 You spotted a problem with the computer models and you did communicate this to Tom Carl. What happened there? Well, one of the things I wanted to look at, they chose two computer models. They had a choice of 14 models and the model they used for temperature, which was the Canadian model, had the largest temperature changes in the United States for the 21st century of all the climate models that were available for the report. And the model that predicted the greatest changes in precipitation, the British model, had was the one that they chose also. So they chose extreme models. And of course, I wanted to see how well they worked. And so I asked to see an incredible simple test to see if the models could produce the 10 year running means as US average temperature back to the year 1900. I mean, that's about a simple thing as you can get. What I mean by that is 1901 to 1910, two to 1911, et cetera, all the way to when the report came out. And not to be too technical about it, but the model added noise to the data. In other words, the data had a certain amount of year to year noise in it, okay? And you apply the model to it and pretend you're running means the result got more noise. So the model created literally negative knowledge. This is the exact analogy to giving students a four-part multiple choice test and have them somehow get less than 25%, which seems impossible, but it can happen. They were worse than random numbers. And so I sent that result to Tom Carl who was the head scientist for the first assessment report. And he wrote back to me, and I can quote from it if you want me to read it, but I think I need to paraphrase it best. He said, yes, you were right, but we didn't just look at 10 year running means we looked at one, five, 10, 20 and 25. And in each case, the models produced more variance than was in the raw data. So the head scientist for the report acknowledges to me, yeah, you were right. In fact, it's worse than you thought. It's everywhere. And to go ahead with that report, I mean, I'll use a word, not a pleasant word, but that's scientific malpractice because it is exactly equivalent to medical malpractice in prescribing something that you know either is not gonna work or is gonna harm the patient or is gonna work in the opposite way that it was supposed to. That's precisely what happened with that report. And are you willing to read his email back to you by the way? Yeah, sure. Hold on, I'm gonna have to do it out of the book. Okay. This is Luke Warming, that's a 2017 book. Actually, it's still pretty valid. Okay, from Tom Carl. Okay, let me send you what I wrote to him. First of all, this was in my review. All implied effects, including the large temperature rise are therefore based upon a multiple scientific failure. The national climate assessments continued use of those models and that approach is a willful choice to disregard the most fundamental scientific rules and that they did not find and eliminate such an egregious error is astounding. For that reason alone, the NCA should be withdrawn from the public sphere until it becomes scientifically based. Okay, those are strong words, but I can back them up. And here's what Tom wrote back. He said, one has to look at time averages in the assessment we were most interested in decadal to century trends, not annual averages. Perenn, note as mentioned above, we use decadal 10 year moving averages, we meaning me use 10 run, we didn't use annual data. I don't know why he said I did. Anyway, going on. So we would not be inclined to perform the test you did. Nevertheless, we ran the test you did but changed the averaging period. And then he included the results for all the averaging periods, one, five, 10, 20 and 25 years. And he provided graphics that I kind of modified a little bit to make them more readable. And you can see that the variance increases when you apply the model rather than decreases. That's a hallmark of the failed model. It's a model that you shouldn't use to protect anything. So it's worth pointing out that both sides agree it is a failed model that makes things worse. And that is even poor result than randomly picking numbers but they still go ahead. Okay, so is this a smoking gun? No, it's a mushroom cloud, obviously. And that was just the beginning. I mean, we had the second report that was so bad that I can find something wrong in every paragraph. And I wrote a multi-thousand page document that looks just like it, hold on. This is the exact cover analog to the second climate report. And the flow of that one's all the same and it goes on and on and shows exactly what's wrong. The third one was simply blatant. The National Oceanic Atmospheric Administration wrote in their introduction that this is a key deliverable in President Obama's climate action plan. Okay, just tell us this political because you just did. And I can go on and on on that but let's talk about the major prediction from the first assessment report. After all, that report was a 2000 report released in 2001. It's 2021, it's 20 years after that. It predicted that US temperatures in this century, the 21st century would rise between five and nine degrees Fahrenheit. And most of the rises in temperature that are predicted by these models, by the way, are linear, they're not exponential. So if you make that linear assumption, we should have had a rise of about a degree, it over a degree Fahrenheit by now in the US record. One interesting thing happened after the report came out. The National Climatic Data Center put out a new temperature monitoring record called the Reference Climate Network. A relatively small number of stations, very good ones, without interfering things like buildings, the same instrumentation, everything calibrated. And it went online in 2004. And you know how much warming it shows in the US between 2004 and now? None, not a lick. And by the way, that matches their other long-term record, the Historical Climate Network II, which doesn't show anything since 2004. The Reference Climate Network is about 100 superb quality monitors spread properly throughout the USA. These were designed to be the base monitor for surface temperature changes, the purpose of which was to avoid any doubt at all as to the changing temperatures over time. I don't know how many people know that, but it's kind of obvious looking at the data. And these have got to be about the best surface temperature measurements that anybody's doing. Oh, the Reference Climate Network most certainly is. The Reference Climate Network is the best surface record that we have because the instruments are all standardized, they're calibrated. And it was designed because of criticism of the older climate networks. They were maybe fussed around with or something like that. And Tom Carl, the same guy who was the head of the National Assessment was the head of the National Climatic Data Center and he pushed for this. So yeah, they produced a very good record. The only problem is it doesn't show like a warming. So peer reviewed in climate science means that your peers can look at your work and you can agree with them that it is wrong, but you can still go ahead and publish it. Today we are in Kelvin Grove and we're having a climate change walk in March. And Brett Humbert is supposed to be here today and I'm inspired by her last time I was wearing this T-shirt. And I do want to change in the world for such a young age or child. Change is important to me. Great. Are you skipping school today? Yes. How do you feel about that? Great. Yeah. I do miss my friends in my school but I do know that it's important to look after our planet. And I've also got a message to Boris Johnson and all the world leaders that you're doing a very bad job right now and you need to really take care of our world because we only have one planet to live on and this planet means everything. Hey, thanks so much. First of all, let me just clear that those are metaphors. In speeches you often use metaphors. Of course, I don't mean literally that I want people to panic. So there was no scientific study that made me come to that conclusion.