Delano

@Troy I can't really take you seriously. I say let's discuss it. You get offended when i suggest you don't understand the graphs. You say you have an MBA and and engineering degree. Then you say you can read it but you can't interpret it. Then you basically say i am not a climate scientists and you don't have any knowledge of my statistical ability. I describe my methodology in setting up the model . The experts have Never posted a model. There are more than 20 forecasts by various agencies. None of which forecast all of the variables of temperature with statistical significance. That is in that 222 page document . I say find one actual regression model. Just one that these projections are based. You say you trust the experts over me. GISS is a NASA branch in New York. Is the source of temperature data. The director has been adjusting the data. And I post an article from Forbes which states this. The article has a quote from Dr John S Theon (check his credentials ) who disagrees with adjusting the raw data. He then goes on to say. That the various forecast are not transparent and they dont show the underlinig data. He also says weather is too complicated to model. I have no idea of your numerical ability. But based on your statements throughout the years. You cant interpret statistical information. I am a statistics hobbyist. Who spent $1000 in 1999 on Statistica a PC software package. In my library i had three different types of statistics books. I tutored statistics for years in undergraduate circa 1982-1986. And was hired by an NYU professor to interpret a study circa 1991. Which lead to a job where I interpreted a million cell matrix. My findings on that project were acknowledged by a PhD who literally wrote a university text book on statistics. I get annoyed when someone doesn't understand my subject matter. And says I'm wrong. Take a statistics refresher course check out the massive two volume book How to Present Visual Data. When you think you're ready lets discuss the data. Because the data tells a story. If you are statistically literate. You have data not information. Data + knowledge = Information. So your opinion is an uninformed one. And not capable of critically discussing the subject matter. You don't have time to learn statistics. You don't even have time to read my posted links. I will discuss regression models with anyone who is competent. Find someone who is competent.

Black Numbers. I am personally more partial to Numbers written in Black than written with white ink.

https://au.pinterest.com/pin/488499890809029461/

Thanks MEl I am familiar with his story. I am currently reading the Man who loved only Numbers.Paul Erdos K. Srinivasa Rao has said,[109] "As for his place in the world of Mathematics, we quote Bruce C. Berndt: 'Paul Erdős has passed on to us Hardy's personal ratings of mathematicians. Suppose that we rate mathematicians on the basis of pure talent on a scale from 0 to 100, Hardy gave himself a score of 25, J. E. Littlewood 30, David Hilbert 80 and Ramanujan 100.'"

My lane is thinking for myself. You have made it clear where you're at. @Mel Hopkins The Big Bang Theory phrase was coined by the Steady State Scientist. Steady State Scientists believed that the universe always existed. The came up with the phrase Big Bang because ot sounds silly and somewhat sexual. The Steady State Scientist were proven wrong. Why are climate changers so rabid and resistant to debate. Follow the money. BTW in mathematics amateur have also made contributions to the body of knowledge. @Mel Hopkins The Big Bang Theory phrase was coined by the Steady State Scientist. Steady State Scientists believed that the universe always existed. The came up with the phrase Big Bang because ot sounds silly and somewhat sexual. The Steady State Scientist were proven wrong. Why are climate changers so rabid and resistant to debate. Follow the money. BTW in mathematics amateur have also made contributions to the body of knowledge.

Troy I bet you posted it without even looking at the data. Because the first thing it says is some of the data is missing. @Mel Hopkins it could be cycles. That are tens of thousands of years long. I don't have that data. My informed opinion is that the numbers don't support the argument. And using 30 years of adjusted data is not science its propaganda. However we should reduce emissions. Since an ecosystem is robust up to a point.

@Mel Hopkins I wanted to decide for myself. I thought that I would look at the statistical model. Since the scientist keep mentioning the projections. I couldn't find one. I looked in reports from Australia, the United States and the UK. Nothing. That was at least five years ago. I had a look the other day. The models aren't shown just their projections and adjustment of the variables. There are about 20 different models only a handful have significant projections. The significant projects are high lighted in red. There isnt one model that has a significant number across all the drivers of weather. So they cherry pick the numbers from rhe 20 models and make that the composite. Since I couldn't find the non-existent model. I decided to create my own. Temperature and climate are different. Getting average temperature is also complicated not just because of location and seasonal differences over time (some regions not only have different seasons the times wuth varying lengths (which makes comparisons difficult )) but there are different ways of taking the temperature: Air, Ocean, ground, high altitude, just above the ground, there may be more but I can't remember. Then i had to read about the drivers for weather: Solar output, Wind, clouds, volcanic activity, again there are others but i can't remember. The hardest thing to predict is wind movement which also effects cloud movement. There are different levels of wind currents. Which is why you will notice that some clouds are stationary while others are moving at a fast clip. Also Volcanoes spew smoke that's miles long that blocks the suns rays. Then i had to find an output measure. That was in use from 1750 to 1980. So i used a few proxies. GDP GNP , i think tried fuel usage but the data wasn't sufficient. Then CO2 emissions which did go back to 1750. But i couldn't find the methodology. So i created the model. A few things struck me as odd. There aren't any spikes in carbon emissions. The industrial revolution had legendary pollution yet no spike in emissions. Also if it is due to production it should drop when economic activity slows. Even if there's a lag you should see a drop. Finally emissions tracked better to population than production. Which leads me to believe that emissions is a formula not a measurement. Recently i found out that all of the projections are based on 1980 - 2005 data. Which may have been altered by GISS in New York from 1980 onwards. GISS is a division of NASA. I believe I also saw an article that said weather on other planets in our solar system was more extreme. But i can't find that either. At the time i tried to present some of my arguments for discussion. People just parroted what they read, without thinking about it. And the people who thought it wasn't man made couldn't discuss it either. I give th same challenge five years later. There are twenty models show me one regression formula.

@Troy @Mel Hopkins @Cynique @Pioneer1 Apparently you can't trust NASA to provide accurate data since 1980. Interesting how 1980 seems to be an important year. For Climate change . All projections are based on 1986 - 2005. So all of Climate Change is based on 30 years of data. But perhaps Forbes Magazine is more convincing https://www.forbes.com/sites/larrybell/2011/07/19/nasas-inconvenient-ruse-the-goddard-institute-for-space-studies/#b03521969632 In a Jan. 29, 2006, New York Times interview Hansen charged that NASA public relations people had pressured him to allow them to review future public lectures, papers and postings on the GISS website. Yet in January 15, 2009 testimony before the U.S. Senate Committee on Environment and Public Works-Minority Committee, his former boss John S. Theon, retired chief of NASA's Climate Processes Research Program, took issue with the interference charge, stating: "Hansen was never muzzled even though he violated official agency position on climate forecasting (i.e., we did not know enough to forecast climate change or mankind's effect on it). Hansen has embarrassed NASA by coming out with his claim of global warming in 1988 in his testimony before Congress." Hey Troy do you think this guy may know what he is talking about. Dr. Theon also testified that: "My own belief concerning anthropogenic [man-made] climate change is that models do not realistically simulate the climate system because there are many very important sub-grid scale processes that the models either replicate poorly or completely omit". He observed: "Furthermore, some scientists have manipulated the observed data to justify their model results. In doing so, they neither explain what they have modeled in the observations, nor explain how they did it…this is contrary to the way science should be done." He then went on to say "Thus, there is no rational justification for using climate model forecasts to determine public policy".

Here's a little tidbit from the report. 9.3.4 CLIMATE DATA Two types of data are delivered to users: • Projected climate changes (relative to the IPCC reference period 1986–2005); • Application-ready future climate data (where projected climate changes are applied to 30 years’ of observed data).

I am going to read the report. And I will let you know if i change my mind. Although either way a discussion isn't possible.

No I'm stating that prior to 1980 temperature was not trending in the same direction as emissions. Troy you aren't equipped to discuss the numbers. It's an unfair argument because. Not because i am smarter than you the scientists or anyone else. Its unfair because people aren't statically savy. And the opposition is to fierce. If tiu want to get an insight on how close minded scientist are search how the Big Bang Theory got its name.

Troy read up on the Industrial Revolution and pollution.

Troy I have analysed the data. Notice that the time frames in the graph matches the study. Also note they start the modelling i the 1980's. There's been 200 years of engines and pollution. Why is there only change starting in 1980. Population. Population matches emissions better than economic activity. I'll connect the dots. The problem isn't production. There are too many people. That's what the numbers say.

Looking at the temperature anamoly notice that up until the 1980's its up and down. Then on the 80's it increases consistently.

Think about this. If its man made how come you have never seen a regression model. Because population is a stronger prediction than economic activity. You can use whatever search you like and you won't find one predictive model. But no one will tell you that you have to find out for yourself. I have gave this challenge almost 8 years ago. @Mel Hopkins let me know if you still have questions. Also see if you can find even one statiscal model showing the link numerically. Heres a model from the Austalian Government. Have a read and tell me what you think. https://www.climatechangeinaustralia.gov.au/en/climate-projections/explore-data/about-data/data-availability/ Here are the technical details. Let me know when anyone wants to discuss it. https://www.climatechangeinaustralia.gov.au/en/climate-projections/about/modelling-choices-and-methodology/model-evaluation/ I am prepared ro read and discuss any all parts if the tecnical report. Notice how the modellinf starts in the 80's just like i said from looking at the data. Because you can try ti lie but the numbers tell a story. If you know where ri look. I have the time skill and motivation to read and understand the 200+ . It is possible I will change my mind. Since in a two minute scan shows them modelling one 30 - 50 year period. Any rational debate has been silenced by grant recipients.

Troy

I wrote numerical literate. I never said i know more. I say let's discuss the data. I have also said let's clean the environment.

Interpret the graph. Its a direct question for the third time. I am not asking for agreement. I am asking you to think. Not parrot what you have read. @Mel Hopkins can you rephrase your question. @Troy Having an MBA doesn't mean you can interpret statistics. However the graphics are pretty simply for someone who is numerically literate.

I encourage everyone to think. I'll ask a point blank question. Can you read the graphs? Are you going to keep avoiding a direct question?

No I mean black numbers, not black scientist.

Pioneer I thought you just were paraphrasing. Did you have any thoughts before reading the other posts.

So what's the bit you understand? .

My Aunt use to say any man can father a child, but not every man is a good father. Thank you, Mel. Ditto to Cynique.

Yes and our solutions have a degree of independence.

Cynique that's very similar to my solution. I think the solutions match the personality.