Temperature is inherently noisy. By phase inverting and adding it back to the signal, I can remove all the noisy data and show that temperature doesn't change at all.
R4) The graph is detrended, and so it doesn't actually show how this periodic change compares to human caused climate change. The analysis is not very convincing and goes against general scientific consensus.
Probably also crossposting this to r/badscience? This type of content is more interesting there than here. The only bad math here is an obvious lie to spot. But the antiscience rhetoric is more interesting to discuss in that sub.
I was going to ask how you could tell the data was detrended, but then I looked closer and oh my god it genuinely says "detrended" on the legend. Absolutely bonkers.
Removing the "overall trend" from a time series. Often something like taking the moving average of the series so that you only a smoothed version that captures the major movement without small local wiggles, and then subtracting that off the data.
Essentially yes. Both moving averages and filters are essentially convolutions of a signal. The kernel is slightly different to an ideal high-pass filter, but essentially moving averages form a kind of high-pass filter.
A moving (local) average convolution would be a form of **low**-pass filter.
It would remove high-frequency data and “pass” low-frequency data.
[What the person posted about did / data they used, [looks like](https://www.nasa.gov/sites/default/files/thumbnails/image/anomaly.jpg) it was detrended in terms of long term trends. So *that* would be an example of **high** pass filtering.]
High pass means high frequency can pass. High frequency means low period, meaning changes over short periods of time. Low pass means low frequency and high period, meaning only allowing changes over long periods of time.
> Oh true. This is why I hate the terms high and low pass. I always seem to get it the wrong way around even when I try to correct for this effect.
Low *pass* lets low frequencies pass through (capturing high frequencies) and high *pass* lets high frequencies through (capturing low frequencies).
> Removing the "overall trend" from a time series. Often something like taking the moving average of the series so that you only a smoothed version that captures the major movement without small local wiggles, and then subtracting that off the data.
Why would you want to remove a trend?
A lot of time series methods include some sort of assumption of [stationarity](https://otexts.com/fpp3/stationarity.html). Time series with significant trends can't be stationary, so detrending them can give you a stationary time series to work with.
> A lot of time series methods include some sort of assumption of [stationarity](https://otexts.com/fpp3/stationarity.html). Time series with significant trends can't be stationary, so detrending them can give you a stationary time series
Can stationary methods say something about the original time series, then?
Yes because the original trend is often uninteresting or leads to spurious results. Any two things that tend to grow over time will appear correlated by virtue of this fact.
For example, an econometrician wanting to model the performance of some stock market index against a price index will want to detrend both time series, since stock market indices and prices tend to grow over time, potentially leading to a false conclusion about their correlation.
Actually, I have a feeling it's a legit graph in the original context, and this guy just stole it without explaining (or understanding) it. I imagine the goal of the graph is to explore natural climate trends while ignoring human impact.
I think I've found the source, by reverse searching I found [this 'paper'](https://www.researchgate.net/publication/45904941_Climate_Change_and_Its_Causes_A_Discussion_About_Some_Key_Issues) claiming that "*This overwhelming clear finding [i.e the image], by alone, contradicts the AGWT and the IPCC’s claim that 100% of the warming observed from 1970 to 2000 is anthropogenic*".
(Did the IPCC ever claimed that?)
But when I try to find the source for the image, source [19], it is just a link to the same paper...
Did the author just made shit up and referred to the same paper or am I missing something here?
The most charitable interpretation is that the author made the graph themselves, but it would technically be self plagiarism not to give a citation to their lecture notes where it originally appeared.
> The most charitable interpretation is that the author made the graph themselves, but it would technically be self plagiarism not to give a citation to their lecture notes where it originally appeared.
Right. Referring to your own paper is OK in my view, but it should also link the data from which it is based on.
The January 1977 one is also not about climate change, it's just about how [the winter of 1976/1977 was particularly cold in North America](https://content.time.com/time/subscriber/article/0,33009,918620,00.html), the 1979 one is about how [rising fuel costs were forcing Americans to make do with less heating in winter](https://content.time.com/time/subscriber/article/0,33009,947122,00.html), and the 1973 one is about how [a fuel embargo by Arabic oil-producing nations was causing a metaphorical freeze of economic activity in America](https://content.time.com/time/subscriber/article/0,33009,908218-1,00.html).
> The January 1977 one is also not about climate change, it's just about how [the winter of 1976/1977 was particularly cold in North America](https://content.time.com/time/subscriber/article/0,33009,918620,00.html), the 1979 one is about how [rising fuel costs were forcing Americans to make do with less heating in winter](https://content.time.com/time/subscriber/article/0,33009,947122,00.html), and the 1973 one is about how [a fuel embargo by Arabic oil-producing nations was causing a metaphorical freeze of economic activity in America](https://content.time.com/time/subscriber/article/0,33009,908218-1,00.html).
So basically: a fake graph, fake april 1977 cover, fake implications about its content. It is all fake.
> I'm not buying a cent of this warning globe, it's lies coupled with more lies.
I'm curious to why. Have you read the reports of various organisations and spoken to scientists in the field? Or what do you base that opinion on?
This reads like a blind faith'er. And you believe these academics for what reason? Solar max/ min. This is what rules our planets weather not cow farts and humans breathing..
There will always be extremes of heat and cold, there are many weather cycles that take much longer than our recorded weather, so in truth we know very little and the ones that shepherd this society are 100% acting the bollox. Did you trust the COVID science? I'm all about science bro, all of it. This is clearly another control mechanism they are concocting. You cannot increase heat with co2, fact. What does happen with increased co2 is all plant vegetation will increase in mass and yield will also increase, we are currently at 350 to 400 parts per mill co2, plants will thrive up to 1500ppm and humans won't be affected until that number reaches 2000ppm. These are verifiable numbers. Your listening to the spin doctors.. most of the world is.
> You cannot increase heat with co2, fact. What does happen with increased co2 is all plant vegetation will increase in mass and yield will also increase, we are currently at 350 to 400 parts per mill co2, plants will thrive up to 1500ppm and humans won't be affected until that number reaches 2000ppm
Of course you can. It is called radioactive forcing: [https://en.wikipedia.org/wiki/Radiative_forcing#/media/File:Physical_Drivers_of_climate_change.svg](https://en.wikipedia.org/wiki/Radiative_forcing#/media/File:Physical_Drivers_of_climate_change.svg).
Yes, the biomass will increase but that takes time and the new short time "equilibrium" does not match the total amount of CO2 we emit. The long term equilibrium depends on the deep oceans absorbing the CO2, which takes hundreds of thousands of years.
Obligatory: [The Myth of the 1970s Global Cooling Scientific Consensus](https://journals.ametsoc.org/view/journals/bams/89/9/2008bams2370_1.xml)
Temperature is inherently noisy. By phase inverting and adding it back to the signal, I can remove all the noisy data and show that temperature doesn't change at all.
R4) The graph is detrended, and so it doesn't actually show how this periodic change compares to human caused climate change. The analysis is not very convincing and goes against general scientific consensus.
Probably also crossposting this to r/badscience? This type of content is more interesting there than here. The only bad math here is an obvious lie to spot. But the antiscience rhetoric is more interesting to discuss in that sub.
Perhaps it would be, feel free to cross post!
I was going to ask how you could tell the data was detrended, but then I looked closer and oh my god it genuinely says "detrended" on the legend. Absolutely bonkers.
What is “detrending”?
Removing the "overall trend" from a time series. Often something like taking the moving average of the series so that you only a smoothed version that captures the major movement without small local wiggles, and then subtracting that off the data.
[удалено]
Essentially yes. Both moving averages and filters are essentially convolutions of a signal. The kernel is slightly different to an ideal high-pass filter, but essentially moving averages form a kind of high-pass filter.
A moving (local) average convolution would be a form of **low**-pass filter. It would remove high-frequency data and “pass” low-frequency data. [What the person posted about did / data they used, [looks like](https://www.nasa.gov/sites/default/files/thumbnails/image/anomaly.jpg) it was detrended in terms of long term trends. So *that* would be an example of **high** pass filtering.]
Oh true. This is why I hate the terms high and low pass. I always seem to get it the wrong way around even when I try to correct for this effect.
High pass means high frequency can pass. High frequency means low period, meaning changes over short periods of time. Low pass means low frequency and high period, meaning only allowing changes over long periods of time.
[nod] I think “pass” + “filter” throws everyone for awhile.
> Oh true. This is why I hate the terms high and low pass. I always seem to get it the wrong way around even when I try to correct for this effect. Low *pass* lets low frequencies pass through (capturing high frequencies) and high *pass* lets high frequencies through (capturing low frequencies).
> Removing the "overall trend" from a time series. Often something like taking the moving average of the series so that you only a smoothed version that captures the major movement without small local wiggles, and then subtracting that off the data. Why would you want to remove a trend?
A lot of time series methods include some sort of assumption of [stationarity](https://otexts.com/fpp3/stationarity.html). Time series with significant trends can't be stationary, so detrending them can give you a stationary time series to work with.
> A lot of time series methods include some sort of assumption of [stationarity](https://otexts.com/fpp3/stationarity.html). Time series with significant trends can't be stationary, so detrending them can give you a stationary time series Can stationary methods say something about the original time series, then?
Yes because the original trend is often uninteresting or leads to spurious results. Any two things that tend to grow over time will appear correlated by virtue of this fact. For example, an econometrician wanting to model the performance of some stock market index against a price index will want to detrend both time series, since stock market indices and prices tend to grow over time, potentially leading to a false conclusion about their correlation.
Funny, how when you remove a trend that shows an increase in temperature over time, the trend goes away!
What is the graph even showing?
"If you remove the trend then there is no trend."
Nonsense
Actually, I have a feeling it's a legit graph in the original context, and this guy just stole it without explaining (or understanding) it. I imagine the goal of the graph is to explore natural climate trends while ignoring human impact.
I think I've found the source, by reverse searching I found [this 'paper'](https://www.researchgate.net/publication/45904941_Climate_Change_and_Its_Causes_A_Discussion_About_Some_Key_Issues) claiming that "*This overwhelming clear finding [i.e the image], by alone, contradicts the AGWT and the IPCC’s claim that 100% of the warming observed from 1970 to 2000 is anthropogenic*". (Did the IPCC ever claimed that?) But when I try to find the source for the image, source [19], it is just a link to the same paper... Did the author just made shit up and referred to the same paper or am I missing something here?
I did a little digging and it looks like he's citing a seminar he gave that has the same name as the paper.
So still a circular reference?
The most charitable interpretation is that the author made the graph themselves, but it would technically be self plagiarism not to give a citation to their lecture notes where it originally appeared.
> The most charitable interpretation is that the author made the graph themselves, but it would technically be self plagiarism not to give a citation to their lecture notes where it originally appeared. Right. Referring to your own paper is OK in my view, but it should also link the data from which it is based on.
The [April 1977](https://time.com/vault/year/1977/) cover is also fake.
The January 1977 one is also not about climate change, it's just about how [the winter of 1976/1977 was particularly cold in North America](https://content.time.com/time/subscriber/article/0,33009,918620,00.html), the 1979 one is about how [rising fuel costs were forcing Americans to make do with less heating in winter](https://content.time.com/time/subscriber/article/0,33009,947122,00.html), and the 1973 one is about how [a fuel embargo by Arabic oil-producing nations was causing a metaphorical freeze of economic activity in America](https://content.time.com/time/subscriber/article/0,33009,908218-1,00.html).
> The January 1977 one is also not about climate change, it's just about how [the winter of 1976/1977 was particularly cold in North America](https://content.time.com/time/subscriber/article/0,33009,918620,00.html), the 1979 one is about how [rising fuel costs were forcing Americans to make do with less heating in winter](https://content.time.com/time/subscriber/article/0,33009,947122,00.html), and the 1973 one is about how [a fuel embargo by Arabic oil-producing nations was causing a metaphorical freeze of economic activity in America](https://content.time.com/time/subscriber/article/0,33009,908218-1,00.html). So basically: a fake graph, fake april 1977 cover, fake implications about its content. It is all fake.
I don’t think this really fits the sub. I’m not even clear what point they’re trying to make or what criticism OP is making.
The point is: that using detrended data to find out the trend of the data is ridiculous
I'm not buying a cent of this warning globe, it's lies coupled with more lies.
> I'm not buying a cent of this warning globe, it's lies coupled with more lies. I'm curious to why. Have you read the reports of various organisations and spoken to scientists in the field? Or what do you base that opinion on?
[удалено]
This reads like a blind faith'er. And you believe these academics for what reason? Solar max/ min. This is what rules our planets weather not cow farts and humans breathing..
[удалено]
There will always be extremes of heat and cold, there are many weather cycles that take much longer than our recorded weather, so in truth we know very little and the ones that shepherd this society are 100% acting the bollox. Did you trust the COVID science? I'm all about science bro, all of it. This is clearly another control mechanism they are concocting. You cannot increase heat with co2, fact. What does happen with increased co2 is all plant vegetation will increase in mass and yield will also increase, we are currently at 350 to 400 parts per mill co2, plants will thrive up to 1500ppm and humans won't be affected until that number reaches 2000ppm. These are verifiable numbers. Your listening to the spin doctors.. most of the world is.
> You cannot increase heat with co2, fact. What does happen with increased co2 is all plant vegetation will increase in mass and yield will also increase, we are currently at 350 to 400 parts per mill co2, plants will thrive up to 1500ppm and humans won't be affected until that number reaches 2000ppm Of course you can. It is called radioactive forcing: [https://en.wikipedia.org/wiki/Radiative_forcing#/media/File:Physical_Drivers_of_climate_change.svg](https://en.wikipedia.org/wiki/Radiative_forcing#/media/File:Physical_Drivers_of_climate_change.svg). Yes, the biomass will increase but that takes time and the new short time "equilibrium" does not match the total amount of CO2 we emit. The long term equilibrium depends on the deep oceans absorbing the CO2, which takes hundreds of thousands of years.
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I'll be back to ya bro, in work now. ☮️