Hello and welcome to the session. In this session, first of all let us discuss special rules of quadratic equations. Now we know that the standard form of the quadratic equation is AX squared plus BX plus C is equal to 0 where A is not equal to 0 and ABC are the constants. Now let P and Q be the roots of this equation and also we know that the sum of the roots that is P plus Q is equal to minus the coefficient of X over the coefficient of X squared in the given equation. So this is equal to minus Q over L and the product of the roots that is P2 is equal to the absolute term over the coefficient of X squared in the given equation which is C over A. Now first of all let us discuss reciprocal roots. Now if one of the roots that is P is equal to 1 by Q that means one root is the reciprocal of the other root. So this implies PQ is equal to 1. Now P2 is the product of the roots which is equal to 0 over A so this implies C over A is equal to 1 therefore we have C is equal to A. That means the coefficient of X squared is equal to the constant term in the given equation the roots are reciprocal roots. Now let us discuss 0 roots. Now let us discuss the case 1. Now if one root of the given equation is equal to 0 now let P be equal to 0 then the product PQ will be also equal to 0. Product PQ is equal to C over A is equal to 0 therefore C is equal to 0 that is the constant term is equal to 0. Now in the case 2 if both the roots are equal to 0 let us let P is equal to Q is equal to 0 then in that case the product of the roots that is PQ is equal to 0 which implies now the sum of the roots and the product of the roots is C over A is equal to 0 therefore B is equal to C is equal to C short the given equation I equal to 0 then in that case and the absolute term R equal to 0 are the roots the quadratic equation AX squared plus BX plus C is equal to 0 let this be equation number 1 also and be found by these two roots and the equation will be that is x whole into x plus product of the roots is equal to 0. The equation of the root is equal to 1 then B is equal to minus of P plus Q the whole which is further equal to minus B which is equal to P plus Q that is 1 by P and 1 by Q. Now for these two roots we can again power equation and that will be equal to x square minus 1 by Q the whole into A into 1 by Q that is equal to 1 by minus equal to C equal to minus equal to 1 so putting all these values here plus BX plus A is equal to the case 1 of infinite roots that is 1 is infinity. Now we are let infinity then it is 1 by P will be equal to 0. Now from the case 1 of 0 roots if 1 of 0 roots of the given equation is equal to 0 then of equation number if 1 by P is equal to 0 that is 1 of the root of this equation is equal to 0 then the constant term that is A will be equal to 0 of this equation. Now P is the root of equation number 1 therefore the corresponding root of equation number 1 is infinity so we have A is equal to 0 in my equation now let us discuss the case 2 when both of the roots of the given equation are infinity now we are let P and Q then in this case the reciprocal of the roots that is 1 by P will be equal to 0 and 1 by Q will be equal to 0. Now from the case 2 of 0 roots if both of these of the given equation are 0 then in that case the constant term constant term which is A will be equal to 0 and B will be equal to 0 equal to 0 and B is equal to 0 in equation number 1. Thus the conditions are if 1 root of the given equation is infinite 2 to 0 that is coefficient of x square is equal to 0 if both of the roots of the given equation are coefficient of x now both roots will be positive then the sum of the root the product of the root which implies minus B over A positive A and B is negative and the product is positive thus implies minus B over A is negative the root which is C over A is positive A will be negative even the product will be positive if A, B and C are all of same signs that is root should be negative when A, B and C are all of same signs. Now the roots will be of opposite signs negative that is 0 that is but minus B over A is equal to 0 when B is equal to 0. Let us find the condition when the 2 product equation we have plus B over x plus C over A is equal to 0 and A 2 x square plus B 2 x plus C 2 is equal to 0 where A 1 is not equal to 0 and A 2 is not equal to 0 and A 1 B 1 C 1 and A 2 B 2 and C 2 are the constants. Now let alpha be the common root of the given product equations it means it will satisfy the given quadratic equations. So we have A 1 alpha square plus B 1 alpha plus C 1 is equal to 0 and A 2 alpha square plus B 2 alpha plus C 2 is equal to 0. Now solving by the method of cross multiplication B 1 C 2 minus B 2 C 1 is equal to alpha over is equal to 2 minus A 2 B 1. Now equating the first 2 B 1 is equal to B 1 C 2 minus B 2 C 1 is equal to A 1 C 2 is equal to A 1 B 1. Now let this B equation A and this B equation B. Now equating A and B minus B 2 C 1 is equal to C 1 A 2 minus A 1 C 2 A 2 B 1. That is both of these are the values of alpha. So we have equating this and find the root minus B 2 C 1 the whole and B 2 minus A 2 B 1 the whole is equal to which is the required condition for the two quadratic equations to have one common root. Now let us find the condition, check equations. We have both roots common. Now again these two quadratic equations add this B equation X and this B equation Y. Now let alpha and beta are the common root equations X and Y. Beta is equal to minus B 1 over A 1 and the product of the roots that is alpha beta is equal to C 1 over A 1. And from the equation X that is alpha plus beta would be equal to minus B 2 over A 2 and the product of the roots that is alpha beta is equal to C 2 over A 2. Now both of these that is the sum of alpha and beta. Therefore we have minus B 1 over A 1 is equal to minus B 2 over A 2. These are the values of C 1 over A 1 is equal to C 2 over A 2. Now from the first one B 2 is equal to A 1 over 2 B 1 over B 2 is equal to C 1 over C 2 the required condition to take equations to have both common root. And now let us discuss what is an identity. Now an identity a mathematical relationship an example identical to X square plus 2 A X plus A square. Now here is used to distinguish it from the sign of an equation. Now let us discuss an important property of identities and that is in an identity the coefficients of the life paths of the variables in world are equal and both the sides. That is into X raised to power n plus A n minus 1 into X raised to power n minus 1 plus so on into X raised to power 2 plus A 1 X plus A naught is identical to B n into X raised to power n plus B n minus 1 into X raised to power n minus 1 plus so on plus B 2 into X raised to power 2 plus B 1 X plus B naught between X is equal to 0 in this identity we get X is equal to B naught.  Now again in this identity putting X is equal to 0 B naught A 1 is equal to B 1 and then repeating A 2 is equal to B 2 A 3 is equal to B 3 etcetera to B n A n minus 1 is equal to B n minus 1 up to A 2 is equal to B 2 A 1 is equal to B 1 and A naught is equal to B naught. Hence we can say in an identity of coefficients of light powers of the values involved are equal at both the sides. So in this session you have learnt about special roots common root and identity. So this completes our session hope you all have enjoyed the session.


Okay, so let's try this problem, which is a problem that was very similar to the last problem that we did, except the only thing we've done is changed the acid that we're titrating. Okay, and the last problem, we're titrating the cedic acid, and this problem we're titrating phosphoric acid. When we do that, hopefully you see that the equation is balanced differently, right? So we have a 3 to 1 ratio, as opposed to a 1 to 1 ratio like we did in the last problem. And this is going to affect our number. Anyway, so this is the titration problem we're wondering about volume and concentration. So we've got volume here, and we've got concentration of NaOH here. So remember, molarity is moles per liter, so I like to write it like that, so we can use it to convert. And we've got our volume of NaOH, our volume of sodium hydroxide in milliliters, so we want to convert that to liters, so we can cancel the volume now. So that'll cancel out our mill step, giving us 0.0947 liters in NaOH. Okay, everybody's okay with that. And then we've got, so we've got that many liters, we're trying to figure out how many moles of NaOH we've got. So we're going to multiply this conversion factor, the molarity, by what we just got, liters of NaOH. That's going to cancel with that. And going to give us 0, 1. So to that point, we've done the exact same thing as the last problem. So it's at this point where the problems kind of switch gears. So here we, again, we're trying to figure out what's the concentration of this. So we've got the number of moles of this, so we're going to have to use the reaction equation for the mole-to-mol conversion. So in order to find the number of moles of phosphoric acid we needed, so it's three moles of NaOH to one mole of fluoric acid, so we cancel there. So divide that number by three, and we get this number, 6.31 times 10 to the negative third moles of phosphoric acid, like that. So notice this is a different number than what we had before, okay, with the acetic acid problem. So we know how many moles of phosphoric acid we've got, this, the liters, so the volume is the same, too. So how do we do the concentration? Well, it's the number of moles of phosphoric acid divided by the liters of phosphoric acid, so 6.31 times 10 to the negative third moles divided by 0.0250 liters to the negative third mole of phosphoric acid. So hopefully I've proved to you that if you, a reaction equation where you need a different number of equivalents of base to acid, you can't just do that M1B1. Are there any questions on this one? Any questions?


Annalisa Braak with Professor Georgia Tech and Sliva Kocher. Annalisa was another XICPP member and she went on to a very brilliant career in the U.S. So Annalisa is going to talk about Tropical Teleconnection in CSM and reanalysis using the approach. This is oceanography. So I kept my climate interest on the side. And last week they were working, collaborating with Annalisa Braak in the College of Computing and trying to develop new tools to look at model output. So here I'm going to present some... Some momentum, momentum between the level of three years ago. And then we find and at some point, throwing away what we had and kind of a visit is easy. So we try to look at quantum models and really try to focus on that connection. So it tries to use quantum analysis to figure out how the connections are reproduced. And it's worth that a student of mine, Abitio, is doing. And Hanos Leine is interested on the cloud side of things. So I'm going to try to explain you something about delta maps, which is this method, the name that we have given to this method. Discuss a little bit the robustness and the test that we've done to show that this more or less work. I will not go too much in the details of that because otherwise I'll spend all my 40 minutes just going into the robustness analysis. And then I'll show some preliminary application to CSM and the large ensemble. And the reason for that is try to figure out how some of the tropical interconnections are reproduced in that model and what are the problems and see if we can use the network analysis to kind of identify the problems and possibly diagnose what's going on in that model. So why we wanted to look at climate networks? Because, I mean, we have so much climate data coming out from models that trying to develop some data mining algorithms may be useful. And talking to the computer community, a computer scientist community, it's kind of interesting. So our first issue when I started talking with Constantine was like, well, can we do something better or slightly different than UIF, essentially? I mean, UIFs traditionally are old, but they have problems. I mean, they give you a lot of information, but they also have problems including the fact that, you know, they are autogonal. And we wanted to develop... CMIT5 was coming out when we started this collaboration. And so we wanted to develop a method that allowed us for intercomparison of models. And in fact, we did publish a couple of papers looking at pretty much the whole suite of CMIT5 and how they simulate tropical connections all the way to 2300, which is kind of interesting because when you pass 2100, they really start to look different to some of the models, the few that have one member continuing. And then the second step, and we just started in that one, so we're not really talking much about that, it's trying to use it for attribution study. And we really want to look at the aerosol problem. So where aerosols start changing teleconnection patterns if you have them in using these kind of tools. So DeltaMaps, which is this network method, works on two... There are essentially two steps in order to get the network. First of all, you start with a domain, a grid of domain, and you need to reduce the dimensionality. So we try to identify functional components that we call domain of the system, which are contiguous regions. They may overlap and they have to be homogeneous under the underlying variable. So on the side, you can see one map that comes from SC anomalies over 35 years. And those are the domains that the network that I will define next is going to identify for that system. And once you have identified the domains, the domains are going to form a network and you can establish whichever link exists between the various components of the various domain of that network. And those links have a weight, and you can calculate what the weight is, and that is essentially linked to the magnitude of their interactions, so it's essentially the covariance between the various domains. And you can also identify interactions that are lagged. The network, the identification of the domains happens on essentially one dataset.  But then you can also identify interactions between the domains that you identify that have a lag. And the other thing that you can do is that you can define a strength of that domain, which is essentially what is color in that map at the bottom. And that depends on the sum of all the links, so all the interaction that that domain has with everybody else. And so obviously if you take the SST and you define the strength for all the domains you identify, the one that corresponds to ENSO is the one that is going to be the strongest, because it's the region, the domain that is teleconnected the most with everything else. But you can also see what the other areas, other domain give you. And then you can also plot the way those domains interact, and this is the last, which is really the network, the last plot on the side. And what you see when it comes to the SST, for example, is that ENSO is the one that has the strongest links with a lot of other areas. There I'm plotting essentially the seven strongest areas. But an interesting thing that appears is that the tropical Atlantic to the south of the equator, which is this area here, is actually preceding the ENSO area. So it's connected. There is a link. But there is a link that goes from the tropical Atlantic into the ENSO area that has a lag of 8 to 10 months. That's something that Fred has studied quite a bit. There are several papers explaining what's going on there, and it's a Gil-Matsuno kind of teleconnection. So if you have SST anomaly in this area in the spring, you modify the worker circulation, you modify the convection in this area, you modify the worker circulation, and you tend to modify the winds. I'll show that later over the Pacific. And so you can, if you have positive anomalies here, you tend to weaker the winds along the equator and the divergence of the winds along the equator. So you have less appalling, and therefore you generate... Sorry, if this is cold, this becomes warm. So if this is a cold anomaly, you get less appalling, and therefore you get warmer SST and vice versa. And this is one of the teleconnections that models have the hardest time to capture for various reasons, including the fact that usually here they have a large error and a large SST bias. So I will focus on that a little later, which is why I'm telling you a little bit more about that. Going back on the network side, so we want to identify the domains first. They have to be contiguous, they have to be functionally homogeneous, so the grid cells that are inside the domain, they must participate in the same dynamic effect. They can overlap, so you can have overlapping domains, and they can have interactions that are both weighted and lag, and so you also keep a sign on the interaction that they can have. So how we do that, we define a neighbor of a grid cell, and that neighbor can contain four cells, which is that case, because your cell that you are considering is the one identified with the I, and we identify a neighbor that is given by four cells, or can have six, eight, twelve, whichever you want. And we did test the robustness of this, and it's very with the data set you are considering, so you have to play a little bit at the beginning to figure it out for that data set, which is the ideal neighbor. You use that, you change K, and you figure out how very easy your network, and we have a matrix to identify that, until you find that around certain range of K, variations are not large anymore, or very, very small, and therefore you know that that K is robust. And then you define, you calculate the homogeneity of a grid cell I, calculating the Pearson correlation around for the neighbor of that cell, and here it's the Pearson correlation coefficient for that cell, and then you establish the homogeneity of the domain, calculating the Pearson correlation of all the cells that belong to the domain, and you establish what is the minimum correlation, Pearson correlation that you want. Usually we require that everything is 99% statistical significant, and so that gives you a parameter delta that you can use to test, so that all the correlations inside the grid are, all the grids belonging to that domain are correlated with each other, at least up to that. And we find domain cores, so the epicenters, a grid cell at which the local homogeneity is maximum, and it's obviously greater than delta, and then we go around the epicenter and we set the threshold for the homogeneity, which is usually, everything needs to be 99% statistical significant, so there is essentially just the alpha, and we find the domain, the grid cell, that satisfy around that epicenter the criterion that we set for the homogeneity. From the beginning, you don't know what are the boundaries of the domain, so you have to identify them, and that's what is called a greedy problem in computer science, because there isn't an optimal choice at priority that you can make, and so you essentially make, we created an algorithm that makes a locally optimal choice at each stage, and then the hope is that you find the global optimum, and we identify first the seeds, and then we expand and merge until we identify all the domain, and I'll give you an example next. So this is an example. We have found the seeds or the cores, so the regions that have the strongest Pearson correlation with all the neighbor cells, we've been arranged, defined by that gamma that we set, which here is 4, just to make it simple, and then we start looking for candidates around it where we could expand each of those domains, and when possible we merge them. So those are the correlations between the seed and all the cells that are colored in the same way. So for example, all the blue cell, the correlation that is 08, all the red one is 08, and now we're going to test if those one and those ones are also correlated enough that is higher than delta, and so this would become one single domain, and then we can also expand to the other group. So essentially this is how it goes, so the first thing we merge those two, and once we merge we have that this whole domain has a lower correlation to 08, but everything is still significant. Here we set delta initial is 05, so to simplify things there's an easy number, this is just an example, then we start to expand around that orange area over this one, and we figure out what the domain become after the first expansion. We continue doing that multiple times until we essentially arrive to the point where there is no further merging or no further expansion. So the great points that are white means that they're not participating to any clear dynamical interaction with anything else, so they don't belong to a domain, a great point doesn't necessarily belong to the domain, and those ones are the two largest domain that we could find that are interacting. Then we define a domain signal, and of course we take into account the latitudinal changes so that we essentially determine what is the signal that the domain is doing, and we look for a correlation between values domain that can be with a lag, and we define how much that lag can be. In this case we usually look at plus and minus 12 months, and we also test for the statistical significance of those lag correlations using the Barlet formula so that we can exclude uncorrelated signals that are producing spurious autocorrelations, essentially. So we get rid of some of the autocorrelation problem that in climate fields is pretty strong because you can have domains that are close by that are essentially autocorrelated and then you're getting a spurious correlation out of it. Then we say that domains are connected if there is at least one significant correlation, and we define a lag as the range at which the correlation is significant located within one standard deviation from the maximum absolute correlation. Then we catalog all the edges, so all the links between one domain and another one as undirected if they essentially there is a lag zero in between, or directed depending on lags. We can be positively lag or negatively lagged. Finally, we weight the links using the covariance matrix between the various domains, and so here we take the correlation in absolute sense, and then the edge weight captures the magnitude of the signal between the two domains. We also know which is the sign, so we can have weights that are positive and weights that are negative, so positive and negative correlations, and at this point we have a final network which is weighted and that is lagged. There has been quite a bit of work on climate networks in the last 10 years. One big difference of this system is that we don't prune the grid cells, and this has been something that we had to work quite a bit with because what most network system, network methodologies developed so far, what they do is that they take the grid cells and they check for correlations between that grid cell and all the other grid cells, and if one grid cell doesn't have a correlation above a significant threshold that they set a priori, that grid cell comes completely out of the network a priori. It's not considered anymore. If you actually look at the correlation matrix for any kind of climate system, that is extremely sensible to the threshold that you set. So essentially, if you take one model output on one reanalysis and you take another reanalysis and you do the same job of the same threshold, you are going to get two very different networks at the end. So it's not robust to the pruning. While in this case we essentially don't prune, we keep all the grid cell, we eventually have grid cells that don't belong to domains. So this is an example of the output of this network that I gave you before. This is the other SST for the period 71, 2015. This is the strength map for the domains that this network finds, and that's the network with the connections and the links between the strongest domain, and what you see when you see numbers is because there is a lag, or a predominant lag at least. So I'm putting them there. So you can see that, for example, the tropical Atlantic is linked to Anso with a lag that is always positive, so it's always preceding the activity of the Anso area. The same is true for Anso versus the North tropical Atlantic. But with Anso preceding what the tropical Atlantic is doing. While the South tropical Atlantic is preceding what Anso is doing. And here we are considering essentially the South Pacific Anso, the Horseshoe patterns, the Indian Ocean, and the two tropical Atlantic areas. One thing that it's nice is that if you take the signal, which is again the find there, for the Anso domain identified by the network on its own, and you plot it and you do the same for two other analysis where they look the same, which is good. I mean, it's over a period where we had satellites. We would hope that. But it's also behaving like the scale first principal component of the UF of the same system. So what you are capturing is eventually more than what the UF can give you, but it's not different than what the UF can give you in a way. Those are two different analysis. We're just comparing strength math to give you an idea. So if you just look at the principal component for the Anso area, for this one and that one, as you saw before, are almost identical. The correlation is 0.99. However, if you start looking at the strength math, some difference shows up. For example, the aliases tend to have all the tropical teleconnection from Anso is slightly stronger than Kobe in the way they are reproduced. This is true for the Indian Ocean. It's true for both Atlantic area and it's true for especially the south of the Osho pattern. So even if the Anso, the principal component, are identical for those two data sets, there are some differences in the way the teleconnection in the SSD are reproduced by those two data sets. Those are the networks for Adelaide, Kobe, and ERSST, which has a different resolution compared to the other two. What you see, pretty much what I was mentioning, this tends to be stronger. So for example, the connection to the South Pacific or the Indian Ocean are stronger here. The color is slightly lighter. It's closer to higher than 0.7 and it's slightly less there. It's red even if it doesn't look red. All of them have the Atlantic being essentially the one that lead Anso. All of them. Yeah, it's true. And the reason for that, and the reason we didn't plot it here, is that essentially it's a cluster that appears exclusively on the Adelaide SSD analysis. Kobe and ERSST essentially do not distinguish the warm pool as his own domain. It simply does not come out. So I do have the network for this one, which includes the West Pacific and the connection from the warm pool area. I didn't put it on because it complicates because of course it's a strongly connected area with everything and then you don't see that all with the other one. Interestingly enough, CSM doesn't have it either. It simply does not come out as an independent domain in any of those networks. So here I'm going, I'm starting to look at what CSM does and I'm just plotting three of the 30 members that we analyze in the large ensemble. Also because they kind of look similar. What you see in all of them, it's of course the Anso area is the strongest one that appears in all of them as well. The Indian Ocean is usually a very strongly, tightly connected. The South Atlantic essentially does not appear as a connected area almost at all. It's sometimes white. It means that it's essentially not responding or not linked to anything on his own or it's dark compared to what is in the analysis so it's much weaker. Most of the areas are pretty well captured. And what we can do here is also do a correlation matrix and compare the domains in one network and the domains on the other, both for the strength and for the geographical location of them and the extension of them and therefore kind of measure the similarity between those networks. And CSM is not doing too badly, especially compared to what some of the CMIP models did which was worse. When we look at the actual networks, this is again, this one is at ASST, the other ones are three of the members of this CSM. What it's in all 30 of them, none of them as the South Tropical Atlantic preceding an Anso activity. None of them as a correlation that goes from the South Tropical Atlantic into the Pacific area. Some of them, about a third, as actually Anso preceding the activity of the Tropical Atlantic or the Tropical Atlantic responding to what the Indian Ocean is doing. But it goes in the other direction essentially. All of them tend to be very strong in the Anso connection. So the links from Anso into the other tropical area tend to be extremely strong, which is known because the Anso strength in this model is very strong. It's essentially stronger than what it should be. The variance is very large, the linear events are really strong. And so this is seen also in the teleconnection. But the structure of the network generally is, it's quite well identified. We've also at least some of the relationship properly captured. They're all anti-correlated in relation to the horseshoe pattern. There is a very strong correlation with the Indian Ocean. There is a correlation that is some kind of lag often with the Pacific. So it's not doing too badly. Here, it's when we start looking at this net correlation, which is essentially the correlation between different network structure calculated between two agent metrics. So we are really comparing the metrics that comes out from one network with the metrics that comes out with the other network. And therefore we are measuring how different are the structure, the topology of the two networks. And despite the flaws in the tropical Atlantic areas, most of the runs do a pretty decent job. So we are using as ground through the Adelaide SSD. So we are comparing to the network that we got from the Adelaide SSD. This is where ERS SSD compares to. So close to one. One, of course, would be perfect match. Colbert is a little bit lower, and indeed it's the one that has lower strength in all the links from the end. So it's not surprising. Several of the runs from the large ensemble do a very decent job in reproducing the structure of the network, the topology of the network. Few of them are not in here of the 30. And the reason for that is that they tend to overestimate the links between ENSO and the South Pacific. And so the South Pacific area, it's together with ENSO. Essentially, if you go back to this map, what happens is that this area, it's completely attached to this one. Appears as a single one. It moves together with this one. And therefore then the net correlation is close to zero. Because it's a strong enough area and it's a strong enough difference in the fact that one has a separate domain there that the other one cannot identify that the net correlation, the comparison with the matrix goes to zero. You can correct for that and essentially assume that you put a boundary between the regions of the domains and you do it artificially. But if you don't, simply the net correlation is very low. This is a plot instead of the strength of the ENSO domain.  And we sum them all. So we sum all the connection that ENSO with the ENSO area as with any other area. And we compare that to all the members. And this is also, you can see that the majority of the runs overestimate those connections. But it's not doing too bad. This is at the SSD. This is Kobe, which was lower. We already saw that from the network maps. And this is the mean of all the CSM runs. So it's actually not doing too badly despite the fact that in the strength for at the SSD, there is a reduction associated with the fact that the, no, there is that the self-topic anti-contribution that goes into the sum in the CSM because the runs don't have it. This is another plot. Here we run the networks for 10 of the ensemble members. We run it for 30, but if I show 30 lines it's almost impossible to see what's going on. And we run it on 45-year periods from 1920 all the way to today, 2015. And this is the evolution of the ENSO strengths in Kobe in at the SSD. It's kind of interesting that the difference between the two analysis is actually higher in the last period than it was before. And this is for all the runs that we analyze for CSM. There is a trend towards larger strengths in recent time compared to what was at the beginning of the 20th century. This is true for the analysis. It's true for most of the runs. Not for all. There are a few runs that start strong in CSM and continue strong. One thing we did this exercise, I don't think I have the, we did this exercise going all the way to 2100 continuing for the models. One thing that we are trying to explore is why those ones that don't have, that have a large variance but high strengths and kind of keep it constant through time continue to keep it constant through time to 2100 while those one continue growing. And it's about one-fifth of the 30 runs that have this characteristic. It's pretty much constant through the 30 runs. So we found six over out of 30 that start with and so very strong at the beginning of the 19, of 20th century and continue all the way to the end of the 21st century. While most of the runs start lower closer to the analysis and then grow in time often too much because on average this has grown more than what the analysis have done. And then I just want to show some preliminary result of the investigation we have done of the problem of the Atlantic. So this is from a paper that Fred Carter Paul et al. appeared in 2015 and kind of summarized how the tropical Atlantic as as the anomalies pretty much at the equator immediately south of the equator is essentially the Atlantic tree region the Atlantic Nino area it affect the circulation you get warm anomalies in the Atlantic convergence on the Atlantic modify the worker's circulation you get divergence on the Pacific more appalling colder waters you tend to go into La Nina kind of preconditioning and vice versa for cold anomalies and you get also response in the ocean and you get rosby waves in the atmosphere essentially doing the job and what you see when you look at the lag correlation between the Atlantic SSD and the ENSO SSD calculated using the domains identifying the network is that indeed you have that ENSO leads but with a very weak correlation over the whole domain and the Atlantic leads with a much stronger anti correlation and that's why it's essentially coming out as the Atlantic leading overall in this signal but when you actually look through the whole 12 months more and less in the lags that we calculate there is also some leading of ENSO in this so following ENSO essentially you do have a response on the Atlantic but the response on the Atlantic is weaker essentially than what the Atlantic is able to do on the ENSO domain so what we did with this was to split the domain in two regions I'll tell you why we choose those two regions in a second and what happens is that if you take a upper half of that domain what you really see is that the leading of the Pacific is very weak and the leading of the Atlantic becomes stronger is the blue line well if you take the southern region which is the red part is actually a more of a leading from the ENSO side and less of a leading from the Atlantic one and the reason for that is that if you take a network and you build a network on the clouds and here we use the Mera2 data those two areas show up very nicely and so in the clouds the signal it's really separated so those two areas that in SSD have essentially the same they are strongly correlated because there are currents ocean currents and therefore you do have a dynamic that connects what's going on in the Gulf of Guinea with what's going on along the coast of Africa for the south are essentially separated in the cloud response in the atmosphere and in fact it's essentially the opposite and you have that in the northern component you have an opposite signal in response the clouds on the ENSO area versus the clouds on the northern component of the south tropical and equatorial Atlantic behaves completely in the opposite way than the other one and it's really the ice cloud component you don't see it in the water side and this is the total and you can see it also in the total and you can see that it's separated by the ice fraction so what happened in CSM and we haven't finished the analysis on the clouds but it seems to be quite consistent is that essentially you don't have the separation and what really you get in CSM is that you get this area in the clouds to be the dominant one and the only one that counts and the reason for that it's in part that you have a strong bias before you're not doing the dynamics properly and you're not have the obvious response from the atmospheric side but it's also that your response to ENSO is strongly dominated by the thermodynamic effect so this is an example we split the area also in the sum of the runs we did it for all the runs I'm just showing a couple here and when you start splitting and really just looking at the northern part or the Atlantic Tree area some of the runs have the signal but it doesn't show overall as a global change in SSD dynamics and what really dominates it's the signal in the mean the model response in the SSD anomaly of the whole area what really counts is what the sounder part is doing it's essentially dominating the overall response of the SSD it's the south which is dominated by the thermodynamic effect from ENSO and here we've done it for more than that some runs when you split it and really just look at the Atlantic Tree area do have the right sign of the interconnections with the Atlantic preceding but most of them don't it's like 20% of them really and what they all have is a very strong impact from the Pacific into the Atlantic which is also seen here this is the response of the large ensemble in precipitation this is a work that E and Sobel and Klara Desert did and just published this here so they took the precipitation in various basins and they looked at how the CSM reproduced in the large ensemble reproduced this precipitation signal when you have a couple model when you have just a slab the same atmospheric model the CSM atmospheric component but couple to a slab ocean on when you have climatological SSDs and what you can see is that for the Atlantic especially the ocean is essentially not doing anything dynamically all the precipitation signal comes from the slab essentially so it's completely teleconnected to what the Pacific is doing it's essentially responding to the anomalies that are on the Pacific side and in fact if you don't get the signal if you have climatological SSD in the Pacific with climatology only on the Pacific but you do get almost completely the signal that you have just a slab the green line so the blue is the model the green is just a slab and the black are the observations and this is essentially what this model is doing is overestimating the thermodynamic response of ENSO it's too strong in this this is data but this is the process that the model is really overdoing and therefore as a response in precipitation that is essentially only linked to this the cloud investigation but right now we have only two members analyzed because we have to download the clouds for all the 30 levels and the pre-processing it's a little bit heavy and this is essentially what we're seeing so it's a very strong response that follow this but doesn't have any of the dynamic feedbacks so I have essentially none of the wave response or too weak so this is dominant so this is what you're essentially seeing in the natural city so just a partial conclusion that we have is that the teleconnection from the Atlantic into the Indian Ocean is quite fragile there are two ninjas that are going on in different basins and they are both influencing each other they can have a destructive or constructing interference and in CSM are essentially cancelling each other the key ingredient to simulate the Atlantic variability is to be able to reproduce the ocean atmosphere wave dynamic that's essentially not there because it's completely killed by the thermodynamic ENSO connection and so the thermodynamic response to an Inyo event dominates we have seen this in two members we are we still have to confirm it for all the others and essentially what happen is that when you look at your cloud network your cloud is really the one that shows the problem because you don't have those two regions you essentially only have the dark blue extending in the clouds on the top one so it's the same domain in the network that comes from CSM versus the one that is in the observations where the two domains are separate and behave separately and this is everything I have


the power trading hour with your host David White call now toll free at 1-877-927-6648 or internationally at<PHONE_NUMBER> now David White and welcome all to another excellent edition of the power trading hour we've certainly got a big day on our hands question is whether or not volume will come in I think there are certain sec sectors that it will it is Friday so you have lighter volume we're doing about 6.5 billion shares on the CBOE consolidated tape so yeah there's not a real clear volume picture here either up or down over the last 20 days or so as we've gone down and retested the 60 excuse me the 36 36 area and kind of doing that yet again today but is the volume blowout it certainly isn't for when I use the CBOE volume and if anybody wants a copy of that I'll be glad to send them the link I've looked high and low for volume and you know there's ways to skew it this way there's not a lot of ways to skew it you may have to do a little bit of research to understand what you're looking at but it is every share no matter where it's traded so we've got that and of course could we have a lot of volume at the end of the day well you almost always do while they're supposed to report dark pool trading within five minutes of the trade it's more of a I'm gonna say it's more of a suggestion than an actual rule more like a guideline the code is more what you're called guidelines the natural rules yeah kind of like that as always we come to you at the appointed time the following takes place between 2 p.m. and 3 p.m. and what else do we have that's kind of it well we're off a hundred almost a hundred points let me update this just to make sure quick these are moving we're off 97 points on the S&P cash dows down no let's call it 590 Nasdaq's off almost 400 Russell's off 46 but again maybe we get the volume at the end of the day I don't see anything that blows us through 18 billion shares which is where I've been marking that 36 36 level on the S&P cash and it's a is the Nasdaq certainly weaker well certainly today it is but I think yeah we got a little bit all that now the question is did they just run this why the Chinese were off on vacation for a week or are we gonna come back and find that this is a retest of the low that we had yet again before now and we're just bouncing around in this trading range and having a kind of manic depressive cycle in the market the first question do I have anything yeah I've got two long positions and both of them both of them are up on the day not much but they're up on the day if you're in the right sector you can do okay if you're not you probably want to be day trading and by day trading I mean not taking anything home at night and maybe trading a little bit pre-market and getting out before the end of the day because it doesn't take much to flip this market from being a huge squeeze fest for the short sellers and of course a huge down day for those that are bullish so when I look at it you know I was I was almost thinking about finding some long positions last night I was looking at the put call ratio in the newsletter today I kind of pointed it out and the trend but the I tend to use the trend on the AmEx since it's only about 250 stocks and most of those are ETFs and most of those are unleveraged and most all of those are positive the newer stocks tend to trade on other exchanges but Arca AmEx there are not that many stocks in it but certainly they are all in that vein and since the retail trader is one at app to go to it I guess I probably ought to bring that up and show it do I have it here I would assume I've got it right here so let's go to that part here I highlighted them yeah 42 has been kind of high on the in the money put calls but normally what you want to be if you're bullish it is something approaching 50 on the put call ratio in the VIX now the VIX put call ratio is just the premiums on the out-of-the-money puts and calls the equities are all of them generally you will see most retail traders trade in the money puts and calls the pros tend to be a lot of times on the VIX because they're hedging positions so they're willing to take some small losses but their hedges will be on those big moves and unfortunately or fortunately when they don't or won't buy the put calls or won't buy puts to the downside as I said many times on the show that's when you tend to see huge gaps down does it happen all the time no but it's enough to tell me that maybe there's a hurricane in the Gulf it's not gonna tell me that it's gonna hit my house but you want to be wary you want to start looking out when you get those very low put call ratios in the VIX which means that people just aren't thinking the market can move a lot generally when everybody doesn't think that the market can move a lot the market moves a lot it just seems like as many people say when everybody expects one thing it just does not happen something else does so as I said on that also looking at the volume so we can get a clear view on that I always put in every newsletter a tabulated version of the CBOE volume mostly because volume depending on where you can get it can be very different and you really got to know if you're using price and volume what you're looking at are you just looking at the shares traded on the NYSE are you looking at all the shares traded everywhere I'm a fan of what's have everything some people it I guess because it's easier and it comes in their feed we'll look at just shares traded across the New York Stock Exchange it's a pretty good sample but a lot of times when they're close that's not good enough but anyway just to show you how close we had on the last couple of days yesterday we had basically 10.5 billion the day before 10.75 billion yesterday on the pushes higher we both had higher volume we had 12.6 billion shares on the first on the second push up and a 11.7 billion shares on the one before that 12.7 going back to last Friday so if you know generally you'll get three four five billion share move out of that kind of area and that gives you the signal we just haven't had a really clear signal on the broad indexes so far we'll be back after this inflation we are purchasing powers eroded there's no better place to protect your harder and money than ain't gold this the gold flagship asset is the Monk Todd Gold project in the northern territory of Australia this is Australia's largest undeveloped gold project we are talking a world-class gold project in a tier one mining district this is a large scale low-cost project with significant existing infrastructure in a politically safe and friendly mining jurisdiction this the gold just completed the Monk Todd feasibility study which resulted in a seven million ounce gold reserve in a 16-year mine life all of this combined with the approvals of all major operational as well as environmental permits this this thing which is Mount Todd is an attractive diverse pot ready development stage gold project this the gold trades on the New York Stock Exchange and the symbol VGZ are you grinding in the market but seeing little to no return or are you a successful trader simply looking to make your job a little easier learn to take the path of least resistance with David White's powerful trading newsletter David White is an accomplished trader whose deep understanding of technology and the markets allows him to consistently find a share winning trades support and resistance define the ranges in which stocks trade by understanding these trading ranges David White is able to find a path of least resistance David White's trading newsletter the path of least resistance is delivered daily before the markets open to make every trading day an easy win visit tfnn.com today and subscribe to David White's ultimate trading newsletter for $119 a month and try all of our newsletters risk-free with our 30-day money back guarantee take the path of least resistance at tfnn educating investors are you looking for a way to consistently add winning trades to your portfolio Tom O'Brien is here to help Tom O'Brien has been successfully trading markets for over 30 years a frequent contributor to TD Ameritrade Network and CNBC Tom O'Brien founded tfnn over 20 years ago to help educate investors just like you Tom's daily market newsletter market insights is published every morning when the markets open to give you the competitive informational edge you need to succeed these newsletters are packed full of Tom's advanced technical analysis in our gear to deliver comprehensive strategies for a successful portfolio get Tom O'Brien's newsletter market insights today and try all of our products and newsletters 30 days risk-free with our money back guarantee at tfnn.com tfnn educating investors toll free at 1-877-927-6648 internationally at<PHONE_NUMBER> question about the Bloomberg thing that I watched for a few minutes at 3 a.m. in the morning when the dogs decided they had to go out actually one dog but you might as well take both right and you may be able to lay in bed just a little bit longer in the morning so anyway no they were they were pretty focused on on the leadership of the United States they weren't mad at somebody in Poughkeepsie they were kind of mad at the overall policy I think maybe part of it is that they're very mad at themselves I think they have five different plans to try to figure out how to lower fuel costs this winter and the question is for them how do they divide up who gets it if they're going to do it all is the EU at the moment they're all fighting over it and driving the prices up but with Germany owning about 80% of everything and all of Europe I don't think I've said this enough I've said it before I don't think people really understand Germany owns everything they lost the war and they and they bought everything back while everybody else was being lazy and I mean that was it buying by 2000 their banks own everything they worked very hard they have a high problem a level of education for the people they got when they reconciled the East Germans they've got a lot of low-dollar workforce they've thought a lot about it now of course they've done some incredibly stupid things and will point the finger at Merkel for making a deal with the devil to get energy from Russia while other people that will remain nameless the US offered huge amounts of natural gas and other resources but no no we can't do that we're going to go to somebody that we know is evil to get our energy so I think they're I think they're mad for a few good reasons I think they're also mad for a few reasons that a lot of times people hate the things they see in themselves that they hate the most and I think a lot of this is looking in the rearview mirror I think they you know if they're gonna talk a lot about a blame I pointed at Merkel her and a bunch of other idiots I don't know how the big industrialists over there let these guys get away with it because it was incredibly stupid but you lay down with the dogs you're gonna get fleece so now of course they're asking for favors from the US that we can't grant because we've cut our nose off to spark spark I can't even say it cut our nose off to spite our face on energy so you know we're you know we could be two billion we could be two million two and a half million extra barrels a day in six months but that's not gonna happen we've got a concerted energy policy here that is suicidal they had their suicidal plan and the question is whether or not after a winter of freezing anybody wants to continue with the suicidal plan on energy<PHONE_NUMBER> email me at path at tfnn.com and let's do a little history and then we will get in to the rest of the very big show on this day in 1952 American inventors Norman Woodland and Bernard Silver granted the US patent for classifying apparatus and method we know it as barcodes of course today we better know these as that and of course they've grown into other things and other versions of these of course they pretty much all depended on some technology that hadn't really made its way through and it wouldn't until the mid 80s or late 80s and that was a laser barcode readers they were highly problematic they sold their patent for $15,000 so they didn't make that much off of it and later they were inducted into the inventors Hall of Fame but like a lot of things they were very early in their idea and yeah this 1952 I think it was 1960 or 61 when the first laser actually was invented and shown working so yeah you can you can look at that let's go ahead and start looking at some charts here I think I've got a few the one I was probably most interested in today if I can get where is it at there it is is taking a look at the SMH's over night we had a got Pearl Harbor again by AMD we'll look at that in a minute today you would think we probably have a lot more volume than this 3.85 million shares last low was five I mean I think we're gonna have enough to get back down to lows but right now I probably thought that by 2 o'clock we'd probably have plenty and already be through that September low of 5.25 million shares so it's probably gonna be more but I mean the real outstanding value that we want to be looking at is this 18994 that's the seven and a quarter million share low of July 5th now do we get to there which is I think a much bigger deal energies about the same on the way up is on the way down so at the moment unless we break the SMH's with heavier volume than seven and a quarter million shares by the end of the day we could have just a lot of back and forth one of the things I dislike is going whole hog in a downtrend I love this pattern much better I'm not saying it's going to complete we're probably gonna get there today but as I've talked about it so many times the double repo pattern when you get one two three four five six seven eight nine ten eleven twelve thirteen days underneath the three by three or nine day you get a couple of days above it we're probably gonna close down below it you get maybe one day the next move back if you're trying to buy a low that's generally the the one you get some retest one of the reasons why why I tried to play this first bounce and didn't get it right on some semis wasn't the end of the world or anything I wouldn't be long these inequities I bought some calls thank God I was in several other positions that are continued to do well even in a down market today but if we get some kind of low out here and then break back above it I will be start buying stuff in the semiconductor industry but at the moment no sign yet and doesn't mean that this is going to do that the thing is though if we close below the three by three have a day or two below it and then close back above it Katie bar the door that is big signal we'll be back in a minute if you want to take advantage of this sector now is the time to subscribe to my goal report the goal report is a comprehensive look at the metal sector as well as the markets that move gold which is the currency markets new subscribers get a 30 day money back guarantee so you have nothing to lose every Monday morning I published a goal report with coverage of gold silver bonds the XAU HUI JDX as well as more than 30 different mining equities to see for yourself the types of profitable trades that are recommended within the goal report sign up now by visiting tfnn.com don't miss out on the next great gold trade sign up today sharpening your skills as an investor is like getting better at playing a musical instrument you have to practice sure but you also need excellent instruction from experts at tfnn you'll get advice and guidance from the authority and technical market analysis and it's not just dry tedious text either tfnn airs live financial content streamed live on tfnn.com and tfnn's youtube channel with tiger tv live every market day from 8 30 a.m. to 4 p.m. eastern for free each host is an experienced trader and gives their take on the market while taking calls and questions live from around the world from the moment the market opens until the closing bell sounds tiger tv has eight different shows with expert hosts to help you make the right moves with your money watch online at tfnn.com or on tfnn's youtube channel and become the investor you were born to be tfnn educating investors tfnn is excited about our new software charting program the art of timing the trade charts in collaboration with tom obrien and using his best-selling book the art of timing the trade your ultimate trading mastery system david white has programmed an outstanding piece of software that will complement any trader's methodology using this first of its kind program the art of timing the trade charts allows you to scan thousands of stocks for fibonacci formation setups including guardleaf abc's butterflies and much more the art of timing the trade charts is designed to help you when scouring the markets for stocks just beginning to form the trading patterns that many investors spend days weeks or even months searching to find and right now we're offering licenses available at only $79 a month we are so confident that you're going to love this new charting software that will even give you a 30-day unconditional money back guarantee don't miss out on this incredible new piece of software get your copy of the art of timing the trade charts today by visiting tfnn.com this segment is brought to you by think or swim for more information just click the think or swim banner on the front page of tfnn.com Hector points out today that kanako phillips is back up to the previous high looks like we're going to be able to have more volume than we did on the june 8th high any any breakout of more than 7 billion shares i'd say the odds are 95 percent that we're going to get more than 7 million shares on kanako phillips today so does that mean we break out i think the market probably has to find some kind of low but as soon as it does i think everybody will be piling on these right now let's take a look at xom the problem is when you have a really good stock almost everybody owns a stinker and even in energy being a clear winner for the foreseeable future we will find people doing stupid things and generally they sell the strongest stocks because they can and they hang on to the stinkingest stocks because they can't sell them without blowing out the price i mean if we sell something we sell a thousand shares or five thousand shares or even ten thousand shares let's say you're swinging a big line eh market pretty much over as soon as you sell now if you've got a million shares or five million shares and you're some kind of big hedge fund guru much more problematic now on xon mobile you do not have the volume today so i'm not exactly sure what the difference is between these two but a lot of times it's sell what you can not what you can't on big down market days so when we look at this you've got 104 55 didn't quite touch it but you did get into the candle you had a little less than 32 million shares today you've got about 16.7 so let's say you get 22 million shares that's going to be into that candle and a bit shy now you know price is a little bit better than volume but generally it's telling you that maybe this is going to take a pause i don't think it's going to take a blowout pause but you may be able to get a pullback on xon c.o.p looks like the faster horse in this race okay what else do we have i'm looking at two potential trades in m e n and f x i okay you're doing nothing but going sideways in this for a couple of weeks i'm not a big fan of getting into these until you get some kind of sign of strength i do like the fact that you're only about half the volume of yesterday on a down day in newmont mining so i can't say that i'm bearish on it so much as i'm waiting for this thing to give us some kind of signal that it's done going sideways but uh at least today's signal i may count it as 15 percent of a decision uh is lighter so far today uh let's take a look at f x i uh this one is getting really pushed uh by the big titans of wall street and i've got to tell you on this one excuse me um yeah on this one uh i uh f x i excuse me uh this is uh being pushed um you've got some pretty nice low volume we'll see what monday brings but this is a nice pattern one of the reasons why i think that we could get off the lows on monday you had a low on march 15th that i had 117 million shares 2602 you dip below it you bounce back in but you dip below it on 35.6 million shares against that 117 that is a signal that a blind man could see and as i like to say it's a burning bush how you're going to ignore that the bush is burning and it's not consumed a little biblical reference for you heathens out there anyway uh you had a nice bounce today and lighter volume out here uh if this thing acts any well or way uh decent on monday i'd keep an idea now here is one of the things that you want to take a look at this is a potential three gap played at the downside which would suggest you have better than usual odds of getting back up to 33 bucks so now what is uh china unleashed the uh the uh dollars of war and start throwing cash around the country uh does the reopening and the end of a lot of these draconian covid mandates go away hard to know exactly uh what's going on in china uh as we've talked before you always see that unis gal from cnbc talking and i i always have a feeling that if she wore mirror sunglasses i'd see uh five guys on either side of the camera with uh ak's kind of pointed at her in case she says the wrong word i get that feeling that hostage feeling about her actually saying anything that she actually believes but you know if you believe the chart out here you certainly had a nice low on extremely light volume you bounce you had a sign of strength uh on this uh what was this you had a sign of strength with decent volume of 62 million shares you went up for another day you gap down i have a feeling that was a lot of people wanting to get out before the golden man i keep on thinking i'm gonna make a mistake and say something else golden week uh out here and uh you didn't have much volume so i'm we'll see what sunday night brings but if we start seeing money flow into china my guess is we might also see some kind of decent low over here in the united states so uh yep thanks from greg from roots minnesota uh let's see what else do we have oh we were gonna get to amd amd breaking through this long-term gap that was support of course there are some of the pre announcements are starting to flow we had a nice gap up on what is that july 24th or 2020 we're back to those lows uh and how much was how much volume was that let me find it here okay 205 million shares on the upside a little over two years ago so what do we have here today 111 million shares so that is compared to 205 so yeah you're getting into at least some part where there's not a absolute ton of volume i think these companies are probably going to turn around i'm just not exactly sure the one good thing is that both amd intel and nvidia in the toilet there are some good sectors to be looking at because of that i've been talking about it in the tech insider i'm not ready to bite right now but i think that there could be some big winners uh not in this sector but because of this sector uh so i'll probably be writing about that in the monday edition of the tech insider<PHONE_NUMBER> and of course uh i got some more stuff here let's take a look da da da da da da da da oh i did have a question here did i delete it uh oh yeah i did not kept it oh we'll get to this when we return uh a question uh from rfb sharpening your skills as an investor is like getting better at playing a musical instrument you have to practice sure but you also need excellent instruction from experts at tfnn you'll get advice and guidance from the authority in technical market analysis and it's not just dry tedious text either tfnn airs live financial content streamed live on tfnn.com and tfnn's youtube channel with tiger tv live every market day from 8 30 a.m to 4 p.m eastern for free each host is an experienced trader and gives their take on the market while taking calls and questions live from around the world from the moment the market opens until the closing bell sounds tiger tv has eight different shows with expert hosts to help you make the right moves with your money watch online at tfnn.com or on tfnn's youtube channel and become the investor you were born to be tfnn educating investors the technology around us is changing every day with so much happening it can seem impossible to keep up with all the information david white's investment newsletter the technology insider is designed to give you all the information you need to understand the technology that shapes today's markets and tomorrow's future david white has 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contain this and other information about direction shares to obtain a prospectus or summary prospectus please contact direction shares at<PHONE_NUMBER> the prospectus or summary prospectus should be read carefully before investing an investment in the funds is subject to risk including the possible loss of principle the funds are designed to be utilized only by sophisticated investors such as traders and active investors distributor for side fund services LLC this program is brought to you by vista gold traded on the nyse american and tsx under the symbol vgz i had to answer a question and anyway uh oh we got another one yeah i got a couple of them here uh us oh uh us uh oh oil fans holding better than the xle um it depends if you want to be the the tortoise and the hare um i think it's kind of like gold stocks uh gold companies have a bunch of uh gold on the ground so when you buy them and it goes up a hundred bucks an ounce uh you take whatever the reserves are and add that uh to their value um the us oh is really kind of just the oil part of it so you get the instant move here but in the coming days just like gold you find that the gold miners end up getting that money back in spades uh more than generally gold itself so it depends on what you're talking about today is a good sign that uh that uh your other etf and energy will probably do very well as i said on a day like this they tend to do the wrong thing for the wrong reason and the us oh much harder to do that because it's actually part of the oil uh industry you can kind of do that with uh with uh with energy stocks uh that aren't just straight oil etfs uh but uh you know you get a big move like this uh you get a big move in the us oh it's normally followed uh by other companies in this sector uh it doesn't do you any good to sell into an etf like a gold one if gold's going higher um it's still going to be there all you do is diminish the value of the how many shares are out there for gold same thing i think with this one i'd have to look at it a little bit more uh but because i know it's a lp so i don't know exactly how that works in this one so you'd want to look at the charter on us so but my guess is that's the way that everybody looks at it whether it's true or not it's never stopped anybody in the stock market uh so uh that's what i'm looking at i think uh much like gold moving you get a lot of movement or a much bigger movement off the companies around it uh generally the idea and i've told you this theory before uh you don't want to be uh the gold miner you want to be in the guy that's selling the picks and the shovels and the blue jeans um you know and whatever it was 1870 how many people remember the people that actually dug you know you probably remember a couple of people that dug um dug and made some money like Comstack stock or something or Hearst but uh how many people know Levi's and where they're closed still today so i'm a big fan of more of being in the part of the industry that's going to go after it because one terrifically horrific winner uh where really bad ideas are going to kill millions of people probably freeze them to death uh that's if we're lucky it may be worse but uh we're going to have a lot of people die especially in europe for very bad decisions uh my guess is that uh they'll look a little bit different about this issue and drilling and fracking we've already seen the uk change you know where's that uh where all those fracking tools going to come from united states guess what we figured out how to do in the last 10 15 years we learned how to frack there's a lot of offshore uh north sea wells that are fairly empty but man if we cracked them open could we get some more oil and a lot more natural gas i think so inquiring minds want to know but uh that's my idea on it uh question also about uh would you compare apple m1 m2 chips versus amd ryzen and intel new upgrade projects um i'm not a big fan of buying apple you didn't tell me where you're from that would be a big uh big decision the reason why is if you buy an apple laptop with one of these m1 m2 versions in it um they put little sensors in there and they void your warranty all the time if it gets very humid those little they're a little button like things maybe half the size of a regular shirt button uh and they will tell you whether there was high humidity there's enough high humidity down here in florida to set those off and they'll void your warranty i'm not a big fan of buying apple laptops or uh computers at the moment unless you have a very specific reason to have them and then i would only buy the desktop i wouldn't buy the portable like i said i know too many people that have left their apple uh laptops in the backseat of their car and it's rained down here it hadn't gotten wet but the humidity was enough uh to uh bust the sensors they take it in and apple says well this this uh machine got wet and it hasn't and you know apple is one of these kind of companies that can get away with it a great deal uh i could see the reasons for buying the ii iPhones i don't see a lot of reasons for buying their laptops especially if you live in humid areas i've run into far too many people that have paid huge amounts of money you're going to pay probably double for the same thing for an apple laptop then you would pay for one with an intel or amd chip in it now if you want to run the software maybe it's worth paying the double but uh i'm not a big fan of buying their hardware and especially their laptops if you're actually going to take them out of the air conditioning in florida texas uh even hot areas uh you know if you there's any humidity there's just lines and lines of people sewing apple over that uh and continuing to have to get in a war to get their stuff fixed uh on that generally uh most of the retail toshiba uh kind of laptop manufacturers do not do that kind of stuff i mean if they get it in the water starts dripping out of it uh the voyager warrant warranty but apple is the only one i know that that is that draconian on it so not a big apple fan to begin with so i will give you that as the stipulation i don't see a reason for paying double what i would get in it but certainly the new chips for intel and for amd are absolute smokers and that may be good or bad depending on how high end you go uh yeah yeah not uh interesting beliefs and of course uh maybe that belief will leave a elitist to nuclear war and it seems like uh maybe one degree wouldn't been that much to pay uh eight seven seven nine two seven six six four eight okay we got some more about 41 seconds uh question look at nvidia we will do that on the way back in vda uh but uh i do digress you did bounce um you're back challenging the previous low look at this when we return this to gold owns and operates the largest undeveloped gold project in australia the mount todd gold project this to gold just completed their feasibility study resulting in a seven million ounce gold reserve this to gold has all major permits approved and has retained cibc capital market assistance in evaluating alternatives and in completing an accreted transaction this to gold trades on the nyse american and tsx under the ticker symbol v gz this to gold executing a strategy to create shareholder value you might think that if you want to be successful at trading in the stock market you're going to need a crystal ball after all it's impossible to predict the future right like any endeavor in life before you decide it's impossible get some advice from the experts you might find that it's not so impossible after all for daily market overviews that give you direction on the key indices selective stocks and commodities subscribe to the opening call newsletter at tfnn.com the opening call newsletter is written by basal chapman creator of the trading methodology known as the chapman wave the chapman wave up down sequence gives you an edge in identifying price 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tfnn stations and uh well we're right down there testing the lows that we've been talking about now for a couple of weeks and that's 36 36 um want to keep a close eye on the volume as i said these fridays we've come down and tested this volume i've been looking for 18 billion shares or maybe even 16 billion shares let's say we don't even get close but still head lower on 16 billion compared to the 18 billion i've been looking at we're doing 7.4 billion shares right now so can you go lower on lower volume you can generally it entails exactly what we're doing which is you come down you hammer the low you hammer it again you hammer it again and it finally chews through the low but right now we've uh we came to this level they ran everybody out on a friday's close the next day we ran it back up this week uh now we're back down here to test it one more time uh the volume uh as we went through was what 12 billion shares for the last friday so now what are we looking at 7.4 billion shares let's say that we get 11 billion shares that would be pretty steep for friday uh being at uh one hour left uh at 7.4 billion shares on the cboe consolidated tape um that's still be lighter uh i don't think that we're going to get a bounce as uh tim ord has said on his uh his uh visits to the show they like to make you sweat the whole weekend long but uh i'd be up i wouldn't do anything today but i would be up sunday night and those chinese markets reopen we could have some real fireworks there so when you can not when you have to we'll see you monday right in shiny all over again building wealth trading in the stock market seems and