you you will get hammered out again and again. It's no longer just that. Other tools, systems like FreeSwitch now which generally used to be ignored are becoming more popular so they are actually attacking other systems. Don't just limit your trunks. If you are a 50-100 person office and you might need 30 calls, limit your individual users. One user does not need to be making 5 calls at once usually. Very good point. It's not just VoIP systems we've had, I've had a client with a commercial voicemail package that got an $80,000 bill last month off their voicemail service that had no dial out capability that had been hacked and used to dial numbers in Afghanistan that were allocated to satellite phones. And that server disappeared out of the data centre at 6am with a couple of guys in ray jackets to be assessed. Aside to the paranoid supply issue that's the group that I work with. We actually have separate limits for international calls. We have separate systems. We've actually blocked certain international destinations like satellite phones from Afghanistan. My Netphone is another company that does that. I'm sure most online ITSPs probably do something similar for the very reason of if someone's on a $14 home plan you don't really want to be sending them a $6,000 bill because even though it was their endpoint that got owned the telecommunications almost generally takes a dim view of these things most people can't generally afford a $6,000 bill. No it doesn't. On that exact point you have systems related straight to the customers bill and the lines of you've had a $100 bill for seven months running we're not going to give you a $10,000 bill or at least without talking to the accounts people of the company. It depends on the size of the attack and how badly they've been owned. We try and hold the line and keep the calls up for a few minutes so we can get told to the customers, hey look we're getting this unusual pattern. Mostly because most people have more than one upstream supplier if they're smart. They'll have their SIP based system and they'll go, well I've got ICDN on site as well. I'll use that as a backup. So great.  It starts dialing out the more expensive link. We actually, and I'm assuming others are like that as well, we get real-time alerts. It'll start SMSing people and we'll try and contact the customer for that reason.


It's my pleasure to welcome Professor John Methuen. Some of you also know John through the hydro tutorial. John and a lot of work along with Andy to organize the hydro tutorial for this summer colloquium. John is a professor of atmospheric dynamics at the University of Reading. John's research interests cover two distinct areas, one of which is the dynamics of weather systems with an emphasis on the role of Rossby waves. And the second one is airborne transport of atmospheric constituents, such as water vapor and pollution with an emphasis on chemical transformation during intercontinental transport. John is a co-chief editor for the QJRMS, Quarterly Journal of Royal Meteorological Society, and a co-chair of the WMO Working Group on Predictability, Dynamics, and Ensemble Forecasting. John's also the department director of internal partnerships at the University of Reading. Thanks, John, looking forward to your talk today on relating on some of the issues. Thank you very much, Anish, and thank you for inviting me to speak and to take part in the whole summer school. So the topic I'm going to consider today is actually related to the monsoons that we've been hearing about earlier today in that I've been talking about predictability and predictive signals in Southeast Asia in particular. And then I'll also talk a bit about relating ensembles to high-impact weather scenarios with examples from the UK, actually, forecast in the UK, which I don't see really influenced by the monsoon. So the motivation here is quite a broad one. We would like to predict high-impact weather and, of course, the impact. So floods, wind damage, anything that we have weather-related damage, and users want that information as far ahead as we can give it to them. But, of course, it needs to be useful information. And we know that the skillful range of prediction falls fast and is highly scale-dependent. So we have kind of naive prediction just based on climatology from the seasonal cycle, but also in modifications to the seasonal cycle. We have longer-range prediction in large-scale modes. And we've heard a lot about that during the summer school. Obviously, synoptic weather systems. But we need to go even further downscale for the high-impact weather variables themselves, like extreme precipitation or damaging surface winds. And so in this prediction, we need to consider the handover from the most predictable scales to the less predictable things that we're actually interested in. And in particular, in this talk, I really want to address how we harness the more predictable phenomena to obtain useful forecasts of weather risk, or risk associated with a high-impact weather. And sometimes people call this a kind of raging conditioned approach. So I'll explain that as we go along in several contexts. So first of all, we need to use ensemble forecasts. I think that goes without saying. And in this approach, we want to characterize the risk associated with a predictable phenomena. So you say a phenomenon is in a particular phase, or it has large amplitude that might change the risk of some high-impact weather, for example, daily precipitation above some high percentile. And then we use the ensemble. This is the dynamical ensemble to predict the predictable parts, not the precipitation directly. And then we obtain a raging conditioned forecast by using the combination of that statistical information with the dynamical forecast. And one complication, which comes up most obviously in tropical cyclones, but in many other contexts, is the ensemble may split into really distinct clusters. So then forecasters need to identify this behavior and then use it in their communications. But it's not immediately obvious how to see that. So here's a good example. This is actually the forecast for today in the UK. And you notice it's actually got an amber warning at the moment for extreme heats in the Southwest. So it's pretty hot in Reading actually at the moment. We're kind of on the edge of that. Let me put the laser point. So Reading's about here. I don't know where it is. So in the UK and many other countries, they tend to accompany their warnings with a risk matrix. So it basically conflates likelihood or you might say probability of a hazard with a potential impact of that hazard. And so today just makes it into the amber because they say it's medium likelihood and medium impact. So it's here. It's quite hard to get into the red category. But it does occur, of course. And so the question is how you use ensemble information to determine where you are on that matrix. And in fact, operational forecasters do that through a combination of quantitative and subjective means. So in this talk, I'm going to be using a couple of things as illustrations. So I'm going to talk first about Southeast Asia in particular because it's a bit of a frontier in prediction. It's predictive skill is much lower for that region than it is in middle attitudes. In a particular sense, there is long range prediction, as they say, within so and so on. But weather prediction is generally less skillful. So I'm going to talk about direct prediction of precipitation. So that's using precipitation output directly from an ensemble to make probabilistic projections. And then I'm going to talk about these hybrid forecasts where we take the predictable components and then use those with a statistical association with the high impact weather to do this kind of hybrid statistical dynamical forecasting. So I'll illustrate that first with equatorial waves, which are thought to be quite a predictable component of the tropical atmosphere. And then I'll talk about weather patterns. So the different series, of course, these waves propagate and they propagate in a predictable fashion, or a typical approach to weather regimes or weather patterns is to identify static patterns through statistical analysis of the data. So they're actually describing very different things. And so the approach here is going to be use large scale and synoptic scale weather patterns. But in both cases, then we see the regime position forecast using S2S ensembles. And then finally, if I have time, I'm not sure. I talk about how we obtain multiple scenarios from the ensembles when there's flow dependent predictability. But the illustration for that is for the EK. So this work in Southeast Asia is really driven by quite a large project with a mess office, or actually a collection of projects. So the mess office actually ran their NWP system downscaling in a kind of nested sense in a semi-operational way for six months. So this is a very expensive operation. So basically, from the global model, they had an 8.8 kilometer kind of large regional ensemble. These are all ensembles. So each member is nested in the global member and downwards. So there are 17 members. Then there is a 4.4 kilometer model domain, which is obviously quite a bit smaller, and then the 2.2 kilometer resolution models. And they're basically, they're in these three locations because they're centered on Kuala Lumpur, Jakarta and Manila, who were the partners in this. So first of all, you have to look at whether the model can actually stimulate the thing that you're interested in. So we were interested in precipitation. This is estimates of daily accumulations of precipitation, so climatology, where the three countries involved. And then this is day one into the forecast, so climatology of the forecast. So it looks reasonable at first sight, but obviously there are some pretty big deficiencies. Like for example, the model likes to put all the rain along these mountains on the west side of Sumatra and the observations, a lot of the rain is actually over the ocean near the coast. But part of that is that there's actually a chain of islands here just offshore, which are not represented in the model, even the high resolution model. So a lot of this rain is actually over these islands. So this is kind of one problem you have to deal with. You can see a similar thing going on in Java. You know the model likes to rain on the mountains essentially in the, in GM we see a lot of rain over the oceans. Although also there are a lot of deficiencies with the rainfall estimate from GPM as well. So, you know whether this is actually real is also quite hard to ascertain. So first of all, we have to think about how to evaluate these high resolution forecasts. So this is a typical approach using fraction scale score. So the forecast has, you know, the gray cells of where precipice occurring. So this might be like set of convection example. We would say it was successful if over the scale of interest, which is this neighborhood here, we've got just as many cells that are precipitating and as we see in some form of observations, so this might be radar or the GPM satellite estimate. So yeah, this is good because the fraction is the same, even though in the particular grid cell in the middle, this one is dry and that one's rain. So this just accepts that on the convective scale, we're never going to predict the location of individual updrafts. And then fraction scale score is just the pain from this comparison, but I won't go into the details of that. But the important thing about fraction scale score is that you vary the size of that neighborhood lane and then you get the measure of fraction scale score that basically increases, it asymptates to a high limit. So it's only asymptates to one if there's no bias in the forecast, otherwise you can predict what it asymptates to. And it starts at a fairly, well, I guess it really comes from zero on the grid scale. And then there's a kind of range of skillful and useful scales. And typically we define the smallest skillful scale being when the fraction scale score is a half. And that's what we use here. So actually then this is for these forecasts. So six months of forecast from Malaysia, Indonesia and the Philippines, and just focus on the red line. So the red line is where the fraction scale score equals a half. And then we've got spatial scale going along the x-axis and lead time going on the y-axis. So basically the skillful spatial scale increases and lead time indicating that we are less and less certain as the forecast go through. There's obviously a strong diurnal cycle which is very typical in this region associated with the convection. So basically skill is larger in the daytime actually from forecast from about local midday and much smaller at night. And that's partly because the precipitation is over the ocean during the night and the model is not very good at that bit. Philippines doesn't such a strong diurnal variation because all that's associated with in the tropical cycle. John, sorry to interrupt you. Okay, actually there is scale. I think your audio was breaking up, maybe for bandwidth three since you could switch off the video. Oh yeah, so I switched it off, yeah. Okay, thanks. Okay, is that better? Yeah, it's better. All right, thanks. So the scale also varies with location. So actually this is basically day one forecast because the gray shading above within the red lines is basically where there's most scale. So you can see there's more scale over the land actually and actually in this region of the sea there's less scale in other regions. So it's interesting to catch is that these are for longer lead times, very long as here don't quite make sense but this is basically the next day in the day. So that's attempting to forecast the high impact weather directly using the dynamical model. So now we're going to try and do it without using the precipitation from the model. So first of all, look at equatorial waves. So there, and when we show them from data that they're associated with high impact weather. In fact, with Kelvin waves for example, extreme rainfall. So you can actually look at higher percentiles in this. It is up to four times more likely when you're in the right phase of the Kelvin one. So if you can predict the Kelvin wave you're predicting the risk of precipitation that's the general idea. And they have very distinctive structures and they have distinctive phase speeds. And Falko Jutes and a number of other people have argued that potential predictability in the tropics is very high due to the presence of these waves. Although as I'll show later the actual predictive skill in current systems isn't that good. So there's a lot of potential predictability which is unrealized. So the basic method is that we take global analyses we identify wave amplitude and phase and then we find the statistic of association between high impact weather at every grid point or every neighborhood with wave amplitude and phase. So we get conditional probability in wave phase space. You could call it that. And then we take global NWP forecast. I've just shown you could use model precipitation directly although actually the precipitation from the global models is really poor. You need convection permitting models really. But anyway, from the global NWP you can forecast wave amplitude of phase. You combine that with the statistical information you get a forecast probability of that weather. So it's bypassing the use of the model precipitation. This is what the waves look like. So actually our identification method is a spatial projection method onto these structures. So these structures come from theory. There's a few parameters that fit but it's fairly straightforward. So we're particularly interested in Kelvin waves here and these westward mixed Rossby gravity waves. So these have meridional wind at the equator. Kelvin waves have zonal wind at the equator. So here's an example of that statistical relationship. So the color field is the GPM actually is trim. It's a bit older. It's trim precipitation but the satellite is the precipitation. And the consulate is where there's convergence in the Kelvin wave. So when there's the Kelvin wave has land soon here the precipitation is more or less with the convergence not very surprising. But you can see there's a lot of structure in where the precipitation is. And so the statistical association knows that. And then here's another example for a westward mixed Rossby gravity wave. So here the centers of action are off the equator. Although the meridional wind is strongest on the equator. And you can see there are heavier precipitation in these solid planters and there's reduced precipitation or suppressed precipitation on the other side of the equator. So these are the kind of signals that we're looking for. And these propagate. So this one is propagating westwards. The Kelvin wave is propagating eastwards. So that's the predictable signal. So then how do we use that? So this is then, sorry, each of these this is Western Indonesia, Southern Indonesia Northern Indonesia and Eastern Indonesia. So we just split it into sectors and then the wave amplitude is given by the radius into these diagrams. So we just split that into three bins and then phases split into four phases. That's partly because we've only got the waves move quite fast and we've only got six hourly data. So four phases is about the best that we can do. And as you might expect, a fraction of time in any one phase at a given location is roughly equal probability because the same wave is propagating through. So it just depends on the phase of the wave. But when you calculate the conditional probability of heavy precipitation given wave phase of amplitude you can see that our probability is much, much higher when we've got high amplitude and we've got the convergence phase of the Kelvin wave in all of these locations. So this is the degree to which this is much larger than all the other boxes tells you how much potential predictability you have. If this was a flat diagram you'd have no potential predictability you might as well just give up there anything. This indicates that we've got a fighting chance and actually it's quite large. So high impact weather defined by this particular percentile threshold is the probability of high impact weather where and where in this region is 30%. I mean, that's really quite a high probability. So can we predict the waves? And because that's the next question, yes, for some extent. So just focus on the dotted lines here. This is the skill in the Kelvin waves versus lead time. I don't have time to explain all the other curves but basically from the analysis it drops off roughly linearly lead time skills getting a bit marginal by day six. The other waves like the Rossby one here has a bit more skill out to longer lead times. So this is just the state of the art. This is where we are currently and it's pretty similar in other systems. This is in the Met Office ensemble. So now we're gonna jump to other predictable components over the region. Because although our equatorial waves have a lot of potential predictability the models are struggling to forecast them beyond the week. So then if you want to look at lead times beyond the week, I think you have to look for something else. So let's think about middle attitude predictability. So this is actually a diagram produced by Lara Ferranti who spoke last week of course. This is a middle attitude example where as lead time increases we're looking at the projection of the forecast or the split of the ensemble between different Euro-Atlantic patterns of variability. So the red one here is blocking. So we know pretty well that these really large scale patterns have skill in the S2S range. Whereas weather types or things like gross weather lagoon or the very old land weather types in the UK they don't have much more skill than individual cyclones. So there is skill in the five to 10 day range. Individual cyclones maybe three to seven days if you actually want to forecast the amplitude and position of the cyclone. Frontal features are actually quite predictable given that they're so narrow because they're completely slaved to the cyclones. So in somewhere like the UK there's very high predictability for fronts. But the actual high impact weather phenomena there's very low predictability, typically less than two days. This is where the high resolution forecast come in. So we're going to use this thinking to think about Southeast Asia which hasn't been explored in this way before. So I'm going to take a two-tier approach where we define a really large domain. In fact, this is a fifth of the Earth's surface and we look for patterns of variability using the data, basically using a K-means clustering approach. In fact, we precondition the data using EOFs just to truncate the data set and then we do K-means clustering which is a usual approach. And then we take a secondary domain within that which has just spanned Southeast Asia which is actually a quarter of the area. So these kind of ratios are deliberate. So we're trying to separate skills artificially in a clustering approach. Then in the second tier, we limit the data that's going into the clustering to only those days that are in one of the tier one regions. So the tier two is deliberately a subset of tier one. So it's like looking for the weather regions that are important when we're in regime of tier one. And so this is the diagram kind of indicating that. So we've got eight tier one regimes and then we have all these tier two regimes as subsets in phase. And I'll show you what they look like a bit lazy. And we did compare it with a flat approach where we just use the same number of regimes but adjusted the clustering over Southeast Asia straight away rather than the conditional approach. But I won't spend much time describing that here. I should say the cluster variable is wind. It's not precipitation. It's 850 hexapascal wind. That's because it's more predictable variable. So let's look at the tier one clusters first. So this is day of the year. And then this is all the years in the data set from 1979 to 2017. And then the color is just the cluster assignment. So you can see to start with that the tier one clusters primarily pick out something that's related to the seasonal cycle. And that's really obvious. Perhaps what's obvious is that if you then reorder the years by phase of ENSO there's actually quite a strong ENSO signal in there. So in boreal winter, the cluster two is related more to La Nina and cluster one is related to my ENSO conditions. So you can see that in the transition from orange to blue. And also that some of them which are related to the summer monsoon Asian summer monsoon there's clearly dependence on ENSO in the timing of the regime. So basically it's a lot later in our linear than it is in La Nina. So the cluster is picked out this information. We didn't impose any seasonality. We just gave it the full data, see what happens. And if you look at the regimes, they make a lot of sense. So regime one and two are both North East monsoon in DJFM. It's just this one is more active in terms of precipitation than that one. So sorry, the color fill is the precipitation. Whereas regimes four and five are summer monsoon and raging flavors are more intense summer monsoon which is also extended a lot further East than in regime four. And then there are transition season regimes. So then we take that into the next year and there are 51 of these. So I can't show you them all, just pick out a few which are quite interesting. So some of these are related to what are called cold stages in this region. So Grand Central 2B here has a really strong cross-sectoral flow between Borneo and Malay, well Borneo and St. Marcha. This is called a cross-cagrile surge associated with heavy precipitation in Java frequently. So this is a kind of large synoptic scale regime. This one here is related to the floral summer interseasonal oscillation. So actually quite similar to Nina's talk where she was talking about the monsoon interseasonal oscillations is a kind of variation on that. And that's coming out of one of these regimes where some of them are clearly related to synoptic scale events. So these are just tropical cyclones being in preferred regions near the Philippines and they're coming out of the clusters as well. So now the question is whether there's any skill in forecasting those things. So we've taken glossy five which is the Met Office S2S forecast. We've taken a whole load of pinecasts. So it's a fairly recent version of the S2S system for the hindcasts of the cover earlier period. And we just take all the hindcasts that there are. And then we assign each ensemble member to regimes based on the era five centuries. So this is another decision you have to make. You could do all the clustering in the model world but we decided not to do that. We decided to project the forecast into the clusters identified from data. And that's a fairly typical approach. So one thing that we learned straight away is obviously there are lead time dependent biases. So this is the tier one. Well, in fact, it's all of them. You can see all of the clusters here but the colors are the tier one. So you can see that there's a lead time dependent bias lead times running out here to day 36 between these two regimes. So basically in the data, this one's occupied a lot less than the red one but towards the end of the forecast it's the other way around. And this is actually because in the model the Asian someone once soon extends from too far east in the model that's just the systematic bias. And you can see it's lead time dependent. But actually the other ones aren't too bad in their representation. There's perhaps some endso dependency of between the red and the blue or orange and blue. So now we're going to use this information to do the raging conditioned precipitation forecast. So the direct precipitation forecast would just use the output of precipitation from the Gossi five model to forecast the probability of precipitation location X exceeding the 90th percentile. But instead we're going to take the probability of being in a regime and which is forecast by Gossi five and then the data relationship between the probability of precipitation exceeding the 90th percentile conditional on being in the regime. So it's a conditional probability. And then we combine that with the forecast probability of the regime to get the conditional forecast probability of precipitation exceeding the percentile. So it's a typical kind of combination of probabilities problem. This is quite remarkable. I still can't believe the results and we've been checking these quite a lot. So this is now the blue one is the tiered cluster approach. And this is prior skill score in the exceedance of 90th percentile precipitation. So there's a scale on the face of it right out to beyond 20 days. And the flat one is less skillful which is quite interesting. So it's important to separate the scales and the clustering. But then we try aggregation of precipitation up to more grid points. You know, the S to S models have just got these one and a half degree data and well at least in the S to S database we aggregate up to more grid points. It doesn't change the range of skill that much although it changes the value of the skill score but this is the straightforward use of the model precipitation. Basically even with aggregation up to 500 kilometers the skill dives to zero in two days. So somehow we've gone from two days to 20 days by doing ranging condition forecast which is amazing really. I mean, we don't get that gain in the latitudes nothing like it but in the tropics it's really important. So here's a case study just to bring that to life. So this is the, it's in a particular week actually only in December 2019. This was the exceedance about 25 millimeters per day daily accumulation from the observations over that week. So this is the kind of thing we're trying to forecast. And then these are the forecast from the ensemble and they were kind of day zero to six which we're calling week zero here and then week one, two and three. So you can see there's actually quite a strong resemblance to the observed exceedance and this is where the skills coming from. So for example, the south or western end of Borneo there's obviously probability of heavy precipitation there and over Java. Right, so now we're going to change tack in the remaining 10 minutes. John, maybe like if you caught up in three, four minutes so we have time for questions. Yeah, yeah, sorry, yeah, that's fine. Yeah, got confused on my time though. This is very short this bit anyway. So this is now focusing on the UK example. So again, it's applying a custering technique but in a different way. We want to identify whether in an ensemble forecast there are several plausible options. So there are 18 members in the basic ensemble here we want to reduce that to two or three important scenarios and they need to be temporarily consistent. So what we do is where I mentioned fronts are important for the UK. So we get a frontal diagnostic using the gradient of wet hole potential temperature and then we look at the position of features in this diagnostic. So in fact, we threshold that field just to get feature features and then we calculate the distance between though distance between ensemble members using fraction skill score. So basically you can relate distance for the neighborhood where the fraction skill score is large that kind of indicates the scale you have to go to for match. So this is the kind of thing we've got a whole ensemble here and the ones with the color frames that as the match are the ones that are falling into the same cluster. And let's look at this one as lead time increases the ensemble spreading increases but we're looking for the point where the sum of distances between all pairs of members suddenly reduces which indicates that there's clustering behavior. So we kind of start a time window when clustering behavior occurs and then look at what happens. This top picture just shows the associated between members and each cluster. So cluster zero is typically got the most members in it and we're interested in this time window here. So members do skip around between clusters which is difficult but we try and look for the ones that are coherent through time. And what was kind of fascinating by this here we've got start time versus lead time. So things on the diagonal are a common validation time or so in fact on this ensemble spread the top picture there are particular events in the flow where ensemble spread is large no matter how early you start your forecast. So longer forecast would have a rapid spread short forecast have a rapid spread. And we find that clustering so the dark blues here is where there's strong clustering that's just related to where the ensemble spread increases rapidly which is what you might expect. But what's interesting that means that there are coherent things going on in the flow where there really are clustering of ensembles which are not dependent on the forecasting system or the lead time at which you start these are properties of the atmosphere. And here's a movie showing this in this case four clusters work best and the different colours are different ensemble members but just overlaying if they call them the same cluster. This is what we're trying to achieve and at the moment we're trying to investigate whether these are indeed associated with different high impact weather scenarios. And this is an advantage of this approach you can look at any field because each of these members is actually just one member of the ensemble. So you have every variable that you have an ensemble forecast. So I'll just summarise there. So, you know, obviously there is skill in direct ensemble prediction of variables but it can be quite limited for some variables like precipitation, particularly if convection is dominant and even with a convection permitting model that's true because the convection itself is inherently less predictable. So it is useful for long range to use these hybrid methods and there's been lots of talk about similar things over the last two weeks. So here we tried it conditional on equatorial waves and also on these kind of clustering approaches where two tiers indicate different scales. And it's, you know, it's amazing how much further you can get them predictive skill even without time aggregation on the lead time. And then, then, you know, given when we have skill ensemble forecasts we have to think about how we're going to use them. And so I think do need to think about different scenarios that could occur in longer range forecast because ultimately that risk matrix that I presented right at the beginning needs to be different for each potential outcome. You can't just present one risk matrix for one ensemble when there are actually two distinct scenarios. So that's where I end there and then quite the questions. Thank you. Thanks, John. Thanks for a great lecture.


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