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New Video : How Homogenization Destroys Climate Science
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Beautifully done, very interesting. If only someone had the time to do the same to all the temp stations.
Of course in Africa, one fifth of the world’s land mass, it is mostly all estimated.
Yep. Virtually no stations in the interior. All the red on the NASA map is pulled from a dark smelly place.
Homogenization causes corruption – clearly! Thanks, Tony!
One of the mechanisms that enabled the embezzlement of trillions of dollars, nicely exposed Tony.
Tony, this was excellent! Thank you!
I wonder how many of the alarmists take the time to watch these videos.
I can’t get any alarmist (so far) to bother with anything that might challenge their POV. Mind made up, don’t confuse me with the facts.
Yes, I see the same thing. Even when they say, “if you think you can prove it, then send me some links!” Of course I send them, but then they never read them.
TOBs
Homogenization
Interpolation to infill places without data
Selective decertification of stations
Very poor siting of numerous weather stations
Any other ways they distort the temperature data and records? Movement of reporting stations to the south in US perhaps?
They have proven they will do whatever they can. It’s a travesty that it is in our faces. Even more so that so many do not recognize it.
rah, I recall that computer algorithms make monthly changes to the historical record, often lowering the past by one or two hundredths of a degree in many areas, with ZERO physical reason for these changes.
Indeed. I was once told that “they explain ever change they make!” I said, “OK, then show me the justification for just one single year, say, oh, 1895. What new information have they recently obtained that justifies changing the data collected in 1895?” No surprise, but I never got an answer.
As Tony has shown, they incrementally change a bit here, another bit there, slowly, patiently, then change the same data a little bit more and a little bit more…
I wish. That. I knew what I know now. When I was younger.
Ooh la la.
https://www.youtube.com/watch?v=GYgdb3Glu3M
For consistency sake, when they adjust the data to cool the PAST, they ought to call it PASTeurization. That would make it safe to consume. (lol)
Questions:
1) How do we know even the rural station measurements are any good? Are there micro-site biases at those stations?
2) They ‘homogenize’ towards warming the rural stations by blending in the urban. This clearly causes the rural stations to appear warming. But, isnt the flip side there as well, do they homogenize the urban stations to show less warming than the raw data would otherwise show?
Any station, no matter where it is, that has it’s reading directly effected by UHI or mechanical means such as jet or vehicle exhaust, A/C exhaust, human caused radiant heat, focused solar energy, etc, is not giving an accurate reading of the ambient temperature and thus is worthless for the purpose of making an accurate evaluation of weather and thus also worthless for evaluating climate.
1) Anything is better than UHI corrupted sites.
2) No.
Hi Tony
Excellent post , as usual .
Here in Australia Joanne Nova has been doing an excellent job highlighting the shocking number of non compliant thermometer locations used by our Bureau of Meteorology. The below is one example;
http://joannenova.com.au/2019/08/feast-your-eyes-on-streaky-bays-thermometer-over-bitumen-for-31-long-hot-years/
The BOM knows all about these stations but does not bother to shut them down or replace them as they support their own “data homogenisation” program.
Funny, in the food business where I work , if you don’t comply you get shut down. I am a compliance auditor so I know what I am talking about. In climate, there are no consequences for bad practices, bad data or just plain bad science.
The graphs you’re showing of the homogenized vs. raw data don’t just contain homogenization adjustments, from the data pages they contain quality control procedures, NCEI adjustments for station moves and non-climatic effects, and finally homogenization to account for urban effects. If you compare the cleaned to the cleaned+homogenized series for the rural stations, you can see that the homogenization has no effect on the trend at all. All the the change in trend is a result of other adjustments. Click back and forth between the “GHCN v4 adj – cleaned” and “GHCN v4 adj – homogenized ” buttons to see what I mean.
https://data.giss.nasa.gov/cgi-bin/gistemp/stdata_show_v4.cgi?id=UY000086490&dt=1&ds=14
When you do the same for the urban station, you can see that the homogenization adjustment lowers the warming trend and makes the series look more like the ones from the rural stations.
https://data.giss.nasa.gov/cgi-bin/gistemp/stdata_show_v4.cgi?id=AR000875850&dt=1&ds=14
Isn’t that precisely what NASA claims the homogenization is doing? Specifically when they say, “GHCN-adj-homogenized: adjusted, cleaned data, homogenized by GISS to account for urban effects.” It seems that homogenization leaves rural stations alone and remove urban bias from urban stations.
Your claim is complete nonsense. The NASA web page shows very clearly that most of the claimed warming at Rocha is due to homogenization.
https://data.giss.nasa.gov/cgi-bin/gistemp/stdata_show_v4.cgi?id=UY000086565&dt=1&ds=15
This is a fair observation, and my descriptionf owhat homogenization is doing was inaccurate. Homogenization isn’t merely making urban stations look like rural ones, it’s making individual stations look more like the other stations in the region. In general this will remove effects of urbanization where they are present in urban stations, but may still effect rural stations, like Rocha.
And I think in this case it’s clear what homogenization is doing. Rocha is missing data from ~1930-1940, and, after initial cleaning but before homogenization, there is a large trend-change that is not present in any other nearby stations with records during that period. It’s very unlikely then that this trend change represents any real climate signal, so removing it during homogenization seems appropriate.
Again, it seems to me that the homogenization process is doing exactly what NASA claims it’s doing. No reason to suspect anything nefarious.
Really? A cooling trend becomes a warming trend after “homogenization”, and there is no reason to suspect anything?
I have some properties I would love to sell you.
Long-term climate trends are regional. This is intuitive. It would be very odd to have a climatic cooling trend centered over a small geographic area when none of the nearby locations experienced that same trend. Such an occurrence would almost certainly mean the cooling trend is an artifact of some non-climatic effect (station move, land-use change, etc).
This is especially true for Rocha given that the cooling trend is broken by a data gap – something definitely happened in this station’s history around that time that was non-climate related. It would be exceedingly weird to have an abrupt change in climate trend right in a single small geographic area right at the time when the station wasn’t recording measurements.
We can discuss whether or not this kind of homogenization is approrpiate to be doing, and I think that kind of discussion is really interesting and worth having, but it seems undeniable that the homogenization algorithm is just doing exactly what NASA claims that it’s doing – making single stations look more like the regional whole – and not something nefarious. That is, it’s fixing weird stuff like in the Rocha series and removing artifacts of urbanization as in the Buenos Aires series.
Long-term climate trends are regional.
WTF? They can be, but they are not necessarily regional. Where do you get this nutty idea?
Such an occurrence would almost certainly mean the cooling trend is an artifact of some non-climatic effect (station move, land-use change, etc).
No Al, what it suggests loudly is that UHI has corrupted the majority of data, and that it needs to be removed. The nationwide trend is very clear, until “homogeniszation”. Even a child can understand this.
How much of a UHI adjustment are they making? That’s the first question you should be asking.
And how do you think GHCN “adjust”, Mr Jones?
They do it by homogenisation with other stations, like Buenos Aires!
The final homogenisation step is simply one that GISS add on the the GHCN adjustments.
Why bother with these weather stations at all if the real data that they present is used in this corrupt fashion?
Why not have just one virtual station driven by the ‘Climate Models™’ and extrapolate all others temperature data from that? Then scientist can remake the the temperatures anything they wish, while the sheeple shiver at home, pretending the propaganda is correct, that the climate has got much warmer, wetter, dryer, stormier, etc.
With the record of our certain future comrades, we toil on to ensure our glorious history will be written yet.
All you have to do is prove with a simple experiment that their physics is wrong. You can do so with multiple electric bar radiators and a thermometer. You can also do a study showing wet regions are cooler than dry regions as I did in the Appendix of my 2013 paper “Planetary Core and Surface Temperatures” at https://ssrn.com/author=2627605.
It is far easier to prove their physics wrong than to argue about temperature data.
Watch for eight minutes my talk to scientists and others outside Parliament House, Canberra – excuse the wind noise on the mike. https://www.youtube.com/watch?v=7ihaY_1KSrE or, for more detail, watch https://www.youtube.com/watch?v=1BEN3iJzlrI&feature=youtu.be
All you have to do is prove with a simple experiment that their physics is wrong. You can do so with multiple electric bar radiators and a thermometer. You can also do a study showing wet regions are cooler than dry regions as I did in the Appendix of my 2013 paper “Planetary Core and Surface Temperatures.”